Project_4_Multi-factor_Model.ipynb

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    "# Project 4: Multi-factor Model\n",
    "## Instructions\n",
    "Each problem consists of a function to implement and instructions on how to implement the function.  The parts of the function that need to be implemented are marked with a `# TODO` comment. After implementing the function, run the cell to test it against the unit tests we've provided. For each problem, we provide one or more unit tests from our `project_tests` package. These unit tests won't tell you if your answer is correct, but will warn you of any major errors. Your code will be checked for the correct solution when you submit it to Udacity.\n",
    "\n",
    "## Packages\n",
    "When you implement the functions, you'll only need to you use the packages you've used in the classroom, like [Pandas](https://pandas.pydata.org/) and [Numpy](http://www.numpy.org/). These packages will be imported for you. We recommend you don't add any import statements, otherwise the grader might not be able to run your code.\n",
    "\n",
    "The other packages that we're importing are `project_helper` and `project_tests`. These are custom packages built to help you solve the problems.  The `project_helper` module contains utility functions and graph functions. The `project_tests` contains the unit tests for all the problems.\n",
    "\n",
    "### Install Packages"
   ]
  },
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   "execution_count": 2,
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      "  Stored in directory: /root/.cache/pip/wheels/9a/79/dc/1cac4dbfe744d781adf64eeab2e66093b1da7c7277dae9c5f3\n",
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      "\u001b[?25h  Created wheel for pandas: filename=pandas-0.18.1-cp36-cp36m-linux_x86_64.whl size=14693866 sha256=da99b24e29173f9eed9635df877fdf49b85860bee1f6046c9612df397f7723a6\n",
      "  Stored in directory: /root/.cache/pip/wheels/90/6d/5e/614faed2b3130fc89c36e185e83a331098324e32d08f6bb2f3\n",
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      "\u001b[?25h  Created wheel for plotly: filename=plotly-2.2.3-py3-none-any.whl size=1122399 sha256=f39ef17784a8f00723d0ead9e3d4a0f846200a3681f846d84bd5f5268e260386\n",
      "  Stored in directory: /root/.cache/pip/wheels/3b/63/08/bfacfd43d79c1851c5d03a6e8c27582203c5746fe00579b5db\n",
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      "\u001b[?25h  Created wheel for zipline: filename=zipline-1.2.0-cp36-cp36m-linux_x86_64.whl size=5585696 sha256=b7471b62d6a214c3c28ed99cc544eb10482c45830ae60675a6e1de02c7daab57\n",
      "  Stored in directory: /root/.cache/pip/wheels/05/13/88/164e4ac4e2662016300b12a0ab0920780bbb725120ccdb858a\n",
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      "\u001b[?25h  Created wheel for sqlalchemy: filename=SQLAlchemy-1.3.0-cp36-cp36m-linux_x86_64.whl size=1182187 sha256=20d62a92213191867ebb5db1b0e784077febdc50361f2c3f423f7e98e914133a\n",
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      "\u001b[?25h  Created wheel for bcolz: filename=bcolz-0.12.1-cp36-cp36m-linux_x86_64.whl size=1112238 sha256=8d988a7638b2a14a81c808a84a3237194322bf4bd95b7d954637e70ecfe3c538\n",
      "  Stored in directory: /root/.cache/pip/wheels/9f/51/d6/173c1dabc3904530cd9527026946789e2a065b004916e5c5bb\n",
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      "\u001b[?25h  Created wheel for cyordereddict: filename=cyordereddict-1.0.0-cp36-cp36m-linux_x86_64.whl size=169593 sha256=3a065e3699b12329e37f327e62aa3de7f826311853287c1be779a82db2d48b47\n",
      "  Stored in directory: /root/.cache/pip/wheels/8d/ff/1a/5f19b34a20e254f738ef53a8469e9e92ee13e66d54de3ea89c\n",
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      "\u001b[?25h  Created wheel for empyrical: filename=empyrical-0.5.5-py3-none-any.whl size=39780 sha256=a440e0049f2d7ac1e3f29ce82a8edf151c8e20268193dccc7f17b189c7f74b77\n",
      "  Stored in directory: /root/.cache/pip/wheels/82/0b/5a/ca1ca63ffb9d995bd8f0d3a75f14e89d54e1b0caee61b68c02\n",
      "  Building wheel for intervaltree (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for intervaltree: filename=intervaltree-3.1.0-py2.py3-none-any.whl size=26119 sha256=f7987fb680f283f44c8f7b5b729c67e8b784d24edc463f5f38d8288a6b728176\n",
      "  Stored in directory: /root/.cache/pip/wheels/fc/e6/3f/1616b381f981006664dd5123f06b231bbbb2e7d604a417e2fd\n",
      "  Building wheel for Logbook (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for Logbook: filename=Logbook-1.5.3-cp36-cp36m-linux_x86_64.whl size=66393 sha256=3d74f4de3ce034963c01d4234fe197dc7e4b9bb79c4e3bdc8f530b79775e0409\n",
      "  Stored in directory: /root/.cache/pip/wheels/27/4c/d7/c08e0670a3318441d3bd095149eb6e86e21656f102530ac8b6\n",
      "  Building wheel for requests-ftp (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for requests-ftp: filename=requests_ftp-0.3.1-py3-none-any.whl size=8183 sha256=c3d56567a279ccc1d6e3acea55d275e79c8625dedc2cc4d5d539b4dcd8a67c9d\n",
      "  Stored in directory: /root/.cache/pip/wheels/ea/e4/5d/72f7aad2c589cd6b0fa0c38feda872115bff8512a46d6c7b74\n",
      "Successfully built alphalens cvxpy pandas plotly zipline sqlalchemy bcolz cyordereddict empyrical intervaltree Logbook requests-ftp\n",
      "Installing collected packages: numpy, scipy, requests-ftp, requests-file, pandas, sqlalchemy, sortedcontainers, qdldl, pandas-datareader, importlib-resources, tables, scs, osqp, multipledispatch, lru-dict, Logbook, intervaltree, empyrical, ecos, cyordereddict, contextlib2, bottleneck, bcolz, alembic, zipline, tqdm, plotly, cvxpy, alphalens\n",
      "  Attempting uninstall: numpy\n",
      "    Found existing installation: numpy 1.12.1\n",
      "    Uninstalling numpy-1.12.1:\n",
      "      Successfully uninstalled numpy-1.12.1\n",
      "  Attempting uninstall: scipy\n",
      "    Found existing installation: scipy 1.2.1\n",
      "    Uninstalling scipy-1.2.1:\n",
      "      Successfully uninstalled scipy-1.2.1\n",
      "  Attempting uninstall: pandas\n",
      "    Found existing installation: pandas 0.23.3\n",
      "    Uninstalling pandas-0.23.3:\n",
      "      Successfully uninstalled pandas-0.23.3\n",
      "  Attempting uninstall: sqlalchemy\n",
      "    Found existing installation: SQLAlchemy 1.1.13\n",
      "    Uninstalling SQLAlchemy-1.1.13:\n",
      "      Successfully uninstalled SQLAlchemy-1.1.13\n",
      "  Attempting uninstall: tqdm\n",
      "    Found existing installation: tqdm 4.11.2\n",
      "    Uninstalling tqdm-4.11.2:\n",
      "      Successfully uninstalled tqdm-4.11.2\n",
      "  Attempting uninstall: plotly\n",
      "    Found existing installation: plotly 2.0.15\n",
      "    Uninstalling plotly-2.0.15:\n",
      "      Successfully uninstalled plotly-2.0.15\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "tensorflow 1.3.0 requires tensorflow-tensorboard<0.2.0,>=0.1.0, which is not installed.\n",
      "moviepy 0.2.3.2 requires tqdm==4.11.2, but you have tqdm 4.19.5 which is incompatible.\u001b[0m\n",
      "Successfully installed Logbook-1.5.3 alembic-1.7.7 alphalens-0.3.6 bcolz-0.12.1 bottleneck-1.3.5 contextlib2-21.6.0 cvxpy-1.1.0 cyordereddict-1.0.0 ecos-2.0.10 empyrical-0.5.5 importlib-resources-5.4.0 intervaltree-3.1.0 lru-dict-1.1.8 multipledispatch-0.6.0 numpy-1.17.0 osqp-0.6.2.post5 pandas-0.18.1 pandas-datareader-0.5.0 plotly-2.2.3 qdldl-0.1.5.post2 requests-file-1.5.1 requests-ftp-0.3.1 scipy-1.1.0 scs-3.2.0 sortedcontainers-2.4.0 sqlalchemy-1.3.0 tables-3.3.0 tqdm-4.19.5 zipline-1.2.0\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install --upgrade pip \n",
    "!{sys.executable} -m pip install --upgrade wheel setuptools build\n",
    "!{sys.executable} -m pip install -r requirements.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cvxpy as cvx\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import time\n",
    "import project_tests\n",
    "import project_helper\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.style.use('ggplot')\n",
    "plt.rcParams['figure.figsize'] = (14, 8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Data Bundle\n",
    "We'll be using Zipline to handle our data. We've created a end of day data bundle for this project. Run the cell below to register this data bundle in zipline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Registered\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import project_helper\n",
    "from zipline.data import bundles\n",
    "\n",
    "os.environ['ZIPLINE_ROOT'] = os.path.join(os.getcwd(), '..', '..', 'data', 'project_4_eod')\n",
    "\n",
    "ingest_func = bundles.csvdir.csvdir_equities(['daily'], project_helper.EOD_BUNDLE_NAME)\n",
    "bundles.register(project_helper.EOD_BUNDLE_NAME, ingest_func)\n",
    "\n",
    "print('Data Registered')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build Pipeline Engine\n",
    "We'll be using Zipline's pipeline package to access our data for this project. To use it, we must build a pipeline engine. Run the cell below to build the engine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.pipeline import Pipeline\n",
    "from zipline.pipeline.factors import AverageDollarVolume\n",
    "from zipline.utils.calendars import get_calendar\n",
    "\n",
    "\n",
    "universe = AverageDollarVolume(window_length=120).top(500) \n",
    "trading_calendar = get_calendar('NYSE') \n",
    "bundle_data = bundles.load(project_helper.EOD_BUNDLE_NAME)\n",
    "engine = project_helper.build_pipeline_engine(bundle_data, trading_calendar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "With the pipeline engine built, let's get the stocks at the end of the period in the universe we're using. We'll use these tickers to generate the returns data for the our risk model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " Equity(262 [KMX]),\n",
       " Equity(263 [KO]),\n",
       " Equity(264 [KORS]),\n",
       " Equity(265 [KR]),\n",
       " Equity(266 [KSS]),\n",
       " Equity(267 [KSU]),\n",
       " Equity(268 [L]),\n",
       " Equity(269 [LB]),\n",
       " Equity(270 [LEG]),\n",
       " Equity(271 [LEN]),\n",
       " Equity(272 [LH]),\n",
       " Equity(273 [LKQ]),\n",
       " Equity(274 [LLL]),\n",
       " Equity(275 [LLY]),\n",
       " Equity(276 [LMT]),\n",
       " Equity(277 [LNC]),\n",
       " Equity(278 [LNT]),\n",
       " Equity(279 [LOW]),\n",
       " Equity(280 [LRCX]),\n",
       " Equity(281 [LUK]),\n",
       " Equity(282 [LUV]),\n",
       " Equity(283 [LVLT]),\n",
       " Equity(284 [LYB]),\n",
       " Equity(285 [M]),\n",
       " Equity(286 [MA]),\n",
       " Equity(287 [MAA]),\n",
       " Equity(288 [MAC]),\n",
       " Equity(289 [MAR]),\n",
       " Equity(290 [MAS]),\n",
       " Equity(291 [MAT]),\n",
       " Equity(292 [MCD]),\n",
       " Equity(293 [MCHP]),\n",
       " Equity(294 [MCK]),\n",
       " Equity(295 [MCO]),\n",
       " Equity(296 [MDLZ]),\n",
       " Equity(297 [MDT]),\n",
       " Equity(298 [MET]),\n",
       " Equity(299 [MGM]),\n",
       " Equity(300 [MHK]),\n",
       " Equity(301 [MKC]),\n",
       " Equity(302 [MLM]),\n",
       " Equity(303 [MMC]),\n",
       " Equity(304 [MNST]),\n",
       " Equity(305 [MO]),\n",
       " Equity(306 [MON]),\n",
       " Equity(307 [MOS]),\n",
       " Equity(308 [MPC]),\n",
       " Equity(309 [MRK]),\n",
       " Equity(310 [MRO]),\n",
       " Equity(311 [MS]),\n",
       " Equity(312 [MSFT]),\n",
       " Equity(313 [MSI]),\n",
       " Equity(314 [MTB]),\n",
       " Equity(315 [MTD]),\n",
       " Equity(316 [MU]),\n",
       " Equity(317 [MYL]),\n",
       " Equity(318 [NAVI]),\n",
       " Equity(319 [NBL]),\n",
       " Equity(320 [NDAQ]),\n",
       " Equity(321 [NEE]),\n",
       " Equity(322 [NEM]),\n",
       " Equity(323 [NFLX]),\n",
       " Equity(324 [NFX]),\n",
       " Equity(325 [NI]),\n",
       " Equity(326 [NKE]),\n",
       " Equity(327 [NLSN]),\n",
       " Equity(328 [NOC]),\n",
       " Equity(329 [NOV]),\n",
       " Equity(330 [NRG]),\n",
       " Equity(331 [NSC]),\n",
       " Equity(332 [NTAP]),\n",
       " Equity(333 [NTRS]),\n",
       " Equity(334 [NUE]),\n",
       " Equity(335 [NVDA]),\n",
       " Equity(336 [NWL]),\n",
       " Equity(337 [NWS]),\n",
       " Equity(338 [NWSA]),\n",
       " Equity(339 [O]),\n",
       " Equity(340 [OKE]),\n",
       " Equity(341 [OMC]),\n",
       " Equity(342 [ORCL]),\n",
       " Equity(343 [ORLY]),\n",
       " Equity(344 [OXY]),\n",
       " Equity(345 [PAYX]),\n",
       " Equity(346 [PBCT]),\n",
       " Equity(347 [PCAR]),\n",
       " Equity(348 [PCG]),\n",
       " Equity(349 [PDCO]),\n",
       " Equity(350 [PEG]),\n",
       " Equity(351 [PEP]),\n",
       " Equity(352 [PFE]),\n",
       " Equity(353 [PFG]),\n",
       " Equity(354 [PG]),\n",
       " Equity(355 [PGR]),\n",
       " Equity(356 [PH]),\n",
       " Equity(357 [PHM]),\n",
       " Equity(358 [PKG]),\n",
       " Equity(359 [PKI]),\n",
       " Equity(360 [PLD]),\n",
       " Equity(361 [PM]),\n",
       " Equity(362 [PNC]),\n",
       " Equity(363 [PNR]),\n",
       " Equity(364 [PNW]),\n",
       " Equity(365 [PPG]),\n",
       " Equity(366 [PPL]),\n",
       " Equity(367 [PRGO]),\n",
       " Equity(368 [PRU]),\n",
       " Equity(369 [PSA]),\n",
       " Equity(370 [PSX]),\n",
       " Equity(371 [PVH]),\n",
       " Equity(372 [PWR]),\n",
       " Equity(373 [PX]),\n",
       " Equity(374 [PXD]),\n",
       " Equity(375 [PYPL]),\n",
       " Equity(376 [QCOM]),\n",
       " Equity(377 [QRVO]),\n",
       " Equity(378 [RCL]),\n",
       " Equity(379 [RE]),\n",
       " Equity(380 [REG]),\n",
       " Equity(381 [REGN]),\n",
       " Equity(382 [RF]),\n",
       " Equity(383 [RHI]),\n",
       " Equity(384 [RHT]),\n",
       " Equity(385 [RJF]),\n",
       " Equity(386 [RL]),\n",
       " Equity(387 [RMD]),\n",
       " Equity(388 [ROK]),\n",
       " Equity(389 [ROP]),\n",
       " Equity(390 [ROST]),\n",
       " Equity(391 [RRC]),\n",
       " Equity(392 [RSG]),\n",
       " Equity(393 [RTN]),\n",
       " Equity(394 [SBAC]),\n",
       " Equity(395 [SBUX]),\n",
       " Equity(396 [SCG]),\n",
       " Equity(397 [SCHW]),\n",
       " Equity(398 [SEE]),\n",
       " Equity(399 [SHW]),\n",
       " Equity(400 [SIG]),\n",
       " Equity(401 [SJM]),\n",
       " Equity(402 [SLB]),\n",
       " Equity(403 [SLG]),\n",
       " Equity(404 [SNA]),\n",
       " Equity(405 [SNI]),\n",
       " Equity(406 [SNPS]),\n",
       " Equity(407 [SO]),\n",
       " Equity(408 [SPG]),\n",
       " Equity(409 [SPLS]),\n",
       " Equity(410 [SRCL]),\n",
       " Equity(411 [SRE]),\n",
       " Equity(412 [STI]),\n",
       " Equity(413 [STT]),\n",
       " Equity(414 [STX]),\n",
       " Equity(415 [STZ]),\n",
       " Equity(416 [SWK]),\n",
       " Equity(417 [SWKS]),\n",
       " Equity(418 [SYF]),\n",
       " Equity(419 [SYK]),\n",
       " Equity(420 [SYMC]),\n",
       " Equity(421 [SYY]),\n",
       " Equity(422 [T]),\n",
       " Equity(423 [TAP]),\n",
       " Equity(424 [TDG]),\n",
       " Equity(425 [TEL]),\n",
       " Equity(426 [TGT]),\n",
       " Equity(427 [TIF]),\n",
       " Equity(428 [TJX]),\n",
       " Equity(429 [TMK]),\n",
       " Equity(430 [TMO]),\n",
       " Equity(431 [TRIP]),\n",
       " Equity(432 [TROW]),\n",
       " Equity(433 [TRV]),\n",
       " Equity(434 [TSCO]),\n",
       " Equity(435 [TSN]),\n",
       " Equity(436 [TSS]),\n",
       " Equity(437 [TWX]),\n",
       " Equity(438 [TXN]),\n",
       " Equity(439 [TXT]),\n",
       " Equity(440 [UAA]),\n",
       " Equity(441 [UAL]),\n",
       " Equity(442 [UDR]),\n",
       " Equity(443 [UHS]),\n",
       " Equity(444 [ULTA]),\n",
       " Equity(445 [UNH]),\n",
       " Equity(446 [UNM]),\n",
       " Equity(447 [UNP]),\n",
       " Equity(448 [UPS]),\n",
       " Equity(449 [URI]),\n",
       " Equity(450 [USB]),\n",
       " Equity(451 [UTX]),\n",
       " Equity(452 [V]),\n",
       " Equity(453 [VAR]),\n",
       " Equity(454 [VFC]),\n",
       " Equity(455 [VIAB]),\n",
       " Equity(456 [VLO]),\n",
       " Equity(457 [VMC]),\n",
       " Equity(458 [VNO]),\n",
       " Equity(459 [VRSK]),\n",
       " Equity(460 [VRSN]),\n",
       " Equity(461 [VRTX]),\n",
       " Equity(462 [VTR]),\n",
       " Equity(463 [VZ]),\n",
       " Equity(464 [WAT]),\n",
       " Equity(465 [WBA]),\n",
       " Equity(466 [WDC]),\n",
       " Equity(467 [WEC]),\n",
       " Equity(468 [WFC]),\n",
       " Equity(469 [WHR]),\n",
       " Equity(471 [WM]),\n",
       " Equity(472 [WMB]),\n",
       " Equity(473 [WMT]),\n",
       " Equity(474 [WRK]),\n",
       " Equity(475 [WU]),\n",
       " Equity(476 [WY]),\n",
       " Equity(477 [WYN]),\n",
       " Equity(478 [WYNN]),\n",
       " Equity(479 [XEC]),\n",
       " Equity(480 [XEL]),\n",
       " Equity(481 [XL]),\n",
       " Equity(482 [XLNX]),\n",
       " Equity(483 [XOM]),\n",
       " Equity(484 [XRAY]),\n",
       " Equity(485 [XRX]),\n",
       " Equity(486 [XYL]),\n",
       " Equity(487 [YUM]),\n",
       " Equity(488 [ZBH]),\n",
       " Equity(489 [ZION]),\n",
       " Equity(490 [ZTS])]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "universe_end_date = pd.Timestamp('2016-01-05', tz='UTC')\n",
    "\n",
    "universe_tickers = engine\\\n",
    "    .run_pipeline(\n",
    "        Pipeline(screen=universe),\n",
    "        universe_end_date,\n",
    "        universe_end_date)\\\n",
    "    .index.get_level_values(1)\\\n",
    "    .values.tolist()\n",
    "    \n",
    "universe_tickers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Returns\n",
    "Not that we have our pipeline built, let's access the returns data. We'll start by building a data portal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.data.data_portal import DataPortal\n",
    "\n",
    "\n",
    "data_portal = DataPortal(\n",
    "    bundle_data.asset_finder,\n",
    "    trading_calendar=trading_calendar,\n",
    "    first_trading_day=bundle_data.equity_daily_bar_reader.first_trading_day,\n",
    "    equity_minute_reader=None,\n",
    "    equity_daily_reader=bundle_data.equity_daily_bar_reader,\n",
    "    adjustment_reader=bundle_data.adjustment_reader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make the code easier to read, we've built the helper function `get_pricing` to get the pricing from the data portal. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_pricing(data_portal, trading_calendar, assets, start_date, end_date, field='close'):\n",
    "    end_dt = pd.Timestamp(end_date.strftime('%Y-%m-%d'), tz='UTC', offset='C')\n",
    "    start_dt = pd.Timestamp(start_date.strftime('%Y-%m-%d'), tz='UTC', offset='C')\n",
    "\n",
    "    end_loc = trading_calendar.closes.index.get_loc(end_dt)\n",
    "    start_loc = trading_calendar.closes.index.get_loc(start_dt)\n",
    "\n",
    "    return data_portal.get_history_window(\n",
    "        assets=assets,\n",
    "        end_dt=end_dt,\n",
    "        bar_count=end_loc - start_loc,\n",
    "        frequency='1d',\n",
    "        field=field,\n",
    "        data_frequency='daily')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's get returns data for our risk model using the `get_pricing` function. For this model, we'll be looking back to 5 years of data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
       "      <th>Equity(9 [ADI])</th>\n",
       "      <th>...</th>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-07 00:00:00+00:00</th>\n",
       "      <td>0.00843652</td>\n",
       "      <td>0.01423027</td>\n",
       "      <td>0.02670202</td>\n",
       "      <td>0.00714639</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00199434</td>\n",
       "      <td>0.00416541</td>\n",
       "      <td>0.00164769</td>\n",
       "      <td>-0.00712736</td>\n",
       "      <td>-0.00581846</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00183775</td>\n",
       "      <td>-0.00561865</td>\n",
       "      <td>0.00546091</td>\n",
       "      <td>-0.00404361</td>\n",
       "      <td>-0.01395259</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01245693</td>\n",
       "      <td>-0.00018145</td>\n",
       "      <td>-0.01045802</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-10 00:00:00+00:00</th>\n",
       "      <td>-0.00417428</td>\n",
       "      <td>0.00619534</td>\n",
       "      <td>0.00743543</td>\n",
       "      <td>0.01885158</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00571429</td>\n",
       "      <td>-0.00889600</td>\n",
       "      <td>-0.00885384</td>\n",
       "      <td>0.02871411</td>\n",
       "      <td>0.00292626</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00094687</td>\n",
       "      <td>0.00781438</td>\n",
       "      <td>-0.00608100</td>\n",
       "      <td>0.01046585</td>\n",
       "      <td>0.00973303</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00143979</td>\n",
       "      <td>0.00778351</td>\n",
       "      <td>-0.01794496</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-11 00:00:00+00:00</th>\n",
       "      <td>-0.00188630</td>\n",
       "      <td>-0.04364361</td>\n",
       "      <td>-0.00592730</td>\n",
       "      <td>-0.00236744</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00978303</td>\n",
       "      <td>-0.00206747</td>\n",
       "      <td>0.01371668</td>\n",
       "      <td>0.00060680</td>\n",
       "      <td>0.00875316</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00131385</td>\n",
       "      <td>0.01017933</td>\n",
       "      <td>0.00744242</td>\n",
       "      <td>0.00735141</td>\n",
       "      <td>0.00611644</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00646974</td>\n",
       "      <td>0.03567570</td>\n",
       "      <td>0.00746728</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-12 00:00:00+00:00</th>\n",
       "      <td>0.01725375</td>\n",
       "      <td>-0.00823708</td>\n",
       "      <td>0.01338721</td>\n",
       "      <td>0.00813289</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00597922</td>\n",
       "      <td>-0.00101061</td>\n",
       "      <td>0.02296913</td>\n",
       "      <td>0.01795027</td>\n",
       "      <td>0.00025710</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00498609</td>\n",
       "      <td>0.01566621</td>\n",
       "      <td>0.01176334</td>\n",
       "      <td>0.02718194</td>\n",
       "      <td>0.00438630</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00263106</td>\n",
       "      <td>0.01474083</td>\n",
       "      <td>-0.01190269</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-13 00:00:00+00:00</th>\n",
       "      <td>-0.00455851</td>\n",
       "      <td>0.00095465</td>\n",
       "      <td>0.00303109</td>\n",
       "      <td>0.00365656</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01492537</td>\n",
       "      <td>-0.00445119</td>\n",
       "      <td>-0.00040011</td>\n",
       "      <td>-0.00571905</td>\n",
       "      <td>-0.00501221</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03049927</td>\n",
       "      <td>-0.00321668</td>\n",
       "      <td>0.00169383</td>\n",
       "      <td>0.00054651</td>\n",
       "      <td>-0.01823475</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00508430</td>\n",
       "      <td>-0.00466453</td>\n",
       "      <td>-0.00917796</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-14 00:00:00+00:00</th>\n",
       "      <td>0.00343886</td>\n",
       "      <td>-0.00915594</td>\n",
       "      <td>0.00302193</td>\n",
       "      <td>0.00810620</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00139452</td>\n",
       "      <td>-0.01011076</td>\n",
       "      <td>0.00259000</td>\n",
       "      <td>0.01228280</td>\n",
       "      <td>0.01982692</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02660653</td>\n",
       "      <td>0.02589425</td>\n",
       "      <td>0.01474258</td>\n",
       "      <td>-0.00028748</td>\n",
       "      <td>0.02649446</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.02166101</td>\n",
       "      <td>0.00594885</td>\n",
       "      <td>0.03317747</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-18 00:00:00+00:00</th>\n",
       "      <td>0.03425353</td>\n",
       "      <td>-0.06208490</td>\n",
       "      <td>-0.00428562</td>\n",
       "      <td>-0.02247419</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02088872</td>\n",
       "      <td>0.00662116</td>\n",
       "      <td>0.00699843</td>\n",
       "      <td>0.01154188</td>\n",
       "      <td>0.03264518</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00167843</td>\n",
       "      <td>0.00250133</td>\n",
       "      <td>0.01116324</td>\n",
       "      <td>0.01158879</td>\n",
       "      <td>0.00604402</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02945339</td>\n",
       "      <td>0.00699753</td>\n",
       "      <td>-0.00853448</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-19 00:00:00+00:00</th>\n",
       "      <td>-0.01022379</td>\n",
       "      <td>-0.00892857</td>\n",
       "      <td>0.00875376</td>\n",
       "      <td>-0.00531448</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.01714410</td>\n",
       "      <td>0.00275342</td>\n",
       "      <td>-0.00296182</td>\n",
       "      <td>-0.00789936</td>\n",
       "      <td>-0.02057462</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01483416</td>\n",
       "      <td>-0.02358990</td>\n",
       "      <td>-0.00596800</td>\n",
       "      <td>-0.01989880</td>\n",
       "      <td>-0.01284667</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00081838</td>\n",
       "      <td>-0.00409759</td>\n",
       "      <td>-0.01843318</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-20 00:00:00+00:00</th>\n",
       "      <td>-0.00849568</td>\n",
       "      <td>0.02195299</td>\n",
       "      <td>-0.00473189</td>\n",
       "      <td>-0.01818900</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00479450</td>\n",
       "      <td>0.01332249</td>\n",
       "      <td>0.01871257</td>\n",
       "      <td>-0.01238573</td>\n",
       "      <td>-0.00281761</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.02451226</td>\n",
       "      <td>0.00774353</td>\n",
       "      <td>-0.00626137</td>\n",
       "      <td>-0.00084112</td>\n",
       "      <td>-0.03379775</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.01318157</td>\n",
       "      <td>-0.00161165</td>\n",
       "      <td>-0.00797236</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-21 00:00:00+00:00</th>\n",
       "      <td>0.00787281</td>\n",
       "      <td>-0.04103759</td>\n",
       "      <td>0.00554409</td>\n",
       "      <td>-0.01791080</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01064197</td>\n",
       "      <td>-0.00085307</td>\n",
       "      <td>-0.00195169</td>\n",
       "      <td>-0.00656913</td>\n",
       "      <td>-0.00411277</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00061472</td>\n",
       "      <td>0.01582494</td>\n",
       "      <td>-0.00304798</td>\n",
       "      <td>-0.00087153</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00759032</td>\n",
       "      <td>0.00932467</td>\n",
       "      <td>0.02402000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-24 00:00:00+00:00</th>\n",
       "      <td>0.01464622</td>\n",
       "      <td>0.02747253</td>\n",
       "      <td>-0.00110591</td>\n",
       "      <td>0.03283704</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00524943</td>\n",
       "      <td>0.00522324</td>\n",
       "      <td>0.00842018</td>\n",
       "      <td>0.02284340</td>\n",
       "      <td>0.01497431</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01235897</td>\n",
       "      <td>0.01601137</td>\n",
       "      <td>-0.00494300</td>\n",
       "      <td>0.00165968</td>\n",
       "      <td>0.00804885</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00060118</td>\n",
       "      <td>-0.01650140</td>\n",
       "      <td>-0.02302058</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-25 00:00:00+00:00</th>\n",
       "      <td>-0.00673624</td>\n",
       "      <td>0.00298231</td>\n",
       "      <td>0.00914590</td>\n",
       "      <td>0.01170955</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00936254</td>\n",
       "      <td>-0.00434674</td>\n",
       "      <td>0.00485935</td>\n",
       "      <td>-0.01381134</td>\n",
       "      <td>-0.01450491</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00217821</td>\n",
       "      <td>0.00627338</td>\n",
       "      <td>0.00115375</td>\n",
       "      <td>0.00113369</td>\n",
       "      <td>0.01514317</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00620848</td>\n",
       "      <td>0.01714176</td>\n",
       "      <td>-0.00883613</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-26 00:00:00+00:00</th>\n",
       "      <td>-0.03073582</td>\n",
       "      <td>0.06613350</td>\n",
       "      <td>0.00359340</td>\n",
       "      <td>0.00719342</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01222707</td>\n",
       "      <td>-0.02524087</td>\n",
       "      <td>0.01219180</td>\n",
       "      <td>-0.00119190</td>\n",
       "      <td>0.00283652</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00262839</td>\n",
       "      <td>0.00593383</td>\n",
       "      <td>0.01245258</td>\n",
       "      <td>0.00055168</td>\n",
       "      <td>-0.07629122</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00480301</td>\n",
       "      <td>-0.01952376</td>\n",
       "      <td>-0.01062584</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-27 00:00:00+00:00</th>\n",
       "      <td>0.00772081</td>\n",
       "      <td>0.02317753</td>\n",
       "      <td>-0.00155262</td>\n",
       "      <td>-0.00187707</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01183286</td>\n",
       "      <td>-0.00792793</td>\n",
       "      <td>0.00017944</td>\n",
       "      <td>0.00984487</td>\n",
       "      <td>0.00747981</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01426699</td>\n",
       "      <td>0.02116856</td>\n",
       "      <td>0.00275077</td>\n",
       "      <td>0.01639630</td>\n",
       "      <td>0.02466443</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00374620</td>\n",
       "      <td>0.06875384</td>\n",
       "      <td>0.02016019</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-28 00:00:00+00:00</th>\n",
       "      <td>-0.01884631</td>\n",
       "      <td>-0.08055268</td>\n",
       "      <td>-0.00093620</td>\n",
       "      <td>-0.02070958</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.02226215</td>\n",
       "      <td>-0.01919983</td>\n",
       "      <td>-0.01603463</td>\n",
       "      <td>-0.04017725</td>\n",
       "      <td>-0.02245999</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.02564740</td>\n",
       "      <td>-0.02010822</td>\n",
       "      <td>-0.01113056</td>\n",
       "      <td>-0.02187072</td>\n",
       "      <td>-0.02222859</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.02500085</td>\n",
       "      <td>-0.00847214</td>\n",
       "      <td>-0.01387340</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-31 00:00:00+00:00</th>\n",
       "      <td>0.00360809</td>\n",
       "      <td>-0.02361480</td>\n",
       "      <td>-0.00235062</td>\n",
       "      <td>0.00957845</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00389347</td>\n",
       "      <td>-0.00724829</td>\n",
       "      <td>-0.00098003</td>\n",
       "      <td>0.01723607</td>\n",
       "      <td>0.01381753</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00484620</td>\n",
       "      <td>0.00029849</td>\n",
       "      <td>0.02139566</td>\n",
       "      <td>-0.00756028</td>\n",
       "      <td>0.00661503</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00774817</td>\n",
       "      <td>0.00990224</td>\n",
       "      <td>0.00637836</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 00:00:00+00:00</th>\n",
       "      <td>0.01165376</td>\n",
       "      <td>-0.00104701</td>\n",
       "      <td>-0.00921769</td>\n",
       "      <td>0.01681783</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01197624</td>\n",
       "      <td>0.00154551</td>\n",
       "      <td>0.01749823</td>\n",
       "      <td>0.01391831</td>\n",
       "      <td>0.02162417</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01568687</td>\n",
       "      <td>0.03200298</td>\n",
       "      <td>0.04003746</td>\n",
       "      <td>0.02479485</td>\n",
       "      <td>0.02449777</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01410150</td>\n",
       "      <td>0.01774607</td>\n",
       "      <td>0.03097047</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-02 00:00:00+00:00</th>\n",
       "      <td>0.01011176</td>\n",
       "      <td>-0.03930406</td>\n",
       "      <td>-0.02747650</td>\n",
       "      <td>-0.00205320</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.02119705</td>\n",
       "      <td>0.01106795</td>\n",
       "      <td>0.00363229</td>\n",
       "      <td>-0.00238735</td>\n",
       "      <td>0.00227994</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01284550</td>\n",
       "      <td>-0.00451785</td>\n",
       "      <td>-0.00595828</td>\n",
       "      <td>-0.01038976</td>\n",
       "      <td>-0.00182689</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00656172</td>\n",
       "      <td>0.00516054</td>\n",
       "      <td>-0.00370596</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-03 00:00:00+00:00</th>\n",
       "      <td>-0.00028893</td>\n",
       "      <td>0.00730962</td>\n",
       "      <td>0.01412639</td>\n",
       "      <td>-0.00256035</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00366196</td>\n",
       "      <td>0.00589443</td>\n",
       "      <td>0.00417765</td>\n",
       "      <td>0.00299133</td>\n",
       "      <td>-0.01334112</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01043038</td>\n",
       "      <td>-0.00816904</td>\n",
       "      <td>0.00034726</td>\n",
       "      <td>0.00855568</td>\n",
       "      <td>0.00459592</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.03141255</td>\n",
       "      <td>-0.00033292</td>\n",
       "      <td>-0.00039386</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-04 00:00:00+00:00</th>\n",
       "      <td>0.00562724</td>\n",
       "      <td>-0.03649951</td>\n",
       "      <td>0.02401434</td>\n",
       "      <td>0.00891547</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.03304712</td>\n",
       "      <td>0.00261602</td>\n",
       "      <td>-0.00436050</td>\n",
       "      <td>-0.00507009</td>\n",
       "      <td>0.01965916</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00947084</td>\n",
       "      <td>0.02470898</td>\n",
       "      <td>-0.00191681</td>\n",
       "      <td>0.00304817</td>\n",
       "      <td>-0.00550607</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00140817</td>\n",
       "      <td>0.00247147</td>\n",
       "      <td>0.01611067</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-07 00:00:00+00:00</th>\n",
       "      <td>0.00770895</td>\n",
       "      <td>0.05204586</td>\n",
       "      <td>0.00811404</td>\n",
       "      <td>0.01553804</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00217765</td>\n",
       "      <td>-0.00934092</td>\n",
       "      <td>0.00227918</td>\n",
       "      <td>0.00599520</td>\n",
       "      <td>-0.00351381</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00680069</td>\n",
       "      <td>-0.00507270</td>\n",
       "      <td>0.00780293</td>\n",
       "      <td>0.00685187</td>\n",
       "      <td>0.00276828</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00202754</td>\n",
       "      <td>-0.01087565</td>\n",
       "      <td>0.02761741</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-08 00:00:00+00:00</th>\n",
       "      <td>0.01085425</td>\n",
       "      <td>0.01645475</td>\n",
       "      <td>0.00620226</td>\n",
       "      <td>0.00943966</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00218240</td>\n",
       "      <td>-0.00173831</td>\n",
       "      <td>-0.00055735</td>\n",
       "      <td>0.00029797</td>\n",
       "      <td>-0.00600987</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00384577</td>\n",
       "      <td>0.00179527</td>\n",
       "      <td>-0.00607698</td>\n",
       "      <td>0.00518223</td>\n",
       "      <td>-0.00276064</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00385105</td>\n",
       "      <td>-0.00049496</td>\n",
       "      <td>0.00477967</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-09 00:00:00+00:00</th>\n",
       "      <td>0.00466351</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01695500</td>\n",
       "      <td>0.00833204</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00300577</td>\n",
       "      <td>-0.00153026</td>\n",
       "      <td>0.00113763</td>\n",
       "      <td>-0.01668156</td>\n",
       "      <td>0.00478144</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01183694</td>\n",
       "      <td>-0.00179205</td>\n",
       "      <td>-0.00517814</td>\n",
       "      <td>-0.01844088</td>\n",
       "      <td>0.00370461</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00182061</td>\n",
       "      <td>-0.00985108</td>\n",
       "      <td>-0.00475694</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-10 00:00:00+00:00</th>\n",
       "      <td>0.00041298</td>\n",
       "      <td>-0.00304846</td>\n",
       "      <td>-0.01136679</td>\n",
       "      <td>-0.01010922</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00110085</td>\n",
       "      <td>-0.00110982</td>\n",
       "      <td>0.00550344</td>\n",
       "      <td>0.01696456</td>\n",
       "      <td>0.00451308</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00894677</td>\n",
       "      <td>0.00391368</td>\n",
       "      <td>0.00787593</td>\n",
       "      <td>0.00551211</td>\n",
       "      <td>-0.00462381</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00485295</td>\n",
       "      <td>0.01144950</td>\n",
       "      <td>-0.02649784</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 00:00:00+00:00</th>\n",
       "      <td>-0.00714982</td>\n",
       "      <td>0.02836356</td>\n",
       "      <td>0.00076442</td>\n",
       "      <td>0.00650490</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00137455</td>\n",
       "      <td>0.00153431</td>\n",
       "      <td>-0.01114607</td>\n",
       "      <td>0.00297885</td>\n",
       "      <td>0.01500657</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00170520</td>\n",
       "      <td>0.01076538</td>\n",
       "      <td>-0.00456215</td>\n",
       "      <td>0.00714655</td>\n",
       "      <td>0.01202070</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00061584</td>\n",
       "      <td>0.00965987</td>\n",
       "      <td>0.01425557</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-14 00:00:00+00:00</th>\n",
       "      <td>0.00166312</td>\n",
       "      <td>-0.01579001</td>\n",
       "      <td>-0.02327358</td>\n",
       "      <td>0.00652903</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00575047</td>\n",
       "      <td>0.00924459</td>\n",
       "      <td>0.00020168</td>\n",
       "      <td>0.00564301</td>\n",
       "      <td>0.00987654</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01161568</td>\n",
       "      <td>0.00031846</td>\n",
       "      <td>0.02522953</td>\n",
       "      <td>-0.00544299</td>\n",
       "      <td>0.00547592</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01065725</td>\n",
       "      <td>0.00248369</td>\n",
       "      <td>-0.01002123</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-15 00:00:00+00:00</th>\n",
       "      <td>-0.01190476</td>\n",
       "      <td>0.01104282</td>\n",
       "      <td>-0.00392614</td>\n",
       "      <td>0.00201613</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00732946</td>\n",
       "      <td>0.01674954</td>\n",
       "      <td>-0.00802079</td>\n",
       "      <td>0.00236267</td>\n",
       "      <td>0.00023854</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00607872</td>\n",
       "      <td>-0.00180403</td>\n",
       "      <td>-0.02285301</td>\n",
       "      <td>0.00409742</td>\n",
       "      <td>0.00360404</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00852564</td>\n",
       "      <td>-0.00181453</td>\n",
       "      <td>-0.00446084</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-16 00:00:00+00:00</th>\n",
       "      <td>0.01512325</td>\n",
       "      <td>0.00195775</td>\n",
       "      <td>0.01385974</td>\n",
       "      <td>0.00896684</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00355392</td>\n",
       "      <td>-0.01050193</td>\n",
       "      <td>0.02732858</td>\n",
       "      <td>0.02209782</td>\n",
       "      <td>-0.00390509</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00917384</td>\n",
       "      <td>0.00386265</td>\n",
       "      <td>0.00868160</td>\n",
       "      <td>0.00028536</td>\n",
       "      <td>0.02709281</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00889849</td>\n",
       "      <td>0.01055741</td>\n",
       "      <td>0.00120638</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-17 00:00:00+00:00</th>\n",
       "      <td>-0.00331066</td>\n",
       "      <td>-0.01779103</td>\n",
       "      <td>-0.02484354</td>\n",
       "      <td>-0.01330906</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02914771</td>\n",
       "      <td>0.00130066</td>\n",
       "      <td>0.01178385</td>\n",
       "      <td>0.00835976</td>\n",
       "      <td>0.00855903</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01565577</td>\n",
       "      <td>0.00031771</td>\n",
       "      <td>0.00227521</td>\n",
       "      <td>-0.00191139</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00390600</td>\n",
       "      <td>0.01532474</td>\n",
       "      <td>-0.00322747</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-18 00:00:00+00:00</th>\n",
       "      <td>0.01107771</td>\n",
       "      <td>-0.02010261</td>\n",
       "      <td>-0.00669325</td>\n",
       "      <td>-0.02159490</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00961998</td>\n",
       "      <td>0.01210641</td>\n",
       "      <td>-0.00795272</td>\n",
       "      <td>0.01172098</td>\n",
       "      <td>-0.00169134</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05340361</td>\n",
       "      <td>0.00144687</td>\n",
       "      <td>0.00739258</td>\n",
       "      <td>0.01314812</td>\n",
       "      <td>-0.00438988</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00411045</td>\n",
       "      <td>0.02378154</td>\n",
       "      <td>-0.01795968</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-20 00:00:00+00:00</th>\n",
       "      <td>0.00107212</td>\n",
       "      <td>-0.00237346</td>\n",
       "      <td>0.00276686</td>\n",
       "      <td>0.00438086</td>\n",
       "      <td>0.00925624</td>\n",
       "      <td>-0.00090483</td>\n",
       "      <td>0.00611281</td>\n",
       "      <td>0.00643014</td>\n",
       "      <td>0.00054490</td>\n",
       "      <td>-0.00584294</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00813121</td>\n",
       "      <td>0.00041182</td>\n",
       "      <td>-0.00635194</td>\n",
       "      <td>0.00279330</td>\n",
       "      <td>0.00289932</td>\n",
       "      <td>-0.00449783</td>\n",
       "      <td>0.01505987</td>\n",
       "      <td>-0.00317570</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00894971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-23 00:00:00+00:00</th>\n",
       "      <td>-0.00709429</td>\n",
       "      <td>0.00237910</td>\n",
       "      <td>-0.00122838</td>\n",
       "      <td>-0.01298872</td>\n",
       "      <td>0.00064612</td>\n",
       "      <td>-0.00372792</td>\n",
       "      <td>-0.01238148</td>\n",
       "      <td>-0.00120585</td>\n",
       "      <td>0.00163381</td>\n",
       "      <td>-0.04410655</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00469574</td>\n",
       "      <td>-0.00695468</td>\n",
       "      <td>0.00613134</td>\n",
       "      <td>0.00734514</td>\n",
       "      <td>0.02769219</td>\n",
       "      <td>0.00132239</td>\n",
       "      <td>-0.00096628</td>\n",
       "      <td>-0.00858098</td>\n",
       "      <td>-0.00199203</td>\n",
       "      <td>-0.00760006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-24 00:00:00+00:00</th>\n",
       "      <td>0.00208486</td>\n",
       "      <td>-0.02530879</td>\n",
       "      <td>0.00350426</td>\n",
       "      <td>0.00959410</td>\n",
       "      <td>-0.00032285</td>\n",
       "      <td>-0.00233603</td>\n",
       "      <td>0.00020972</td>\n",
       "      <td>-0.00453713</td>\n",
       "      <td>0.00043497</td>\n",
       "      <td>0.06374097</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00077707</td>\n",
       "      <td>0.01295953</td>\n",
       "      <td>0.01993523</td>\n",
       "      <td>-0.00956300</td>\n",
       "      <td>-0.01299182</td>\n",
       "      <td>-0.00187091</td>\n",
       "      <td>-0.00425172</td>\n",
       "      <td>-0.00904325</td>\n",
       "      <td>0.00264987</td>\n",
       "      <td>-0.00065084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-25 00:00:00+00:00</th>\n",
       "      <td>-0.00820649</td>\n",
       "      <td>0.00193813</td>\n",
       "      <td>0.00680544</td>\n",
       "      <td>-0.00715141</td>\n",
       "      <td>-0.01374361</td>\n",
       "      <td>0.00436515</td>\n",
       "      <td>-0.00086201</td>\n",
       "      <td>-0.00233759</td>\n",
       "      <td>-0.00250000</td>\n",
       "      <td>-0.00281048</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00888765</td>\n",
       "      <td>-0.00445842</td>\n",
       "      <td>-0.00768963</td>\n",
       "      <td>-0.00279190</td>\n",
       "      <td>-0.00191255</td>\n",
       "      <td>0.00482386</td>\n",
       "      <td>0.00289380</td>\n",
       "      <td>-0.00617420</td>\n",
       "      <td>-0.00030891</td>\n",
       "      <td>0.00086836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-27 00:00:00+00:00</th>\n",
       "      <td>-0.00325586</td>\n",
       "      <td>0.00920070</td>\n",
       "      <td>0.00328491</td>\n",
       "      <td>-0.00186283</td>\n",
       "      <td>-0.00480271</td>\n",
       "      <td>0.00061184</td>\n",
       "      <td>0.00020986</td>\n",
       "      <td>0.00336265</td>\n",
       "      <td>0.00435872</td>\n",
       "      <td>0.00331472</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00473588</td>\n",
       "      <td>0.00447839</td>\n",
       "      <td>-0.00025651</td>\n",
       "      <td>0.00263307</td>\n",
       "      <td>0.00379485</td>\n",
       "      <td>-0.00213974</td>\n",
       "      <td>0.00510503</td>\n",
       "      <td>-0.00286889</td>\n",
       "      <td>0.00501270</td>\n",
       "      <td>0.00234253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-30 00:00:00+00:00</th>\n",
       "      <td>-0.01020870</td>\n",
       "      <td>-0.01032093</td>\n",
       "      <td>-0.01279784</td>\n",
       "      <td>0.00415919</td>\n",
       "      <td>-0.03083813</td>\n",
       "      <td>-0.00354229</td>\n",
       "      <td>-0.01100361</td>\n",
       "      <td>-0.00222774</td>\n",
       "      <td>-0.00770316</td>\n",
       "      <td>0.01952228</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00421152</td>\n",
       "      <td>0.00934761</td>\n",
       "      <td>0.00529351</td>\n",
       "      <td>-0.00736321</td>\n",
       "      <td>-0.00752358</td>\n",
       "      <td>-0.00692784</td>\n",
       "      <td>-0.00618325</td>\n",
       "      <td>0.00010131</td>\n",
       "      <td>-0.00433862</td>\n",
       "      <td>-0.00807150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-01 00:00:00+00:00</th>\n",
       "      <td>0.01574786</td>\n",
       "      <td>0.04849282</td>\n",
       "      <td>-0.00239635</td>\n",
       "      <td>-0.00811576</td>\n",
       "      <td>0.01495718</td>\n",
       "      <td>0.00871792</td>\n",
       "      <td>0.01202178</td>\n",
       "      <td>0.00848039</td>\n",
       "      <td>0.01191778</td>\n",
       "      <td>-0.00097042</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01519233</td>\n",
       "      <td>0.01107484</td>\n",
       "      <td>0.00282087</td>\n",
       "      <td>0.02160044</td>\n",
       "      <td>0.01327550</td>\n",
       "      <td>0.00858179</td>\n",
       "      <td>0.02716952</td>\n",
       "      <td>0.01692683</td>\n",
       "      <td>0.01502831</td>\n",
       "      <td>0.00663191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-02 00:00:00+00:00</th>\n",
       "      <td>-0.00528420</td>\n",
       "      <td>0.01293012</td>\n",
       "      <td>-0.02716607</td>\n",
       "      <td>-0.00902983</td>\n",
       "      <td>-0.02202152</td>\n",
       "      <td>-0.00653437</td>\n",
       "      <td>-0.00528731</td>\n",
       "      <td>-0.00499107</td>\n",
       "      <td>-0.00572663</td>\n",
       "      <td>-0.00699034</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00385752</td>\n",
       "      <td>-0.02469292</td>\n",
       "      <td>-0.02857143</td>\n",
       "      <td>0.00757240</td>\n",
       "      <td>-0.02996241</td>\n",
       "      <td>-0.01833503</td>\n",
       "      <td>0.00631281</td>\n",
       "      <td>-0.00447256</td>\n",
       "      <td>-0.01544806</td>\n",
       "      <td>-0.01360986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-03 00:00:00+00:00</th>\n",
       "      <td>-0.00952117</td>\n",
       "      <td>-0.01255465</td>\n",
       "      <td>-0.01994438</td>\n",
       "      <td>-0.00929219</td>\n",
       "      <td>-0.02772394</td>\n",
       "      <td>-0.00141471</td>\n",
       "      <td>-0.02365007</td>\n",
       "      <td>-0.01542891</td>\n",
       "      <td>-0.02292980</td>\n",
       "      <td>-0.02782630</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00829420</td>\n",
       "      <td>-0.01081970</td>\n",
       "      <td>-0.01432669</td>\n",
       "      <td>0.00273291</td>\n",
       "      <td>-0.00095925</td>\n",
       "      <td>-0.00567594</td>\n",
       "      <td>-0.02427203</td>\n",
       "      <td>-0.02836674</td>\n",
       "      <td>-0.01572478</td>\n",
       "      <td>-0.02524442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-04 00:00:00+00:00</th>\n",
       "      <td>0.02019919</td>\n",
       "      <td>0.03930296</td>\n",
       "      <td>0.00677909</td>\n",
       "      <td>0.03324578</td>\n",
       "      <td>0.01889890</td>\n",
       "      <td>0.01195750</td>\n",
       "      <td>0.02604566</td>\n",
       "      <td>0.02992398</td>\n",
       "      <td>0.02969636</td>\n",
       "      <td>0.00271314</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02221053</td>\n",
       "      <td>0.01032552</td>\n",
       "      <td>0.00573563</td>\n",
       "      <td>0.00749501</td>\n",
       "      <td>0.01159888</td>\n",
       "      <td>0.02477363</td>\n",
       "      <td>0.04115927</td>\n",
       "      <td>0.01197660</td>\n",
       "      <td>0.02445235</td>\n",
       "      <td>0.02788171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-07 00:00:00+00:00</th>\n",
       "      <td>-0.00033987</td>\n",
       "      <td>0.01801987</td>\n",
       "      <td>-0.02957813</td>\n",
       "      <td>-0.00629799</td>\n",
       "      <td>-0.01592051</td>\n",
       "      <td>0.00089849</td>\n",
       "      <td>0.00572671</td>\n",
       "      <td>-0.00146283</td>\n",
       "      <td>-0.03218838</td>\n",
       "      <td>-0.01198796</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00879092</td>\n",
       "      <td>-0.02612215</td>\n",
       "      <td>-0.00190007</td>\n",
       "      <td>-0.02957591</td>\n",
       "      <td>-0.01964712</td>\n",
       "      <td>0.00353962</td>\n",
       "      <td>-0.00138396</td>\n",
       "      <td>-0.04208519</td>\n",
       "      <td>-0.01184133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-08 00:00:00+00:00</th>\n",
       "      <td>-0.02330712</td>\n",
       "      <td>-0.02687583</td>\n",
       "      <td>-0.00886608</td>\n",
       "      <td>-0.00042489</td>\n",
       "      <td>0.00711446</td>\n",
       "      <td>0.00490595</td>\n",
       "      <td>-0.00020917</td>\n",
       "      <td>-0.00027950</td>\n",
       "      <td>0.02366071</td>\n",
       "      <td>-0.00821590</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00460567</td>\n",
       "      <td>-0.00391018</td>\n",
       "      <td>-0.02825109</td>\n",
       "      <td>-0.01206744</td>\n",
       "      <td>-0.00492958</td>\n",
       "      <td>-0.01707392</td>\n",
       "      <td>-0.01073476</td>\n",
       "      <td>-0.00627720</td>\n",
       "      <td>-0.03181317</td>\n",
       "      <td>0.00066573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-09 00:00:00+00:00</th>\n",
       "      <td>-0.00516964</td>\n",
       "      <td>-0.02021340</td>\n",
       "      <td>0.02222267</td>\n",
       "      <td>-0.02207699</td>\n",
       "      <td>-0.01130272</td>\n",
       "      <td>0.00198396</td>\n",
       "      <td>-0.01294807</td>\n",
       "      <td>-0.01487559</td>\n",
       "      <td>-0.02354993</td>\n",
       "      <td>-0.02360837</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01309164</td>\n",
       "      <td>-0.00993443</td>\n",
       "      <td>0.01338977</td>\n",
       "      <td>-0.02106570</td>\n",
       "      <td>-0.00986868</td>\n",
       "      <td>-0.00056952</td>\n",
       "      <td>-0.02367896</td>\n",
       "      <td>0.00220474</td>\n",
       "      <td>-0.00748954</td>\n",
       "      <td>-0.01590047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-10 00:00:00+00:00</th>\n",
       "      <td>0.01503860</td>\n",
       "      <td>0.01009224</td>\n",
       "      <td>-0.00946596</td>\n",
       "      <td>0.00476320</td>\n",
       "      <td>-0.00446315</td>\n",
       "      <td>0.01271990</td>\n",
       "      <td>0.00777184</td>\n",
       "      <td>0.00289674</td>\n",
       "      <td>-0.00669942</td>\n",
       "      <td>0.00882138</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00675676</td>\n",
       "      <td>0.00188278</td>\n",
       "      <td>0.00079770</td>\n",
       "      <td>-0.00031695</td>\n",
       "      <td>0.01497042</td>\n",
       "      <td>0.01213779</td>\n",
       "      <td>-0.00825643</td>\n",
       "      <td>-0.00029673</td>\n",
       "      <td>0.01475919</td>\n",
       "      <td>0.01969533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-11 00:00:00+00:00</th>\n",
       "      <td>-0.01222670</td>\n",
       "      <td>-0.04535632</td>\n",
       "      <td>-0.01917906</td>\n",
       "      <td>-0.02573993</td>\n",
       "      <td>-0.03118548</td>\n",
       "      <td>0.00127956</td>\n",
       "      <td>-0.02096235</td>\n",
       "      <td>-0.02137978</td>\n",
       "      <td>0.02765288</td>\n",
       "      <td>-0.00384301</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01493822</td>\n",
       "      <td>-0.01271252</td>\n",
       "      <td>-0.01783980</td>\n",
       "      <td>-0.01775464</td>\n",
       "      <td>-0.01279343</td>\n",
       "      <td>-0.01306196</td>\n",
       "      <td>-0.02583602</td>\n",
       "      <td>-0.01011228</td>\n",
       "      <td>-0.02978165</td>\n",
       "      <td>-0.00585635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-14 00:00:00+00:00</th>\n",
       "      <td>-0.01119741</td>\n",
       "      <td>-0.00761835</td>\n",
       "      <td>-0.00832534</td>\n",
       "      <td>-0.00618871</td>\n",
       "      <td>0.02589759</td>\n",
       "      <td>0.00440628</td>\n",
       "      <td>0.01014465</td>\n",
       "      <td>0.01007090</td>\n",
       "      <td>0.02012689</td>\n",
       "      <td>-0.00193824</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00721594</td>\n",
       "      <td>-0.00094052</td>\n",
       "      <td>0.02273800</td>\n",
       "      <td>-0.00183474</td>\n",
       "      <td>-0.01791305</td>\n",
       "      <td>0.01158048</td>\n",
       "      <td>0.00490982</td>\n",
       "      <td>0.00535594</td>\n",
       "      <td>-0.01499098</td>\n",
       "      <td>0.01658331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-15 00:00:00+00:00</th>\n",
       "      <td>0.02468348</td>\n",
       "      <td>0.01976847</td>\n",
       "      <td>0.05799045</td>\n",
       "      <td>-0.01768577</td>\n",
       "      <td>0.01713257</td>\n",
       "      <td>-0.00819372</td>\n",
       "      <td>0.01741535</td>\n",
       "      <td>0.00338602</td>\n",
       "      <td>0.00814926</td>\n",
       "      <td>-0.00474296</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01539193</td>\n",
       "      <td>0.01351594</td>\n",
       "      <td>0.04471023</td>\n",
       "      <td>0.00435700</td>\n",
       "      <td>0.01622211</td>\n",
       "      <td>0.00163542</td>\n",
       "      <td>0.01341047</td>\n",
       "      <td>0.01578682</td>\n",
       "      <td>0.03562574</td>\n",
       "      <td>0.00815639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-16 00:00:00+00:00</th>\n",
       "      <td>0.01078027</td>\n",
       "      <td>0.01419020</td>\n",
       "      <td>0.02977102</td>\n",
       "      <td>0.00768495</td>\n",
       "      <td>0.02199833</td>\n",
       "      <td>-0.00098521</td>\n",
       "      <td>0.01007990</td>\n",
       "      <td>0.02210700</td>\n",
       "      <td>0.01637949</td>\n",
       "      <td>0.01733616</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00471295</td>\n",
       "      <td>0.00053077</td>\n",
       "      <td>-0.00352152</td>\n",
       "      <td>0.00850674</td>\n",
       "      <td>0.02493746</td>\n",
       "      <td>0.02071897</td>\n",
       "      <td>0.01280939</td>\n",
       "      <td>0.00860603</td>\n",
       "      <td>0.01075467</td>\n",
       "      <td>0.00253774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-17 00:00:00+00:00</th>\n",
       "      <td>-0.01721238</td>\n",
       "      <td>-0.01712199</td>\n",
       "      <td>-0.04819014</td>\n",
       "      <td>-0.02119576</td>\n",
       "      <td>-0.02169610</td>\n",
       "      <td>0.00738610</td>\n",
       "      <td>-0.01715337</td>\n",
       "      <td>-0.05335502</td>\n",
       "      <td>-0.01423190</td>\n",
       "      <td>-0.02450989</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.00156361</td>\n",
       "      <td>-0.01814726</td>\n",
       "      <td>-0.01503666</td>\n",
       "      <td>-0.00314212</td>\n",
       "      <td>-0.00778738</td>\n",
       "      <td>-0.02669682</td>\n",
       "      <td>-0.01822419</td>\n",
       "      <td>-0.01196571</td>\n",
       "      <td>-0.01596035</td>\n",
       "      <td>-0.00763722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-18 00:00:00+00:00</th>\n",
       "      <td>-0.04108447</td>\n",
       "      <td>-0.03225884</td>\n",
       "      <td>-0.02286262</td>\n",
       "      <td>-0.02706364</td>\n",
       "      <td>-0.01134153</td>\n",
       "      <td>-0.00449706</td>\n",
       "      <td>-0.03446098</td>\n",
       "      <td>-0.01288309</td>\n",
       "      <td>-0.03067941</td>\n",
       "      <td>-0.01693954</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01901256</td>\n",
       "      <td>-0.01231427</td>\n",
       "      <td>-0.00872355</td>\n",
       "      <td>-0.01045055</td>\n",
       "      <td>-0.00394377</td>\n",
       "      <td>-0.01700150</td>\n",
       "      <td>-0.00499057</td>\n",
       "      <td>-0.01738362</td>\n",
       "      <td>-0.03784484</td>\n",
       "      <td>-0.00279062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-21 00:00:00+00:00</th>\n",
       "      <td>0.00945523</td>\n",
       "      <td>0.03186317</td>\n",
       "      <td>0.00053085</td>\n",
       "      <td>0.01225425</td>\n",
       "      <td>0.00824462</td>\n",
       "      <td>0.00991570</td>\n",
       "      <td>0.00777786</td>\n",
       "      <td>0.01040390</td>\n",
       "      <td>0.00339503</td>\n",
       "      <td>0.01196200</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00635765</td>\n",
       "      <td>0.01677569</td>\n",
       "      <td>-0.00025549</td>\n",
       "      <td>0.00703494</td>\n",
       "      <td>0.01477910</td>\n",
       "      <td>0.00835952</td>\n",
       "      <td>0.02171387</td>\n",
       "      <td>0.01284185</td>\n",
       "      <td>0.00227072</td>\n",
       "      <td>0.01589418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-22 00:00:00+00:00</th>\n",
       "      <td>0.01050225</td>\n",
       "      <td>0.01167033</td>\n",
       "      <td>-0.01175973</td>\n",
       "      <td>-0.00092672</td>\n",
       "      <td>0.02474629</td>\n",
       "      <td>0.00261687</td>\n",
       "      <td>0.00997788</td>\n",
       "      <td>0.00747281</td>\n",
       "      <td>0.02401222</td>\n",
       "      <td>0.00332573</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03167093</td>\n",
       "      <td>0.00273487</td>\n",
       "      <td>0.00505438</td>\n",
       "      <td>0.01004736</td>\n",
       "      <td>0.03886271</td>\n",
       "      <td>0.00997684</td>\n",
       "      <td>-0.00544780</td>\n",
       "      <td>0.01496575</td>\n",
       "      <td>0.01455341</td>\n",
       "      <td>0.00802720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-23 00:00:00+00:00</th>\n",
       "      <td>0.01180348</td>\n",
       "      <td>0.00921901</td>\n",
       "      <td>0.00832501</td>\n",
       "      <td>0.01286896</td>\n",
       "      <td>0.01717833</td>\n",
       "      <td>0.00756710</td>\n",
       "      <td>0.01395006</td>\n",
       "      <td>0.00636498</td>\n",
       "      <td>0.00937966</td>\n",
       "      <td>0.00829624</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00919881</td>\n",
       "      <td>0.00950124</td>\n",
       "      <td>0.03270236</td>\n",
       "      <td>0.00758616</td>\n",
       "      <td>0.01119292</td>\n",
       "      <td>0.01723748</td>\n",
       "      <td>0.01534943</td>\n",
       "      <td>0.01021896</td>\n",
       "      <td>0.01877295</td>\n",
       "      <td>0.00544406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-24 00:00:00+00:00</th>\n",
       "      <td>-0.00368236</td>\n",
       "      <td>0.01202196</td>\n",
       "      <td>0.00046505</td>\n",
       "      <td>-0.00534053</td>\n",
       "      <td>-0.00204082</td>\n",
       "      <td>0.00009036</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>-0.00181999</td>\n",
       "      <td>-0.00422386</td>\n",
       "      <td>0.00567317</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00962284</td>\n",
       "      <td>-0.00062007</td>\n",
       "      <td>-0.01072430</td>\n",
       "      <td>-0.00212741</td>\n",
       "      <td>0.00555290</td>\n",
       "      <td>-0.00161385</td>\n",
       "      <td>-0.00162043</td>\n",
       "      <td>0.00136401</td>\n",
       "      <td>0.00397518</td>\n",
       "      <td>0.00312135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-28 00:00:00+00:00</th>\n",
       "      <td>0.00704030</td>\n",
       "      <td>-0.01325882</td>\n",
       "      <td>0.00952567</td>\n",
       "      <td>-0.01120361</td>\n",
       "      <td>0.00495300</td>\n",
       "      <td>0.00230910</td>\n",
       "      <td>-0.00154955</td>\n",
       "      <td>-0.00144052</td>\n",
       "      <td>-0.00106045</td>\n",
       "      <td>-0.00616419</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00050303</td>\n",
       "      <td>-0.00106364</td>\n",
       "      <td>-0.00743906</td>\n",
       "      <td>0.00493013</td>\n",
       "      <td>-0.02113809</td>\n",
       "      <td>-0.00348374</td>\n",
       "      <td>-0.00217727</td>\n",
       "      <td>-0.00641306</td>\n",
       "      <td>-0.00503256</td>\n",
       "      <td>-0.00478388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-29 00:00:00+00:00</th>\n",
       "      <td>0.01944279</td>\n",
       "      <td>0.00625637</td>\n",
       "      <td>0.01095726</td>\n",
       "      <td>0.01797599</td>\n",
       "      <td>0.01191076</td>\n",
       "      <td>0.00556913</td>\n",
       "      <td>0.01754180</td>\n",
       "      <td>0.01191401</td>\n",
       "      <td>0.01199575</td>\n",
       "      <td>0.01522413</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01381318</td>\n",
       "      <td>0.00796362</td>\n",
       "      <td>0.00533553</td>\n",
       "      <td>0.01143615</td>\n",
       "      <td>0.01128297</td>\n",
       "      <td>0.00430697</td>\n",
       "      <td>0.00541538</td>\n",
       "      <td>0.00723499</td>\n",
       "      <td>0.00617376</td>\n",
       "      <td>0.00899694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-30 00:00:00+00:00</th>\n",
       "      <td>-0.00638405</td>\n",
       "      <td>-0.01608535</td>\n",
       "      <td>-0.00525423</td>\n",
       "      <td>-0.01305616</td>\n",
       "      <td>0.00590373</td>\n",
       "      <td>0.00239063</td>\n",
       "      <td>-0.01201673</td>\n",
       "      <td>0.00512422</td>\n",
       "      <td>-0.00052449</td>\n",
       "      <td>-0.01325558</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01461683</td>\n",
       "      <td>-0.00706442</td>\n",
       "      <td>-0.01326109</td>\n",
       "      <td>-0.00807866</td>\n",
       "      <td>0.00184720</td>\n",
       "      <td>-0.00618212</td>\n",
       "      <td>-0.00578080</td>\n",
       "      <td>-0.00292090</td>\n",
       "      <td>-0.01223479</td>\n",
       "      <td>-0.00145450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31 00:00:00+00:00</th>\n",
       "      <td>-0.01243206</td>\n",
       "      <td>-0.01053186</td>\n",
       "      <td>-0.00587919</td>\n",
       "      <td>-0.01919944</td>\n",
       "      <td>-0.00937219</td>\n",
       "      <td>-0.01248112</td>\n",
       "      <td>-0.00795266</td>\n",
       "      <td>-0.01284442</td>\n",
       "      <td>-0.01406381</td>\n",
       "      <td>-0.02174525</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.01605213</td>\n",
       "      <td>-0.01817456</td>\n",
       "      <td>-0.00205030</td>\n",
       "      <td>-0.00911914</td>\n",
       "      <td>-0.00837082</td>\n",
       "      <td>-0.01003138</td>\n",
       "      <td>-0.01029925</td>\n",
       "      <td>0.00117577</td>\n",
       "      <td>-0.00621188</td>\n",
       "      <td>-0.00705088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-04 00:00:00+00:00</th>\n",
       "      <td>-0.02828157</td>\n",
       "      <td>-0.03398810</td>\n",
       "      <td>0.01149418</td>\n",
       "      <td>0.00085542</td>\n",
       "      <td>-0.02751240</td>\n",
       "      <td>-0.01774070</td>\n",
       "      <td>-0.04406668</td>\n",
       "      <td>-0.02555086</td>\n",
       "      <td>-0.02097083</td>\n",
       "      <td>-0.01591868</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.02476714</td>\n",
       "      <td>-0.02492212</td>\n",
       "      <td>-0.00627612</td>\n",
       "      <td>-0.03271090</td>\n",
       "      <td>-0.03105128</td>\n",
       "      <td>-0.01151995</td>\n",
       "      <td>-0.01148918</td>\n",
       "      <td>-0.00760365</td>\n",
       "      <td>-0.02161389</td>\n",
       "      <td>-0.01356408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-05 00:00:00+00:00</th>\n",
       "      <td>0.00405845</td>\n",
       "      <td>-0.00954098</td>\n",
       "      <td>-0.00683002</td>\n",
       "      <td>-0.02505441</td>\n",
       "      <td>-0.00416936</td>\n",
       "      <td>0.01462920</td>\n",
       "      <td>-0.00024665</td>\n",
       "      <td>0.00520704</td>\n",
       "      <td>0.00402305</td>\n",
       "      <td>-0.00734750</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00209794</td>\n",
       "      <td>0.01486318</td>\n",
       "      <td>0.00851070</td>\n",
       "      <td>0.02039022</td>\n",
       "      <td>-0.00195732</td>\n",
       "      <td>-0.00028634</td>\n",
       "      <td>-0.00249493</td>\n",
       "      <td>0.02081954</td>\n",
       "      <td>-0.01085325</td>\n",
       "      <td>0.01564723</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1256 rows × 490 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Equity(0 [A])  Equity(1 [AAL])  Equity(2 [AAP])  \\\n",
       "2011-01-07 00:00:00+00:00     0.00843652       0.01423027       0.02670202   \n",
       "2011-01-10 00:00:00+00:00    -0.00417428       0.00619534       0.00743543   \n",
       "2011-01-11 00:00:00+00:00    -0.00188630      -0.04364361      -0.00592730   \n",
       "2011-01-12 00:00:00+00:00     0.01725375      -0.00823708       0.01338721   \n",
       "2011-01-13 00:00:00+00:00    -0.00455851       0.00095465       0.00303109   \n",
       "2011-01-14 00:00:00+00:00     0.00343886      -0.00915594       0.00302193   \n",
       "2011-01-18 00:00:00+00:00     0.03425353      -0.06208490      -0.00428562   \n",
       "2011-01-19 00:00:00+00:00    -0.01022379      -0.00892857       0.00875376   \n",
       "2011-01-20 00:00:00+00:00    -0.00849568       0.02195299      -0.00473189   \n",
       "2011-01-21 00:00:00+00:00     0.00787281      -0.04103759       0.00554409   \n",
       "2011-01-24 00:00:00+00:00     0.01464622       0.02747253      -0.00110591   \n",
       "2011-01-25 00:00:00+00:00    -0.00673624       0.00298231       0.00914590   \n",
       "2011-01-26 00:00:00+00:00    -0.03073582       0.06613350       0.00359340   \n",
       "2011-01-27 00:00:00+00:00     0.00772081       0.02317753      -0.00155262   \n",
       "2011-01-28 00:00:00+00:00    -0.01884631      -0.08055268      -0.00093620   \n",
       "2011-01-31 00:00:00+00:00     0.00360809      -0.02361480      -0.00235062   \n",
       "2011-02-01 00:00:00+00:00     0.01165376      -0.00104701      -0.00921769   \n",
       "2011-02-02 00:00:00+00:00     0.01011176      -0.03930406      -0.02747650   \n",
       "2011-02-03 00:00:00+00:00    -0.00028893       0.00730962       0.01412639   \n",
       "2011-02-04 00:00:00+00:00     0.00562724      -0.03649951       0.02401434   \n",
       "2011-02-07 00:00:00+00:00     0.00770895       0.05204586       0.00811404   \n",
       "2011-02-08 00:00:00+00:00     0.01085425       0.01645475       0.00620226   \n",
       "2011-02-09 00:00:00+00:00     0.00466351       0.00000000       0.01695500   \n",
       "2011-02-10 00:00:00+00:00     0.00041298      -0.00304846      -0.01136679   \n",
       "2011-02-11 00:00:00+00:00    -0.00714982       0.02836356       0.00076442   \n",
       "2011-02-14 00:00:00+00:00     0.00166312      -0.01579001      -0.02327358   \n",
       "2011-02-15 00:00:00+00:00    -0.01190476       0.01104282      -0.00392614   \n",
       "2011-02-16 00:00:00+00:00     0.01512325       0.00195775       0.01385974   \n",
       "2011-02-17 00:00:00+00:00    -0.00331066      -0.01779103      -0.02484354   \n",
       "2011-02-18 00:00:00+00:00     0.01107771      -0.02010261      -0.00669325   \n",
       "...                                  ...              ...              ...   \n",
       "2015-11-20 00:00:00+00:00     0.00107212      -0.00237346       0.00276686   \n",
       "2015-11-23 00:00:00+00:00    -0.00709429       0.00237910      -0.00122838   \n",
       "2015-11-24 00:00:00+00:00     0.00208486      -0.02530879       0.00350426   \n",
       "2015-11-25 00:00:00+00:00    -0.00820649       0.00193813       0.00680544   \n",
       "2015-11-27 00:00:00+00:00    -0.00325586       0.00920070       0.00328491   \n",
       "2015-11-30 00:00:00+00:00    -0.01020870      -0.01032093      -0.01279784   \n",
       "2015-12-01 00:00:00+00:00     0.01574786       0.04849282      -0.00239635   \n",
       "2015-12-02 00:00:00+00:00    -0.00528420       0.01293012      -0.02716607   \n",
       "2015-12-03 00:00:00+00:00    -0.00952117      -0.01255465      -0.01994438   \n",
       "2015-12-04 00:00:00+00:00     0.02019919       0.03930296       0.00677909   \n",
       "2015-12-07 00:00:00+00:00    -0.00033987       0.01801987      -0.02957813   \n",
       "2015-12-08 00:00:00+00:00    -0.02330712      -0.02687583      -0.00886608   \n",
       "2015-12-09 00:00:00+00:00    -0.00516964      -0.02021340       0.02222267   \n",
       "2015-12-10 00:00:00+00:00     0.01503860       0.01009224      -0.00946596   \n",
       "2015-12-11 00:00:00+00:00    -0.01222670      -0.04535632      -0.01917906   \n",
       "2015-12-14 00:00:00+00:00    -0.01119741      -0.00761835      -0.00832534   \n",
       "2015-12-15 00:00:00+00:00     0.02468348       0.01976847       0.05799045   \n",
       "2015-12-16 00:00:00+00:00     0.01078027       0.01419020       0.02977102   \n",
       "2015-12-17 00:00:00+00:00    -0.01721238      -0.01712199      -0.04819014   \n",
       "2015-12-18 00:00:00+00:00    -0.04108447      -0.03225884      -0.02286262   \n",
       "2015-12-21 00:00:00+00:00     0.00945523       0.03186317       0.00053085   \n",
       "2015-12-22 00:00:00+00:00     0.01050225       0.01167033      -0.01175973   \n",
       "2015-12-23 00:00:00+00:00     0.01180348       0.00921901       0.00832501   \n",
       "2015-12-24 00:00:00+00:00    -0.00368236       0.01202196       0.00046505   \n",
       "2015-12-28 00:00:00+00:00     0.00704030      -0.01325882       0.00952567   \n",
       "2015-12-29 00:00:00+00:00     0.01944279       0.00625637       0.01095726   \n",
       "2015-12-30 00:00:00+00:00    -0.00638405      -0.01608535      -0.00525423   \n",
       "2015-12-31 00:00:00+00:00    -0.01243206      -0.01053186      -0.00587919   \n",
       "2016-01-04 00:00:00+00:00    -0.02828157      -0.03398810       0.01149418   \n",
       "2016-01-05 00:00:00+00:00     0.00405845      -0.00954098      -0.00683002   \n",
       "\n",
       "                           Equity(3 [AAPL])  Equity(4 [ABBV])  \\\n",
       "2011-01-07 00:00:00+00:00        0.00714639        0.00000000   \n",
       "2011-01-10 00:00:00+00:00        0.01885158        0.00000000   \n",
       "2011-01-11 00:00:00+00:00       -0.00236744        0.00000000   \n",
       "2011-01-12 00:00:00+00:00        0.00813289        0.00000000   \n",
       "2011-01-13 00:00:00+00:00        0.00365656        0.00000000   \n",
       "2011-01-14 00:00:00+00:00        0.00810620        0.00000000   \n",
       "2011-01-18 00:00:00+00:00       -0.02247419        0.00000000   \n",
       "2011-01-19 00:00:00+00:00       -0.00531448        0.00000000   \n",
       "2011-01-20 00:00:00+00:00       -0.01818900        0.00000000   \n",
       "2011-01-21 00:00:00+00:00       -0.01791080        0.00000000   \n",
       "2011-01-24 00:00:00+00:00        0.03283704        0.00000000   \n",
       "2011-01-25 00:00:00+00:00        0.01170955        0.00000000   \n",
       "2011-01-26 00:00:00+00:00        0.00719342        0.00000000   \n",
       "2011-01-27 00:00:00+00:00       -0.00187707        0.00000000   \n",
       "2011-01-28 00:00:00+00:00       -0.02070958        0.00000000   \n",
       "2011-01-31 00:00:00+00:00        0.00957845        0.00000000   \n",
       "2011-02-01 00:00:00+00:00        0.01681783        0.00000000   \n",
       "2011-02-02 00:00:00+00:00       -0.00205320        0.00000000   \n",
       "2011-02-03 00:00:00+00:00       -0.00256035        0.00000000   \n",
       "2011-02-04 00:00:00+00:00        0.00891547        0.00000000   \n",
       "2011-02-07 00:00:00+00:00        0.01553804        0.00000000   \n",
       "2011-02-08 00:00:00+00:00        0.00943966        0.00000000   \n",
       "2011-02-09 00:00:00+00:00        0.00833204        0.00000000   \n",
       "2011-02-10 00:00:00+00:00       -0.01010922        0.00000000   \n",
       "2011-02-11 00:00:00+00:00        0.00650490        0.00000000   \n",
       "2011-02-14 00:00:00+00:00        0.00652903        0.00000000   \n",
       "2011-02-15 00:00:00+00:00        0.00201613        0.00000000   \n",
       "2011-02-16 00:00:00+00:00        0.00896684        0.00000000   \n",
       "2011-02-17 00:00:00+00:00       -0.01330906        0.00000000   \n",
       "2011-02-18 00:00:00+00:00       -0.02159490        0.00000000   \n",
       "...                                     ...               ...   \n",
       "2015-11-20 00:00:00+00:00        0.00438086        0.00925624   \n",
       "2015-11-23 00:00:00+00:00       -0.01298872        0.00064612   \n",
       "2015-11-24 00:00:00+00:00        0.00959410       -0.00032285   \n",
       "2015-11-25 00:00:00+00:00       -0.00715141       -0.01374361   \n",
       "2015-11-27 00:00:00+00:00       -0.00186283       -0.00480271   \n",
       "2015-11-30 00:00:00+00:00        0.00415919       -0.03083813   \n",
       "2015-12-01 00:00:00+00:00       -0.00811576        0.01495718   \n",
       "2015-12-02 00:00:00+00:00       -0.00902983       -0.02202152   \n",
       "2015-12-03 00:00:00+00:00       -0.00929219       -0.02772394   \n",
       "2015-12-04 00:00:00+00:00        0.03324578        0.01889890   \n",
       "2015-12-07 00:00:00+00:00       -0.00629799       -0.01592051   \n",
       "2015-12-08 00:00:00+00:00       -0.00042489        0.00711446   \n",
       "2015-12-09 00:00:00+00:00       -0.02207699       -0.01130272   \n",
       "2015-12-10 00:00:00+00:00        0.00476320       -0.00446315   \n",
       "2015-12-11 00:00:00+00:00       -0.02573993       -0.03118548   \n",
       "2015-12-14 00:00:00+00:00       -0.00618871        0.02589759   \n",
       "2015-12-15 00:00:00+00:00       -0.01768577        0.01713257   \n",
       "2015-12-16 00:00:00+00:00        0.00768495        0.02199833   \n",
       "2015-12-17 00:00:00+00:00       -0.02119576       -0.02169610   \n",
       "2015-12-18 00:00:00+00:00       -0.02706364       -0.01134153   \n",
       "2015-12-21 00:00:00+00:00        0.01225425        0.00824462   \n",
       "2015-12-22 00:00:00+00:00       -0.00092672        0.02474629   \n",
       "2015-12-23 00:00:00+00:00        0.01286896        0.01717833   \n",
       "2015-12-24 00:00:00+00:00       -0.00534053       -0.00204082   \n",
       "2015-12-28 00:00:00+00:00       -0.01120361        0.00495300   \n",
       "2015-12-29 00:00:00+00:00        0.01797599        0.01191076   \n",
       "2015-12-30 00:00:00+00:00       -0.01305616        0.00590373   \n",
       "2015-12-31 00:00:00+00:00       -0.01919944       -0.00937219   \n",
       "2016-01-04 00:00:00+00:00        0.00085542       -0.02751240   \n",
       "2016-01-05 00:00:00+00:00       -0.02505441       -0.00416936   \n",
       "\n",
       "                           Equity(5 [ABC])  Equity(6 [ABT])  Equity(7 [ACN])  \\\n",
       "2011-01-07 00:00:00+00:00       0.00199434       0.00416541       0.00164769   \n",
       "2011-01-10 00:00:00+00:00      -0.00571429      -0.00889600      -0.00885384   \n",
       "2011-01-11 00:00:00+00:00       0.00978303      -0.00206747       0.01371668   \n",
       "2011-01-12 00:00:00+00:00      -0.00597922      -0.00101061       0.02296913   \n",
       "2011-01-13 00:00:00+00:00       0.01492537      -0.00445119      -0.00040011   \n",
       "2011-01-14 00:00:00+00:00       0.00139452      -0.01011076       0.00259000   \n",
       "2011-01-18 00:00:00+00:00       0.02088872       0.00662116       0.00699843   \n",
       "2011-01-19 00:00:00+00:00      -0.01714410       0.00275342      -0.00296182   \n",
       "2011-01-20 00:00:00+00:00       0.00479450       0.01332249       0.01871257   \n",
       "2011-01-21 00:00:00+00:00       0.01064197      -0.00085307      -0.00195169   \n",
       "2011-01-24 00:00:00+00:00       0.00524943       0.00522324       0.00842018   \n",
       "2011-01-25 00:00:00+00:00      -0.00936254      -0.00434674       0.00485935   \n",
       "2011-01-26 00:00:00+00:00       0.01222707      -0.02524087       0.01219180   \n",
       "2011-01-27 00:00:00+00:00       0.01183286      -0.00792793       0.00017944   \n",
       "2011-01-28 00:00:00+00:00      -0.02226215      -0.01919983      -0.01603463   \n",
       "2011-01-31 00:00:00+00:00      -0.00389347      -0.00724829      -0.00098003   \n",
       "2011-02-01 00:00:00+00:00       0.01197624       0.00154551       0.01749823   \n",
       "2011-02-02 00:00:00+00:00      -0.02119705       0.01106795       0.00363229   \n",
       "2011-02-03 00:00:00+00:00      -0.00366196       0.00589443       0.00417765   \n",
       "2011-02-04 00:00:00+00:00       0.03304712       0.00261602      -0.00436050   \n",
       "2011-02-07 00:00:00+00:00      -0.00217765      -0.00934092       0.00227918   \n",
       "2011-02-08 00:00:00+00:00       0.00218240      -0.00173831      -0.00055735   \n",
       "2011-02-09 00:00:00+00:00       0.00300577      -0.00153026       0.00113763   \n",
       "2011-02-10 00:00:00+00:00       0.00110085      -0.00110982       0.00550344   \n",
       "2011-02-11 00:00:00+00:00      -0.00137455       0.00153431      -0.01114607   \n",
       "2011-02-14 00:00:00+00:00       0.00575047       0.00924459       0.00020168   \n",
       "2011-02-15 00:00:00+00:00      -0.00732946       0.01674954      -0.00802079   \n",
       "2011-02-16 00:00:00+00:00      -0.00355392      -0.01050193       0.02732858   \n",
       "2011-02-17 00:00:00+00:00       0.02914771       0.00130066       0.01178385   \n",
       "2011-02-18 00:00:00+00:00       0.00961998       0.01210641      -0.00795272   \n",
       "...                                    ...              ...              ...   \n",
       "2015-11-20 00:00:00+00:00      -0.00090483       0.00611281       0.00643014   \n",
       "2015-11-23 00:00:00+00:00      -0.00372792      -0.01238148      -0.00120585   \n",
       "2015-11-24 00:00:00+00:00      -0.00233603       0.00020972      -0.00453713   \n",
       "2015-11-25 00:00:00+00:00       0.00436515      -0.00086201      -0.00233759   \n",
       "2015-11-27 00:00:00+00:00       0.00061184       0.00020986       0.00336265   \n",
       "2015-11-30 00:00:00+00:00      -0.00354229      -0.01100361      -0.00222774   \n",
       "2015-12-01 00:00:00+00:00       0.00871792       0.01202178       0.00848039   \n",
       "2015-12-02 00:00:00+00:00      -0.00653437      -0.00528731      -0.00499107   \n",
       "2015-12-03 00:00:00+00:00      -0.00141471      -0.02365007      -0.01542891   \n",
       "2015-12-04 00:00:00+00:00       0.01195750       0.02604566       0.02992398   \n",
       "2015-12-07 00:00:00+00:00       0.00089849       0.00572671      -0.00146283   \n",
       "2015-12-08 00:00:00+00:00       0.00490595      -0.00020917      -0.00027950   \n",
       "2015-12-09 00:00:00+00:00       0.00198396      -0.01294807      -0.01487559   \n",
       "2015-12-10 00:00:00+00:00       0.01271990       0.00777184       0.00289674   \n",
       "2015-12-11 00:00:00+00:00       0.00127956      -0.02096235      -0.02137978   \n",
       "2015-12-14 00:00:00+00:00       0.00440628       0.01014465       0.01007090   \n",
       "2015-12-15 00:00:00+00:00      -0.00819372       0.01741535       0.00338602   \n",
       "2015-12-16 00:00:00+00:00      -0.00098521       0.01007990       0.02210700   \n",
       "2015-12-17 00:00:00+00:00       0.00738610      -0.01715337      -0.05335502   \n",
       "2015-12-18 00:00:00+00:00      -0.00449706      -0.03446098      -0.01288309   \n",
       "2015-12-21 00:00:00+00:00       0.00991570       0.00777786       0.01040390   \n",
       "2015-12-22 00:00:00+00:00       0.00261687       0.00997788       0.00747281   \n",
       "2015-12-23 00:00:00+00:00       0.00756710       0.01395006       0.00636498   \n",
       "2015-12-24 00:00:00+00:00       0.00009036       0.00000000      -0.00181999   \n",
       "2015-12-28 00:00:00+00:00       0.00230910      -0.00154955      -0.00144052   \n",
       "2015-12-29 00:00:00+00:00       0.00556913       0.01754180       0.01191401   \n",
       "2015-12-30 00:00:00+00:00       0.00239063      -0.01201673       0.00512422   \n",
       "2015-12-31 00:00:00+00:00      -0.01248112      -0.00795266      -0.01284442   \n",
       "2016-01-04 00:00:00+00:00      -0.01774070      -0.04406668      -0.02555086   \n",
       "2016-01-05 00:00:00+00:00       0.01462920      -0.00024665       0.00520704   \n",
       "\n",
       "                           Equity(8 [ADBE])  Equity(9 [ADI])  \\\n",
       "2011-01-07 00:00:00+00:00       -0.00712736      -0.00581846   \n",
       "2011-01-10 00:00:00+00:00        0.02871411       0.00292626   \n",
       "2011-01-11 00:00:00+00:00        0.00060680       0.00875316   \n",
       "2011-01-12 00:00:00+00:00        0.01795027       0.00025710   \n",
       "2011-01-13 00:00:00+00:00       -0.00571905      -0.00501221   \n",
       "2011-01-14 00:00:00+00:00        0.01228280       0.01982692   \n",
       "2011-01-18 00:00:00+00:00        0.01154188       0.03264518   \n",
       "2011-01-19 00:00:00+00:00       -0.00789936      -0.02057462   \n",
       "2011-01-20 00:00:00+00:00       -0.01238573      -0.00281761   \n",
       "2011-01-21 00:00:00+00:00       -0.00656913      -0.00411277   \n",
       "2011-01-24 00:00:00+00:00        0.02284340       0.01497431   \n",
       "2011-01-25 00:00:00+00:00       -0.01381134      -0.01450491   \n",
       "2011-01-26 00:00:00+00:00       -0.00119190       0.00283652   \n",
       "2011-01-27 00:00:00+00:00        0.00984487       0.00747981   \n",
       "2011-01-28 00:00:00+00:00       -0.04017725      -0.02245999   \n",
       "2011-01-31 00:00:00+00:00        0.01723607       0.01381753   \n",
       "2011-02-01 00:00:00+00:00        0.01391831       0.02162417   \n",
       "2011-02-02 00:00:00+00:00       -0.00238735       0.00227994   \n",
       "2011-02-03 00:00:00+00:00        0.00299133      -0.01334112   \n",
       "2011-02-04 00:00:00+00:00       -0.00507009       0.01965916   \n",
       "2011-02-07 00:00:00+00:00        0.00599520      -0.00351381   \n",
       "2011-02-08 00:00:00+00:00        0.00029797      -0.00600987   \n",
       "2011-02-09 00:00:00+00:00       -0.01668156       0.00478144   \n",
       "2011-02-10 00:00:00+00:00        0.01696456       0.00451308   \n",
       "2011-02-11 00:00:00+00:00        0.00297885       0.01500657   \n",
       "2011-02-14 00:00:00+00:00        0.00564301       0.00987654   \n",
       "2011-02-15 00:00:00+00:00        0.00236267       0.00023854   \n",
       "2011-02-16 00:00:00+00:00        0.02209782      -0.00390509   \n",
       "2011-02-17 00:00:00+00:00        0.00835976       0.00855903   \n",
       "2011-02-18 00:00:00+00:00        0.01172098      -0.00169134   \n",
       "...                                     ...              ...   \n",
       "2015-11-20 00:00:00+00:00        0.00054490      -0.00584294   \n",
       "2015-11-23 00:00:00+00:00        0.00163381      -0.04410655   \n",
       "2015-11-24 00:00:00+00:00        0.00043497       0.06374097   \n",
       "2015-11-25 00:00:00+00:00       -0.00250000      -0.00281048   \n",
       "2015-11-27 00:00:00+00:00        0.00435872       0.00331472   \n",
       "2015-11-30 00:00:00+00:00       -0.00770316       0.01952228   \n",
       "2015-12-01 00:00:00+00:00        0.01191778      -0.00097042   \n",
       "2015-12-02 00:00:00+00:00       -0.00572663      -0.00699034   \n",
       "2015-12-03 00:00:00+00:00       -0.02292980      -0.02782630   \n",
       "2015-12-04 00:00:00+00:00        0.02969636       0.00271314   \n",
       "2015-12-07 00:00:00+00:00       -0.03218838      -0.01198796   \n",
       "2015-12-08 00:00:00+00:00        0.02366071      -0.00821590   \n",
       "2015-12-09 00:00:00+00:00       -0.02354993      -0.02360837   \n",
       "2015-12-10 00:00:00+00:00       -0.00669942       0.00882138   \n",
       "2015-12-11 00:00:00+00:00        0.02765288      -0.00384301   \n",
       "2015-12-14 00:00:00+00:00        0.02012689      -0.00193824   \n",
       "2015-12-15 00:00:00+00:00        0.00814926      -0.00474296   \n",
       "2015-12-16 00:00:00+00:00        0.01637949       0.01733616   \n",
       "2015-12-17 00:00:00+00:00       -0.01423190      -0.02450989   \n",
       "2015-12-18 00:00:00+00:00       -0.03067941      -0.01693954   \n",
       "2015-12-21 00:00:00+00:00        0.00339503       0.01196200   \n",
       "2015-12-22 00:00:00+00:00        0.02401222       0.00332573   \n",
       "2015-12-23 00:00:00+00:00        0.00937966       0.00829624   \n",
       "2015-12-24 00:00:00+00:00       -0.00422386       0.00567317   \n",
       "2015-12-28 00:00:00+00:00       -0.00106045      -0.00616419   \n",
       "2015-12-29 00:00:00+00:00        0.01199575       0.01522413   \n",
       "2015-12-30 00:00:00+00:00       -0.00052449      -0.01325558   \n",
       "2015-12-31 00:00:00+00:00       -0.01406381      -0.02174525   \n",
       "2016-01-04 00:00:00+00:00       -0.02097083      -0.01591868   \n",
       "2016-01-05 00:00:00+00:00        0.00402305      -0.00734750   \n",
       "\n",
       "                                 ...          Equity(481 [XL])  \\\n",
       "2011-01-07 00:00:00+00:00        ...               -0.00183775   \n",
       "2011-01-10 00:00:00+00:00        ...                0.00094687   \n",
       "2011-01-11 00:00:00+00:00        ...                0.00131385   \n",
       "2011-01-12 00:00:00+00:00        ...                0.00498609   \n",
       "2011-01-13 00:00:00+00:00        ...                0.03049927   \n",
       "2011-01-14 00:00:00+00:00        ...                0.02660653   \n",
       "2011-01-18 00:00:00+00:00        ...                0.00167843   \n",
       "2011-01-19 00:00:00+00:00        ...               -0.01483416   \n",
       "2011-01-20 00:00:00+00:00        ...               -0.02451226   \n",
       "2011-01-21 00:00:00+00:00        ...                0.00000000   \n",
       "2011-01-24 00:00:00+00:00        ...                0.01235897   \n",
       "2011-01-25 00:00:00+00:00        ...                0.00217821   \n",
       "2011-01-26 00:00:00+00:00        ...                0.00262839   \n",
       "2011-01-27 00:00:00+00:00        ...                0.01426699   \n",
       "2011-01-28 00:00:00+00:00        ...               -0.02564740   \n",
       "2011-01-31 00:00:00+00:00        ...                0.00484620   \n",
       "2011-02-01 00:00:00+00:00        ...                0.01568687   \n",
       "2011-02-02 00:00:00+00:00        ...               -0.01284550   \n",
       "2011-02-03 00:00:00+00:00        ...                0.01043038   \n",
       "2011-02-04 00:00:00+00:00        ...                0.00947084   \n",
       "2011-02-07 00:00:00+00:00        ...                0.00680069   \n",
       "2011-02-08 00:00:00+00:00        ...                0.00384577   \n",
       "2011-02-09 00:00:00+00:00        ...               -0.01183694   \n",
       "2011-02-10 00:00:00+00:00        ...               -0.00894677   \n",
       "2011-02-11 00:00:00+00:00        ...                0.00170520   \n",
       "2011-02-14 00:00:00+00:00        ...               -0.01161568   \n",
       "2011-02-15 00:00:00+00:00        ...               -0.00607872   \n",
       "2011-02-16 00:00:00+00:00        ...                0.00917384   \n",
       "2011-02-17 00:00:00+00:00        ...                0.01565577   \n",
       "2011-02-18 00:00:00+00:00        ...                0.05340361   \n",
       "...                              ...                       ...   \n",
       "2015-11-20 00:00:00+00:00        ...                0.00813121   \n",
       "2015-11-23 00:00:00+00:00        ...               -0.00469574   \n",
       "2015-11-24 00:00:00+00:00        ...               -0.00077707   \n",
       "2015-11-25 00:00:00+00:00        ...               -0.00888765   \n",
       "2015-11-27 00:00:00+00:00        ...                0.00473588   \n",
       "2015-11-30 00:00:00+00:00        ...                0.00421152   \n",
       "2015-12-01 00:00:00+00:00        ...                0.01519233   \n",
       "2015-12-02 00:00:00+00:00        ...               -0.00385752   \n",
       "2015-12-03 00:00:00+00:00        ...               -0.00829420   \n",
       "2015-12-04 00:00:00+00:00        ...                0.02221053   \n",
       "2015-12-07 00:00:00+00:00        ...                0.00000000   \n",
       "2015-12-08 00:00:00+00:00        ...               -0.00460567   \n",
       "2015-12-09 00:00:00+00:00        ...               -0.01309164   \n",
       "2015-12-10 00:00:00+00:00        ...               -0.00675676   \n",
       "2015-12-11 00:00:00+00:00        ...               -0.01493822   \n",
       "2015-12-14 00:00:00+00:00        ...                0.00721594   \n",
       "2015-12-15 00:00:00+00:00        ...                0.01539193   \n",
       "2015-12-16 00:00:00+00:00        ...                0.00471295   \n",
       "2015-12-17 00:00:00+00:00        ...               -0.00156361   \n",
       "2015-12-18 00:00:00+00:00        ...               -0.01901256   \n",
       "2015-12-21 00:00:00+00:00        ...                0.00635765   \n",
       "2015-12-22 00:00:00+00:00        ...                0.03167093   \n",
       "2015-12-23 00:00:00+00:00        ...                0.00919881   \n",
       "2015-12-24 00:00:00+00:00        ...                0.00962284   \n",
       "2015-12-28 00:00:00+00:00        ...                0.00050303   \n",
       "2015-12-29 00:00:00+00:00        ...                0.01381318   \n",
       "2015-12-30 00:00:00+00:00        ...               -0.01461683   \n",
       "2015-12-31 00:00:00+00:00        ...               -0.01605213   \n",
       "2016-01-04 00:00:00+00:00        ...               -0.02476714   \n",
       "2016-01-05 00:00:00+00:00        ...                0.00209794   \n",
       "\n",
       "                           Equity(482 [XLNX])  Equity(483 [XOM])  \\\n",
       "2011-01-07 00:00:00+00:00         -0.00561865         0.00546091   \n",
       "2011-01-10 00:00:00+00:00          0.00781438        -0.00608100   \n",
       "2011-01-11 00:00:00+00:00          0.01017933         0.00744242   \n",
       "2011-01-12 00:00:00+00:00          0.01566621         0.01176334   \n",
       "2011-01-13 00:00:00+00:00         -0.00321668         0.00169383   \n",
       "2011-01-14 00:00:00+00:00          0.02589425         0.01474258   \n",
       "2011-01-18 00:00:00+00:00          0.00250133         0.01116324   \n",
       "2011-01-19 00:00:00+00:00         -0.02358990        -0.00596800   \n",
       "2011-01-20 00:00:00+00:00          0.00774353        -0.00626137   \n",
       "2011-01-21 00:00:00+00:00          0.00061472         0.01582494   \n",
       "2011-01-24 00:00:00+00:00          0.01601137        -0.00494300   \n",
       "2011-01-25 00:00:00+00:00          0.00627338         0.00115375   \n",
       "2011-01-26 00:00:00+00:00          0.00593383         0.01245258   \n",
       "2011-01-27 00:00:00+00:00          0.02116856         0.00275077   \n",
       "2011-01-28 00:00:00+00:00         -0.02010822        -0.01113056   \n",
       "2011-01-31 00:00:00+00:00          0.00029849         0.02139566   \n",
       "2011-02-01 00:00:00+00:00          0.03200298         0.04003746   \n",
       "2011-02-02 00:00:00+00:00         -0.00451785        -0.00595828   \n",
       "2011-02-03 00:00:00+00:00         -0.00816904         0.00034726   \n",
       "2011-02-04 00:00:00+00:00          0.02470898        -0.00191681   \n",
       "2011-02-07 00:00:00+00:00         -0.00507270         0.00780293   \n",
       "2011-02-08 00:00:00+00:00          0.00179527        -0.00607698   \n",
       "2011-02-09 00:00:00+00:00         -0.00179205        -0.00517814   \n",
       "2011-02-10 00:00:00+00:00          0.00391368         0.00787593   \n",
       "2011-02-11 00:00:00+00:00          0.01076538        -0.00456215   \n",
       "2011-02-14 00:00:00+00:00          0.00031846         0.02522953   \n",
       "2011-02-15 00:00:00+00:00         -0.00180403        -0.02285301   \n",
       "2011-02-16 00:00:00+00:00          0.00386265         0.00868160   \n",
       "2011-02-17 00:00:00+00:00          0.00031771         0.00227521   \n",
       "2011-02-18 00:00:00+00:00          0.00144687         0.00739258   \n",
       "...                                       ...                ...   \n",
       "2015-11-20 00:00:00+00:00          0.00041182        -0.00635194   \n",
       "2015-11-23 00:00:00+00:00         -0.00695468         0.00613134   \n",
       "2015-11-24 00:00:00+00:00          0.01295953         0.01993523   \n",
       "2015-11-25 00:00:00+00:00         -0.00445842        -0.00768963   \n",
       "2015-11-27 00:00:00+00:00          0.00447839        -0.00025651   \n",
       "2015-11-30 00:00:00+00:00          0.00934761         0.00529351   \n",
       "2015-12-01 00:00:00+00:00          0.01107484         0.00282087   \n",
       "2015-12-02 00:00:00+00:00         -0.02469292        -0.02857143   \n",
       "2015-12-03 00:00:00+00:00         -0.01081970        -0.01432669   \n",
       "2015-12-04 00:00:00+00:00          0.01032552         0.00573563   \n",
       "2015-12-07 00:00:00+00:00         -0.00879092        -0.02612215   \n",
       "2015-12-08 00:00:00+00:00         -0.00391018        -0.02825109   \n",
       "2015-12-09 00:00:00+00:00         -0.00993443         0.01338977   \n",
       "2015-12-10 00:00:00+00:00          0.00188278         0.00079770   \n",
       "2015-12-11 00:00:00+00:00         -0.01271252        -0.01783980   \n",
       "2015-12-14 00:00:00+00:00         -0.00094052         0.02273800   \n",
       "2015-12-15 00:00:00+00:00          0.01351594         0.04471023   \n",
       "2015-12-16 00:00:00+00:00          0.00053077        -0.00352152   \n",
       "2015-12-17 00:00:00+00:00         -0.01814726        -0.01503666   \n",
       "2015-12-18 00:00:00+00:00         -0.01231427        -0.00872355   \n",
       "2015-12-21 00:00:00+00:00          0.01677569        -0.00025549   \n",
       "2015-12-22 00:00:00+00:00          0.00273487         0.00505438   \n",
       "2015-12-23 00:00:00+00:00          0.00950124         0.03270236   \n",
       "2015-12-24 00:00:00+00:00         -0.00062007        -0.01072430   \n",
       "2015-12-28 00:00:00+00:00         -0.00106364        -0.00743906   \n",
       "2015-12-29 00:00:00+00:00          0.00796362         0.00533553   \n",
       "2015-12-30 00:00:00+00:00         -0.00706442        -0.01326109   \n",
       "2015-12-31 00:00:00+00:00         -0.01817456        -0.00205030   \n",
       "2016-01-04 00:00:00+00:00         -0.02492212        -0.00627612   \n",
       "2016-01-05 00:00:00+00:00          0.01486318         0.00851070   \n",
       "\n",
       "                           Equity(484 [XRAY])  Equity(485 [XRX])  \\\n",
       "2011-01-07 00:00:00+00:00         -0.00404361        -0.01395259   \n",
       "2011-01-10 00:00:00+00:00          0.01046585         0.00973303   \n",
       "2011-01-11 00:00:00+00:00          0.00735141         0.00611644   \n",
       "2011-01-12 00:00:00+00:00          0.02718194         0.00438630   \n",
       "2011-01-13 00:00:00+00:00          0.00054651        -0.01823475   \n",
       "2011-01-14 00:00:00+00:00         -0.00028748         0.02649446   \n",
       "2011-01-18 00:00:00+00:00          0.01158879         0.00604402   \n",
       "2011-01-19 00:00:00+00:00         -0.01989880        -0.01284667   \n",
       "2011-01-20 00:00:00+00:00         -0.00084112        -0.03379775   \n",
       "2011-01-21 00:00:00+00:00         -0.00304798        -0.00087153   \n",
       "2011-01-24 00:00:00+00:00          0.00165968         0.00804885   \n",
       "2011-01-25 00:00:00+00:00          0.00113369         0.01514317   \n",
       "2011-01-26 00:00:00+00:00          0.00055168        -0.07629122   \n",
       "2011-01-27 00:00:00+00:00          0.01639630         0.02466443   \n",
       "2011-01-28 00:00:00+00:00         -0.02187072        -0.02222859   \n",
       "2011-01-31 00:00:00+00:00         -0.00756028         0.00661503   \n",
       "2011-02-01 00:00:00+00:00          0.02479485         0.02449777   \n",
       "2011-02-02 00:00:00+00:00         -0.01038976        -0.00182689   \n",
       "2011-02-03 00:00:00+00:00          0.00855568         0.00459592   \n",
       "2011-02-04 00:00:00+00:00          0.00304817        -0.00550607   \n",
       "2011-02-07 00:00:00+00:00          0.00685187         0.00276828   \n",
       "2011-02-08 00:00:00+00:00          0.00518223        -0.00276064   \n",
       "2011-02-09 00:00:00+00:00         -0.01844088         0.00370461   \n",
       "2011-02-10 00:00:00+00:00          0.00551211        -0.00462381   \n",
       "2011-02-11 00:00:00+00:00          0.00714655         0.01202070   \n",
       "2011-02-14 00:00:00+00:00         -0.00544299         0.00547592   \n",
       "2011-02-15 00:00:00+00:00          0.00409742         0.00360404   \n",
       "2011-02-16 00:00:00+00:00          0.00028536         0.02709281   \n",
       "2011-02-17 00:00:00+00:00         -0.00191139         0.00000000   \n",
       "2011-02-18 00:00:00+00:00          0.01314812        -0.00438988   \n",
       "...                                       ...                ...   \n",
       "2015-11-20 00:00:00+00:00          0.00279330         0.00289932   \n",
       "2015-11-23 00:00:00+00:00          0.00734514         0.02769219   \n",
       "2015-11-24 00:00:00+00:00         -0.00956300        -0.01299182   \n",
       "2015-11-25 00:00:00+00:00         -0.00279190        -0.00191255   \n",
       "2015-11-27 00:00:00+00:00          0.00263307         0.00379485   \n",
       "2015-11-30 00:00:00+00:00         -0.00736321        -0.00752358   \n",
       "2015-12-01 00:00:00+00:00          0.02160044         0.01327550   \n",
       "2015-12-02 00:00:00+00:00          0.00757240        -0.02996241   \n",
       "2015-12-03 00:00:00+00:00          0.00273291        -0.00095925   \n",
       "2015-12-04 00:00:00+00:00          0.00749501         0.01159888   \n",
       "2015-12-07 00:00:00+00:00         -0.00190007        -0.02957591   \n",
       "2015-12-08 00:00:00+00:00         -0.01206744        -0.00492958   \n",
       "2015-12-09 00:00:00+00:00         -0.02106570        -0.00986868   \n",
       "2015-12-10 00:00:00+00:00         -0.00031695         0.01497042   \n",
       "2015-12-11 00:00:00+00:00         -0.01775464        -0.01279343   \n",
       "2015-12-14 00:00:00+00:00         -0.00183474        -0.01791305   \n",
       "2015-12-15 00:00:00+00:00          0.00435700         0.01622211   \n",
       "2015-12-16 00:00:00+00:00          0.00850674         0.02493746   \n",
       "2015-12-17 00:00:00+00:00         -0.00314212        -0.00778738   \n",
       "2015-12-18 00:00:00+00:00         -0.01045055        -0.00394377   \n",
       "2015-12-21 00:00:00+00:00          0.00703494         0.01477910   \n",
       "2015-12-22 00:00:00+00:00          0.01004736         0.03886271   \n",
       "2015-12-23 00:00:00+00:00          0.00758616         0.01119292   \n",
       "2015-12-24 00:00:00+00:00         -0.00212741         0.00555290   \n",
       "2015-12-28 00:00:00+00:00          0.00493013        -0.02113809   \n",
       "2015-12-29 00:00:00+00:00          0.01143615         0.01128297   \n",
       "2015-12-30 00:00:00+00:00         -0.00807866         0.00184720   \n",
       "2015-12-31 00:00:00+00:00         -0.00911914        -0.00837082   \n",
       "2016-01-04 00:00:00+00:00         -0.03271090        -0.03105128   \n",
       "2016-01-05 00:00:00+00:00          0.02039022        -0.00195732   \n",
       "\n",
       "                           Equity(486 [XYL])  Equity(487 [YUM])  \\\n",
       "2011-01-07 00:00:00+00:00         0.00000000         0.01245693   \n",
       "2011-01-10 00:00:00+00:00         0.00000000         0.00143979   \n",
       "2011-01-11 00:00:00+00:00         0.00000000        -0.00646974   \n",
       "2011-01-12 00:00:00+00:00         0.00000000         0.00263106   \n",
       "2011-01-13 00:00:00+00:00         0.00000000        -0.00508430   \n",
       "2011-01-14 00:00:00+00:00         0.00000000        -0.02166101   \n",
       "2011-01-18 00:00:00+00:00         0.00000000         0.02945339   \n",
       "2011-01-19 00:00:00+00:00         0.00000000         0.00081838   \n",
       "2011-01-20 00:00:00+00:00         0.00000000        -0.01318157   \n",
       "2011-01-21 00:00:00+00:00         0.00000000        -0.00759032   \n",
       "2011-01-24 00:00:00+00:00         0.00000000         0.00060118   \n",
       "2011-01-25 00:00:00+00:00         0.00000000        -0.00620848   \n",
       "2011-01-26 00:00:00+00:00         0.00000000        -0.00480301   \n",
       "2011-01-27 00:00:00+00:00         0.00000000        -0.00374620   \n",
       "2011-01-28 00:00:00+00:00         0.00000000        -0.02500085   \n",
       "2011-01-31 00:00:00+00:00         0.00000000         0.00774817   \n",
       "2011-02-01 00:00:00+00:00         0.00000000         0.01410150   \n",
       "2011-02-02 00:00:00+00:00         0.00000000         0.00656172   \n",
       "2011-02-03 00:00:00+00:00         0.00000000         0.03141255   \n",
       "2011-02-04 00:00:00+00:00         0.00000000         0.00140817   \n",
       "2011-02-07 00:00:00+00:00         0.00000000         0.00202754   \n",
       "2011-02-08 00:00:00+00:00         0.00000000         0.00385105   \n",
       "2011-02-09 00:00:00+00:00         0.00000000        -0.00182061   \n",
       "2011-02-10 00:00:00+00:00         0.00000000         0.00485295   \n",
       "2011-02-11 00:00:00+00:00         0.00000000         0.00061584   \n",
       "2011-02-14 00:00:00+00:00         0.00000000         0.01065725   \n",
       "2011-02-15 00:00:00+00:00         0.00000000         0.00852564   \n",
       "2011-02-16 00:00:00+00:00         0.00000000         0.00889849   \n",
       "2011-02-17 00:00:00+00:00         0.00000000         0.00390600   \n",
       "2011-02-18 00:00:00+00:00         0.00000000        -0.00411045   \n",
       "...                                      ...                ...   \n",
       "2015-11-20 00:00:00+00:00        -0.00449783         0.01505987   \n",
       "2015-11-23 00:00:00+00:00         0.00132239        -0.00096628   \n",
       "2015-11-24 00:00:00+00:00        -0.00187091        -0.00425172   \n",
       "2015-11-25 00:00:00+00:00         0.00482386         0.00289380   \n",
       "2015-11-27 00:00:00+00:00        -0.00213974         0.00510503   \n",
       "2015-11-30 00:00:00+00:00        -0.00692784        -0.00618325   \n",
       "2015-12-01 00:00:00+00:00         0.00858179         0.02716952   \n",
       "2015-12-02 00:00:00+00:00        -0.01833503         0.00631281   \n",
       "2015-12-03 00:00:00+00:00        -0.00567594        -0.02427203   \n",
       "2015-12-04 00:00:00+00:00         0.02477363         0.04115927   \n",
       "2015-12-07 00:00:00+00:00        -0.01964712         0.00353962   \n",
       "2015-12-08 00:00:00+00:00        -0.01707392        -0.01073476   \n",
       "2015-12-09 00:00:00+00:00        -0.00056952        -0.02367896   \n",
       "2015-12-10 00:00:00+00:00         0.01213779        -0.00825643   \n",
       "2015-12-11 00:00:00+00:00        -0.01306196        -0.02583602   \n",
       "2015-12-14 00:00:00+00:00         0.01158048         0.00490982   \n",
       "2015-12-15 00:00:00+00:00         0.00163542         0.01341047   \n",
       "2015-12-16 00:00:00+00:00         0.02071897         0.01280939   \n",
       "2015-12-17 00:00:00+00:00        -0.02669682        -0.01822419   \n",
       "2015-12-18 00:00:00+00:00        -0.01700150        -0.00499057   \n",
       "2015-12-21 00:00:00+00:00         0.00835952         0.02171387   \n",
       "2015-12-22 00:00:00+00:00         0.00997684        -0.00544780   \n",
       "2015-12-23 00:00:00+00:00         0.01723748         0.01534943   \n",
       "2015-12-24 00:00:00+00:00        -0.00161385        -0.00162043   \n",
       "2015-12-28 00:00:00+00:00        -0.00348374        -0.00217727   \n",
       "2015-12-29 00:00:00+00:00         0.00430697         0.00541538   \n",
       "2015-12-30 00:00:00+00:00        -0.00618212        -0.00578080   \n",
       "2015-12-31 00:00:00+00:00        -0.01003138        -0.01029925   \n",
       "2016-01-04 00:00:00+00:00        -0.01151995        -0.01148918   \n",
       "2016-01-05 00:00:00+00:00        -0.00028634        -0.00249493   \n",
       "\n",
       "                           Equity(488 [ZBH])  Equity(489 [ZION])  \\\n",
       "2011-01-07 00:00:00+00:00        -0.00018145         -0.01045802   \n",
       "2011-01-10 00:00:00+00:00         0.00778351         -0.01794496   \n",
       "2011-01-11 00:00:00+00:00         0.03567570          0.00746728   \n",
       "2011-01-12 00:00:00+00:00         0.01474083         -0.01190269   \n",
       "2011-01-13 00:00:00+00:00        -0.00466453         -0.00917796   \n",
       "2011-01-14 00:00:00+00:00         0.00594885          0.03317747   \n",
       "2011-01-18 00:00:00+00:00         0.00699753         -0.00853448   \n",
       "2011-01-19 00:00:00+00:00        -0.00409759         -0.01843318   \n",
       "2011-01-20 00:00:00+00:00        -0.00161165         -0.00797236   \n",
       "2011-01-21 00:00:00+00:00         0.00932467          0.02402000   \n",
       "2011-01-24 00:00:00+00:00        -0.01650140         -0.02302058   \n",
       "2011-01-25 00:00:00+00:00         0.01714176         -0.00883613   \n",
       "2011-01-26 00:00:00+00:00        -0.01952376         -0.01062584   \n",
       "2011-01-27 00:00:00+00:00         0.06875384          0.02016019   \n",
       "2011-01-28 00:00:00+00:00        -0.00847214         -0.01387340   \n",
       "2011-01-31 00:00:00+00:00         0.00990224          0.00637836   \n",
       "2011-02-01 00:00:00+00:00         0.01774607          0.03097047   \n",
       "2011-02-02 00:00:00+00:00         0.00516054         -0.00370596   \n",
       "2011-02-03 00:00:00+00:00        -0.00033292         -0.00039386   \n",
       "2011-02-04 00:00:00+00:00         0.00247147          0.01611067   \n",
       "2011-02-07 00:00:00+00:00        -0.01087565          0.02761741   \n",
       "2011-02-08 00:00:00+00:00        -0.00049496          0.00477967   \n",
       "2011-02-09 00:00:00+00:00        -0.00985108         -0.00475694   \n",
       "2011-02-10 00:00:00+00:00         0.01144950         -0.02649784   \n",
       "2011-02-11 00:00:00+00:00         0.00965987          0.01425557   \n",
       "2011-02-14 00:00:00+00:00         0.00248369         -0.01002123   \n",
       "2011-02-15 00:00:00+00:00        -0.00181453         -0.00446084   \n",
       "2011-02-16 00:00:00+00:00         0.01055741          0.00120638   \n",
       "2011-02-17 00:00:00+00:00         0.01532474         -0.00322747   \n",
       "2011-02-18 00:00:00+00:00         0.02378154         -0.01795968   \n",
       "...                                      ...                 ...   \n",
       "2015-11-20 00:00:00+00:00        -0.00317570          0.00000000   \n",
       "2015-11-23 00:00:00+00:00        -0.00858098         -0.00199203   \n",
       "2015-11-24 00:00:00+00:00        -0.00904325          0.00264987   \n",
       "2015-11-25 00:00:00+00:00        -0.00617420         -0.00030891   \n",
       "2015-11-27 00:00:00+00:00        -0.00286889          0.00501270   \n",
       "2015-11-30 00:00:00+00:00         0.00010131         -0.00433862   \n",
       "2015-12-01 00:00:00+00:00         0.01692683          0.01502831   \n",
       "2015-12-02 00:00:00+00:00        -0.00447256         -0.01544806   \n",
       "2015-12-03 00:00:00+00:00        -0.02836674         -0.01572478   \n",
       "2015-12-04 00:00:00+00:00         0.01197660          0.02445235   \n",
       "2015-12-07 00:00:00+00:00        -0.00138396         -0.04208519   \n",
       "2015-12-08 00:00:00+00:00        -0.00627720         -0.03181317   \n",
       "2015-12-09 00:00:00+00:00         0.00220474         -0.00748954   \n",
       "2015-12-10 00:00:00+00:00        -0.00029673          0.01475919   \n",
       "2015-12-11 00:00:00+00:00        -0.01011228         -0.02978165   \n",
       "2015-12-14 00:00:00+00:00         0.00535594         -0.01499098   \n",
       "2015-12-15 00:00:00+00:00         0.01578682          0.03562574   \n",
       "2015-12-16 00:00:00+00:00         0.00860603          0.01075467   \n",
       "2015-12-17 00:00:00+00:00        -0.01196571         -0.01596035   \n",
       "2015-12-18 00:00:00+00:00        -0.01738362         -0.03784484   \n",
       "2015-12-21 00:00:00+00:00         0.01284185          0.00227072   \n",
       "2015-12-22 00:00:00+00:00         0.01496575          0.01455341   \n",
       "2015-12-23 00:00:00+00:00         0.01021896          0.01877295   \n",
       "2015-12-24 00:00:00+00:00         0.00136401          0.00397518   \n",
       "2015-12-28 00:00:00+00:00        -0.00641306         -0.00503256   \n",
       "2015-12-29 00:00:00+00:00         0.00723499          0.00617376   \n",
       "2015-12-30 00:00:00+00:00        -0.00292090         -0.01223479   \n",
       "2015-12-31 00:00:00+00:00         0.00117577         -0.00621188   \n",
       "2016-01-04 00:00:00+00:00        -0.00760365         -0.02161389   \n",
       "2016-01-05 00:00:00+00:00         0.02081954         -0.01085325   \n",
       "\n",
       "                           Equity(490 [ZTS])  \n",
       "2011-01-07 00:00:00+00:00         0.00000000  \n",
       "2011-01-10 00:00:00+00:00         0.00000000  \n",
       "2011-01-11 00:00:00+00:00         0.00000000  \n",
       "2011-01-12 00:00:00+00:00         0.00000000  \n",
       "2011-01-13 00:00:00+00:00         0.00000000  \n",
       "2011-01-14 00:00:00+00:00         0.00000000  \n",
       "2011-01-18 00:00:00+00:00         0.00000000  \n",
       "2011-01-19 00:00:00+00:00         0.00000000  \n",
       "2011-01-20 00:00:00+00:00         0.00000000  \n",
       "2011-01-21 00:00:00+00:00         0.00000000  \n",
       "2011-01-24 00:00:00+00:00         0.00000000  \n",
       "2011-01-25 00:00:00+00:00         0.00000000  \n",
       "2011-01-26 00:00:00+00:00         0.00000000  \n",
       "2011-01-27 00:00:00+00:00         0.00000000  \n",
       "2011-01-28 00:00:00+00:00         0.00000000  \n",
       "2011-01-31 00:00:00+00:00         0.00000000  \n",
       "2011-02-01 00:00:00+00:00         0.00000000  \n",
       "2011-02-02 00:00:00+00:00         0.00000000  \n",
       "2011-02-03 00:00:00+00:00         0.00000000  \n",
       "2011-02-04 00:00:00+00:00         0.00000000  \n",
       "2011-02-07 00:00:00+00:00         0.00000000  \n",
       "2011-02-08 00:00:00+00:00         0.00000000  \n",
       "2011-02-09 00:00:00+00:00         0.00000000  \n",
       "2011-02-10 00:00:00+00:00         0.00000000  \n",
       "2011-02-11 00:00:00+00:00         0.00000000  \n",
       "2011-02-14 00:00:00+00:00         0.00000000  \n",
       "2011-02-15 00:00:00+00:00         0.00000000  \n",
       "2011-02-16 00:00:00+00:00         0.00000000  \n",
       "2011-02-17 00:00:00+00:00         0.00000000  \n",
       "2011-02-18 00:00:00+00:00         0.00000000  \n",
       "...                                      ...  \n",
       "2015-11-20 00:00:00+00:00         0.00894971  \n",
       "2015-11-23 00:00:00+00:00        -0.00760006  \n",
       "2015-11-24 00:00:00+00:00        -0.00065084  \n",
       "2015-11-25 00:00:00+00:00         0.00086836  \n",
       "2015-11-27 00:00:00+00:00         0.00234253  \n",
       "2015-11-30 00:00:00+00:00        -0.00807150  \n",
       "2015-12-01 00:00:00+00:00         0.00663191  \n",
       "2015-12-02 00:00:00+00:00        -0.01360986  \n",
       "2015-12-03 00:00:00+00:00        -0.02524442  \n",
       "2015-12-04 00:00:00+00:00         0.02788171  \n",
       "2015-12-07 00:00:00+00:00        -0.01184133  \n",
       "2015-12-08 00:00:00+00:00         0.00066573  \n",
       "2015-12-09 00:00:00+00:00        -0.01590047  \n",
       "2015-12-10 00:00:00+00:00         0.01969533  \n",
       "2015-12-11 00:00:00+00:00        -0.00585635  \n",
       "2015-12-14 00:00:00+00:00         0.01658331  \n",
       "2015-12-15 00:00:00+00:00         0.00815639  \n",
       "2015-12-16 00:00:00+00:00         0.00253774  \n",
       "2015-12-17 00:00:00+00:00        -0.00763722  \n",
       "2015-12-18 00:00:00+00:00        -0.00279062  \n",
       "2015-12-21 00:00:00+00:00         0.01589418  \n",
       "2015-12-22 00:00:00+00:00         0.00802720  \n",
       "2015-12-23 00:00:00+00:00         0.00544406  \n",
       "2015-12-24 00:00:00+00:00         0.00312135  \n",
       "2015-12-28 00:00:00+00:00        -0.00478388  \n",
       "2015-12-29 00:00:00+00:00         0.00899694  \n",
       "2015-12-30 00:00:00+00:00        -0.00145450  \n",
       "2015-12-31 00:00:00+00:00        -0.00705088  \n",
       "2016-01-04 00:00:00+00:00        -0.01356408  \n",
       "2016-01-05 00:00:00+00:00         0.01564723  \n",
       "\n",
       "[1256 rows x 490 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "five_year_returns = \\\n",
    "    get_pricing(\n",
    "        data_portal,\n",
    "        trading_calendar,\n",
    "        universe_tickers,\n",
    "        universe_end_date - pd.DateOffset(years=5),\n",
    "        universe_end_date)\\\n",
    "    .pct_change()[1:].fillna(0)\n",
    "\n",
    "five_year_returns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistical Risk Model\n",
    "It's time to build the risk model. You'll be creating a statistical risk model using PCA. So, the first thing is building the PCA model.\n",
    "## Fit PCA\n",
    "Implement `fit_pca` to fit a PCA model to the returns data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "\n",
    "def fit_pca(returns, num_factor_exposures, svd_solver):\n",
    "    \"\"\"\n",
    "    Fit PCA model with returns.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    returns : DataFrame\n",
    "        Returns for each ticker and date\n",
    "    num_factor_exposures : int\n",
    "        Number of factors for PCA\n",
    "    svd_solver: str\n",
    "        The solver to use for the PCA model\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    pca : PCA\n",
    "        Model fit to returns\n",
    "    \"\"\"\n",
    "    #TODO: Implement function\n",
    "    \n",
    "    pca = PCA(n_components=num_factor_exposures, svd_solver=svd_solver)\n",
    "    pca.fit(returns)\n",
    "    \n",
    "    return pca\n",
    "\n",
    "\n",
    "project_tests.test_fit_pca(fit_pca)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's see what the model looks like. First, we'll look at the PCA components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.04316847, -0.05874471, -0.03433256, ..., -0.03843904,\n",
       "        -0.06092493, -0.01367163],\n",
       "       [ 0.01955111,  0.19637679,  0.03451503, ...,  0.01749339,\n",
       "        -0.01044197,  0.01892192],\n",
       "       [-0.00993375,  0.07868756,  0.01133839, ..., -0.0157519 ,\n",
       "         0.01261759,  0.01867875],\n",
       "       ...,\n",
       "       [-0.01174265,  0.01398085,  0.05143999, ...,  0.04125323,\n",
       "         0.0035229 ,  0.03682367],\n",
       "       [ 0.00526925, -0.04680674,  0.05716915, ...,  0.00671842,\n",
       "        -0.02193923,  0.00833979],\n",
       "       [-0.00535269, -0.01599057,  0.08414961, ..., -0.01540844,\n",
       "         0.02188794,  0.01500221]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_factor_exposures = 20\n",
    "pca = fit_pca(five_year_returns, num_factor_exposures, 'full')\n",
    "\n",
    "pca.components_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's also look at the PCA's percent of variance explained by each factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 20 artists>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f01487a4080>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(np.arange(num_factor_exposures), pca.explained_variance_ratio_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You will see that the first factor dominates. The precise definition of each factor in a latent model is unknown, however we can guess at the likely interpretation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Factor Betas\n",
    "Implement `factor_betas` to get the factor betas from the PCA model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def factor_betas(pca, factor_beta_indices, factor_beta_columns):\n",
    "    \"\"\"\n",
    "    Get the factor betas from the PCA model.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    pca : PCA\n",
    "        Model fit to returns\n",
    "    factor_beta_indices : 1 dimensional Ndarray\n",
    "        Factor beta indices\n",
    "    factor_beta_columns : 1 dimensional Ndarray\n",
    "        Factor beta columns\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    factor_betas : DataFrame\n",
    "        Factor betas\n",
    "    \"\"\"\n",
    "    assert len(factor_beta_indices.shape) == 1\n",
    "    assert len(factor_beta_columns.shape) == 1\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    factor_betas = pd.DataFrame(\n",
    "            data=pca.components_.T,\n",
    "            index=factor_beta_indices\n",
    "    )\n",
    "    \n",
    "    return factor_betas\n",
    "\n",
    "\n",
    "project_tests.test_factor_betas(factor_betas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's view the factor betas from this model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <td>-0.04316847</td>\n",
       "      <td>0.01955111</td>\n",
       "      <td>-0.00993375</td>\n",
       "      <td>0.01054038</td>\n",
       "      <td>-0.01819821</td>\n",
       "      <td>0.01074517</td>\n",
       "      <td>0.00112915</td>\n",
       "      <td>0.03973914</td>\n",
       "      <td>-0.01380519</td>\n",
       "      <td>0.01273651</td>\n",
       "      <td>-0.02384028</td>\n",
       "      <td>-0.00141663</td>\n",
       "      <td>0.02099338</td>\n",
       "      <td>0.03460997</td>\n",
       "      <td>-0.03048936</td>\n",
       "      <td>0.03360635</td>\n",
       "      <td>-0.01142920</td>\n",
       "      <td>-0.01174265</td>\n",
       "      <td>0.00526925</td>\n",
       "      <td>-0.00535269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <td>-0.05874471</td>\n",
       "      <td>0.19637679</td>\n",
       "      <td>0.07868756</td>\n",
       "      <td>0.08209582</td>\n",
       "      <td>0.34847826</td>\n",
       "      <td>-0.13808246</td>\n",
       "      <td>0.07129285</td>\n",
       "      <td>0.10524788</td>\n",
       "      <td>-0.04588957</td>\n",
       "      <td>-0.08547793</td>\n",
       "      <td>0.00328328</td>\n",
       "      <td>0.10534284</td>\n",
       "      <td>0.06721603</td>\n",
       "      <td>-0.04405955</td>\n",
       "      <td>-0.02231617</td>\n",
       "      <td>0.01726309</td>\n",
       "      <td>-0.03310836</td>\n",
       "      <td>0.01398085</td>\n",
       "      <td>-0.04680674</td>\n",
       "      <td>-0.01599057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <td>-0.03433256</td>\n",
       "      <td>0.03451503</td>\n",
       "      <td>0.01133839</td>\n",
       "      <td>-0.02543666</td>\n",
       "      <td>-0.00817211</td>\n",
       "      <td>-0.01318319</td>\n",
       "      <td>-0.06095238</td>\n",
       "      <td>0.00654915</td>\n",
       "      <td>-0.03265404</td>\n",
       "      <td>-0.01351522</td>\n",
       "      <td>0.02896685</td>\n",
       "      <td>0.03836520</td>\n",
       "      <td>-0.04960451</td>\n",
       "      <td>-0.00524576</td>\n",
       "      <td>-0.02196994</td>\n",
       "      <td>0.02976718</td>\n",
       "      <td>-0.01163585</td>\n",
       "      <td>0.05143999</td>\n",
       "      <td>0.05716915</td>\n",
       "      <td>0.08414961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <td>-0.03409988</td>\n",
       "      <td>-0.00139319</td>\n",
       "      <td>0.03946700</td>\n",
       "      <td>-0.01721303</td>\n",
       "      <td>-0.03046983</td>\n",
       "      <td>-0.01757067</td>\n",
       "      <td>0.02325117</td>\n",
       "      <td>0.01142987</td>\n",
       "      <td>-0.02656849</td>\n",
       "      <td>-0.00771904</td>\n",
       "      <td>0.02686350</td>\n",
       "      <td>0.00731877</td>\n",
       "      <td>0.00481832</td>\n",
       "      <td>0.01288623</td>\n",
       "      <td>0.05256513</td>\n",
       "      <td>-0.07344470</td>\n",
       "      <td>-0.03179158</td>\n",
       "      <td>0.09079374</td>\n",
       "      <td>-0.01118851</td>\n",
       "      <td>0.04291373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <td>-0.01803099</td>\n",
       "      <td>0.02568151</td>\n",
       "      <td>0.00435183</td>\n",
       "      <td>-0.07078179</td>\n",
       "      <td>0.01319937</td>\n",
       "      <td>0.05427710</td>\n",
       "      <td>-0.01567842</td>\n",
       "      <td>0.04046172</td>\n",
       "      <td>-0.01245487</td>\n",
       "      <td>-0.03515086</td>\n",
       "      <td>-0.05132433</td>\n",
       "      <td>-0.04041614</td>\n",
       "      <td>-0.05120320</td>\n",
       "      <td>-0.01858166</td>\n",
       "      <td>-0.01126857</td>\n",
       "      <td>-0.04200714</td>\n",
       "      <td>0.01588559</td>\n",
       "      <td>0.04598554</td>\n",
       "      <td>0.01599288</td>\n",
       "      <td>0.06587978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <td>-0.02890016</td>\n",
       "      <td>0.03259161</td>\n",
       "      <td>-0.00742074</td>\n",
       "      <td>-0.03355183</td>\n",
       "      <td>-0.01152149</td>\n",
       "      <td>0.02648421</td>\n",
       "      <td>0.01084965</td>\n",
       "      <td>-0.00570393</td>\n",
       "      <td>0.01354800</td>\n",
       "      <td>-0.02967931</td>\n",
       "      <td>-0.03161765</td>\n",
       "      <td>0.01715152</td>\n",
       "      <td>-0.00304998</td>\n",
       "      <td>0.02635564</td>\n",
       "      <td>0.00787900</td>\n",
       "      <td>0.00833106</td>\n",
       "      <td>-0.01834622</td>\n",
       "      <td>-0.01391370</td>\n",
       "      <td>0.01062042</td>\n",
       "      <td>-0.02739565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <td>-0.02905740</td>\n",
       "      <td>0.02977821</td>\n",
       "      <td>-0.02970871</td>\n",
       "      <td>-0.03574263</td>\n",
       "      <td>-0.01157351</td>\n",
       "      <td>0.06020073</td>\n",
       "      <td>-0.02004042</td>\n",
       "      <td>0.04098522</td>\n",
       "      <td>-0.01803987</td>\n",
       "      <td>-0.00620785</td>\n",
       "      <td>-0.03157790</td>\n",
       "      <td>-0.02308041</td>\n",
       "      <td>-0.01436789</td>\n",
       "      <td>-0.00054254</td>\n",
       "      <td>-0.01932887</td>\n",
       "      <td>0.01428819</td>\n",
       "      <td>-0.03938064</td>\n",
       "      <td>0.01071208</td>\n",
       "      <td>0.01712006</td>\n",
       "      <td>0.00210689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <td>-0.04337745</td>\n",
       "      <td>0.00256907</td>\n",
       "      <td>0.00413229</td>\n",
       "      <td>-0.00349265</td>\n",
       "      <td>-0.05430743</td>\n",
       "      <td>0.00537434</td>\n",
       "      <td>0.00277996</td>\n",
       "      <td>0.03043220</td>\n",
       "      <td>-0.01880168</td>\n",
       "      <td>-0.00178336</td>\n",
       "      <td>-0.03540357</td>\n",
       "      <td>-0.01093170</td>\n",
       "      <td>0.02611241</td>\n",
       "      <td>-0.01233115</td>\n",
       "      <td>0.00322097</td>\n",
       "      <td>0.01770011</td>\n",
       "      <td>-0.00285123</td>\n",
       "      <td>-0.01235874</td>\n",
       "      <td>-0.01400935</td>\n",
       "      <td>-0.03855653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
       "      <td>-0.04730285</td>\n",
       "      <td>0.02661175</td>\n",
       "      <td>0.03057072</td>\n",
       "      <td>-0.02114690</td>\n",
       "      <td>-0.04838794</td>\n",
       "      <td>-0.00708698</td>\n",
       "      <td>0.00743385</td>\n",
       "      <td>0.00747095</td>\n",
       "      <td>0.01487098</td>\n",
       "      <td>-0.00153422</td>\n",
       "      <td>-0.01238383</td>\n",
       "      <td>-0.00667442</td>\n",
       "      <td>0.03500718</td>\n",
       "      <td>-0.04336579</td>\n",
       "      <td>0.01060255</td>\n",
       "      <td>-0.00637875</td>\n",
       "      <td>0.02127339</td>\n",
       "      <td>-0.03638845</td>\n",
       "      <td>0.00126811</td>\n",
       "      <td>-0.04844555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(9 [ADI])</th>\n",
       "      <td>-0.04712287</td>\n",
       "      <td>-0.00381150</td>\n",
       "      <td>0.05600847</td>\n",
       "      <td>-0.01553775</td>\n",
       "      <td>-0.06946243</td>\n",
       "      <td>-0.00560418</td>\n",
       "      <td>0.10070366</td>\n",
       "      <td>0.06307694</td>\n",
       "      <td>0.00160769</td>\n",
       "      <td>0.01912993</td>\n",
       "      <td>0.01101680</td>\n",
       "      <td>0.00348733</td>\n",
       "      <td>-0.05465749</td>\n",
       "      <td>-0.04223802</td>\n",
       "      <td>-0.00014275</td>\n",
       "      <td>-0.04843166</td>\n",
       "      <td>0.00374282</td>\n",
       "      <td>0.04583322</td>\n",
       "      <td>0.01483456</td>\n",
       "      <td>0.00768623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(10 [ADM])</th>\n",
       "      <td>-0.04375945</td>\n",
       "      <td>-0.01130045</td>\n",
       "      <td>-0.03457005</td>\n",
       "      <td>0.00400541</td>\n",
       "      <td>-0.00645333</td>\n",
       "      <td>0.01746845</td>\n",
       "      <td>-0.00146122</td>\n",
       "      <td>0.04177642</td>\n",
       "      <td>-0.00478644</td>\n",
       "      <td>-0.01859623</td>\n",
       "      <td>0.00422432</td>\n",
       "      <td>-0.00952513</td>\n",
       "      <td>-0.01336835</td>\n",
       "      <td>0.01753074</td>\n",
       "      <td>0.00993158</td>\n",
       "      <td>0.02405739</td>\n",
       "      <td>-0.02009143</td>\n",
       "      <td>-0.00246866</td>\n",
       "      <td>0.00264238</td>\n",
       "      <td>-0.00851815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(11 [ADP])</th>\n",
       "      <td>-0.03648136</td>\n",
       "      <td>0.02528125</td>\n",
       "      <td>-0.01114832</td>\n",
       "      <td>-0.00940984</td>\n",
       "      <td>-0.03357614</td>\n",
       "      <td>0.02887659</td>\n",
       "      <td>-0.00509280</td>\n",
       "      <td>0.04466799</td>\n",
       "      <td>-0.00676480</td>\n",
       "      <td>0.00335015</td>\n",
       "      <td>-0.00493401</td>\n",
       "      <td>0.00194010</td>\n",
       "      <td>-0.01057350</td>\n",
       "      <td>-0.00616905</td>\n",
       "      <td>-0.00351046</td>\n",
       "      <td>-0.00218630</td>\n",
       "      <td>-0.00363522</td>\n",
       "      <td>0.00584571</td>\n",
       "      <td>0.00578868</td>\n",
       "      <td>-0.02465380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(12 [ADS])</th>\n",
       "      <td>-0.04136654</td>\n",
       "      <td>0.01659887</td>\n",
       "      <td>0.01716323</td>\n",
       "      <td>-0.02418717</td>\n",
       "      <td>-0.00389740</td>\n",
       "      <td>0.00098181</td>\n",
       "      <td>-0.02299563</td>\n",
       "      <td>0.01316338</td>\n",
       "      <td>-0.02790599</td>\n",
       "      <td>0.00654660</td>\n",
       "      <td>0.00628604</td>\n",
       "      <td>-0.00342924</td>\n",
       "      <td>0.01596979</td>\n",
       "      <td>-0.02290249</td>\n",
       "      <td>0.01812681</td>\n",
       "      <td>0.00269984</td>\n",
       "      <td>-0.01166061</td>\n",
       "      <td>-0.02387829</td>\n",
       "      <td>-0.01844799</td>\n",
       "      <td>0.02639087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(13 [ADSK])</th>\n",
       "      <td>-0.06028785</td>\n",
       "      <td>0.01995266</td>\n",
       "      <td>0.05164356</td>\n",
       "      <td>0.00105689</td>\n",
       "      <td>-0.06889175</td>\n",
       "      <td>-0.04893180</td>\n",
       "      <td>0.04706144</td>\n",
       "      <td>-0.02746946</td>\n",
       "      <td>0.00290438</td>\n",
       "      <td>0.00534281</td>\n",
       "      <td>-0.01150281</td>\n",
       "      <td>-0.00105789</td>\n",
       "      <td>0.04046916</td>\n",
       "      <td>-0.03266419</td>\n",
       "      <td>0.02070996</td>\n",
       "      <td>0.02100687</td>\n",
       "      <td>0.05625388</td>\n",
       "      <td>-0.06442852</td>\n",
       "      <td>-0.03374250</td>\n",
       "      <td>-0.02718282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(14 [AEE])</th>\n",
       "      <td>-0.02646901</td>\n",
       "      <td>0.02222316</td>\n",
       "      <td>-0.10714999</td>\n",
       "      <td>-0.03824488</td>\n",
       "      <td>-0.00157895</td>\n",
       "      <td>-0.02310383</td>\n",
       "      <td>0.02412315</td>\n",
       "      <td>0.04419314</td>\n",
       "      <td>0.00041473</td>\n",
       "      <td>-0.02597657</td>\n",
       "      <td>0.02325386</td>\n",
       "      <td>-0.05456489</td>\n",
       "      <td>0.00729924</td>\n",
       "      <td>-0.00884432</td>\n",
       "      <td>0.02876494</td>\n",
       "      <td>0.02575176</td>\n",
       "      <td>0.03531642</td>\n",
       "      <td>-0.00801202</td>\n",
       "      <td>-0.03297087</td>\n",
       "      <td>-0.03074790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(15 [AEP])</th>\n",
       "      <td>-0.02263370</td>\n",
       "      <td>0.01880106</td>\n",
       "      <td>-0.10030310</td>\n",
       "      <td>-0.04210462</td>\n",
       "      <td>0.00205558</td>\n",
       "      <td>-0.03150526</td>\n",
       "      <td>0.02496444</td>\n",
       "      <td>0.05473617</td>\n",
       "      <td>0.00166554</td>\n",
       "      <td>-0.02261936</td>\n",
       "      <td>0.01766823</td>\n",
       "      <td>-0.04791054</td>\n",
       "      <td>-0.01334963</td>\n",
       "      <td>-0.00584932</td>\n",
       "      <td>0.03513664</td>\n",
       "      <td>0.02664964</td>\n",
       "      <td>0.03949487</td>\n",
       "      <td>0.00571290</td>\n",
       "      <td>-0.01621889</td>\n",
       "      <td>-0.01421124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(16 [AES])</th>\n",
       "      <td>-0.04557539</td>\n",
       "      <td>-0.01859287</td>\n",
       "      <td>-0.06960047</td>\n",
       "      <td>-0.02023102</td>\n",
       "      <td>0.01303429</td>\n",
       "      <td>-0.01748403</td>\n",
       "      <td>0.02894033</td>\n",
       "      <td>0.03053573</td>\n",
       "      <td>-0.01228381</td>\n",
       "      <td>-0.02623395</td>\n",
       "      <td>0.00383933</td>\n",
       "      <td>-0.05881947</td>\n",
       "      <td>-0.01427757</td>\n",
       "      <td>0.01071751</td>\n",
       "      <td>0.04800697</td>\n",
       "      <td>0.00823278</td>\n",
       "      <td>0.00968720</td>\n",
       "      <td>-0.02229136</td>\n",
       "      <td>-0.05731240</td>\n",
       "      <td>-0.01503171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(17 [AET])</th>\n",
       "      <td>-0.04072498</td>\n",
       "      <td>0.02731997</td>\n",
       "      <td>-0.00507231</td>\n",
       "      <td>-0.02802199</td>\n",
       "      <td>-0.00180323</td>\n",
       "      <td>0.06383735</td>\n",
       "      <td>0.00044765</td>\n",
       "      <td>-0.03716524</td>\n",
       "      <td>0.00999656</td>\n",
       "      <td>-0.09646860</td>\n",
       "      <td>-0.04571407</td>\n",
       "      <td>0.04559328</td>\n",
       "      <td>-0.08527159</td>\n",
       "      <td>0.06484179</td>\n",
       "      <td>-0.07164819</td>\n",
       "      <td>0.00852602</td>\n",
       "      <td>0.01958565</td>\n",
       "      <td>0.00069996</td>\n",
       "      <td>0.00650320</td>\n",
       "      <td>-0.05091908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(18 [AFL])</th>\n",
       "      <td>-0.05336864</td>\n",
       "      <td>0.00134653</td>\n",
       "      <td>-0.02782496</td>\n",
       "      <td>0.06688998</td>\n",
       "      <td>-0.01355109</td>\n",
       "      <td>0.04111821</td>\n",
       "      <td>-0.00401011</td>\n",
       "      <td>-0.01388700</td>\n",
       "      <td>0.01362724</td>\n",
       "      <td>0.00343990</td>\n",
       "      <td>-0.00993833</td>\n",
       "      <td>-0.00945988</td>\n",
       "      <td>0.01378441</td>\n",
       "      <td>-0.00676370</td>\n",
       "      <td>0.00047075</td>\n",
       "      <td>0.00042919</td>\n",
       "      <td>0.00010718</td>\n",
       "      <td>0.00397769</td>\n",
       "      <td>0.01677661</td>\n",
       "      <td>-0.03209361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(19 [AGN])</th>\n",
       "      <td>-0.03534102</td>\n",
       "      <td>0.04465091</td>\n",
       "      <td>0.02264084</td>\n",
       "      <td>-0.09556088</td>\n",
       "      <td>0.02867567</td>\n",
       "      <td>0.06515425</td>\n",
       "      <td>-0.02264216</td>\n",
       "      <td>-0.01928860</td>\n",
       "      <td>-0.02379115</td>\n",
       "      <td>-0.02578767</td>\n",
       "      <td>-0.02640179</td>\n",
       "      <td>-0.00734949</td>\n",
       "      <td>-0.01375720</td>\n",
       "      <td>0.01729325</td>\n",
       "      <td>0.00910558</td>\n",
       "      <td>0.01765223</td>\n",
       "      <td>-0.02289392</td>\n",
       "      <td>0.02583835</td>\n",
       "      <td>-0.02092126</td>\n",
       "      <td>0.01964563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(20 [AIG])</th>\n",
       "      <td>-0.05982324</td>\n",
       "      <td>0.00588515</td>\n",
       "      <td>-0.01162873</td>\n",
       "      <td>0.06668318</td>\n",
       "      <td>0.01385338</td>\n",
       "      <td>0.04010201</td>\n",
       "      <td>-0.01874280</td>\n",
       "      <td>-0.02394864</td>\n",
       "      <td>0.01457678</td>\n",
       "      <td>0.02061950</td>\n",
       "      <td>-0.00588748</td>\n",
       "      <td>-0.01886738</td>\n",
       "      <td>-0.00536267</td>\n",
       "      <td>-0.02808023</td>\n",
       "      <td>0.03227634</td>\n",
       "      <td>-0.01100650</td>\n",
       "      <td>-0.00994737</td>\n",
       "      <td>-0.04884961</td>\n",
       "      <td>-0.01447059</td>\n",
       "      <td>-0.00092722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(21 [AIV])</th>\n",
       "      <td>-0.04111735</td>\n",
       "      <td>0.03100207</td>\n",
       "      <td>-0.10211708</td>\n",
       "      <td>-0.00919327</td>\n",
       "      <td>0.01055402</td>\n",
       "      <td>-0.04739093</td>\n",
       "      <td>0.05244727</td>\n",
       "      <td>-0.09495931</td>\n",
       "      <td>0.04963087</td>\n",
       "      <td>0.00394508</td>\n",
       "      <td>0.02486556</td>\n",
       "      <td>0.02540802</td>\n",
       "      <td>0.02094801</td>\n",
       "      <td>-0.04206507</td>\n",
       "      <td>-0.02048654</td>\n",
       "      <td>-0.03732772</td>\n",
       "      <td>-0.01518008</td>\n",
       "      <td>0.02499635</td>\n",
       "      <td>0.04526409</td>\n",
       "      <td>0.06168561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(22 [AIZ])</th>\n",
       "      <td>-0.04150874</td>\n",
       "      <td>0.01695771</td>\n",
       "      <td>-0.03297298</td>\n",
       "      <td>0.04770347</td>\n",
       "      <td>-0.00003273</td>\n",
       "      <td>0.04220872</td>\n",
       "      <td>-0.00295921</td>\n",
       "      <td>0.01717020</td>\n",
       "      <td>0.02192818</td>\n",
       "      <td>-0.01979049</td>\n",
       "      <td>0.00845285</td>\n",
       "      <td>-0.00209358</td>\n",
       "      <td>-0.02121338</td>\n",
       "      <td>-0.01017076</td>\n",
       "      <td>0.02874684</td>\n",
       "      <td>0.01121282</td>\n",
       "      <td>0.00889890</td>\n",
       "      <td>-0.01278457</td>\n",
       "      <td>0.00035505</td>\n",
       "      <td>0.00788631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(23 [AJG])</th>\n",
       "      <td>-0.03351812</td>\n",
       "      <td>0.01723113</td>\n",
       "      <td>-0.02538602</td>\n",
       "      <td>0.01303842</td>\n",
       "      <td>-0.00670008</td>\n",
       "      <td>0.02117990</td>\n",
       "      <td>-0.01015869</td>\n",
       "      <td>0.00117300</td>\n",
       "      <td>0.00768045</td>\n",
       "      <td>0.00434263</td>\n",
       "      <td>-0.00824876</td>\n",
       "      <td>0.01520847</td>\n",
       "      <td>-0.00142810</td>\n",
       "      <td>-0.00802982</td>\n",
       "      <td>-0.00533986</td>\n",
       "      <td>-0.00140466</td>\n",
       "      <td>-0.00386327</td>\n",
       "      <td>-0.01466289</td>\n",
       "      <td>-0.00523534</td>\n",
       "      <td>0.01165450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(24 [AKAM])</th>\n",
       "      <td>-0.05587884</td>\n",
       "      <td>0.00798596</td>\n",
       "      <td>0.06670064</td>\n",
       "      <td>-0.00705542</td>\n",
       "      <td>-0.05149731</td>\n",
       "      <td>-0.04837770</td>\n",
       "      <td>0.02745032</td>\n",
       "      <td>-0.00620225</td>\n",
       "      <td>0.02668695</td>\n",
       "      <td>-0.01154353</td>\n",
       "      <td>0.00107161</td>\n",
       "      <td>-0.06366032</td>\n",
       "      <td>-0.07429360</td>\n",
       "      <td>0.00240076</td>\n",
       "      <td>0.12416841</td>\n",
       "      <td>0.13836518</td>\n",
       "      <td>0.00667736</td>\n",
       "      <td>0.00052245</td>\n",
       "      <td>-0.00203434</td>\n",
       "      <td>0.04370206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(25 [ALB])</th>\n",
       "      <td>-0.05982022</td>\n",
       "      <td>-0.03657577</td>\n",
       "      <td>0.01798669</td>\n",
       "      <td>0.01363477</td>\n",
       "      <td>-0.01737160</td>\n",
       "      <td>-0.03079886</td>\n",
       "      <td>0.04201500</td>\n",
       "      <td>0.00605395</td>\n",
       "      <td>-0.02047597</td>\n",
       "      <td>0.03736635</td>\n",
       "      <td>-0.00136191</td>\n",
       "      <td>0.01865916</td>\n",
       "      <td>0.04131905</td>\n",
       "      <td>0.09156602</td>\n",
       "      <td>-0.06656052</td>\n",
       "      <td>-0.01740400</td>\n",
       "      <td>-0.04603229</td>\n",
       "      <td>-0.02452548</td>\n",
       "      <td>-0.02975526</td>\n",
       "      <td>0.05708918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(26 [ALGN])</th>\n",
       "      <td>-0.05959262</td>\n",
       "      <td>0.01420686</td>\n",
       "      <td>0.04030645</td>\n",
       "      <td>-0.00223610</td>\n",
       "      <td>0.00381377</td>\n",
       "      <td>0.03559561</td>\n",
       "      <td>0.04027152</td>\n",
       "      <td>-0.09389473</td>\n",
       "      <td>0.03501042</td>\n",
       "      <td>0.00979674</td>\n",
       "      <td>-0.07400799</td>\n",
       "      <td>0.02204550</td>\n",
       "      <td>0.10784517</td>\n",
       "      <td>0.07096981</td>\n",
       "      <td>-0.05965948</td>\n",
       "      <td>-0.06617279</td>\n",
       "      <td>0.04902407</td>\n",
       "      <td>0.00156817</td>\n",
       "      <td>-0.03738565</td>\n",
       "      <td>-0.00223241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(27 [ALK])</th>\n",
       "      <td>-0.04887994</td>\n",
       "      <td>0.12134700</td>\n",
       "      <td>0.03971829</td>\n",
       "      <td>0.02356295</td>\n",
       "      <td>0.12648496</td>\n",
       "      <td>-0.05703822</td>\n",
       "      <td>0.02168427</td>\n",
       "      <td>0.06427147</td>\n",
       "      <td>-0.01679148</td>\n",
       "      <td>-0.02374091</td>\n",
       "      <td>-0.00059277</td>\n",
       "      <td>0.06395819</td>\n",
       "      <td>0.00033085</td>\n",
       "      <td>0.00597074</td>\n",
       "      <td>0.01458408</td>\n",
       "      <td>0.02170190</td>\n",
       "      <td>0.04257028</td>\n",
       "      <td>0.00789058</td>\n",
       "      <td>0.04963085</td>\n",
       "      <td>-0.04169300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(28 [ALL])</th>\n",
       "      <td>-0.03960459</td>\n",
       "      <td>0.01388579</td>\n",
       "      <td>-0.04298737</td>\n",
       "      <td>0.04705234</td>\n",
       "      <td>-0.00073028</td>\n",
       "      <td>0.03487833</td>\n",
       "      <td>-0.01156382</td>\n",
       "      <td>0.00877075</td>\n",
       "      <td>-0.00074882</td>\n",
       "      <td>-0.00128949</td>\n",
       "      <td>0.01279480</td>\n",
       "      <td>-0.00687101</td>\n",
       "      <td>-0.00986285</td>\n",
       "      <td>-0.00905731</td>\n",
       "      <td>0.02499562</td>\n",
       "      <td>-0.00494904</td>\n",
       "      <td>-0.00115539</td>\n",
       "      <td>0.00082421</td>\n",
       "      <td>0.00224048</td>\n",
       "      <td>-0.00639780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(29 [ALLE])</th>\n",
       "      <td>-0.01215236</td>\n",
       "      <td>0.01485340</td>\n",
       "      <td>0.01783511</td>\n",
       "      <td>-0.02151478</td>\n",
       "      <td>0.00049741</td>\n",
       "      <td>0.02208048</td>\n",
       "      <td>-0.01396758</td>\n",
       "      <td>0.04557020</td>\n",
       "      <td>-0.01575920</td>\n",
       "      <td>0.00225117</td>\n",
       "      <td>-0.01540340</td>\n",
       "      <td>-0.02608136</td>\n",
       "      <td>-0.00635063</td>\n",
       "      <td>-0.04124458</td>\n",
       "      <td>-0.00784737</td>\n",
       "      <td>-0.01976681</td>\n",
       "      <td>-0.00865976</td>\n",
       "      <td>0.03592991</td>\n",
       "      <td>0.00767178</td>\n",
       "      <td>0.03158662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(460 [VRSN])</th>\n",
       "      <td>-0.03899324</td>\n",
       "      <td>0.01109333</td>\n",
       "      <td>0.04065347</td>\n",
       "      <td>-0.01351021</td>\n",
       "      <td>-0.03906872</td>\n",
       "      <td>0.00844214</td>\n",
       "      <td>0.01232426</td>\n",
       "      <td>-0.02031680</td>\n",
       "      <td>-0.01427350</td>\n",
       "      <td>-0.00833205</td>\n",
       "      <td>-0.02485455</td>\n",
       "      <td>0.02115889</td>\n",
       "      <td>0.00062521</td>\n",
       "      <td>0.01354571</td>\n",
       "      <td>0.02242982</td>\n",
       "      <td>0.03594197</td>\n",
       "      <td>-0.00752310</td>\n",
       "      <td>-0.00611545</td>\n",
       "      <td>-0.02595021</td>\n",
       "      <td>-0.00005537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(461 [VRTX])</th>\n",
       "      <td>-0.04909379</td>\n",
       "      <td>0.09821506</td>\n",
       "      <td>0.07490354</td>\n",
       "      <td>-0.22874272</td>\n",
       "      <td>0.18286011</td>\n",
       "      <td>0.29795662</td>\n",
       "      <td>0.16783749</td>\n",
       "      <td>-0.08588784</td>\n",
       "      <td>0.17241447</td>\n",
       "      <td>0.26880311</td>\n",
       "      <td>0.58246071</td>\n",
       "      <td>-0.03464001</td>\n",
       "      <td>-0.12627708</td>\n",
       "      <td>0.36184696</td>\n",
       "      <td>-0.14161962</td>\n",
       "      <td>-0.10440960</td>\n",
       "      <td>0.15669116</td>\n",
       "      <td>0.00258548</td>\n",
       "      <td>0.05374391</td>\n",
       "      <td>-0.10088761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(462 [VTR])</th>\n",
       "      <td>-0.03291326</td>\n",
       "      <td>0.03068907</td>\n",
       "      <td>-0.12174007</td>\n",
       "      <td>-0.03757317</td>\n",
       "      <td>-0.00091457</td>\n",
       "      <td>-0.05384826</td>\n",
       "      <td>0.03088016</td>\n",
       "      <td>-0.06663125</td>\n",
       "      <td>0.04680683</td>\n",
       "      <td>0.00814737</td>\n",
       "      <td>-0.00367371</td>\n",
       "      <td>0.02294498</td>\n",
       "      <td>0.02497163</td>\n",
       "      <td>-0.03310961</td>\n",
       "      <td>-0.01353316</td>\n",
       "      <td>-0.02038055</td>\n",
       "      <td>-0.02035280</td>\n",
       "      <td>-0.00581734</td>\n",
       "      <td>0.04174183</td>\n",
       "      <td>0.02905358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(463 [VZ])</th>\n",
       "      <td>-0.07033190</td>\n",
       "      <td>0.00068427</td>\n",
       "      <td>-0.01610414</td>\n",
       "      <td>0.05981359</td>\n",
       "      <td>-0.01922444</td>\n",
       "      <td>0.03298870</td>\n",
       "      <td>-0.00089302</td>\n",
       "      <td>-0.00205798</td>\n",
       "      <td>0.03346385</td>\n",
       "      <td>-0.00820052</td>\n",
       "      <td>0.01313467</td>\n",
       "      <td>-0.01333200</td>\n",
       "      <td>0.00415716</td>\n",
       "      <td>-0.00898788</td>\n",
       "      <td>0.00645221</td>\n",
       "      <td>-0.01738755</td>\n",
       "      <td>0.00335631</td>\n",
       "      <td>-0.03321116</td>\n",
       "      <td>-0.03424556</td>\n",
       "      <td>-0.02031272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(464 [WAT])</th>\n",
       "      <td>-0.04787963</td>\n",
       "      <td>0.01976102</td>\n",
       "      <td>0.00630830</td>\n",
       "      <td>-0.01309650</td>\n",
       "      <td>-0.02786813</td>\n",
       "      <td>0.02969891</td>\n",
       "      <td>0.01135497</td>\n",
       "      <td>-0.01289454</td>\n",
       "      <td>0.02281688</td>\n",
       "      <td>0.00205729</td>\n",
       "      <td>-0.05584809</td>\n",
       "      <td>0.02544186</td>\n",
       "      <td>0.02317906</td>\n",
       "      <td>0.01111012</td>\n",
       "      <td>-0.03735916</td>\n",
       "      <td>0.03053670</td>\n",
       "      <td>-0.01161567</td>\n",
       "      <td>0.05062677</td>\n",
       "      <td>-0.01607733</td>\n",
       "      <td>-0.02896756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(465 [WBA])</th>\n",
       "      <td>-0.03065220</td>\n",
       "      <td>0.03421533</td>\n",
       "      <td>-0.01027997</td>\n",
       "      <td>-0.04006665</td>\n",
       "      <td>-0.01725655</td>\n",
       "      <td>0.02037446</td>\n",
       "      <td>-0.00923922</td>\n",
       "      <td>0.04976024</td>\n",
       "      <td>-0.02415684</td>\n",
       "      <td>-0.02906100</td>\n",
       "      <td>-0.01704871</td>\n",
       "      <td>-0.00978625</td>\n",
       "      <td>-0.02967145</td>\n",
       "      <td>-0.00855083</td>\n",
       "      <td>-0.02413786</td>\n",
       "      <td>0.01716925</td>\n",
       "      <td>0.02913337</td>\n",
       "      <td>0.03131836</td>\n",
       "      <td>0.01484323</td>\n",
       "      <td>0.00683342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(466 [WDC])</th>\n",
       "      <td>-0.05340806</td>\n",
       "      <td>-0.00776436</td>\n",
       "      <td>0.06117296</td>\n",
       "      <td>-0.01397300</td>\n",
       "      <td>-0.02898379</td>\n",
       "      <td>-0.05151527</td>\n",
       "      <td>0.10653647</td>\n",
       "      <td>0.00360483</td>\n",
       "      <td>-0.00177534</td>\n",
       "      <td>-0.01754129</td>\n",
       "      <td>0.03043852</td>\n",
       "      <td>-0.00839301</td>\n",
       "      <td>-0.11248908</td>\n",
       "      <td>0.02938310</td>\n",
       "      <td>0.13499041</td>\n",
       "      <td>0.17141412</td>\n",
       "      <td>0.11221658</td>\n",
       "      <td>-0.22112989</td>\n",
       "      <td>-0.05340130</td>\n",
       "      <td>0.27231589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(467 [WEC])</th>\n",
       "      <td>-0.02279115</td>\n",
       "      <td>0.02557593</td>\n",
       "      <td>-0.10491696</td>\n",
       "      <td>-0.04691482</td>\n",
       "      <td>-0.00109145</td>\n",
       "      <td>-0.02887550</td>\n",
       "      <td>0.01886320</td>\n",
       "      <td>0.05105952</td>\n",
       "      <td>0.01033805</td>\n",
       "      <td>-0.02583748</td>\n",
       "      <td>0.02240632</td>\n",
       "      <td>-0.04433949</td>\n",
       "      <td>0.00086058</td>\n",
       "      <td>-0.01721494</td>\n",
       "      <td>0.02251708</td>\n",
       "      <td>0.01433085</td>\n",
       "      <td>0.04781420</td>\n",
       "      <td>-0.01020607</td>\n",
       "      <td>-0.01687023</td>\n",
       "      <td>-0.01798607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(468 [WFC])</th>\n",
       "      <td>-0.05131308</td>\n",
       "      <td>0.01109305</td>\n",
       "      <td>-0.03096455</td>\n",
       "      <td>0.08514607</td>\n",
       "      <td>0.00399898</td>\n",
       "      <td>0.06168940</td>\n",
       "      <td>-0.01917540</td>\n",
       "      <td>-0.00980213</td>\n",
       "      <td>0.02012808</td>\n",
       "      <td>0.00922159</td>\n",
       "      <td>0.02755224</td>\n",
       "      <td>-0.01813056</td>\n",
       "      <td>-0.00880242</td>\n",
       "      <td>-0.02231278</td>\n",
       "      <td>0.02429464</td>\n",
       "      <td>0.00372331</td>\n",
       "      <td>-0.00454128</td>\n",
       "      <td>0.00335586</td>\n",
       "      <td>-0.02606330</td>\n",
       "      <td>0.01015222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(469 [WHR])</th>\n",
       "      <td>-0.05507142</td>\n",
       "      <td>0.03637282</td>\n",
       "      <td>-0.00100598</td>\n",
       "      <td>0.00590479</td>\n",
       "      <td>0.01092658</td>\n",
       "      <td>-0.06423664</td>\n",
       "      <td>-0.05592381</td>\n",
       "      <td>0.02535313</td>\n",
       "      <td>-0.04216377</td>\n",
       "      <td>0.13444741</td>\n",
       "      <td>-0.01648804</td>\n",
       "      <td>0.01561092</td>\n",
       "      <td>-0.05450337</td>\n",
       "      <td>0.04108206</td>\n",
       "      <td>0.04115321</td>\n",
       "      <td>0.02808061</td>\n",
       "      <td>0.04912976</td>\n",
       "      <td>0.02732405</td>\n",
       "      <td>0.01817701</td>\n",
       "      <td>0.01086811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(471 [WM])</th>\n",
       "      <td>-0.03151644</td>\n",
       "      <td>0.01496675</td>\n",
       "      <td>-0.03234348</td>\n",
       "      <td>-0.00111937</td>\n",
       "      <td>-0.02960532</td>\n",
       "      <td>0.00379175</td>\n",
       "      <td>-0.00185568</td>\n",
       "      <td>0.01331670</td>\n",
       "      <td>-0.00239896</td>\n",
       "      <td>-0.00938471</td>\n",
       "      <td>0.00277936</td>\n",
       "      <td>0.00920572</td>\n",
       "      <td>-0.00692979</td>\n",
       "      <td>0.03223594</td>\n",
       "      <td>-0.01134834</td>\n",
       "      <td>0.03628231</td>\n",
       "      <td>0.01820702</td>\n",
       "      <td>-0.01988943</td>\n",
       "      <td>0.02403495</td>\n",
       "      <td>0.01042652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(472 [WMB])</th>\n",
       "      <td>-0.05476156</td>\n",
       "      <td>-0.08924998</td>\n",
       "      <td>-0.02426238</td>\n",
       "      <td>-0.05723889</td>\n",
       "      <td>0.07886307</td>\n",
       "      <td>-0.01255032</td>\n",
       "      <td>-0.03519116</td>\n",
       "      <td>0.02300738</td>\n",
       "      <td>-0.03160335</td>\n",
       "      <td>-0.02914851</td>\n",
       "      <td>0.00854960</td>\n",
       "      <td>0.01996384</td>\n",
       "      <td>-0.01039337</td>\n",
       "      <td>-0.00287563</td>\n",
       "      <td>0.03826935</td>\n",
       "      <td>-0.02475861</td>\n",
       "      <td>-0.02989245</td>\n",
       "      <td>-0.01712986</td>\n",
       "      <td>-0.10290158</td>\n",
       "      <td>-0.01224658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(473 [WMT])</th>\n",
       "      <td>-0.01988671</td>\n",
       "      <td>0.03467415</td>\n",
       "      <td>-0.04017193</td>\n",
       "      <td>-0.00769646</td>\n",
       "      <td>-0.01460066</td>\n",
       "      <td>0.00726635</td>\n",
       "      <td>-0.02275936</td>\n",
       "      <td>0.03829212</td>\n",
       "      <td>-0.01129245</td>\n",
       "      <td>-0.00761002</td>\n",
       "      <td>0.00867345</td>\n",
       "      <td>0.00383922</td>\n",
       "      <td>-0.04340883</td>\n",
       "      <td>0.02467536</td>\n",
       "      <td>0.01323727</td>\n",
       "      <td>0.01194552</td>\n",
       "      <td>-0.02497356</td>\n",
       "      <td>0.00351902</td>\n",
       "      <td>0.00777862</td>\n",
       "      <td>0.01076198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(474 [WRK])</th>\n",
       "      <td>-0.00563001</td>\n",
       "      <td>-0.00526226</td>\n",
       "      <td>0.00630657</td>\n",
       "      <td>-0.00994056</td>\n",
       "      <td>0.00615504</td>\n",
       "      <td>0.01085219</td>\n",
       "      <td>0.00188007</td>\n",
       "      <td>0.01706454</td>\n",
       "      <td>-0.00685762</td>\n",
       "      <td>-0.00781146</td>\n",
       "      <td>0.00359568</td>\n",
       "      <td>-0.02948648</td>\n",
       "      <td>-0.02071811</td>\n",
       "      <td>0.00905441</td>\n",
       "      <td>0.00186650</td>\n",
       "      <td>-0.01865369</td>\n",
       "      <td>-0.01239063</td>\n",
       "      <td>0.02357001</td>\n",
       "      <td>-0.02087232</td>\n",
       "      <td>0.04046773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(475 [WU])</th>\n",
       "      <td>-0.04059879</td>\n",
       "      <td>0.00365919</td>\n",
       "      <td>0.01271940</td>\n",
       "      <td>0.00231537</td>\n",
       "      <td>-0.01726731</td>\n",
       "      <td>0.03143078</td>\n",
       "      <td>0.02344129</td>\n",
       "      <td>0.01431019</td>\n",
       "      <td>-0.02394147</td>\n",
       "      <td>-0.00790867</td>\n",
       "      <td>-0.02335012</td>\n",
       "      <td>-0.00977388</td>\n",
       "      <td>-0.00331322</td>\n",
       "      <td>-0.02121476</td>\n",
       "      <td>0.00574640</td>\n",
       "      <td>-0.03553201</td>\n",
       "      <td>-0.00661356</td>\n",
       "      <td>-0.03045924</td>\n",
       "      <td>0.00995369</td>\n",
       "      <td>-0.04708063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(476 [WY])</th>\n",
       "      <td>-0.04860757</td>\n",
       "      <td>0.01225382</td>\n",
       "      <td>-0.04997087</td>\n",
       "      <td>0.00551805</td>\n",
       "      <td>-0.00278578</td>\n",
       "      <td>-0.03035081</td>\n",
       "      <td>0.01706471</td>\n",
       "      <td>-0.04454320</td>\n",
       "      <td>0.02067441</td>\n",
       "      <td>0.04950772</td>\n",
       "      <td>-0.02155464</td>\n",
       "      <td>-0.01867393</td>\n",
       "      <td>-0.00268823</td>\n",
       "      <td>0.02518978</td>\n",
       "      <td>-0.01532718</td>\n",
       "      <td>-0.02625075</td>\n",
       "      <td>-0.02418712</td>\n",
       "      <td>0.00957536</td>\n",
       "      <td>0.01679332</td>\n",
       "      <td>-0.00412955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(477 [WYN])</th>\n",
       "      <td>-0.05535480</td>\n",
       "      <td>0.02642294</td>\n",
       "      <td>0.00304199</td>\n",
       "      <td>-0.00979668</td>\n",
       "      <td>-0.00616717</td>\n",
       "      <td>-0.02917053</td>\n",
       "      <td>-0.01685646</td>\n",
       "      <td>-0.03459347</td>\n",
       "      <td>-0.04851210</td>\n",
       "      <td>-0.00714578</td>\n",
       "      <td>0.02188880</td>\n",
       "      <td>0.02067000</td>\n",
       "      <td>0.01051755</td>\n",
       "      <td>0.02073259</td>\n",
       "      <td>0.01106532</td>\n",
       "      <td>0.01470477</td>\n",
       "      <td>-0.00226587</td>\n",
       "      <td>-0.02256858</td>\n",
       "      <td>-0.03784605</td>\n",
       "      <td>-0.01748119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(478 [WYNN])</th>\n",
       "      <td>-0.06224023</td>\n",
       "      <td>-0.03777009</td>\n",
       "      <td>0.05699233</td>\n",
       "      <td>-0.04984462</td>\n",
       "      <td>0.00328186</td>\n",
       "      <td>-0.05450135</td>\n",
       "      <td>-0.01461477</td>\n",
       "      <td>-0.13651307</td>\n",
       "      <td>-0.10364775</td>\n",
       "      <td>-0.13173348</td>\n",
       "      <td>0.08154700</td>\n",
       "      <td>-0.21134975</td>\n",
       "      <td>0.05793940</td>\n",
       "      <td>0.06955993</td>\n",
       "      <td>-0.05215021</td>\n",
       "      <td>0.00468932</td>\n",
       "      <td>-0.04338772</td>\n",
       "      <td>0.14131780</td>\n",
       "      <td>-0.02504257</td>\n",
       "      <td>0.02417878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(479 [XEC])</th>\n",
       "      <td>-0.06269690</td>\n",
       "      <td>-0.17159838</td>\n",
       "      <td>0.01127251</td>\n",
       "      <td>-0.03690692</td>\n",
       "      <td>0.07210881</td>\n",
       "      <td>0.04237735</td>\n",
       "      <td>-0.01733096</td>\n",
       "      <td>-0.00894589</td>\n",
       "      <td>-0.00116263</td>\n",
       "      <td>-0.04083135</td>\n",
       "      <td>0.00912637</td>\n",
       "      <td>0.02183445</td>\n",
       "      <td>-0.00217537</td>\n",
       "      <td>-0.10441731</td>\n",
       "      <td>-0.05669005</td>\n",
       "      <td>0.00593931</td>\n",
       "      <td>0.06575714</td>\n",
       "      <td>-0.03770747</td>\n",
       "      <td>0.09486709</td>\n",
       "      <td>-0.06387098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(480 [XEL])</th>\n",
       "      <td>-0.02213358</td>\n",
       "      <td>0.02037290</td>\n",
       "      <td>-0.09965905</td>\n",
       "      <td>-0.04339570</td>\n",
       "      <td>-0.00356988</td>\n",
       "      <td>-0.02492272</td>\n",
       "      <td>0.01491957</td>\n",
       "      <td>0.05105363</td>\n",
       "      <td>-0.00024236</td>\n",
       "      <td>-0.02451330</td>\n",
       "      <td>0.01835319</td>\n",
       "      <td>-0.05349810</td>\n",
       "      <td>-0.00097559</td>\n",
       "      <td>-0.00596671</td>\n",
       "      <td>0.02197929</td>\n",
       "      <td>0.01863163</td>\n",
       "      <td>0.04664665</td>\n",
       "      <td>-0.00826953</td>\n",
       "      <td>-0.01791475</td>\n",
       "      <td>-0.02072648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <td>-0.04533940</td>\n",
       "      <td>0.01070557</td>\n",
       "      <td>-0.03511721</td>\n",
       "      <td>0.04642140</td>\n",
       "      <td>-0.00583933</td>\n",
       "      <td>0.01175012</td>\n",
       "      <td>0.01269465</td>\n",
       "      <td>-0.02088638</td>\n",
       "      <td>0.01106751</td>\n",
       "      <td>-0.00003951</td>\n",
       "      <td>0.00649962</td>\n",
       "      <td>0.00959532</td>\n",
       "      <td>0.00151969</td>\n",
       "      <td>-0.00052693</td>\n",
       "      <td>0.00744188</td>\n",
       "      <td>0.01978538</td>\n",
       "      <td>-0.00164444</td>\n",
       "      <td>0.00315162</td>\n",
       "      <td>0.00519293</td>\n",
       "      <td>-0.03064259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <td>-0.04210479</td>\n",
       "      <td>-0.00382104</td>\n",
       "      <td>0.05760794</td>\n",
       "      <td>-0.01871999</td>\n",
       "      <td>-0.06972723</td>\n",
       "      <td>-0.01255952</td>\n",
       "      <td>0.09049018</td>\n",
       "      <td>0.05367295</td>\n",
       "      <td>0.00001376</td>\n",
       "      <td>0.00960728</td>\n",
       "      <td>0.01455370</td>\n",
       "      <td>0.00163722</td>\n",
       "      <td>-0.03587944</td>\n",
       "      <td>-0.04241793</td>\n",
       "      <td>0.00144974</td>\n",
       "      <td>-0.03148143</td>\n",
       "      <td>0.03558220</td>\n",
       "      <td>0.01661543</td>\n",
       "      <td>0.01022713</td>\n",
       "      <td>-0.00396583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <td>-0.03773468</td>\n",
       "      <td>-0.05378131</td>\n",
       "      <td>-0.03367517</td>\n",
       "      <td>-0.01036467</td>\n",
       "      <td>-0.00395082</td>\n",
       "      <td>0.02952766</td>\n",
       "      <td>-0.00565258</td>\n",
       "      <td>0.04906130</td>\n",
       "      <td>0.00089804</td>\n",
       "      <td>-0.00311029</td>\n",
       "      <td>-0.00739458</td>\n",
       "      <td>-0.01164590</td>\n",
       "      <td>-0.01051455</td>\n",
       "      <td>0.01413654</td>\n",
       "      <td>0.00286959</td>\n",
       "      <td>0.00192552</td>\n",
       "      <td>-0.00324646</td>\n",
       "      <td>0.00012369</td>\n",
       "      <td>0.01694194</td>\n",
       "      <td>0.01003126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <td>-0.04417162</td>\n",
       "      <td>0.01778874</td>\n",
       "      <td>-0.00062230</td>\n",
       "      <td>0.00814409</td>\n",
       "      <td>-0.02933804</td>\n",
       "      <td>0.01859296</td>\n",
       "      <td>0.01513543</td>\n",
       "      <td>-0.00291478</td>\n",
       "      <td>-0.00638183</td>\n",
       "      <td>-0.00958277</td>\n",
       "      <td>-0.01879890</td>\n",
       "      <td>0.00101476</td>\n",
       "      <td>0.01167483</td>\n",
       "      <td>0.02288506</td>\n",
       "      <td>-0.02825392</td>\n",
       "      <td>0.01102642</td>\n",
       "      <td>0.01849776</td>\n",
       "      <td>0.00975355</td>\n",
       "      <td>0.00668087</td>\n",
       "      <td>-0.04636686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <td>-0.05418096</td>\n",
       "      <td>-0.00344402</td>\n",
       "      <td>0.01002127</td>\n",
       "      <td>0.02970052</td>\n",
       "      <td>-0.04632619</td>\n",
       "      <td>0.01414187</td>\n",
       "      <td>0.01544957</td>\n",
       "      <td>0.03335353</td>\n",
       "      <td>-0.00134738</td>\n",
       "      <td>-0.03200626</td>\n",
       "      <td>-0.00744424</td>\n",
       "      <td>-0.01931881</td>\n",
       "      <td>-0.03324697</td>\n",
       "      <td>0.01915283</td>\n",
       "      <td>-0.01067988</td>\n",
       "      <td>-0.01247793</td>\n",
       "      <td>0.00098390</td>\n",
       "      <td>-0.04865041</td>\n",
       "      <td>0.01743092</td>\n",
       "      <td>0.00666409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <td>-0.02818794</td>\n",
       "      <td>-0.01716654</td>\n",
       "      <td>0.03265037</td>\n",
       "      <td>-0.01947739</td>\n",
       "      <td>-0.00284445</td>\n",
       "      <td>0.00870998</td>\n",
       "      <td>-0.01888604</td>\n",
       "      <td>0.06659425</td>\n",
       "      <td>-0.02409194</td>\n",
       "      <td>0.03602542</td>\n",
       "      <td>-0.02482881</td>\n",
       "      <td>-0.03921085</td>\n",
       "      <td>-0.00964275</td>\n",
       "      <td>-0.04118213</td>\n",
       "      <td>-0.05878742</td>\n",
       "      <td>-0.02300320</td>\n",
       "      <td>0.00625647</td>\n",
       "      <td>0.04733302</td>\n",
       "      <td>-0.00256510</td>\n",
       "      <td>0.04937012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <td>-0.03630261</td>\n",
       "      <td>0.02726148</td>\n",
       "      <td>0.00226076</td>\n",
       "      <td>-0.02614444</td>\n",
       "      <td>-0.01418528</td>\n",
       "      <td>0.00132929</td>\n",
       "      <td>-0.04156624</td>\n",
       "      <td>0.00017706</td>\n",
       "      <td>-0.03049746</td>\n",
       "      <td>-0.02788495</td>\n",
       "      <td>0.01280995</td>\n",
       "      <td>0.00298781</td>\n",
       "      <td>-0.01235304</td>\n",
       "      <td>0.00926070</td>\n",
       "      <td>0.00035906</td>\n",
       "      <td>-0.00496092</td>\n",
       "      <td>-0.01453755</td>\n",
       "      <td>0.01909012</td>\n",
       "      <td>-0.01126627</td>\n",
       "      <td>-0.00177409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <td>-0.03843904</td>\n",
       "      <td>0.01749339</td>\n",
       "      <td>-0.01575190</td>\n",
       "      <td>-0.01540756</td>\n",
       "      <td>-0.00162086</td>\n",
       "      <td>0.04604255</td>\n",
       "      <td>0.00107619</td>\n",
       "      <td>-0.00762158</td>\n",
       "      <td>0.00942745</td>\n",
       "      <td>-0.01275463</td>\n",
       "      <td>-0.06637911</td>\n",
       "      <td>-0.01112025</td>\n",
       "      <td>-0.02675098</td>\n",
       "      <td>0.01827896</td>\n",
       "      <td>-0.04768582</td>\n",
       "      <td>0.01395948</td>\n",
       "      <td>0.01018115</td>\n",
       "      <td>0.04125323</td>\n",
       "      <td>0.00671842</td>\n",
       "      <td>-0.01540844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <td>-0.06092493</td>\n",
       "      <td>-0.01044197</td>\n",
       "      <td>0.01261759</td>\n",
       "      <td>0.13419161</td>\n",
       "      <td>0.02396471</td>\n",
       "      <td>0.09232022</td>\n",
       "      <td>-0.04477488</td>\n",
       "      <td>-0.03030878</td>\n",
       "      <td>0.03194794</td>\n",
       "      <td>-0.01095035</td>\n",
       "      <td>0.04091415</td>\n",
       "      <td>-0.01621729</td>\n",
       "      <td>-0.01158269</td>\n",
       "      <td>-0.03556539</td>\n",
       "      <td>0.00554836</td>\n",
       "      <td>-0.00341750</td>\n",
       "      <td>0.00706111</td>\n",
       "      <td>0.00352290</td>\n",
       "      <td>-0.02193923</td>\n",
       "      <td>0.02188794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "      <td>-0.01367163</td>\n",
       "      <td>0.01892192</td>\n",
       "      <td>0.01867875</td>\n",
       "      <td>-0.04878703</td>\n",
       "      <td>0.01263697</td>\n",
       "      <td>0.04831930</td>\n",
       "      <td>-0.00205544</td>\n",
       "      <td>0.01613385</td>\n",
       "      <td>-0.01918963</td>\n",
       "      <td>-0.03072014</td>\n",
       "      <td>-0.04031418</td>\n",
       "      <td>-0.03085290</td>\n",
       "      <td>-0.05612824</td>\n",
       "      <td>-0.01541907</td>\n",
       "      <td>0.00108249</td>\n",
       "      <td>-0.02396138</td>\n",
       "      <td>-0.01026795</td>\n",
       "      <td>0.03682367</td>\n",
       "      <td>0.00833979</td>\n",
       "      <td>0.01500221</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>490 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            0           1           2           3   \\\n",
       "Equity(0 [A])      -0.04316847  0.01955111 -0.00993375  0.01054038   \n",
       "Equity(1 [AAL])    -0.05874471  0.19637679  0.07868756  0.08209582   \n",
       "Equity(2 [AAP])    -0.03433256  0.03451503  0.01133839 -0.02543666   \n",
       "Equity(3 [AAPL])   -0.03409988 -0.00139319  0.03946700 -0.01721303   \n",
       "Equity(4 [ABBV])   -0.01803099  0.02568151  0.00435183 -0.07078179   \n",
       "Equity(5 [ABC])    -0.02890016  0.03259161 -0.00742074 -0.03355183   \n",
       "Equity(6 [ABT])    -0.02905740  0.02977821 -0.02970871 -0.03574263   \n",
       "Equity(7 [ACN])    -0.04337745  0.00256907  0.00413229 -0.00349265   \n",
       "Equity(8 [ADBE])   -0.04730285  0.02661175  0.03057072 -0.02114690   \n",
       "Equity(9 [ADI])    -0.04712287 -0.00381150  0.05600847 -0.01553775   \n",
       "Equity(10 [ADM])   -0.04375945 -0.01130045 -0.03457005  0.00400541   \n",
       "Equity(11 [ADP])   -0.03648136  0.02528125 -0.01114832 -0.00940984   \n",
       "Equity(12 [ADS])   -0.04136654  0.01659887  0.01716323 -0.02418717   \n",
       "Equity(13 [ADSK])  -0.06028785  0.01995266  0.05164356  0.00105689   \n",
       "Equity(14 [AEE])   -0.02646901  0.02222316 -0.10714999 -0.03824488   \n",
       "Equity(15 [AEP])   -0.02263370  0.01880106 -0.10030310 -0.04210462   \n",
       "Equity(16 [AES])   -0.04557539 -0.01859287 -0.06960047 -0.02023102   \n",
       "Equity(17 [AET])   -0.04072498  0.02731997 -0.00507231 -0.02802199   \n",
       "Equity(18 [AFL])   -0.05336864  0.00134653 -0.02782496  0.06688998   \n",
       "Equity(19 [AGN])   -0.03534102  0.04465091  0.02264084 -0.09556088   \n",
       "Equity(20 [AIG])   -0.05982324  0.00588515 -0.01162873  0.06668318   \n",
       "Equity(21 [AIV])   -0.04111735  0.03100207 -0.10211708 -0.00919327   \n",
       "Equity(22 [AIZ])   -0.04150874  0.01695771 -0.03297298  0.04770347   \n",
       "Equity(23 [AJG])   -0.03351812  0.01723113 -0.02538602  0.01303842   \n",
       "Equity(24 [AKAM])  -0.05587884  0.00798596  0.06670064 -0.00705542   \n",
       "Equity(25 [ALB])   -0.05982022 -0.03657577  0.01798669  0.01363477   \n",
       "Equity(26 [ALGN])  -0.05959262  0.01420686  0.04030645 -0.00223610   \n",
       "Equity(27 [ALK])   -0.04887994  0.12134700  0.03971829  0.02356295   \n",
       "Equity(28 [ALL])   -0.03960459  0.01388579 -0.04298737  0.04705234   \n",
       "Equity(29 [ALLE])  -0.01215236  0.01485340  0.01783511 -0.02151478   \n",
       "...                        ...         ...         ...         ...   \n",
       "Equity(460 [VRSN]) -0.03899324  0.01109333  0.04065347 -0.01351021   \n",
       "Equity(461 [VRTX]) -0.04909379  0.09821506  0.07490354 -0.22874272   \n",
       "Equity(462 [VTR])  -0.03291326  0.03068907 -0.12174007 -0.03757317   \n",
       "Equity(463 [VZ])   -0.07033190  0.00068427 -0.01610414  0.05981359   \n",
       "Equity(464 [WAT])  -0.04787963  0.01976102  0.00630830 -0.01309650   \n",
       "Equity(465 [WBA])  -0.03065220  0.03421533 -0.01027997 -0.04006665   \n",
       "Equity(466 [WDC])  -0.05340806 -0.00776436  0.06117296 -0.01397300   \n",
       "Equity(467 [WEC])  -0.02279115  0.02557593 -0.10491696 -0.04691482   \n",
       "Equity(468 [WFC])  -0.05131308  0.01109305 -0.03096455  0.08514607   \n",
       "Equity(469 [WHR])  -0.05507142  0.03637282 -0.00100598  0.00590479   \n",
       "Equity(471 [WM])   -0.03151644  0.01496675 -0.03234348 -0.00111937   \n",
       "Equity(472 [WMB])  -0.05476156 -0.08924998 -0.02426238 -0.05723889   \n",
       "Equity(473 [WMT])  -0.01988671  0.03467415 -0.04017193 -0.00769646   \n",
       "Equity(474 [WRK])  -0.00563001 -0.00526226  0.00630657 -0.00994056   \n",
       "Equity(475 [WU])   -0.04059879  0.00365919  0.01271940  0.00231537   \n",
       "Equity(476 [WY])   -0.04860757  0.01225382 -0.04997087  0.00551805   \n",
       "Equity(477 [WYN])  -0.05535480  0.02642294  0.00304199 -0.00979668   \n",
       "Equity(478 [WYNN]) -0.06224023 -0.03777009  0.05699233 -0.04984462   \n",
       "Equity(479 [XEC])  -0.06269690 -0.17159838  0.01127251 -0.03690692   \n",
       "Equity(480 [XEL])  -0.02213358  0.02037290 -0.09965905 -0.04339570   \n",
       "Equity(481 [XL])   -0.04533940  0.01070557 -0.03511721  0.04642140   \n",
       "Equity(482 [XLNX]) -0.04210479 -0.00382104  0.05760794 -0.01871999   \n",
       "Equity(483 [XOM])  -0.03773468 -0.05378131 -0.03367517 -0.01036467   \n",
       "Equity(484 [XRAY]) -0.04417162  0.01778874 -0.00062230  0.00814409   \n",
       "Equity(485 [XRX])  -0.05418096 -0.00344402  0.01002127  0.02970052   \n",
       "Equity(486 [XYL])  -0.02818794 -0.01716654  0.03265037 -0.01947739   \n",
       "Equity(487 [YUM])  -0.03630261  0.02726148  0.00226076 -0.02614444   \n",
       "Equity(488 [ZBH])  -0.03843904  0.01749339 -0.01575190 -0.01540756   \n",
       "Equity(489 [ZION]) -0.06092493 -0.01044197  0.01261759  0.13419161   \n",
       "Equity(490 [ZTS])  -0.01367163  0.01892192  0.01867875 -0.04878703   \n",
       "\n",
       "                            4           5           6           7   \\\n",
       "Equity(0 [A])      -0.01819821  0.01074517  0.00112915  0.03973914   \n",
       "Equity(1 [AAL])     0.34847826 -0.13808246  0.07129285  0.10524788   \n",
       "Equity(2 [AAP])    -0.00817211 -0.01318319 -0.06095238  0.00654915   \n",
       "Equity(3 [AAPL])   -0.03046983 -0.01757067  0.02325117  0.01142987   \n",
       "Equity(4 [ABBV])    0.01319937  0.05427710 -0.01567842  0.04046172   \n",
       "Equity(5 [ABC])    -0.01152149  0.02648421  0.01084965 -0.00570393   \n",
       "Equity(6 [ABT])    -0.01157351  0.06020073 -0.02004042  0.04098522   \n",
       "Equity(7 [ACN])    -0.05430743  0.00537434  0.00277996  0.03043220   \n",
       "Equity(8 [ADBE])   -0.04838794 -0.00708698  0.00743385  0.00747095   \n",
       "Equity(9 [ADI])    -0.06946243 -0.00560418  0.10070366  0.06307694   \n",
       "Equity(10 [ADM])   -0.00645333  0.01746845 -0.00146122  0.04177642   \n",
       "Equity(11 [ADP])   -0.03357614  0.02887659 -0.00509280  0.04466799   \n",
       "Equity(12 [ADS])   -0.00389740  0.00098181 -0.02299563  0.01316338   \n",
       "Equity(13 [ADSK])  -0.06889175 -0.04893180  0.04706144 -0.02746946   \n",
       "Equity(14 [AEE])   -0.00157895 -0.02310383  0.02412315  0.04419314   \n",
       "Equity(15 [AEP])    0.00205558 -0.03150526  0.02496444  0.05473617   \n",
       "Equity(16 [AES])    0.01303429 -0.01748403  0.02894033  0.03053573   \n",
       "Equity(17 [AET])   -0.00180323  0.06383735  0.00044765 -0.03716524   \n",
       "Equity(18 [AFL])   -0.01355109  0.04111821 -0.00401011 -0.01388700   \n",
       "Equity(19 [AGN])    0.02867567  0.06515425 -0.02264216 -0.01928860   \n",
       "Equity(20 [AIG])    0.01385338  0.04010201 -0.01874280 -0.02394864   \n",
       "Equity(21 [AIV])    0.01055402 -0.04739093  0.05244727 -0.09495931   \n",
       "Equity(22 [AIZ])   -0.00003273  0.04220872 -0.00295921  0.01717020   \n",
       "Equity(23 [AJG])   -0.00670008  0.02117990 -0.01015869  0.00117300   \n",
       "Equity(24 [AKAM])  -0.05149731 -0.04837770  0.02745032 -0.00620225   \n",
       "Equity(25 [ALB])   -0.01737160 -0.03079886  0.04201500  0.00605395   \n",
       "Equity(26 [ALGN])   0.00381377  0.03559561  0.04027152 -0.09389473   \n",
       "Equity(27 [ALK])    0.12648496 -0.05703822  0.02168427  0.06427147   \n",
       "Equity(28 [ALL])   -0.00073028  0.03487833 -0.01156382  0.00877075   \n",
       "Equity(29 [ALLE])   0.00049741  0.02208048 -0.01396758  0.04557020   \n",
       "...                        ...         ...         ...         ...   \n",
       "Equity(460 [VRSN]) -0.03906872  0.00844214  0.01232426 -0.02031680   \n",
       "Equity(461 [VRTX])  0.18286011  0.29795662  0.16783749 -0.08588784   \n",
       "Equity(462 [VTR])  -0.00091457 -0.05384826  0.03088016 -0.06663125   \n",
       "Equity(463 [VZ])   -0.01922444  0.03298870 -0.00089302 -0.00205798   \n",
       "Equity(464 [WAT])  -0.02786813  0.02969891  0.01135497 -0.01289454   \n",
       "Equity(465 [WBA])  -0.01725655  0.02037446 -0.00923922  0.04976024   \n",
       "Equity(466 [WDC])  -0.02898379 -0.05151527  0.10653647  0.00360483   \n",
       "Equity(467 [WEC])  -0.00109145 -0.02887550  0.01886320  0.05105952   \n",
       "Equity(468 [WFC])   0.00399898  0.06168940 -0.01917540 -0.00980213   \n",
       "Equity(469 [WHR])   0.01092658 -0.06423664 -0.05592381  0.02535313   \n",
       "Equity(471 [WM])   -0.02960532  0.00379175 -0.00185568  0.01331670   \n",
       "Equity(472 [WMB])   0.07886307 -0.01255032 -0.03519116  0.02300738   \n",
       "Equity(473 [WMT])  -0.01460066  0.00726635 -0.02275936  0.03829212   \n",
       "Equity(474 [WRK])   0.00615504  0.01085219  0.00188007  0.01706454   \n",
       "Equity(475 [WU])   -0.01726731  0.03143078  0.02344129  0.01431019   \n",
       "Equity(476 [WY])   -0.00278578 -0.03035081  0.01706471 -0.04454320   \n",
       "Equity(477 [WYN])  -0.00616717 -0.02917053 -0.01685646 -0.03459347   \n",
       "Equity(478 [WYNN])  0.00328186 -0.05450135 -0.01461477 -0.13651307   \n",
       "Equity(479 [XEC])   0.07210881  0.04237735 -0.01733096 -0.00894589   \n",
       "Equity(480 [XEL])  -0.00356988 -0.02492272  0.01491957  0.05105363   \n",
       "Equity(481 [XL])   -0.00583933  0.01175012  0.01269465 -0.02088638   \n",
       "Equity(482 [XLNX]) -0.06972723 -0.01255952  0.09049018  0.05367295   \n",
       "Equity(483 [XOM])  -0.00395082  0.02952766 -0.00565258  0.04906130   \n",
       "Equity(484 [XRAY]) -0.02933804  0.01859296  0.01513543 -0.00291478   \n",
       "Equity(485 [XRX])  -0.04632619  0.01414187  0.01544957  0.03335353   \n",
       "Equity(486 [XYL])  -0.00284445  0.00870998 -0.01888604  0.06659425   \n",
       "Equity(487 [YUM])  -0.01418528  0.00132929 -0.04156624  0.00017706   \n",
       "Equity(488 [ZBH])  -0.00162086  0.04604255  0.00107619 -0.00762158   \n",
       "Equity(489 [ZION])  0.02396471  0.09232022 -0.04477488 -0.03030878   \n",
       "Equity(490 [ZTS])   0.01263697  0.04831930 -0.00205544  0.01613385   \n",
       "\n",
       "                            8           9           10          11  \\\n",
       "Equity(0 [A])      -0.01380519  0.01273651 -0.02384028 -0.00141663   \n",
       "Equity(1 [AAL])    -0.04588957 -0.08547793  0.00328328  0.10534284   \n",
       "Equity(2 [AAP])    -0.03265404 -0.01351522  0.02896685  0.03836520   \n",
       "Equity(3 [AAPL])   -0.02656849 -0.00771904  0.02686350  0.00731877   \n",
       "Equity(4 [ABBV])   -0.01245487 -0.03515086 -0.05132433 -0.04041614   \n",
       "Equity(5 [ABC])     0.01354800 -0.02967931 -0.03161765  0.01715152   \n",
       "Equity(6 [ABT])    -0.01803987 -0.00620785 -0.03157790 -0.02308041   \n",
       "Equity(7 [ACN])    -0.01880168 -0.00178336 -0.03540357 -0.01093170   \n",
       "Equity(8 [ADBE])    0.01487098 -0.00153422 -0.01238383 -0.00667442   \n",
       "Equity(9 [ADI])     0.00160769  0.01912993  0.01101680  0.00348733   \n",
       "Equity(10 [ADM])   -0.00478644 -0.01859623  0.00422432 -0.00952513   \n",
       "Equity(11 [ADP])   -0.00676480  0.00335015 -0.00493401  0.00194010   \n",
       "Equity(12 [ADS])   -0.02790599  0.00654660  0.00628604 -0.00342924   \n",
       "Equity(13 [ADSK])   0.00290438  0.00534281 -0.01150281 -0.00105789   \n",
       "Equity(14 [AEE])    0.00041473 -0.02597657  0.02325386 -0.05456489   \n",
       "Equity(15 [AEP])    0.00166554 -0.02261936  0.01766823 -0.04791054   \n",
       "Equity(16 [AES])   -0.01228381 -0.02623395  0.00383933 -0.05881947   \n",
       "Equity(17 [AET])    0.00999656 -0.09646860 -0.04571407  0.04559328   \n",
       "Equity(18 [AFL])    0.01362724  0.00343990 -0.00993833 -0.00945988   \n",
       "Equity(19 [AGN])   -0.02379115 -0.02578767 -0.02640179 -0.00734949   \n",
       "Equity(20 [AIG])    0.01457678  0.02061950 -0.00588748 -0.01886738   \n",
       "Equity(21 [AIV])    0.04963087  0.00394508  0.02486556  0.02540802   \n",
       "Equity(22 [AIZ])    0.02192818 -0.01979049  0.00845285 -0.00209358   \n",
       "Equity(23 [AJG])    0.00768045  0.00434263 -0.00824876  0.01520847   \n",
       "Equity(24 [AKAM])   0.02668695 -0.01154353  0.00107161 -0.06366032   \n",
       "Equity(25 [ALB])   -0.02047597  0.03736635 -0.00136191  0.01865916   \n",
       "Equity(26 [ALGN])   0.03501042  0.00979674 -0.07400799  0.02204550   \n",
       "Equity(27 [ALK])   -0.01679148 -0.02374091 -0.00059277  0.06395819   \n",
       "Equity(28 [ALL])   -0.00074882 -0.00128949  0.01279480 -0.00687101   \n",
       "Equity(29 [ALLE])  -0.01575920  0.00225117 -0.01540340 -0.02608136   \n",
       "...                        ...         ...         ...         ...   \n",
       "Equity(460 [VRSN]) -0.01427350 -0.00833205 -0.02485455  0.02115889   \n",
       "Equity(461 [VRTX])  0.17241447  0.26880311  0.58246071 -0.03464001   \n",
       "Equity(462 [VTR])   0.04680683  0.00814737 -0.00367371  0.02294498   \n",
       "Equity(463 [VZ])    0.03346385 -0.00820052  0.01313467 -0.01333200   \n",
       "Equity(464 [WAT])   0.02281688  0.00205729 -0.05584809  0.02544186   \n",
       "Equity(465 [WBA])  -0.02415684 -0.02906100 -0.01704871 -0.00978625   \n",
       "Equity(466 [WDC])  -0.00177534 -0.01754129  0.03043852 -0.00839301   \n",
       "Equity(467 [WEC])   0.01033805 -0.02583748  0.02240632 -0.04433949   \n",
       "Equity(468 [WFC])   0.02012808  0.00922159  0.02755224 -0.01813056   \n",
       "Equity(469 [WHR])  -0.04216377  0.13444741 -0.01648804  0.01561092   \n",
       "Equity(471 [WM])   -0.00239896 -0.00938471  0.00277936  0.00920572   \n",
       "Equity(472 [WMB])  -0.03160335 -0.02914851  0.00854960  0.01996384   \n",
       "Equity(473 [WMT])  -0.01129245 -0.00761002  0.00867345  0.00383922   \n",
       "Equity(474 [WRK])  -0.00685762 -0.00781146  0.00359568 -0.02948648   \n",
       "Equity(475 [WU])   -0.02394147 -0.00790867 -0.02335012 -0.00977388   \n",
       "Equity(476 [WY])    0.02067441  0.04950772 -0.02155464 -0.01867393   \n",
       "Equity(477 [WYN])  -0.04851210 -0.00714578  0.02188880  0.02067000   \n",
       "Equity(478 [WYNN]) -0.10364775 -0.13173348  0.08154700 -0.21134975   \n",
       "Equity(479 [XEC])  -0.00116263 -0.04083135  0.00912637  0.02183445   \n",
       "Equity(480 [XEL])  -0.00024236 -0.02451330  0.01835319 -0.05349810   \n",
       "Equity(481 [XL])    0.01106751 -0.00003951  0.00649962  0.00959532   \n",
       "Equity(482 [XLNX])  0.00001376  0.00960728  0.01455370  0.00163722   \n",
       "Equity(483 [XOM])   0.00089804 -0.00311029 -0.00739458 -0.01164590   \n",
       "Equity(484 [XRAY]) -0.00638183 -0.00958277 -0.01879890  0.00101476   \n",
       "Equity(485 [XRX])  -0.00134738 -0.03200626 -0.00744424 -0.01931881   \n",
       "Equity(486 [XYL])  -0.02409194  0.03602542 -0.02482881 -0.03921085   \n",
       "Equity(487 [YUM])  -0.03049746 -0.02788495  0.01280995  0.00298781   \n",
       "Equity(488 [ZBH])   0.00942745 -0.01275463 -0.06637911 -0.01112025   \n",
       "Equity(489 [ZION])  0.03194794 -0.01095035  0.04091415 -0.01621729   \n",
       "Equity(490 [ZTS])  -0.01918963 -0.03072014 -0.04031418 -0.03085290   \n",
       "\n",
       "                            12          13          14          15  \\\n",
       "Equity(0 [A])       0.02099338  0.03460997 -0.03048936  0.03360635   \n",
       "Equity(1 [AAL])     0.06721603 -0.04405955 -0.02231617  0.01726309   \n",
       "Equity(2 [AAP])    -0.04960451 -0.00524576 -0.02196994  0.02976718   \n",
       "Equity(3 [AAPL])    0.00481832  0.01288623  0.05256513 -0.07344470   \n",
       "Equity(4 [ABBV])   -0.05120320 -0.01858166 -0.01126857 -0.04200714   \n",
       "Equity(5 [ABC])    -0.00304998  0.02635564  0.00787900  0.00833106   \n",
       "Equity(6 [ABT])    -0.01436789 -0.00054254 -0.01932887  0.01428819   \n",
       "Equity(7 [ACN])     0.02611241 -0.01233115  0.00322097  0.01770011   \n",
       "Equity(8 [ADBE])    0.03500718 -0.04336579  0.01060255 -0.00637875   \n",
       "Equity(9 [ADI])    -0.05465749 -0.04223802 -0.00014275 -0.04843166   \n",
       "Equity(10 [ADM])   -0.01336835  0.01753074  0.00993158  0.02405739   \n",
       "Equity(11 [ADP])   -0.01057350 -0.00616905 -0.00351046 -0.00218630   \n",
       "Equity(12 [ADS])    0.01596979 -0.02290249  0.01812681  0.00269984   \n",
       "Equity(13 [ADSK])   0.04046916 -0.03266419  0.02070996  0.02100687   \n",
       "Equity(14 [AEE])    0.00729924 -0.00884432  0.02876494  0.02575176   \n",
       "Equity(15 [AEP])   -0.01334963 -0.00584932  0.03513664  0.02664964   \n",
       "Equity(16 [AES])   -0.01427757  0.01071751  0.04800697  0.00823278   \n",
       "Equity(17 [AET])   -0.08527159  0.06484179 -0.07164819  0.00852602   \n",
       "Equity(18 [AFL])    0.01378441 -0.00676370  0.00047075  0.00042919   \n",
       "Equity(19 [AGN])   -0.01375720  0.01729325  0.00910558  0.01765223   \n",
       "Equity(20 [AIG])   -0.00536267 -0.02808023  0.03227634 -0.01100650   \n",
       "Equity(21 [AIV])    0.02094801 -0.04206507 -0.02048654 -0.03732772   \n",
       "Equity(22 [AIZ])   -0.02121338 -0.01017076  0.02874684  0.01121282   \n",
       "Equity(23 [AJG])   -0.00142810 -0.00802982 -0.00533986 -0.00140466   \n",
       "Equity(24 [AKAM])  -0.07429360  0.00240076  0.12416841  0.13836518   \n",
       "Equity(25 [ALB])    0.04131905  0.09156602 -0.06656052 -0.01740400   \n",
       "Equity(26 [ALGN])   0.10784517  0.07096981 -0.05965948 -0.06617279   \n",
       "Equity(27 [ALK])    0.00033085  0.00597074  0.01458408  0.02170190   \n",
       "Equity(28 [ALL])   -0.00986285 -0.00905731  0.02499562 -0.00494904   \n",
       "Equity(29 [ALLE])  -0.00635063 -0.04124458 -0.00784737 -0.01976681   \n",
       "...                        ...         ...         ...         ...   \n",
       "Equity(460 [VRSN])  0.00062521  0.01354571  0.02242982  0.03594197   \n",
       "Equity(461 [VRTX]) -0.12627708  0.36184696 -0.14161962 -0.10440960   \n",
       "Equity(462 [VTR])   0.02497163 -0.03310961 -0.01353316 -0.02038055   \n",
       "Equity(463 [VZ])    0.00415716 -0.00898788  0.00645221 -0.01738755   \n",
       "Equity(464 [WAT])   0.02317906  0.01111012 -0.03735916  0.03053670   \n",
       "Equity(465 [WBA])  -0.02967145 -0.00855083 -0.02413786  0.01716925   \n",
       "Equity(466 [WDC])  -0.11248908  0.02938310  0.13499041  0.17141412   \n",
       "Equity(467 [WEC])   0.00086058 -0.01721494  0.02251708  0.01433085   \n",
       "Equity(468 [WFC])  -0.00880242 -0.02231278  0.02429464  0.00372331   \n",
       "Equity(469 [WHR])  -0.05450337  0.04108206  0.04115321  0.02808061   \n",
       "Equity(471 [WM])   -0.00692979  0.03223594 -0.01134834  0.03628231   \n",
       "Equity(472 [WMB])  -0.01039337 -0.00287563  0.03826935 -0.02475861   \n",
       "Equity(473 [WMT])  -0.04340883  0.02467536  0.01323727  0.01194552   \n",
       "Equity(474 [WRK])  -0.02071811  0.00905441  0.00186650 -0.01865369   \n",
       "Equity(475 [WU])   -0.00331322 -0.02121476  0.00574640 -0.03553201   \n",
       "Equity(476 [WY])   -0.00268823  0.02518978 -0.01532718 -0.02625075   \n",
       "Equity(477 [WYN])   0.01051755  0.02073259  0.01106532  0.01470477   \n",
       "Equity(478 [WYNN])  0.05793940  0.06955993 -0.05215021  0.00468932   \n",
       "Equity(479 [XEC])  -0.00217537 -0.10441731 -0.05669005  0.00593931   \n",
       "Equity(480 [XEL])  -0.00097559 -0.00596671  0.02197929  0.01863163   \n",
       "Equity(481 [XL])    0.00151969 -0.00052693  0.00744188  0.01978538   \n",
       "Equity(482 [XLNX]) -0.03587944 -0.04241793  0.00144974 -0.03148143   \n",
       "Equity(483 [XOM])  -0.01051455  0.01413654  0.00286959  0.00192552   \n",
       "Equity(484 [XRAY])  0.01167483  0.02288506 -0.02825392  0.01102642   \n",
       "Equity(485 [XRX])  -0.03324697  0.01915283 -0.01067988 -0.01247793   \n",
       "Equity(486 [XYL])  -0.00964275 -0.04118213 -0.05878742 -0.02300320   \n",
       "Equity(487 [YUM])  -0.01235304  0.00926070  0.00035906 -0.00496092   \n",
       "Equity(488 [ZBH])  -0.02675098  0.01827896 -0.04768582  0.01395948   \n",
       "Equity(489 [ZION]) -0.01158269 -0.03556539  0.00554836 -0.00341750   \n",
       "Equity(490 [ZTS])  -0.05612824 -0.01541907  0.00108249 -0.02396138   \n",
       "\n",
       "                            16          17          18          19  \n",
       "Equity(0 [A])      -0.01142920 -0.01174265  0.00526925 -0.00535269  \n",
       "Equity(1 [AAL])    -0.03310836  0.01398085 -0.04680674 -0.01599057  \n",
       "Equity(2 [AAP])    -0.01163585  0.05143999  0.05716915  0.08414961  \n",
       "Equity(3 [AAPL])   -0.03179158  0.09079374 -0.01118851  0.04291373  \n",
       "Equity(4 [ABBV])    0.01588559  0.04598554  0.01599288  0.06587978  \n",
       "Equity(5 [ABC])    -0.01834622 -0.01391370  0.01062042 -0.02739565  \n",
       "Equity(6 [ABT])    -0.03938064  0.01071208  0.01712006  0.00210689  \n",
       "Equity(7 [ACN])    -0.00285123 -0.01235874 -0.01400935 -0.03855653  \n",
       "Equity(8 [ADBE])    0.02127339 -0.03638845  0.00126811 -0.04844555  \n",
       "Equity(9 [ADI])     0.00374282  0.04583322  0.01483456  0.00768623  \n",
       "Equity(10 [ADM])   -0.02009143 -0.00246866  0.00264238 -0.00851815  \n",
       "Equity(11 [ADP])   -0.00363522  0.00584571  0.00578868 -0.02465380  \n",
       "Equity(12 [ADS])   -0.01166061 -0.02387829 -0.01844799  0.02639087  \n",
       "Equity(13 [ADSK])   0.05625388 -0.06442852 -0.03374250 -0.02718282  \n",
       "Equity(14 [AEE])    0.03531642 -0.00801202 -0.03297087 -0.03074790  \n",
       "Equity(15 [AEP])    0.03949487  0.00571290 -0.01621889 -0.01421124  \n",
       "Equity(16 [AES])    0.00968720 -0.02229136 -0.05731240 -0.01503171  \n",
       "Equity(17 [AET])    0.01958565  0.00069996  0.00650320 -0.05091908  \n",
       "Equity(18 [AFL])    0.00010718  0.00397769  0.01677661 -0.03209361  \n",
       "Equity(19 [AGN])   -0.02289392  0.02583835 -0.02092126  0.01964563  \n",
       "Equity(20 [AIG])   -0.00994737 -0.04884961 -0.01447059 -0.00092722  \n",
       "Equity(21 [AIV])   -0.01518008  0.02499635  0.04526409  0.06168561  \n",
       "Equity(22 [AIZ])    0.00889890 -0.01278457  0.00035505  0.00788631  \n",
       "Equity(23 [AJG])   -0.00386327 -0.01466289 -0.00523534  0.01165450  \n",
       "Equity(24 [AKAM])   0.00667736  0.00052245 -0.00203434  0.04370206  \n",
       "Equity(25 [ALB])   -0.04603229 -0.02452548 -0.02975526  0.05708918  \n",
       "Equity(26 [ALGN])   0.04902407  0.00156817 -0.03738565 -0.00223241  \n",
       "Equity(27 [ALK])    0.04257028  0.00789058  0.04963085 -0.04169300  \n",
       "Equity(28 [ALL])   -0.00115539  0.00082421  0.00224048 -0.00639780  \n",
       "Equity(29 [ALLE])  -0.00865976  0.03592991  0.00767178  0.03158662  \n",
       "...                        ...         ...         ...         ...  \n",
       "Equity(460 [VRSN]) -0.00752310 -0.00611545 -0.02595021 -0.00005537  \n",
       "Equity(461 [VRTX])  0.15669116  0.00258548  0.05374391 -0.10088761  \n",
       "Equity(462 [VTR])  -0.02035280 -0.00581734  0.04174183  0.02905358  \n",
       "Equity(463 [VZ])    0.00335631 -0.03321116 -0.03424556 -0.02031272  \n",
       "Equity(464 [WAT])  -0.01161567  0.05062677 -0.01607733 -0.02896756  \n",
       "Equity(465 [WBA])   0.02913337  0.03131836  0.01484323  0.00683342  \n",
       "Equity(466 [WDC])   0.11221658 -0.22112989 -0.05340130  0.27231589  \n",
       "Equity(467 [WEC])   0.04781420 -0.01020607 -0.01687023 -0.01798607  \n",
       "Equity(468 [WFC])  -0.00454128  0.00335586 -0.02606330  0.01015222  \n",
       "Equity(469 [WHR])   0.04912976  0.02732405  0.01817701  0.01086811  \n",
       "Equity(471 [WM])    0.01820702 -0.01988943  0.02403495  0.01042652  \n",
       "Equity(472 [WMB])  -0.02989245 -0.01712986 -0.10290158 -0.01224658  \n",
       "Equity(473 [WMT])  -0.02497356  0.00351902  0.00777862  0.01076198  \n",
       "Equity(474 [WRK])  -0.01239063  0.02357001 -0.02087232  0.04046773  \n",
       "Equity(475 [WU])   -0.00661356 -0.03045924  0.00995369 -0.04708063  \n",
       "Equity(476 [WY])   -0.02418712  0.00957536  0.01679332 -0.00412955  \n",
       "Equity(477 [WYN])  -0.00226587 -0.02256858 -0.03784605 -0.01748119  \n",
       "Equity(478 [WYNN]) -0.04338772  0.14131780 -0.02504257  0.02417878  \n",
       "Equity(479 [XEC])   0.06575714 -0.03770747  0.09486709 -0.06387098  \n",
       "Equity(480 [XEL])   0.04664665 -0.00826953 -0.01791475 -0.02072648  \n",
       "Equity(481 [XL])   -0.00164444  0.00315162  0.00519293 -0.03064259  \n",
       "Equity(482 [XLNX])  0.03558220  0.01661543  0.01022713 -0.00396583  \n",
       "Equity(483 [XOM])  -0.00324646  0.00012369  0.01694194  0.01003126  \n",
       "Equity(484 [XRAY])  0.01849776  0.00975355  0.00668087 -0.04636686  \n",
       "Equity(485 [XRX])   0.00098390 -0.04865041  0.01743092  0.00666409  \n",
       "Equity(486 [XYL])   0.00625647  0.04733302 -0.00256510  0.04937012  \n",
       "Equity(487 [YUM])  -0.01453755  0.01909012 -0.01126627 -0.00177409  \n",
       "Equity(488 [ZBH])   0.01018115  0.04125323  0.00671842 -0.01540844  \n",
       "Equity(489 [ZION])  0.00706111  0.00352290 -0.02193923  0.02188794  \n",
       "Equity(490 [ZTS])  -0.01026795  0.03682367  0.00833979  0.01500221  \n",
       "\n",
       "[490 rows x 20 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risk_model = {}\n",
    "risk_model['factor_betas'] = factor_betas(pca, five_year_returns.columns.values, np.arange(num_factor_exposures))\n",
    "\n",
    "risk_model['factor_betas']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Factor Returns\n",
    "Implement `factor_returns` to get the factor returns from the PCA model using the returns data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def factor_returns(pca, returns, factor_return_indices, factor_return_columns):\n",
    "    \"\"\"\n",
    "    Get the factor returns from the PCA model.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    pca : PCA\n",
    "        Model fit to returns\n",
    "    returns : DataFrame\n",
    "        Returns for each ticker and date\n",
    "    factor_return_indices : 1 dimensional Ndarray\n",
    "        Factor return indices\n",
    "    factor_return_columns : 1 dimensional Ndarray\n",
    "        Factor return columns\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    factor_returns : DataFrame\n",
    "        Factor returns\n",
    "    \"\"\"\n",
    "    assert len(factor_return_indices.shape) == 1\n",
    "    assert len(factor_return_columns.shape) == 1\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    factor_returns = pd.DataFrame(\n",
    "            data=pca.transform(returns),\n",
    "            index=returns.index\n",
    "    )\n",
    "    \n",
    "    return factor_returns\n",
    "\n",
    "\n",
    "project_tests.test_factor_returns(factor_returns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's see what these factor returns looks like over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0148593320>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f01485dcf60>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "risk_model['factor_returns'] = factor_returns(\n",
    "    pca,\n",
    "    five_year_returns,\n",
    "    five_year_returns.index,\n",
    "    np.arange(num_factor_exposures))\n",
    "\n",
    "risk_model['factor_returns'].cumsum().plot(legend=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Factor Covariance Matrix\n",
    "Implement `factor_cov_matrix` to get the factor covariance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def factor_cov_matrix(factor_returns, ann_factor):\n",
    "    \"\"\"\n",
    "    Get the factor covariance matrix\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    factor_returns : DataFrame\n",
    "        Factor returns\n",
    "    ann_factor : int\n",
    "        Annualization factor\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    factor_cov_matrix : 2 dimensional Ndarray\n",
    "        Factor covariance matrix\n",
    "    \"\"\"\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    factor_cov_matrix = np.diag(\n",
    "            factor_returns.var(axis=0, ddof=1)*ann_factor\n",
    "    )\n",
    "    \n",
    "    return factor_cov_matrix\n",
    "\n",
    "\n",
    "project_tests.test_factor_cov_matrix(factor_cov_matrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "         0.        ,  0.        ,  0.        ,  0.        ,  0.18725609]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ann_factor = 252\n",
    "risk_model['factor_cov_matrix'] = factor_cov_matrix(risk_model['factor_returns'], ann_factor)\n",
    "\n",
    "risk_model['factor_cov_matrix']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Idiosyncratic Variance Matrix\n",
    "Implement `idiosyncratic_var_matrix` to get the idiosyncratic variance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def idiosyncratic_var_matrix(returns, factor_returns, factor_betas, ann_factor):\n",
    "    \"\"\"\n",
    "    Get the idiosyncratic variance matrix\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    returns : DataFrame\n",
    "        Returns for each ticker and date\n",
    "    factor_returns : DataFrame\n",
    "        Factor returns\n",
    "    factor_betas : DataFrame\n",
    "        Factor betas\n",
    "    ann_factor : int\n",
    "        Annualization factor\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    idiosyncratic_var_matrix : DataFrame\n",
    "        Idiosyncratic variance matrix\n",
    "    \"\"\"\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    common_returns = pd.DataFrame(\n",
    "            data=np.dot(factor_returns, factor_betas.T),\n",
    "            index=returns.index, columns=returns.columns)\n",
    "    \n",
    "    residuals = returns - common_returns\n",
    "\n",
    "    idiosyncratic_var_matrix = pd.DataFrame(\n",
    "            data=np.diag(np.var(residuals))*ann_factor,\n",
    "            index=returns.columns, columns=returns.columns\n",
    "    )\n",
    "    \n",
    "    return idiosyncratic_var_matrix\n",
    "\n",
    "\n",
    "project_tests.test_idiosyncratic_var_matrix(idiosyncratic_var_matrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Equity(2 [AAP])</th>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
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       "      <th>Equity(481 [XL])</th>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
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       "    <tr>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.05190083</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "    <tr>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "    <tr>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02177470</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.03442125</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(9 [ADI])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
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       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01898404</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(10 [ADM])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(11 [ADP])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(12 [ADS])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(13 [ADSK])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(14 [AEE])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(15 [AEP])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(16 [AES])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(17 [AET])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(18 [AFL])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(19 [AGN])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(20 [AIG])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(21 [AIV])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(22 [AIZ])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(23 [AJG])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(24 [AKAM])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(25 [ALB])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(26 [ALGN])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(27 [ALK])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(28 [ALL])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(29 [ALLE])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(460 [VRSN])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(461 [VRTX])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(462 [VTR])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(463 [VZ])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(464 [WAT])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(465 [WBA])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(466 [WDC])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(467 [WEC])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(468 [WFC])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(469 [WHR])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(471 [WM])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(472 [WMB])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(473 [WMT])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(474 [WRK])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(475 [WU])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(476 [WY])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(477 [WYN])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(478 [WYNN])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(479 [XEC])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(480 [XEL])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02051926</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02684299</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01059841</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.01537171</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.03946866</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.03191603</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.04385518</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02233019</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02337210</td>\n",
       "      <td>0.00000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.00000000</td>\n",
       "      <td>0.02735075</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>490 rows × 490 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Equity(0 [A])  Equity(1 [AAL])  Equity(2 [AAP])  \\\n",
       "Equity(0 [A])          0.02272535       0.00000000       0.00000000   \n",
       "Equity(1 [AAL])        0.00000000       0.05190083       0.00000000   \n",
       "Equity(2 [AAP])        0.00000000       0.00000000       0.05431181   \n",
       "Equity(3 [AAPL])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(4 [ABBV])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(5 [ABC])        0.00000000       0.00000000       0.00000000   \n",
       "Equity(6 [ABT])        0.00000000       0.00000000       0.00000000   \n",
       "Equity(7 [ACN])        0.00000000       0.00000000       0.00000000   \n",
       "Equity(8 [ADBE])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(9 [ADI])        0.00000000       0.00000000       0.00000000   \n",
       "Equity(10 [ADM])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(11 [ADP])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(12 [ADS])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(13 [ADSK])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(14 [AEE])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(15 [AEP])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(16 [AES])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(17 [AET])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(18 [AFL])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(19 [AGN])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(20 [AIG])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(21 [AIV])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(22 [AIZ])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(23 [AJG])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(24 [AKAM])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(25 [ALB])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(26 [ALGN])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(27 [ALK])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(28 [ALL])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(29 [ALLE])      0.00000000       0.00000000       0.00000000   \n",
       "...                           ...              ...              ...   \n",
       "Equity(460 [VRSN])     0.00000000       0.00000000       0.00000000   \n",
       "Equity(461 [VRTX])     0.00000000       0.00000000       0.00000000   \n",
       "Equity(462 [VTR])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(463 [VZ])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(464 [WAT])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(465 [WBA])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(466 [WDC])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(467 [WEC])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(468 [WFC])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(469 [WHR])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(471 [WM])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(472 [WMB])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(473 [WMT])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(474 [WRK])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(475 [WU])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(476 [WY])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(477 [WYN])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(478 [WYNN])     0.00000000       0.00000000       0.00000000   \n",
       "Equity(479 [XEC])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(480 [XEL])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(481 [XL])       0.00000000       0.00000000       0.00000000   \n",
       "Equity(482 [XLNX])     0.00000000       0.00000000       0.00000000   \n",
       "Equity(483 [XOM])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(484 [XRAY])     0.00000000       0.00000000       0.00000000   \n",
       "Equity(485 [XRX])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(486 [XYL])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(487 [YUM])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(488 [ZBH])      0.00000000       0.00000000       0.00000000   \n",
       "Equity(489 [ZION])     0.00000000       0.00000000       0.00000000   \n",
       "Equity(490 [ZTS])      0.00000000       0.00000000       0.00000000   \n",
       "\n",
       "                    Equity(3 [AAPL])  Equity(4 [ABBV])  Equity(5 [ABC])  \\\n",
       "Equity(0 [A])             0.00000000        0.00000000       0.00000000   \n",
       "Equity(1 [AAL])           0.00000000        0.00000000       0.00000000   \n",
       "Equity(2 [AAP])           0.00000000        0.00000000       0.00000000   \n",
       "Equity(3 [AAPL])          0.04801884        0.00000000       0.00000000   \n",
       "Equity(4 [ABBV])          0.00000000        0.03040361       0.00000000   \n",
       "Equity(5 [ABC])           0.00000000        0.00000000       0.01854504   \n",
       "Equity(6 [ABT])           0.00000000        0.00000000       0.00000000   \n",
       "Equity(7 [ACN])           0.00000000        0.00000000       0.00000000   \n",
       "Equity(8 [ADBE])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(9 [ADI])           0.00000000        0.00000000       0.00000000   \n",
       "Equity(10 [ADM])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(11 [ADP])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(12 [ADS])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(13 [ADSK])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(14 [AEE])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(15 [AEP])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(16 [AES])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(17 [AET])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(18 [AFL])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(19 [AGN])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(20 [AIG])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(21 [AIV])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(22 [AIZ])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(23 [AJG])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(24 [AKAM])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(25 [ALB])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(26 [ALGN])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(27 [ALK])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(28 [ALL])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(29 [ALLE])         0.00000000        0.00000000       0.00000000   \n",
       "...                              ...               ...              ...   \n",
       "Equity(460 [VRSN])        0.00000000        0.00000000       0.00000000   \n",
       "Equity(461 [VRTX])        0.00000000        0.00000000       0.00000000   \n",
       "Equity(462 [VTR])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(463 [VZ])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(464 [WAT])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(465 [WBA])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(466 [WDC])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(467 [WEC])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(468 [WFC])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(469 [WHR])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(471 [WM])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(472 [WMB])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(473 [WMT])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(474 [WRK])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(475 [WU])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(476 [WY])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(477 [WYN])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(478 [WYNN])        0.00000000        0.00000000       0.00000000   \n",
       "Equity(479 [XEC])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(480 [XEL])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(481 [XL])          0.00000000        0.00000000       0.00000000   \n",
       "Equity(482 [XLNX])        0.00000000        0.00000000       0.00000000   \n",
       "Equity(483 [XOM])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(484 [XRAY])        0.00000000        0.00000000       0.00000000   \n",
       "Equity(485 [XRX])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(486 [XYL])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(487 [YUM])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(488 [ZBH])         0.00000000        0.00000000       0.00000000   \n",
       "Equity(489 [ZION])        0.00000000        0.00000000       0.00000000   \n",
       "Equity(490 [ZTS])         0.00000000        0.00000000       0.00000000   \n",
       "\n",
       "                    Equity(6 [ABT])  Equity(7 [ACN])  Equity(8 [ADBE])  \\\n",
       "Equity(0 [A])            0.00000000       0.00000000        0.00000000   \n",
       "Equity(1 [AAL])          0.00000000       0.00000000        0.00000000   \n",
       "Equity(2 [AAP])          0.00000000       0.00000000        0.00000000   \n",
       "Equity(3 [AAPL])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(4 [ABBV])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(5 [ABC])          0.00000000       0.00000000        0.00000000   \n",
       "Equity(6 [ABT])          0.01481514       0.00000000        0.00000000   \n",
       "Equity(7 [ACN])          0.00000000       0.02177470        0.00000000   \n",
       "Equity(8 [ADBE])         0.00000000       0.00000000        0.03442125   \n",
       "Equity(9 [ADI])          0.00000000       0.00000000        0.00000000   \n",
       "Equity(10 [ADM])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(11 [ADP])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(12 [ADS])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(13 [ADSK])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(14 [AEE])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(15 [AEP])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(16 [AES])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(17 [AET])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(18 [AFL])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(19 [AGN])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(20 [AIG])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(21 [AIV])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(22 [AIZ])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(23 [AJG])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(24 [AKAM])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(25 [ALB])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(26 [ALGN])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(27 [ALK])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(28 [ALL])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(29 [ALLE])        0.00000000       0.00000000        0.00000000   \n",
       "...                             ...              ...               ...   \n",
       "Equity(460 [VRSN])       0.00000000       0.00000000        0.00000000   \n",
       "Equity(461 [VRTX])       0.00000000       0.00000000        0.00000000   \n",
       "Equity(462 [VTR])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(463 [VZ])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(464 [WAT])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(465 [WBA])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(466 [WDC])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(467 [WEC])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(468 [WFC])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(469 [WHR])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(471 [WM])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(472 [WMB])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(473 [WMT])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(474 [WRK])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(475 [WU])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(476 [WY])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(477 [WYN])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(478 [WYNN])       0.00000000       0.00000000        0.00000000   \n",
       "Equity(479 [XEC])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(480 [XEL])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(481 [XL])         0.00000000       0.00000000        0.00000000   \n",
       "Equity(482 [XLNX])       0.00000000       0.00000000        0.00000000   \n",
       "Equity(483 [XOM])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(484 [XRAY])       0.00000000       0.00000000        0.00000000   \n",
       "Equity(485 [XRX])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(486 [XYL])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(487 [YUM])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(488 [ZBH])        0.00000000       0.00000000        0.00000000   \n",
       "Equity(489 [ZION])       0.00000000       0.00000000        0.00000000   \n",
       "Equity(490 [ZTS])        0.00000000       0.00000000        0.00000000   \n",
       "\n",
       "                    Equity(9 [ADI])        ...          Equity(481 [XL])  \\\n",
       "Equity(0 [A])            0.00000000        ...                0.00000000   \n",
       "Equity(1 [AAL])          0.00000000        ...                0.00000000   \n",
       "Equity(2 [AAP])          0.00000000        ...                0.00000000   \n",
       "Equity(3 [AAPL])         0.00000000        ...                0.00000000   \n",
       "Equity(4 [ABBV])         0.00000000        ...                0.00000000   \n",
       "Equity(5 [ABC])          0.00000000        ...                0.00000000   \n",
       "Equity(6 [ABT])          0.00000000        ...                0.00000000   \n",
       "Equity(7 [ACN])          0.00000000        ...                0.00000000   \n",
       "Equity(8 [ADBE])         0.00000000        ...                0.00000000   \n",
       "Equity(9 [ADI])          0.01898404        ...                0.00000000   \n",
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       "\n",
       "                    Equity(482 [XLNX])  Equity(483 [XOM])  Equity(484 [XRAY])  \\\n",
       "Equity(0 [A])               0.00000000         0.00000000          0.00000000   \n",
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       "Equity(22 [AIZ])            0.00000000         0.00000000          0.00000000   \n",
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       "Equity(24 [AKAM])           0.00000000         0.00000000          0.00000000   \n",
       "Equity(25 [ALB])            0.00000000         0.00000000          0.00000000   \n",
       "Equity(26 [ALGN])           0.00000000         0.00000000          0.00000000   \n",
       "Equity(27 [ALK])            0.00000000         0.00000000          0.00000000   \n",
       "Equity(28 [ALL])            0.00000000         0.00000000          0.00000000   \n",
       "Equity(29 [ALLE])           0.00000000         0.00000000          0.00000000   \n",
       "...                                ...                ...                 ...   \n",
       "Equity(460 [VRSN])          0.00000000         0.00000000          0.00000000   \n",
       "Equity(461 [VRTX])          0.00000000         0.00000000          0.00000000   \n",
       "Equity(462 [VTR])           0.00000000         0.00000000          0.00000000   \n",
       "Equity(463 [VZ])            0.00000000         0.00000000          0.00000000   \n",
       "Equity(464 [WAT])           0.00000000         0.00000000          0.00000000   \n",
       "Equity(465 [WBA])           0.00000000         0.00000000          0.00000000   \n",
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       "Equity(489 [ZION])          0.00000000         0.00000000          0.00000000   \n",
       "Equity(490 [ZTS])           0.00000000         0.00000000          0.00000000   \n",
       "\n",
       "                    Equity(485 [XRX])  Equity(486 [XYL])  Equity(487 [YUM])  \\\n",
       "Equity(0 [A])              0.00000000         0.00000000         0.00000000   \n",
       "Equity(1 [AAL])            0.00000000         0.00000000         0.00000000   \n",
       "Equity(2 [AAP])            0.00000000         0.00000000         0.00000000   \n",
       "Equity(3 [AAPL])           0.00000000         0.00000000         0.00000000   \n",
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       "Equity(5 [ABC])            0.00000000         0.00000000         0.00000000   \n",
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       "Equity(9 [ADI])            0.00000000         0.00000000         0.00000000   \n",
       "Equity(10 [ADM])           0.00000000         0.00000000         0.00000000   \n",
       "Equity(11 [ADP])           0.00000000         0.00000000         0.00000000   \n",
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       "Equity(13 [ADSK])          0.00000000         0.00000000         0.00000000   \n",
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       "...                               ...                ...                ...   \n",
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       "Equity(466 [WDC])          0.00000000         0.00000000         0.00000000   \n",
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       "Equity(488 [ZBH])          0.00000000         0.00000000         0.00000000   \n",
       "Equity(489 [ZION])         0.00000000         0.00000000         0.00000000   \n",
       "Equity(490 [ZTS])          0.00000000         0.00000000         0.00000000   \n",
       "\n",
       "                    Equity(488 [ZBH])  Equity(489 [ZION])  Equity(490 [ZTS])  \n",
       "Equity(0 [A])              0.00000000          0.00000000         0.00000000  \n",
       "Equity(1 [AAL])            0.00000000          0.00000000         0.00000000  \n",
       "Equity(2 [AAP])            0.00000000          0.00000000         0.00000000  \n",
       "Equity(3 [AAPL])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(4 [ABBV])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(5 [ABC])            0.00000000          0.00000000         0.00000000  \n",
       "Equity(6 [ABT])            0.00000000          0.00000000         0.00000000  \n",
       "Equity(7 [ACN])            0.00000000          0.00000000         0.00000000  \n",
       "Equity(8 [ADBE])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(9 [ADI])            0.00000000          0.00000000         0.00000000  \n",
       "Equity(10 [ADM])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(11 [ADP])           0.00000000          0.00000000         0.00000000  \n",
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       "Equity(13 [ADSK])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(14 [AEE])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(15 [AEP])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(16 [AES])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(17 [AET])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(18 [AFL])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(19 [AGN])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(20 [AIG])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(21 [AIV])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(22 [AIZ])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(23 [AJG])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(24 [AKAM])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(25 [ALB])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(26 [ALGN])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(27 [ALK])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(28 [ALL])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(29 [ALLE])          0.00000000          0.00000000         0.00000000  \n",
       "...                               ...                 ...                ...  \n",
       "Equity(460 [VRSN])         0.00000000          0.00000000         0.00000000  \n",
       "Equity(461 [VRTX])         0.00000000          0.00000000         0.00000000  \n",
       "Equity(462 [VTR])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(463 [VZ])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(464 [WAT])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(465 [WBA])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(466 [WDC])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(467 [WEC])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(468 [WFC])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(469 [WHR])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(471 [WM])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(472 [WMB])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(473 [WMT])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(474 [WRK])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(475 [WU])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(476 [WY])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(477 [WYN])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(478 [WYNN])         0.00000000          0.00000000         0.00000000  \n",
       "Equity(479 [XEC])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(480 [XEL])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(481 [XL])           0.00000000          0.00000000         0.00000000  \n",
       "Equity(482 [XLNX])         0.00000000          0.00000000         0.00000000  \n",
       "Equity(483 [XOM])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(484 [XRAY])         0.00000000          0.00000000         0.00000000  \n",
       "Equity(485 [XRX])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(486 [XYL])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(487 [YUM])          0.00000000          0.00000000         0.00000000  \n",
       "Equity(488 [ZBH])          0.02233019          0.00000000         0.00000000  \n",
       "Equity(489 [ZION])         0.00000000          0.02337210         0.00000000  \n",
       "Equity(490 [ZTS])          0.00000000          0.00000000         0.02735075  \n",
       "\n",
       "[490 rows x 490 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risk_model['idiosyncratic_var_matrix'] = idiosyncratic_var_matrix(five_year_returns, risk_model['factor_returns'], risk_model['factor_betas'], ann_factor)\n",
    "\n",
    "risk_model['idiosyncratic_var_matrix']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Idiosyncratic Variance Vector\n",
    "Implement `idiosyncratic_var_vector` to get the idiosyncratic variance Vector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def idiosyncratic_var_vector(returns, idiosyncratic_var_matrix):\n",
    "    \"\"\"\n",
    "    Get the idiosyncratic variance vector\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    returns : DataFrame\n",
    "        Returns for each ticker and date\n",
    "    idiosyncratic_var_matrix : DataFrame\n",
    "        Idiosyncratic variance matrix\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    idiosyncratic_var_vector : DataFrame\n",
    "        Idiosyncratic variance Vector\n",
    "    \"\"\"\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    idiosyncratic_var_vector = pd.DataFrame(\n",
    "            data=np.diag(idiosyncratic_var_matrix.values),\n",
    "            index=returns.columns)\n",
    "    \n",
    "    return idiosyncratic_var_vector\n",
    "\n",
    "\n",
    "project_tests.test_idiosyncratic_var_vector(idiosyncratic_var_vector)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>0</th>\n",
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       "      <th>Equity(9 [ADI])</th>\n",
       "      <td>0.01898404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(10 [ADM])</th>\n",
       "      <td>0.02951444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(11 [ADP])</th>\n",
       "      <td>0.00828126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(12 [ADS])</th>\n",
       "      <td>0.02703428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(13 [ADSK])</th>\n",
       "      <td>0.05224263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(14 [AEE])</th>\n",
       "      <td>0.00961462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(15 [AEP])</th>\n",
       "      <td>0.00800376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(16 [AES])</th>\n",
       "      <td>0.03079578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(17 [AET])</th>\n",
       "      <td>0.03579077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(18 [AFL])</th>\n",
       "      <td>0.01894194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(19 [AGN])</th>\n",
       "      <td>0.04211602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(20 [AIG])</th>\n",
       "      <td>0.03317545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(21 [AIV])</th>\n",
       "      <td>0.01468534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(22 [AIZ])</th>\n",
       "      <td>0.02061951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(23 [AJG])</th>\n",
       "      <td>0.01157320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(24 [AKAM])</th>\n",
       "      <td>0.09690009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(25 [ALB])</th>\n",
       "      <td>0.04106647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(26 [ALGN])</th>\n",
       "      <td>0.10508661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(27 [ALK])</th>\n",
       "      <td>0.03388559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(28 [ALL])</th>\n",
       "      <td>0.01674196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(29 [ALLE])</th>\n",
       "      <td>0.01456581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(460 [VRSN])</th>\n",
       "      <td>0.04356330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(461 [VRTX])</th>\n",
       "      <td>0.01133104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(462 [VTR])</th>\n",
       "      <td>0.01239277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(463 [VZ])</th>\n",
       "      <td>0.01826124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(464 [WAT])</th>\n",
       "      <td>0.02519289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(465 [WBA])</th>\n",
       "      <td>0.04833797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(466 [WDC])</th>\n",
       "      <td>0.04271307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(467 [WEC])</th>\n",
       "      <td>0.00660139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(468 [WFC])</th>\n",
       "      <td>0.01138111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(469 [WHR])</th>\n",
       "      <td>0.05778786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(471 [WM])</th>\n",
       "      <td>0.01511105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(472 [WMB])</th>\n",
       "      <td>0.05868578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(473 [WMT])</th>\n",
       "      <td>0.01608075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(474 [WRK])</th>\n",
       "      <td>0.00835928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(475 [WU])</th>\n",
       "      <td>0.04770344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(476 [WY])</th>\n",
       "      <td>0.02646036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(477 [WYN])</th>\n",
       "      <td>0.02429392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(478 [WYNN])</th>\n",
       "      <td>0.05814062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(479 [XEC])</th>\n",
       "      <td>0.04861817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(480 [XEL])</th>\n",
       "      <td>0.00534852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <td>0.02051926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <td>0.02684299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <td>0.01059841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <td>0.01537171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <td>0.03946866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <td>0.03191603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <td>0.04385518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <td>0.02233019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <td>0.02337210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "      <td>0.02735075</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>490 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            0\n",
       "Equity(0 [A])      0.02272535\n",
       "Equity(1 [AAL])    0.05190083\n",
       "Equity(2 [AAP])    0.05431181\n",
       "Equity(3 [AAPL])   0.04801884\n",
       "Equity(4 [ABBV])   0.03040361\n",
       "Equity(5 [ABC])    0.01854504\n",
       "Equity(6 [ABT])    0.01481514\n",
       "Equity(7 [ACN])    0.02177470\n",
       "Equity(8 [ADBE])   0.03442125\n",
       "Equity(9 [ADI])    0.01898404\n",
       "Equity(10 [ADM])   0.02951444\n",
       "Equity(11 [ADP])   0.00828126\n",
       "Equity(12 [ADS])   0.02703428\n",
       "Equity(13 [ADSK])  0.05224263\n",
       "Equity(14 [AEE])   0.00961462\n",
       "Equity(15 [AEP])   0.00800376\n",
       "Equity(16 [AES])   0.03079578\n",
       "Equity(17 [AET])   0.03579077\n",
       "Equity(18 [AFL])   0.01894194\n",
       "Equity(19 [AGN])   0.04211602\n",
       "Equity(20 [AIG])   0.03317545\n",
       "Equity(21 [AIV])   0.01468534\n",
       "Equity(22 [AIZ])   0.02061951\n",
       "Equity(23 [AJG])   0.01157320\n",
       "Equity(24 [AKAM])  0.09690009\n",
       "Equity(25 [ALB])   0.04106647\n",
       "Equity(26 [ALGN])  0.10508661\n",
       "Equity(27 [ALK])   0.03388559\n",
       "Equity(28 [ALL])   0.01674196\n",
       "Equity(29 [ALLE])  0.01456581\n",
       "...                       ...\n",
       "Equity(460 [VRSN]) 0.04356330\n",
       "Equity(461 [VRTX]) 0.01133104\n",
       "Equity(462 [VTR])  0.01239277\n",
       "Equity(463 [VZ])   0.01826124\n",
       "Equity(464 [WAT])  0.02519289\n",
       "Equity(465 [WBA])  0.04833797\n",
       "Equity(466 [WDC])  0.04271307\n",
       "Equity(467 [WEC])  0.00660139\n",
       "Equity(468 [WFC])  0.01138111\n",
       "Equity(469 [WHR])  0.05778786\n",
       "Equity(471 [WM])   0.01511105\n",
       "Equity(472 [WMB])  0.05868578\n",
       "Equity(473 [WMT])  0.01608075\n",
       "Equity(474 [WRK])  0.00835928\n",
       "Equity(475 [WU])   0.04770344\n",
       "Equity(476 [WY])   0.02646036\n",
       "Equity(477 [WYN])  0.02429392\n",
       "Equity(478 [WYNN]) 0.05814062\n",
       "Equity(479 [XEC])  0.04861817\n",
       "Equity(480 [XEL])  0.00534852\n",
       "Equity(481 [XL])   0.02051926\n",
       "Equity(482 [XLNX]) 0.02684299\n",
       "Equity(483 [XOM])  0.01059841\n",
       "Equity(484 [XRAY]) 0.01537171\n",
       "Equity(485 [XRX])  0.03946866\n",
       "Equity(486 [XYL])  0.03191603\n",
       "Equity(487 [YUM])  0.04385518\n",
       "Equity(488 [ZBH])  0.02233019\n",
       "Equity(489 [ZION]) 0.02337210\n",
       "Equity(490 [ZTS])  0.02735075\n",
       "\n",
       "[490 rows x 1 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risk_model['idiosyncratic_var_vector'] = idiosyncratic_var_vector(five_year_returns, risk_model['idiosyncratic_var_matrix'])\n",
    "\n",
    "risk_model['idiosyncratic_var_vector']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predict using the Risk Model\n",
    "Using the data we calculated in the risk model, implement `predict_portfolio_risk` to predict the portfolio risk using the formula $ \\sqrt{X^{T}(BFB^{T} + S)X} $ where:\n",
    "- $ X $ is the portfolio weights\n",
    "- $ B $ is the factor betas\n",
    "- $ F $ is the factor covariance matrix\n",
    "- $ S $ is the idiosyncratic variance matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def predict_portfolio_risk(factor_betas, factor_cov_matrix, idiosyncratic_var_matrix, weights):\n",
    "    \"\"\"\n",
    "    Get the predicted portfolio risk\n",
    "    \n",
    "    Formula for predicted portfolio risk is sqrt(X.T(BFB.T + S)X) where:\n",
    "      X is the portfolio weights\n",
    "      B is the factor betas\n",
    "      F is the factor covariance matrix\n",
    "      S is the idiosyncratic variance matrix\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    factor_betas : DataFrame\n",
    "        Factor betas\n",
    "    factor_cov_matrix : 2 dimensional Ndarray\n",
    "        Factor covariance matrix\n",
    "    idiosyncratic_var_matrix : DataFrame\n",
    "        Idiosyncratic variance matrix\n",
    "    weights : DataFrame\n",
    "        Portfolio weights\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    predicted_portfolio_risk : float\n",
    "        Predicted portfolio risk\n",
    "    \"\"\"\n",
    "    assert len(factor_cov_matrix.shape) == 2\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    f = np.dot(np.dot(factor_betas, factor_cov_matrix), factor_betas.T) + idiosyncratic_var_matrix\n",
    "    \n",
    "    predicted_portfolio_risk = np.sqrt(np.dot(np.dot(weights.T, f), weights)[0][0])\n",
    "    \n",
    "    return predicted_portfolio_risk\n",
    "\n",
    "\n",
    "project_tests.test_predict_portfolio_risk(predict_portfolio_risk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's see what the portfolio risk would be if we had even weights across all stocks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.16094824687040474"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_weights = pd.DataFrame(np.repeat(1/len(universe_tickers), len(universe_tickers)), universe_tickers)\n",
    "\n",
    "predict_portfolio_risk(\n",
    "    risk_model['factor_betas'],\n",
    "    risk_model['factor_cov_matrix'],\n",
    "    risk_model['idiosyncratic_var_matrix'],\n",
    "    all_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create Alpha Factors\n",
    "With the profile risk calculated, it's time to start working on the alpha factors. In this project, we'll create the following factors:\n",
    "- Momentum 1 Year Factor\n",
    "- Mean Reversion 5 Day Sector Neutral Factor\n",
    "- Mean Reversion 5 Day Sector Neutral Smoothed Factor\n",
    "- Overnight Sentiment Factor\n",
    "- Overnight Sentiment Smoothed Factor\n",
    "\n",
    "## Momentum 1 Year Factor\n",
    "Each factor will have a hypothesis that goes with it. For this factor, it is \"Higher past 12-month (252 days) returns are proportional to future return.\" Using that hypothesis, we've generated this code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.pipeline.factors import Returns\n",
    "\n",
    "def momentum_1yr(window_length, universe, sector):\n",
    "    return Returns(window_length=window_length, mask=universe) \\\n",
    "        .demean(groupby=sector) \\\n",
    "        .rank() \\\n",
    "        .zscore()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Reversion 5 Day Sector Neutral Factor\n",
    "Now it's time for you to implement `mean_reversion_5day_sector_neutral` using the hypothesis \"Short-term outperformers(underperformers) compared to their sector will revert.\" Use the returns data from `universe`, demean using the sector data to partition, rank, then converted to a zscore."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Integration Test on pipeline:\n",
      "> start_dat = pd.Timestamp('2015-01-05', tz='utc')\n",
      "> end_date = pd.Timestamp('2015-01-07', tz='utc')\n",
      "> universe = AverageDollarVolume(window_length=2).top(4)\n",
      "> factor = mean_reversion_5day_sector_neutral(\n",
      "    window_length=3,\n",
      "    universe=universe,\n",
      "    sector=project_helper.Sector())\n",
      "> pipeline.add(factor, 'Mean_Reversion_5Day_Sector_Neutral')\n",
      "> engine.run_pipeline(pipeline, start_dat, end_date)\n",
      "\n",
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def mean_reversion_5day_sector_neutral(window_length, universe, sector):\n",
    "    \"\"\"\n",
    "    Generate the mean reversion 5 day sector neutral factor\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    window_length : int\n",
    "        Returns window length\n",
    "    universe : Zipline Filter\n",
    "        Universe of stocks filter\n",
    "    sector : Zipline Classifier\n",
    "        Sector classifier\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    factor : Zipline Factor\n",
    "        Mean reversion 5 day sector neutral factor\n",
    "    \"\"\"\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    factor = momentum_1yr(window_length, universe, sector)*-1\n",
    "    \n",
    "    return factor \n",
    "\n",
    "project_tests.test_mean_reversion_5day_sector_neutral(mean_reversion_5day_sector_neutral)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's see what some of the factor data looks like. For calculating factors, we'll be looking back 2 years.\n",
    "\n",
    "**Note:** _Going back 2 years falls on a day when the market is closed. Pipeline package doesn't handle start or end dates that don't fall on days when the market is open. To fix this, we went back 2 extra days to fall on the next day when the market is open._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Mean_Reversion_5Day_Sector_Neutral</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2014-01-03 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <td>0.85326482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <td>1.62630815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <td>0.64906469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <td>1.40752230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <td>1.45857233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <td>0.14585723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <td>-0.30630019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <td>0.88243626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
       "      <td>-0.06563576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(9 [ADI])</th>\n",
       "      <td>1.67006532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(10 [ADM])</th>\n",
       "      <td>1.18144359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(11 [ADP])</th>\n",
       "      <td>0.24066444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(12 [ADS])</th>\n",
       "      <td>-1.69194391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(13 [ADSK])</th>\n",
       "      <td>-0.35735022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(14 [AEE])</th>\n",
       "      <td>0.34276450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(15 [AEP])</th>\n",
       "      <td>-0.45215742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(16 [AES])</th>\n",
       "      <td>0.50320746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(17 [AET])</th>\n",
       "      <td>0.79492192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(18 [AFL])</th>\n",
       "      <td>1.15227214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(19 [AGN])</th>\n",
       "      <td>-1.48045092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(20 [AIG])</th>\n",
       "      <td>-0.27712874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(21 [AIV])</th>\n",
       "      <td>-0.37922881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(22 [AIZ])</th>\n",
       "      <td>0.91890057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(23 [AJG])</th>\n",
       "      <td>-0.82409337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(24 [AKAM])</th>\n",
       "      <td>1.22520076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(25 [ALB])</th>\n",
       "      <td>0.69282186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(26 [ALGN])</th>\n",
       "      <td>1.08663639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(27 [ALK])</th>\n",
       "      <td>-1.30542224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(28 [ALL])</th>\n",
       "      <td>-0.48862173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(29 [ALLE])</th>\n",
       "      <td>1.42940089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2016-01-05 00:00:00+00:00</th>\n",
       "      <th>Equity(460 [VRSN])</th>\n",
       "      <td>1.48614551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(461 [VRTX])</th>\n",
       "      <td>-1.15826688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(462 [VTR])</th>\n",
       "      <td>-1.55742347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(463 [VZ])</th>\n",
       "      <td>-1.42912314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(464 [WAT])</th>\n",
       "      <td>0.47399845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(465 [WBA])</th>\n",
       "      <td>1.21528925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(466 [WDC])</th>\n",
       "      <td>-1.59306245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(467 [WEC])</th>\n",
       "      <td>-0.13899203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(468 [WFC])</th>\n",
       "      <td>0.35995371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(469 [WHR])</th>\n",
       "      <td>-1.15113908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(471 [WM])</th>\n",
       "      <td>0.38133710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(472 [WMB])</th>\n",
       "      <td>-1.69285160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(473 [WMT])</th>\n",
       "      <td>-1.52891228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(474 [WRK])</th>\n",
       "      <td>-1.32220619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(475 [WU])</th>\n",
       "      <td>0.54527641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(476 [WY])</th>\n",
       "      <td>0.08196966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(477 [WYN])</th>\n",
       "      <td>1.19390586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(478 [WYNN])</th>\n",
       "      <td>-1.49327330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(479 [XEC])</th>\n",
       "      <td>0.30293134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(480 [XEL])</th>\n",
       "      <td>0.02494729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <td>1.06560553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <td>1.34358958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <td>1.60019024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <td>1.22241705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <td>0.33144252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <td>-0.13186423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <td>0.18175880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <td>-1.40061195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <td>0.52389302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "      <td>-0.93730520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244259 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Mean_Reversion_5Day_Sector_Neutral\n",
       "2014-01-03 00:00:00+00:00 Equity(0 [A])                               0.85326482\n",
       "                          Equity(1 [AAL])                             1.62630815\n",
       "                          Equity(2 [AAP])                             0.64906469\n",
       "                          Equity(3 [AAPL])                            1.40752230\n",
       "                          Equity(4 [ABBV])                            1.45857233\n",
       "                          Equity(5 [ABC])                             0.14585723\n",
       "                          Equity(6 [ABT])                            -0.30630019\n",
       "                          Equity(7 [ACN])                             0.88243626\n",
       "                          Equity(8 [ADBE])                           -0.06563576\n",
       "                          Equity(9 [ADI])                             1.67006532\n",
       "                          Equity(10 [ADM])                            1.18144359\n",
       "                          Equity(11 [ADP])                            0.24066444\n",
       "                          Equity(12 [ADS])                           -1.69194391\n",
       "                          Equity(13 [ADSK])                          -0.35735022\n",
       "                          Equity(14 [AEE])                            0.34276450\n",
       "                          Equity(15 [AEP])                           -0.45215742\n",
       "                          Equity(16 [AES])                            0.50320746\n",
       "                          Equity(17 [AET])                            0.79492192\n",
       "                          Equity(18 [AFL])                            1.15227214\n",
       "                          Equity(19 [AGN])                           -1.48045092\n",
       "                          Equity(20 [AIG])                           -0.27712874\n",
       "                          Equity(21 [AIV])                           -0.37922881\n",
       "                          Equity(22 [AIZ])                            0.91890057\n",
       "                          Equity(23 [AJG])                           -0.82409337\n",
       "                          Equity(24 [AKAM])                           1.22520076\n",
       "                          Equity(25 [ALB])                            0.69282186\n",
       "                          Equity(26 [ALGN])                           1.08663639\n",
       "                          Equity(27 [ALK])                           -1.30542224\n",
       "                          Equity(28 [ALL])                           -0.48862173\n",
       "                          Equity(29 [ALLE])                           1.42940089\n",
       "...                                                                          ...\n",
       "2016-01-05 00:00:00+00:00 Equity(460 [VRSN])                          1.48614551\n",
       "                          Equity(461 [VRTX])                         -1.15826688\n",
       "                          Equity(462 [VTR])                          -1.55742347\n",
       "                          Equity(463 [VZ])                           -1.42912314\n",
       "                          Equity(464 [WAT])                           0.47399845\n",
       "                          Equity(465 [WBA])                           1.21528925\n",
       "                          Equity(466 [WDC])                          -1.59306245\n",
       "                          Equity(467 [WEC])                          -0.13899203\n",
       "                          Equity(468 [WFC])                           0.35995371\n",
       "                          Equity(469 [WHR])                          -1.15113908\n",
       "                          Equity(471 [WM])                            0.38133710\n",
       "                          Equity(472 [WMB])                          -1.69285160\n",
       "                          Equity(473 [WMT])                          -1.52891228\n",
       "                          Equity(474 [WRK])                          -1.32220619\n",
       "                          Equity(475 [WU])                            0.54527641\n",
       "                          Equity(476 [WY])                            0.08196966\n",
       "                          Equity(477 [WYN])                           1.19390586\n",
       "                          Equity(478 [WYNN])                         -1.49327330\n",
       "                          Equity(479 [XEC])                           0.30293134\n",
       "                          Equity(480 [XEL])                           0.02494729\n",
       "                          Equity(481 [XL])                            1.06560553\n",
       "                          Equity(482 [XLNX])                          1.34358958\n",
       "                          Equity(483 [XOM])                           1.60019024\n",
       "                          Equity(484 [XRAY])                          1.22241705\n",
       "                          Equity(485 [XRX])                           0.33144252\n",
       "                          Equity(486 [XYL])                          -0.13186423\n",
       "                          Equity(487 [YUM])                           0.18175880\n",
       "                          Equity(488 [ZBH])                          -1.40061195\n",
       "                          Equity(489 [ZION])                          0.52389302\n",
       "                          Equity(490 [ZTS])                          -0.93730520\n",
       "\n",
       "[244259 rows x 1 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factor_start_date = universe_end_date - pd.DateOffset(years=2, days=2)\n",
    "sector = project_helper.Sector()\n",
    "window_length = 5\n",
    "\n",
    "pipeline = Pipeline(screen=universe)\n",
    "pipeline.add(\n",
    "    mean_reversion_5day_sector_neutral(window_length, universe, sector),\n",
    "    'Mean_Reversion_5Day_Sector_Neutral')\n",
    "engine.run_pipeline(pipeline, factor_start_date, universe_end_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Reversion 5 Day Sector Neutral Smoothed Factor\n",
    "Taking the output of the previous factor, let's create a smoothed version. Implement `mean_reversion_5day_sector_neutral_smoothed` to generate a mean reversion 5 fay sector neutral smoothed factor. Call the `mean_reversion_5day_sector_neutral` function to get the unsmoothed factor, then use `SimpleMovingAverage` function to smooth it. You'll have to apply rank and zscore again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Integration Test on pipeline:\n",
      "> start_dat = pd.Timestamp('2015-01-05', tz='utc')\n",
      "> end_date = pd.Timestamp('2015-01-07', tz='utc')\n",
      "> universe = AverageDollarVolume(window_length=2).top(4)\n",
      "> factor = mean_reversion_5day_sector_neutral_smoothed(\n",
      "    window_length=3,\n",
      "    universe=universe,\n",
      "    sector=project_helper.Sector())\n",
      "> pipeline.add(factor, 'Mean_Reversion_5Day_Sector_Neutral_Smoothed')\n",
      "> engine.run_pipeline(pipeline, start_dat, end_date)\n",
      "\n",
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "from zipline.pipeline.factors import SimpleMovingAverage\n",
    "\n",
    "def mean_reversion_5day_sector_neutral_smoothed(window_length, universe, sector):\n",
    "    \"\"\"\n",
    "    Generate the mean reversion 5 day sector neutral smoothed factor\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    window_length : int\n",
    "        Returns window length\n",
    "    universe : Zipline Filter\n",
    "        Universe of stocks filter\n",
    "    sector : Zipline Classifier\n",
    "        Sector classifier\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    factor : Zipline Factor\n",
    "        Mean reversion 5 day sector neutral smoothed factor\n",
    "    \"\"\"\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    factor = SimpleMovingAverage(inputs=[mean_reversion_5day_sector_neutral(window_length, universe, sector)],\n",
    "                                 window_length=window_length).rank().zscore()\n",
    "    return factor\n",
    "\n",
    "\n",
    "project_tests.test_mean_reversion_5day_sector_neutral_smoothed(mean_reversion_5day_sector_neutral_smoothed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's see what some of the smoothed data looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Mean_Reversion_5Day_Sector_Neutral_Smoothed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2014-01-03 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <td>1.11580784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <td>1.72840822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <td>1.34188655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <td>0.91160771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <td>0.96265774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <td>0.77304334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <td>0.48862173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <td>-0.45945029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
       "      <td>0.81680051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(9 [ADI])</th>\n",
       "      <td>0.94807202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(10 [ADM])</th>\n",
       "      <td>0.73657903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(11 [ADP])</th>\n",
       "      <td>0.32088591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(12 [ADS])</th>\n",
       "      <td>-1.59713671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(13 [ADSK])</th>\n",
       "      <td>0.08022148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(14 [AEE])</th>\n",
       "      <td>0.11668579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(15 [AEP])</th>\n",
       "      <td>0.21878585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(16 [AES])</th>\n",
       "      <td>-0.75116475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(17 [AET])</th>\n",
       "      <td>-1.09392925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(18 [AFL])</th>\n",
       "      <td>-0.07292862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(19 [AGN])</th>\n",
       "      <td>-0.37922881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(20 [AIG])</th>\n",
       "      <td>1.05017208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(21 [AIV])</th>\n",
       "      <td>-0.14585723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(22 [AIZ])</th>\n",
       "      <td>0.67094327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(23 [AJG])</th>\n",
       "      <td>-0.56155035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(24 [AKAM])</th>\n",
       "      <td>1.67735818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(25 [ALB])</th>\n",
       "      <td>1.35647227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(26 [ALGN])</th>\n",
       "      <td>1.32730082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(27 [ALK])</th>\n",
       "      <td>0.57613607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(28 [ALL])</th>\n",
       "      <td>0.02187859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(29 [ALLE])</th>\n",
       "      <td>1.65547960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2016-01-05 00:00:00+00:00</th>\n",
       "      <th>Equity(460 [VRSN])</th>\n",
       "      <td>1.12262790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(461 [VRTX])</th>\n",
       "      <td>-1.62157363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(462 [VTR])</th>\n",
       "      <td>-1.60731804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(463 [VZ])</th>\n",
       "      <td>-1.68572380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(464 [WAT])</th>\n",
       "      <td>-1.00858316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(465 [WBA])</th>\n",
       "      <td>0.98007198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(466 [WDC])</th>\n",
       "      <td>-1.22241705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(467 [WEC])</th>\n",
       "      <td>-0.78762148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(468 [WFC])</th>\n",
       "      <td>0.72347131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(469 [WHR])</th>\n",
       "      <td>0.37420930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(471 [WM])</th>\n",
       "      <td>-0.53814861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(472 [WMB])</th>\n",
       "      <td>-1.65721261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(473 [WMT])</th>\n",
       "      <td>-1.41486754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(474 [WRK])</th>\n",
       "      <td>-1.46476212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(475 [WU])</th>\n",
       "      <td>1.55742347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(476 [WY])</th>\n",
       "      <td>-0.41697608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(477 [WYN])</th>\n",
       "      <td>0.48112624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(478 [WYNN])</th>\n",
       "      <td>-1.36497297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(479 [XEC])</th>\n",
       "      <td>-0.47399845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(480 [XEL])</th>\n",
       "      <td>-0.95156079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <td>-0.76623809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <td>1.47188991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <td>1.08698892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <td>0.10335304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <td>0.98719977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <td>0.66644894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <td>1.07273333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <td>-0.13186423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <td>0.31718693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "      <td>0.16750321</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244259 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Mean_Reversion_5Day_Sector_Neutral_Smoothed\n",
       "2014-01-03 00:00:00+00:00 Equity(0 [A])                                        1.11580784\n",
       "                          Equity(1 [AAL])                                      1.72840822\n",
       "                          Equity(2 [AAP])                                      1.34188655\n",
       "                          Equity(3 [AAPL])                                     0.91160771\n",
       "                          Equity(4 [ABBV])                                     0.96265774\n",
       "                          Equity(5 [ABC])                                      0.77304334\n",
       "                          Equity(6 [ABT])                                      0.48862173\n",
       "                          Equity(7 [ACN])                                     -0.45945029\n",
       "                          Equity(8 [ADBE])                                     0.81680051\n",
       "                          Equity(9 [ADI])                                      0.94807202\n",
       "                          Equity(10 [ADM])                                     0.73657903\n",
       "                          Equity(11 [ADP])                                     0.32088591\n",
       "                          Equity(12 [ADS])                                    -1.59713671\n",
       "                          Equity(13 [ADSK])                                    0.08022148\n",
       "                          Equity(14 [AEE])                                     0.11668579\n",
       "                          Equity(15 [AEP])                                     0.21878585\n",
       "                          Equity(16 [AES])                                    -0.75116475\n",
       "                          Equity(17 [AET])                                    -1.09392925\n",
       "                          Equity(18 [AFL])                                    -0.07292862\n",
       "                          Equity(19 [AGN])                                    -0.37922881\n",
       "                          Equity(20 [AIG])                                     1.05017208\n",
       "                          Equity(21 [AIV])                                    -0.14585723\n",
       "                          Equity(22 [AIZ])                                     0.67094327\n",
       "                          Equity(23 [AJG])                                    -0.56155035\n",
       "                          Equity(24 [AKAM])                                    1.67735818\n",
       "                          Equity(25 [ALB])                                     1.35647227\n",
       "                          Equity(26 [ALGN])                                    1.32730082\n",
       "                          Equity(27 [ALK])                                     0.57613607\n",
       "                          Equity(28 [ALL])                                     0.02187859\n",
       "                          Equity(29 [ALLE])                                    1.65547960\n",
       "...                                                                                   ...\n",
       "2016-01-05 00:00:00+00:00 Equity(460 [VRSN])                                   1.12262790\n",
       "                          Equity(461 [VRTX])                                  -1.62157363\n",
       "                          Equity(462 [VTR])                                   -1.60731804\n",
       "                          Equity(463 [VZ])                                    -1.68572380\n",
       "                          Equity(464 [WAT])                                   -1.00858316\n",
       "                          Equity(465 [WBA])                                    0.98007198\n",
       "                          Equity(466 [WDC])                                   -1.22241705\n",
       "                          Equity(467 [WEC])                                   -0.78762148\n",
       "                          Equity(468 [WFC])                                    0.72347131\n",
       "                          Equity(469 [WHR])                                    0.37420930\n",
       "                          Equity(471 [WM])                                    -0.53814861\n",
       "                          Equity(472 [WMB])                                   -1.65721261\n",
       "                          Equity(473 [WMT])                                   -1.41486754\n",
       "                          Equity(474 [WRK])                                   -1.46476212\n",
       "                          Equity(475 [WU])                                     1.55742347\n",
       "                          Equity(476 [WY])                                    -0.41697608\n",
       "                          Equity(477 [WYN])                                    0.48112624\n",
       "                          Equity(478 [WYNN])                                  -1.36497297\n",
       "                          Equity(479 [XEC])                                   -0.47399845\n",
       "                          Equity(480 [XEL])                                   -0.95156079\n",
       "                          Equity(481 [XL])                                    -0.76623809\n",
       "                          Equity(482 [XLNX])                                   1.47188991\n",
       "                          Equity(483 [XOM])                                    1.08698892\n",
       "                          Equity(484 [XRAY])                                   0.10335304\n",
       "                          Equity(485 [XRX])                                    0.98719977\n",
       "                          Equity(486 [XYL])                                    0.66644894\n",
       "                          Equity(487 [YUM])                                    1.07273333\n",
       "                          Equity(488 [ZBH])                                   -0.13186423\n",
       "                          Equity(489 [ZION])                                   0.31718693\n",
       "                          Equity(490 [ZTS])                                    0.16750321\n",
       "\n",
       "[244259 rows x 1 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline = Pipeline(screen=universe)\n",
    "pipeline.add(\n",
    "    mean_reversion_5day_sector_neutral_smoothed(5, universe, sector),\n",
    "    'Mean_Reversion_5Day_Sector_Neutral_Smoothed')\n",
    "engine.run_pipeline(pipeline, factor_start_date, universe_end_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overnight Sentiment Factor\n",
    "For this factor, were using the hypothesis from the paper [_Overnight Returns and Firm-Specific Investor Sentiment_](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2554010)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.pipeline.data import USEquityPricing\n",
    "\n",
    "\n",
    "class CTO(Returns):\n",
    "    \"\"\"\n",
    "    Computes the overnight return, per hypothesis from\n",
    "    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2554010\n",
    "    \"\"\"\n",
    "    inputs = [USEquityPricing.open, USEquityPricing.close]\n",
    "    \n",
    "    def compute(self, today, assets, out, opens, closes):\n",
    "        \"\"\"\n",
    "        The opens and closes matrix is 2 rows x N assets, with the most recent at the bottom.\n",
    "        As such, opens[-1] is the most recent open, and closes[0] is the earlier close\n",
    "        \"\"\"\n",
    "        out[:] = (opens[-1] - closes[0]) / closes[0]\n",
    "\n",
    "        \n",
    "class TrailingOvernightReturns(Returns):\n",
    "    \"\"\"\n",
    "    Sum of trailing 1m O/N returns\n",
    "    \"\"\"\n",
    "    window_safe = True\n",
    "    \n",
    "    def compute(self, today, asset_ids, out, cto):\n",
    "        out[:] = np.nansum(cto, axis=0)\n",
    "\n",
    "        \n",
    "def overnight_sentiment(cto_window_length, trail_overnight_returns_window_length, universe):\n",
    "    cto_out = CTO(mask=universe, window_length=cto_window_length)\n",
    "    return TrailingOvernightReturns(inputs=[cto_out], window_length=trail_overnight_returns_window_length) \\\n",
    "        .rank() \\\n",
    "        .zscore()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overnight Sentiment Smoothed Factor\n",
    "Just like the factor you implemented, we'll also smooth this factor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def overnight_sentiment_smoothed(cto_window_length, trail_overnight_returns_window_length, universe):\n",
    "    unsmoothed_factor = overnight_sentiment(cto_window_length, trail_overnight_returns_window_length, universe)\n",
    "    return SimpleMovingAverage(inputs=[unsmoothed_factor], window_length=trail_overnight_returns_window_length) \\\n",
    "        .rank() \\\n",
    "        .zscore()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combine the Factors to a single Pipeline\n",
    "With all the factor implementations done, let's add them to a pipeline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Mean_Reversion_5Day_Sector_Neutral</th>\n",
       "      <th>Mean_Reversion_5Day_Sector_Neutral_Smoothed</th>\n",
       "      <th>Momentum_1YR</th>\n",
       "      <th>Overnight_Sentiment</th>\n",
       "      <th>Overnight_Sentiment_Smoothed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2014-01-03 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <td>0.85326482</td>\n",
       "      <td>1.11580784</td>\n",
       "      <td>1.49939067</td>\n",
       "      <td>0.70659131</td>\n",
       "      <td>1.11242837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <td>1.62630815</td>\n",
       "      <td>1.72840822</td>\n",
       "      <td>1.60279693</td>\n",
       "      <td>-1.70668978</td>\n",
       "      <td>-1.72843105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <td>0.64906469</td>\n",
       "      <td>1.34188655</td>\n",
       "      <td>0.37669421</td>\n",
       "      <td>0.03261191</td>\n",
       "      <td>-0.62687332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <td>1.40752230</td>\n",
       "      <td>0.91160771</td>\n",
       "      <td>-1.48461835</td>\n",
       "      <td>-1.67770142</td>\n",
       "      <td>0.53990823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <td>1.45857233</td>\n",
       "      <td>0.96265774</td>\n",
       "      <td>0.91588396</td>\n",
       "      <td>-1.47478289</td>\n",
       "      <td>-0.06160027</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            Mean_Reversion_5Day_Sector_Neutral  \\\n",
       "2014-01-03 00:00:00+00:00 Equity(0 [A])                             0.85326482   \n",
       "                          Equity(1 [AAL])                           1.62630815   \n",
       "                          Equity(2 [AAP])                           0.64906469   \n",
       "                          Equity(3 [AAPL])                          1.40752230   \n",
       "                          Equity(4 [ABBV])                          1.45857233   \n",
       "\n",
       "                                            Mean_Reversion_5Day_Sector_Neutral_Smoothed  \\\n",
       "2014-01-03 00:00:00+00:00 Equity(0 [A])                                      1.11580784   \n",
       "                          Equity(1 [AAL])                                    1.72840822   \n",
       "                          Equity(2 [AAP])                                    1.34188655   \n",
       "                          Equity(3 [AAPL])                                   0.91160771   \n",
       "                          Equity(4 [ABBV])                                   0.96265774   \n",
       "\n",
       "                                            Momentum_1YR  Overnight_Sentiment  \\\n",
       "2014-01-03 00:00:00+00:00 Equity(0 [A])       1.49939067           0.70659131   \n",
       "                          Equity(1 [AAL])     1.60279693          -1.70668978   \n",
       "                          Equity(2 [AAP])     0.37669421           0.03261191   \n",
       "                          Equity(3 [AAPL])   -1.48461835          -1.67770142   \n",
       "                          Equity(4 [ABBV])    0.91588396          -1.47478289   \n",
       "\n",
       "                                            Overnight_Sentiment_Smoothed  \n",
       "2014-01-03 00:00:00+00:00 Equity(0 [A])                       1.11242837  \n",
       "                          Equity(1 [AAL])                    -1.72843105  \n",
       "                          Equity(2 [AAP])                    -0.62687332  \n",
       "                          Equity(3 [AAPL])                    0.53990823  \n",
       "                          Equity(4 [ABBV])                   -0.06160027  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "universe = AverageDollarVolume(window_length=120).top(500)\n",
    "sector = project_helper.Sector()\n",
    "\n",
    "pipeline = Pipeline(screen=universe)\n",
    "pipeline.add(\n",
    "    momentum_1yr(252, universe, sector),\n",
    "    'Momentum_1YR')\n",
    "pipeline.add(\n",
    "    mean_reversion_5day_sector_neutral(5, universe, sector),\n",
    "    'Mean_Reversion_5Day_Sector_Neutral')\n",
    "pipeline.add(\n",
    "    mean_reversion_5day_sector_neutral_smoothed(5, universe, sector),\n",
    "    'Mean_Reversion_5Day_Sector_Neutral_Smoothed')\n",
    "pipeline.add(\n",
    "    overnight_sentiment(2, 5, universe),\n",
    "    'Overnight_Sentiment')\n",
    "pipeline.add(\n",
    "    overnight_sentiment_smoothed(2, 5, universe),\n",
    "    'Overnight_Sentiment_Smoothed')\n",
    "all_factors = engine.run_pipeline(pipeline, factor_start_date, universe_end_date)\n",
    "\n",
    "all_factors.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluate Alpha Factors\n",
    "*Note:* _We're evaluating the alpha factors using delay of 1_\n",
    "## Get Pricing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import alphalens as al\n",
    "\n",
    "assets = all_factors.index.levels[1].values.tolist()\n",
    "pricing = get_pricing(\n",
    "    data_portal,\n",
    "    trading_calendar,\n",
    "    assets,\n",
    "    factor_start_date,\n",
    "    universe_end_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Format alpha factors and pricing for Alphalens\n",
    "In order to use a lot of the alphalens functions, we need to aligned the indices and convert the time to unix timestamp. In this next cell, we'll do just that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped 1.2% entries from factor data: 1.2% in forward returns computation and 0.0% in binning phase (set max_loss=0 to see potentially suppressed Exceptions).\n",
      "max_loss is 35.0%, not exceeded: OK!\n",
      "Dropped 1.2% entries from factor data: 1.2% in forward returns computation and 0.0% in binning phase (set max_loss=0 to see potentially suppressed Exceptions).\n",
      "max_loss is 35.0%, not exceeded: OK!\n",
      "Dropped 2.3% entries from factor data: 2.3% in forward returns computation and 0.0% in binning phase (set max_loss=0 to see potentially suppressed Exceptions).\n",
      "max_loss is 35.0%, not exceeded: OK!\n",
      "Dropped 0.4% entries from factor data: 0.4% in forward returns computation and 0.0% in binning phase (set max_loss=0 to see potentially suppressed Exceptions).\n",
      "max_loss is 35.0%, not exceeded: OK!\n",
      "Dropped 0.4% entries from factor data: 0.4% in forward returns computation and 0.0% in binning phase (set max_loss=0 to see potentially suppressed Exceptions).\n",
      "max_loss is 35.0%, not exceeded: OK!\n"
     ]
    }
   ],
   "source": [
    "clean_factor_data = {\n",
    "    factor: al.utils.get_clean_factor_and_forward_returns(factor=factor_data, prices=pricing, periods=[1])\n",
    "    for factor, factor_data in all_factors.iteritems()}\n",
    "\n",
    "unixt_factor_data = {\n",
    "    factor: factor_data.set_index(pd.MultiIndex.from_tuples(\n",
    "        [(x.timestamp(), y) for x, y in factor_data.index.values],\n",
    "        names=['date', 'asset']))\n",
    "    for factor, factor_data in clean_factor_data.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantile Analysis\n",
    "### Factor Returns\n",
    "Let's view the factor returns over time. We should be seeing it generally move up and to the right."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f013b105550>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f013b105358>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ls_factor_returns = pd.DataFrame()\n",
    "\n",
    "for factor, factor_data in clean_factor_data.items():\n",
    "    ls_factor_returns[factor] = al.performance.factor_returns(factor_data).iloc[:, 0]\n",
    "\n",
    "(1+ls_factor_returns).cumprod().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basis Points Per Day per Quantile\n",
    "It is not enough to look just at the factor weighted return. A good alpha is also monotonic in quantiles. Let's looks the basis points for the factor returns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f013566c7f0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f0135527a58>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f01355e8b70>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f013550a240>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f013561efd0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f013561e400>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f0135536e10>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f01354069b0>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0135642dd8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qr_factor_returns = pd.DataFrame()\n",
    "\n",
    "for factor, factor_data in unixt_factor_data.items():\n",
    "    qr_factor_returns[factor] = al.performance.mean_return_by_quantile(factor_data)[0].iloc[:, 0]\n",
    "\n",
    "(10000*qr_factor_returns).plot.bar(\n",
    "    subplots=True,\n",
    "    sharey=True,\n",
    "    layout=(4,2),\n",
    "    figsize=(14, 14),\n",
    "    legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you observe?\n",
    "\n",
    "- None of these alphas are **strictly monotonic**; this should lead you to question why this is? Further research and refinement of the alphas needs to be done. What is it about these alphas that leads to the highest ranking stocks in all alphas except MR 5D smoothed to *not* perform the best.\n",
    "- The majority of the return is coming from the **short side** in all these alphas. The negative return in quintile 1 is very large in all alphas. This could also a cause for concern becuase when you short stocks, you need to locate the short; shorts can be expensive or not available at all.\n",
    "- If you look at the magnitude of the return spread (i.e., Q1 minus Q5), we are working with daily returns in the 0.03%, i.e., **3 basis points**, neighborhood *before all transaction costs, shorting costs, etc.*. Assuming 252 days in a year, that's 7.56% return annualized. Transaction costs may cut this in half. As such, it should be clear that these alphas can only survive in an institutional setting and that leverage will likely need to be applied in order to achieve an attractive return.\n",
    "\n",
    "## Turnover Analysis\n",
    "\n",
    "Without doing a full and formal backtest, we can analyze how stable the alphas are over time. Stability in this sense means that from period to period, the alpha ranks do not change much. Since trading is costly, we always prefer, all other things being equal, that the ranks do not change significantly per period. We can measure this with the **factor rank autocorrelation (FRA)**.\n",
    "\n",
    "[alphalens.performance.factor_rank_autocorrelation](https://quantopian.github.io/alphalens/alphalens.html?highlight=factor_rank_autocorrelation#alphalens.performance.factor_rank_autocorrelation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01353d5240>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f01352b4748>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ls_FRA = pd.DataFrame()\n",
    "\n",
    "for factor, factor_data in unixt_factor_data.items():\n",
    "    ls_FRA[factor] = al.performance.factor_rank_autocorrelation(factor_data)\n",
    "\n",
    "ls_FRA.plot(title=\"Factor Rank Autocorrelation\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sharpe Ratio of the Alphas\n",
    "\n",
    "The last analysis we'll do on the factors will be sharpe ratio. Implement `sharpe_ratio` to calculate the sharpe ratio of factor returns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "def sharpe_ratio(factor_returns, annualization_factor):\n",
    "    \"\"\"\n",
    "    Get the sharpe ratio for each factor for the entire period\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    factor_returns : DataFrame\n",
    "        Factor returns for each factor and date\n",
    "    annualization_factor: float\n",
    "        Annualization Factor\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    sharpe_ratio : Pandas Series of floats\n",
    "        Sharpe ratio\n",
    "    \"\"\"\n",
    "    \n",
    "    #TODO: Implement function\n",
    "    \n",
    "    sharpe_ratio = factor_returns.mean() / factor_returns.std() * annualization_factor\n",
    "    \n",
    "    return sharpe_ratio\n",
    "\n",
    "\n",
    "project_tests.test_sharpe_ratio(sharpe_ratio)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "Let's see what the sharpe ratio for the factors are. Generally, a Sharpe Ratio of near 1.0 or higher is an acceptable single alpha for this universe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mean_Reversion_5Day_Sector_Neutral            1.37000000\n",
       "Mean_Reversion_5Day_Sector_Neutral_Smoothed   1.27000000\n",
       "Momentum_1YR                                  1.13000000\n",
       "Overnight_Sentiment                           0.12000000\n",
       "Overnight_Sentiment_Smoothed                  0.45000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_annualization_factor = np.sqrt(252)\n",
    "sharpe_ratio(ls_factor_returns, daily_annualization_factor).round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question: What do you think would happen if we smooth the momentum factor? Would the performance increase, decrease, or no major change? Why?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_#TODO: Put Answer In this Cell_\n",
    "\n",
    "**Answer:** I think the performance would increase a bit if we smooth the momentum factor. I expect the volatility to decrease and the standard deviation of the returns to decrease which would lead to higher sharpe ratio."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Combined Alpha Vector\n",
    "\n",
    "To use these alphas in a portfolio, we need to combine them somehow so we get a single score per stock. This is a area where machine learning can be very helpful. In this module, however, we will take the simplest approach of combination: simply averaging the scores from each alpha."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected Factors: Mean_Reversion_5Day_Sector_Neutral_Smoothed, Momentum_1YR, Overnight_Sentiment_Smoothed\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>alpha_vector</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asset</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <td>-0.58642457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <td>-0.45333845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <td>-0.69993898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <td>-0.06790952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <td>-1.21617871</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  alpha_vector\n",
       "asset                         \n",
       "Equity(0 [A])      -0.58642457\n",
       "Equity(1 [AAL])    -0.45333845\n",
       "Equity(2 [AAP])    -0.69993898\n",
       "Equity(3 [AAPL])   -0.06790952\n",
       "Equity(4 [ABBV])   -1.21617871"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_factors = all_factors.columns[[1, 2, 4]]\n",
    "print('Selected Factors: {}'.format(', '.join(selected_factors)))\n",
    "\n",
    "all_factors['alpha_vector'] = all_factors[selected_factors].mean(axis=1)\n",
    "alphas = all_factors[['alpha_vector']]\n",
    "alpha_vector = alphas.loc[all_factors.index.get_level_values(0)[-1]]\n",
    "alpha_vector.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Optimal Portfolio Constrained by Risk Model\n",
    "You have an alpha model and a risk model. Let's find a portfolio that trades as close as possible to the alpha model but limiting risk as measured by the risk model. You'll be building thie optimizer for this portfolio. To help you out. we have provided you with an abstract class called `AbstractOptimalHoldings`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from abc import ABC, abstractmethod\n",
    "\n",
    "\n",
    "class AbstractOptimalHoldings(ABC):    \n",
    "    @abstractmethod\n",
    "    def _get_obj(self, weights, alpha_vector):\n",
    "        \"\"\"\n",
    "        Get the objective function\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        weights : CVXPY Variable\n",
    "            Portfolio weights\n",
    "        alpha_vector : DataFrame\n",
    "            Alpha vector\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        objective : CVXPY Objective\n",
    "            Objective function\n",
    "        \"\"\"\n",
    "        \n",
    "        raise NotImplementedError()\n",
    "    \n",
    "    @abstractmethod\n",
    "    def _get_constraints(self, weights, factor_betas, risk):\n",
    "        \"\"\"\n",
    "        Get the constraints\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        weights : CVXPY Variable\n",
    "            Portfolio weights\n",
    "        factor_betas : 2 dimensional Ndarray\n",
    "            Factor betas\n",
    "        risk: CVXPY Atom\n",
    "            Predicted variance of the portfolio returns\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        constraints : List of CVXPY Constraint\n",
    "            Constraints\n",
    "        \"\"\"\n",
    "        \n",
    "        raise NotImplementedError()\n",
    "        \n",
    "    def _get_risk(self, weights, factor_betas, alpha_vector_index, factor_cov_matrix, idiosyncratic_var_vector):\n",
    "        f = factor_betas.loc[alpha_vector_index].values.T * weights\n",
    "        X = factor_cov_matrix\n",
    "        S = np.diag(idiosyncratic_var_vector.loc[alpha_vector_index].values.flatten())\n",
    "\n",
    "        return cvx.quad_form(f, X) + cvx.quad_form(weights, S)\n",
    "    \n",
    "    def find(self, alpha_vector, factor_betas, factor_cov_matrix, idiosyncratic_var_vector):\n",
    "        weights = cvx.Variable(len(alpha_vector))\n",
    "        risk = self._get_risk(weights, factor_betas, alpha_vector.index, factor_cov_matrix, idiosyncratic_var_vector)\n",
    "        \n",
    "        obj = self._get_obj(weights, alpha_vector)\n",
    "        constraints = self._get_constraints(weights, factor_betas.loc[alpha_vector.index].values, risk)\n",
    "        \n",
    "        prob = cvx.Problem(obj, constraints)\n",
    "        prob.solve(max_iters=500)\n",
    "\n",
    "        optimal_weights = np.asarray(weights.value).flatten()\n",
    "        \n",
    "        return pd.DataFrame(data=optimal_weights, index=alpha_vector.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objective and Constraints\n",
    "Using this class as a base class, you'll implement the `OptimalHoldings` class. There's two functions that need to be implemented in this class, the `_get_obj` and `_get_constraints` functions.\n",
    "\n",
    "The `_get_obj` function should return an CVXPY objective function that maximizes $ \\alpha^T * x \\\\ $, where $ x $ is the portfolio weights and $ \\alpha $ is the alpha vector.\n",
    "\n",
    "The `_get_constraints` function should return a list of the following constraints:\n",
    "- $ r \\leq risk_{\\text{cap}}^2 \\\\ $\n",
    "- $ B^T * x \\preceq factor_{\\text{max}} \\\\ $\n",
    "- $ B^T * x \\succeq factor_{\\text{min}} \\\\ $\n",
    "- $ x^T\\mathbb{1} = 0 \\\\ $\n",
    "- $ \\|x\\|_1 \\leq 1 \\\\ $\n",
    "- $ x \\succeq weights_{\\text{min}} \\\\ $\n",
    "- $ x \\preceq weights_{\\text{max}} $\n",
    "\n",
    "Where $ x $ is the portfolio weights, $ B $ is the factor betas, and $ r $ is the portfolio risk\n",
    "\n",
    "The first constraint is that the predicted risk be less than some maximum limit. The second and third constraints are on the maximum and minimum portfolio factor exposures. The fourth constraint is the \"market neutral constraint: the sum of the weights must be zero. The fifth constraint is the leverage constraint: the sum of the absolute value of the weights must be less than or equal to 1.0. The last are some minimum and maximum limits on individual holdings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Integration Test on Problem.solve:\n",
      "> constaints = [sum(weights) == 0.0, sum(cvx.abs(weights)) <= 1.0]\n",
      "> obj = optimal_holdings._get_obj(weights, alpha_vector)\n",
      "> prob = cvx.Problem(obj, constaints)\n",
      "> prob.solve(max_iters=500)\n",
      "> solution = np.asarray(weights.value).flatten()\n",
      "\n",
      "Tests Passed\n",
      "\n",
      "Running Integration Test on Problem.solve:\n",
      "> x = np.diag(np.arange(3))\n",
      "> s = np.diag(np.arange(4))\n",
      "> factor_betas = np.arange(4 * 3).reshape([4, 3])\n",
      "> risk = cvx.quad_form(weights * factor_betas, x) + cvx.quad_form(weights, s)\n",
      "> constaints = optimal_holdings._get_constraints(weights, factor_betas, risk)\n",
      "> obj = cvx.Maximize([0, 1, 5, -1] * weights)\n",
      "> prob = cvx.Problem(obj, constaints)\n",
      "> prob.solve(max_iters=500)\n",
      "> solution = np.asarray(weights.value).flatten()\n",
      "\n",
      "Tests Passed\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n"
     ]
    }
   ],
   "source": [
    "class OptimalHoldings(AbstractOptimalHoldings):\n",
    "    def _get_obj(self, weights, alpha_vector):\n",
    "        \"\"\"\n",
    "        Get the objective function\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        weights : CVXPY Variable\n",
    "            Portfolio weights\n",
    "        alpha_vector : DataFrame\n",
    "            Alpha vector\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        objective : CVXPY Objective\n",
    "            Objective function\n",
    "        \"\"\"\n",
    "        assert(len(alpha_vector.columns) == 1)\n",
    "\n",
    "        #TODO: Implement function\n",
    "        objective = cvx.Minimize(alpha_vector.T.values[0]*weights*-1)\n",
    "        \n",
    "        return objective\n",
    "    \n",
    "    def _get_constraints(self, weights, factor_betas, risk):\n",
    "        \"\"\"\n",
    "        Get the constraints\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        weights : CVXPY Variable\n",
    "            Portfolio weights\n",
    "        factor_betas : 2 dimensional Ndarray\n",
    "            Factor betas\n",
    "        risk: CVXPY Atom\n",
    "            Predicted variance of the portfolio returns\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        constraints : List of CVXPY Constraint\n",
    "            Constraints\n",
    "        \"\"\"\n",
    "        assert(len(factor_betas.shape) == 2)\n",
    "        \n",
    "        #TODO: Implement function\n",
    "        constraints = [\n",
    "            risk<=self.risk_cap**2, \n",
    "            factor_betas.T*weights<=self.factor_max,\n",
    "            factor_betas.T*weights>=self.factor_min,\n",
    "            sum(weights)==0,\n",
    "            sum(cvx.abs(weights))<=1,\n",
    "            weights>=self.weights_min,\n",
    "            weights<=self.weights_max\n",
    "        ]\n",
    "        \n",
    "        return constraints\n",
    "\n",
    "    def __init__(self, risk_cap=0.05, factor_max=10.0, factor_min=-10.0, weights_max=0.55, weights_min=-0.55):\n",
    "        self.risk_cap=risk_cap\n",
    "        self.factor_max=factor_max\n",
    "        self.factor_min=factor_min\n",
    "        self.weights_max=weights_max\n",
    "        self.weights_min=weights_min\n",
    "\n",
    "\n",
    "project_tests.test_optimal_holdings_get_obj(OptimalHoldings)\n",
    "project_tests.test_optimal_holdings_get_constraints(OptimalHoldings)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data\n",
    "With the `OptimalHoldings` class implemented, let's see the weights it generates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:106: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f013438dcf8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimal_weights = OptimalHoldings().find(alpha_vector, risk_model['factor_betas'], risk_model['factor_cov_matrix'], risk_model['idiosyncratic_var_vector'])\n",
    "\n",
    "optimal_weights.plot.bar(legend=None, title='Portfolio % Holdings by Stock')\n",
    "x_axis = plt.axes().get_xaxis()\n",
    "x_axis.set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yikes. It put most of the weight in a few stocks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0134059898>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0133bafb00>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "project_helper.get_factor_exposures(risk_model['factor_betas'], optimal_weights).plot.bar(\n",
    "    title='Portfolio Net Factor Exposures',\n",
    "    legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimize with a Regularization Parameter\n",
    "In order to enforce diversification, we'll use regularization in the objective function. We'll create a new class called `OptimalHoldingsRegualization` which gets its constraints from the `OptimalHoldings` class. In this new class, implement the `_get_obj` function to return a CVXPY objective function that maximize $ \\alpha^T * x + \\lambda\\|x\\|_2\\\\ $, where $ x $ is the portfolio weights, $ \\alpha $ is the alpha vector, and $ \\lambda $ is the regularization parameter.\n",
    "\n",
    "**Note:** * $ \\lambda $ is located in `self.lambda_reg`. *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Integration Test on Problem.solve:\n",
      "> constaints = [sum(weights) == 0.0, sum(cvx.abs(weights)) <= 1.0]\n",
      "> obj = optimal_holdings_regualization._get_obj(weights, alpha_vector)\n",
      "> prob = cvx.Problem(obj, constaints)\n",
      "> prob.solve(max_iters=500)\n",
      "> solution = np.asarray(weights.value).flatten()\n",
      "\n",
      "Tests Passed\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n"
     ]
    }
   ],
   "source": [
    "class OptimalHoldingsRegualization(OptimalHoldings):\n",
    "    def _get_obj(self, weights, alpha_vector):\n",
    "        \"\"\"\n",
    "        Get the objective function\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        weights : CVXPY Variable\n",
    "            Portfolio weights\n",
    "        alpha_vector : DataFrame\n",
    "            Alpha vector\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        objective : CVXPY Objective\n",
    "            Objective function\n",
    "        \"\"\"\n",
    "        assert(len(alpha_vector.columns) == 1)\n",
    "        \n",
    "        #TODO: Implement function\n",
    "        objective = cvx.Minimize(alpha_vector.T.values[0]*weights + self.lambda_reg*cvx.pnorm(weights,2))\n",
    "        \n",
    "        return objective\n",
    "\n",
    "    def __init__(self, lambda_reg=0.5, risk_cap=0.05, factor_max=10.0, factor_min=-10.0, weights_max=0.55, weights_min=-0.55):\n",
    "        self.lambda_reg = lambda_reg\n",
    "        self.risk_cap=risk_cap\n",
    "        self.factor_max=factor_max\n",
    "        self.factor_min=factor_min\n",
    "        self.weights_max=weights_max\n",
    "        self.weights_min=weights_min\n",
    "        \n",
    "\n",
    "project_tests.test_optimal_holdings_regualization_get_obj(OptimalHoldingsRegualization)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:106: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0133af5f60>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimal_weights_1 = OptimalHoldingsRegualization(lambda_reg=5.0).find(alpha_vector, risk_model['factor_betas'], risk_model['factor_cov_matrix'], risk_model['idiosyncratic_var_vector'])\n",
    "\n",
    "optimal_weights_1.plot.bar(legend=None, title='Portfolio % Holdings by Stock')\n",
    "x_axis = plt.axes().get_xaxis()\n",
    "x_axis.set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nice. Well diversified."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0134006f28>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0133665a90>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "project_helper.get_factor_exposures(risk_model['factor_betas'], optimal_weights_1).plot.bar(\n",
    "    title='Portfolio Net Factor Exposures',\n",
    "    legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimize with a Strict Factor Constraints and Target Weighting\n",
    "Another common formulation is to take a predefined target weighting, $x^*$ (e.g., a quantile portfolio), and solve to get as close to that portfolio while respecting portfolio-level constraints. For this next class, `OptimalHoldingsStrictFactor`, you'll implement the `_get_obj` function to minimize on on $ \\|x - x^*\\|_2 $, where $ x $ is the portfolio weights  $ x^* $ is the target weighting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Integration Test on Problem.solve:\n",
      "> constaints = [sum(weights) == 0.0, sum(cvx.abs(weights)) <= 1.0]\n",
      "> obj = optimal_holdings_strict_factor._get_obj(weights, alpha_vector)\n",
      "> prob = cvx.Problem(obj, constaints)\n",
      "> prob.solve(max_iters=500)\n",
      "> solution = np.asarray(weights.value).flatten()\n",
      "\n",
      "Tests Passed\n"
     ]
    }
   ],
   "source": [
    "class OptimalHoldingsStrictFactor(OptimalHoldings):\n",
    "    def _get_obj(self, weights, alpha_vector):\n",
    "        \"\"\"\n",
    "        Get the objective function\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        weights : CVXPY Variable\n",
    "            Portfolio weights\n",
    "        alpha_vector : DataFrame\n",
    "            Alpha vector\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        objective : CVXPY Objective\n",
    "            Objective function\n",
    "        \"\"\"\n",
    "        assert(len(alpha_vector.columns) == 1)\n",
    "        \n",
    "        #TODO: Implement function\n",
    "        a = alpha_vector.values[:,0]\n",
    "        target_weights = (a-a.mean())/sum(abs(a))\n",
    "        objective = cvx.Minimize(cvx.pnorm(weights-target_weights,2))\n",
    "        \n",
    "        return objective\n",
    "\n",
    "\n",
    "project_tests.test_optimal_holdings_strict_factor_get_obj(OptimalHoldingsStrictFactor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/cvxpy/expressions/expression.py:516: UserWarning: \n",
      "This use of ``*`` has resulted in matrix multiplication.\n",
      "Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1.\n",
      "    Use ``*`` for matrix-scalar and vector-scalar multiplication.\n",
      "    Use ``@`` for matrix-matrix and matrix-vector multiplication.\n",
      "    Use ``multiply`` for elementwise multiplication.\n",
      "\n",
      "  warnings.warn(__STAR_MATMUL_WARNING__, UserWarning)\n",
      "/opt/conda/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:106: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f01337800f0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimal_weights_2 = OptimalHoldingsStrictFactor(\n",
    "    weights_max=0.02,\n",
    "    weights_min=-0.02,\n",
    "    risk_cap=0.0015,\n",
    "    factor_max=0.015,\n",
    "    factor_min=-0.015).find(alpha_vector, risk_model['factor_betas'], risk_model['factor_cov_matrix'], risk_model['idiosyncratic_var_vector'])\n",
    "\n",
    "optimal_weights_2.plot.bar(legend=None, title='Portfolio % Holdings by Stock')\n",
    "x_axis = plt.axes().get_xaxis()\n",
    "x_axis.set_visible(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0133683a58>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0133c32630>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "project_helper.get_factor_exposures(risk_model['factor_betas'], optimal_weights_2).plot.bar(\n",
    "    title='Portfolio Net Factor Exposures',\n",
    "    legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Submission\n",
    "Now that you're done with the project, it's time to submit it. Click the submit button in the bottom right. One of our reviewers will give you feedback on your project with a pass or not passed grade. You can continue to the next section while you wait for feedback."
   ]
  }
 ],
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