Tutorial.ipynb

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    "# <font color='red'>STOCK MARKET IS VERY RISKY UNTIL YOU DO IT PROPERLY. PLEASE DO NOT TAKE TRADES JUST BECAUSE THIS TOOL GIVES YOU THE NAME. APPLY YOUR OWN LEARNINGS, CREATE YOUR OWN STRATEGY, ASSESS RISK & TRADE THE PLAN.</font>"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "# Imports, Defaults and Initializations\n",
    "Clicking on the below cell is mandatory. Click on the cell below and press `Shift + Enter`. To run any cell, use the same keyboard shortcut."
   ]
  },
  {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking Fresh Data.....\n"
     ]
    }
   ],
   "source": [
    "# import backtrader\n",
    "from helpers.datahandler import *\n",
    "from helpers.investing import *\n",
    "from helpers.journal_handler import *\n",
    "from helpers.intraday import *\n",
    "from helpers.nse_data import *\n",
    "from helpers.backtest import *\n",
    "from helpers.FnO import analyse_option_chain, get_next_expiry_date\n",
    "from helpers.online_brokers import KiteZerodha # Yes! Finally we can have live Data for Free!!!\n",
    "\n",
    "\n",
    "pd.set_option('display.max_rows', 100)\n",
    "pd.set_option('display.max_columns', 25)\n",
    "\n",
    "In = Investing(check_fresh = True) # Investing or Swing trading analysis\n",
    "Intra = IntraDay() # Intraday strategies and analysis\n",
    "NSE = NSEData() # Get NSE Live data\n",
    "MS = MarketSentiment() # Get Live Market Sentiment TICK, TRIN and 52W high/ low stocks\n",
    "BT = Backtest()\n",
    "ISS  = IntradayStockSelection() # Few of the Intraday Stock Selection methods. Not methods, but just a few things like stats of Move, Range etc\n",
    "\n",
    "# In.update_new_listings() # Good to run once in a while say after every 1 month\n",
    "# In.update_fresh_nifty_indices()\n",
    "# In.update_FnO() # Future and Options List"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80a84b04",
   "metadata": {},
   "source": [
    "# [Journal](https://drive.google.com/file/d/1JipUU6Im1YVKSdufw4VHitwS010nFigL/view)\n",
    "Make a journal in Google Drive for each trade you take to analyse. **It is a not so simple process and need to connect with Google API so if you're not comfortable with it, just skip it**"
   ]
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     "text": [
      "--------------------------------------------------------------------------- \n",
      "\n",
      "--------------------------------------------------------------------------- \n",
      "\n"
     ]
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       "-1693.15"
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   "source": [
    "private_key = join(expanduser('~'),'Documents','client_secret.json') # Personal for each user. Mine is stored in /home/Documents\n",
    "JH = JournalHandler(private_key)\n",
    "\n",
    "journal = JH.get_journal('Finance Journal') # My Google Sheet jornam has name \"Finance Journal\"\n",
    "\n",
    "JH.total_pl(journal) # total Profit and Loss up until now"
   ]
  },
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   "source": [
    "# [Swing  Trading Strategies](https://www.investopedia.com/terms/s/swingtrading.asp)\n",
    "## Tweak parameters by reading the Docstring\n",
    "## Basic Details\n",
    "Basic Details about stocks such as Momentum, Ichimoku, 1-2-3 candles pattern etc"
   ]
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      "/home/admin1/anaconda3/envs/finance/lib/python3.7/site-packages/ta/trend.py:768: RuntimeWarning:\n",
      "\n",
      "invalid value encountered in double_scalars\n",
      "\n",
      "/home/admin1/anaconda3/envs/finance/lib/python3.7/site-packages/ta/trend.py:772: RuntimeWarning:\n",
      "\n",
      "invalid value encountered in double_scalars\n",
      "\n"
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Name</th>\n",
       "      <th>LTP</th>\n",
       "      <th>Index</th>\n",
       "      <th>CCI Signal</th>\n",
       "      <th>RSI Signal</th>\n",
       "      <th>MACD Signal</th>\n",
       "      <th>Over 20-SMA</th>\n",
       "      <th>Over 50-SMA</th>\n",
       "      <th>Over 100-SMA</th>\n",
       "      <th>Over 200-SMA</th>\n",
       "      <th>Momentum ADX</th>\n",
       "      <th>Ichi Count</th>\n",
       "      <th>1 Candle</th>\n",
       "      <th>2 Candles</th>\n",
       "      <th>3 Candles</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>TATAPOWER</td>\n",
       "      <td>244.40</td>\n",
       "      <td>Nifty 200</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>Sell</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>13.685009</td>\n",
       "      <td>2</td>\n",
       "      <td>Inverted Hammer</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>BSOFT</td>\n",
       "      <td>557.00</td>\n",
       "      <td>Nifty 500</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>Sell</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>31.572243</td>\n",
       "      <td>2</td>\n",
       "      <td>Unknown Red</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>CIPLA</td>\n",
       "      <td>921.50</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.073990</td>\n",
       "      <td>1</td>\n",
       "      <td>Red Doji</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>1870.25</td>\n",
       "      <td>Nifty 100</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>14.290830</td>\n",
       "      <td>2</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>V Pattern</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "        Date       Name      LTP      Index CCI Signal RSI Signal MACD Signal  \\\n",
       "0 2022-01-14  TATAPOWER   244.40  Nifty 200  No Signal       Sell   No Signal   \n",
       "1 2022-01-14      BSOFT   557.00  Nifty 500  No Signal  No Signal        Sell   \n",
       "2 2022-01-14      CIPLA   921.50   Nifty 50  No Signal  No Signal   No Signal   \n",
       "3 2022-01-14   ADANIENT  1870.25  Nifty 100  No Signal  No Signal   No Signal   \n",
       "\n",
       "   Over 20-SMA  Over 50-SMA  Over 100-SMA  Over 200-SMA  Momentum ADX  \\\n",
       "0         True         True          True          True     13.685009   \n",
       "1         True         True          True          True     31.572243   \n",
       "2         True         True         False         False     10.073990   \n",
       "3         True         True          True          True     14.290830   \n",
       "\n",
       "   Ichi Count         1 Candle 2 Candles  3 Candles  \n",
       "0           2  Inverted Hammer   Unknown    Unknown  \n",
       "1           2      Unknown Red   Unknown    Unknown  \n",
       "2           1         Red Doji   Unknown    Unknown  \n",
       "3           2    Unknown Green   Unknown  V Pattern  "
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   "source": [
    "budget = 40000\n",
    "\n",
    "\n",
    "df = In.get_recent_info(nifty = 500, custom_list= ['TATAPOWER','BSOFT', 'CIPLA', 'ADANIENT'], **{'mvs':[20,50,100,200]})\n",
    "df.head(4) # show first 4 values"
   ]
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   "source": [
    "## Breakout\n",
    "Stocks that might breakout. Includes only those stocks which are above 50 days SMA, have atleast `n` number of touches within the `p%` of the recent candle. Just look at these stocks manually. Change the parameters to control the number of stocks to scan."
   ]
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   "cell_type": "code",
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       "{'HAL': 6, 'CYIENT': 6, 'PERSISTENT': 5}"
      ]
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   "source": [
    "In.tight_consolidation_stocks(stocks = 'nifty_500', diff = 0.007, min_count = 5, lookback_period = 10) # There should be atleast 5 candles touching the +- 0.75% of the line within 7 days"
   ]
  },
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   "source": [
    "## 44-SMA \n",
    "If you find a `Green` candle taking support on 44 days `Simple Moving Average` line and stock is in uptrend, you can take the trade and set Risk to Reward ratio as 1:2"
   ]
  },
  {
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   "execution_count": 4,
   "id": "b883fbf7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/admin1/anaconda3/envs/finance/lib/python3.7/site-packages/ta/trend.py:768: RuntimeWarning:\n",
      "\n",
      "invalid value encountered in double_scalars\n",
      "\n",
      "/home/admin1/anaconda3/envs/finance/lib/python3.7/site-packages/ta/trend.py:772: RuntimeWarning:\n",
      "\n",
      "invalid value encountered in double_scalars\n",
      "\n",
      "/home/admin1/Desktop/ML Study/Finance/helpers/investing.py:254: UserWarning:\n",
      "\n",
      "Risk should be atleast 843.51 for you to afford SHREECEM\n",
      "\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>OPEN</th>\n",
       "      <th>HIGH</th>\n",
       "      <th>LOW</th>\n",
       "      <th>CLOSE</th>\n",
       "      <th>52W H</th>\n",
       "      <th>52W L</th>\n",
       "      <th>SYMBOL</th>\n",
       "      <th>Diff</th>\n",
       "      <th>CCI Value</th>\n",
       "      <th>RSI Value</th>\n",
       "      <th>MACD Signal</th>\n",
       "      <th>ADX</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Ichi</th>\n",
       "      <th>ATR</th>\n",
       "      <th>Triple Candle</th>\n",
       "      <th>Double Candle</th>\n",
       "      <th>Recent Candle</th>\n",
       "      <th>Index</th>\n",
       "      <th>Expected Change %</th>\n",
       "      <th>Max Config Risk</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>121.50</td>\n",
       "      <td>124.40</td>\n",
       "      <td>121.35</td>\n",
       "      <td>123.30</td>\n",
       "      <td>141.50</td>\n",
       "      <td>86.75</td>\n",
       "      <td>IOC</td>\n",
       "      <td>2.50</td>\n",
       "      <td>156.07</td>\n",
       "      <td>65.401471</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>25.582498</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>2.632577</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>9.30</td>\n",
       "      <td>399.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>730.20</td>\n",
       "      <td>777.00</td>\n",
       "      <td>727.00</td>\n",
       "      <td>762.50</td>\n",
       "      <td>889.00</td>\n",
       "      <td>554.25</td>\n",
       "      <td>TATACONSUM</td>\n",
       "      <td>2.71</td>\n",
       "      <td>176.90</td>\n",
       "      <td>57.600282</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>26.459180</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>18.745219</td>\n",
       "      <td>V Pattern</td>\n",
       "      <td>Bullish Engulfing</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>14.12</td>\n",
       "      <td>384.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>395.00</td>\n",
       "      <td>399.95</td>\n",
       "      <td>392.50</td>\n",
       "      <td>398.45</td>\n",
       "      <td>503.00</td>\n",
       "      <td>357.40</td>\n",
       "      <td>BPCL</td>\n",
       "      <td>2.97</td>\n",
       "      <td>95.75</td>\n",
       "      <td>57.207319</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>16.331214</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>8.642031</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>6.74</td>\n",
       "      <td>391.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1909.00</td>\n",
       "      <td>1945.00</td>\n",
       "      <td>1898.00</td>\n",
       "      <td>1938.20</td>\n",
       "      <td>2253.00</td>\n",
       "      <td>1626.00</td>\n",
       "      <td>KOTAKBANK</td>\n",
       "      <td>3.25</td>\n",
       "      <td>85.08</td>\n",
       "      <td>57.769626</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>24.591789</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>47.238806</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>5.22</td>\n",
       "      <td>355.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>134.40</td>\n",
       "      <td>136.15</td>\n",
       "      <td>133.30</td>\n",
       "      <td>135.35</td>\n",
       "      <td>152.10</td>\n",
       "      <td>88.15</td>\n",
       "      <td>NTPC</td>\n",
       "      <td>4.49</td>\n",
       "      <td>111.33</td>\n",
       "      <td>64.151473</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>24.508930</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>3.167456</td>\n",
       "      <td>Reverse V Pattern</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>4.58</td>\n",
       "      <td>399.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1530.00</td>\n",
       "      <td>1548.70</td>\n",
       "      <td>1519.00</td>\n",
       "      <td>1545.15</td>\n",
       "      <td>1725.00</td>\n",
       "      <td>1342.00</td>\n",
       "      <td>HDFCBANK</td>\n",
       "      <td>9.50</td>\n",
       "      <td>58.74</td>\n",
       "      <td>56.424449</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>27.511609</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>28.712721</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>4.23</td>\n",
       "      <td>393.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>164.75</td>\n",
       "      <td>166.15</td>\n",
       "      <td>163.25</td>\n",
       "      <td>164.75</td>\n",
       "      <td>203.80</td>\n",
       "      <td>123.40</td>\n",
       "      <td>COALINDIA</td>\n",
       "      <td>10.06</td>\n",
       "      <td>146.05</td>\n",
       "      <td>66.073250</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>25.071845</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>3.948298</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Doji</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>8.99</td>\n",
       "      <td>396.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>679.90</td>\n",
       "      <td>689.55</td>\n",
       "      <td>677.25</td>\n",
       "      <td>682.70</td>\n",
       "      <td>776.50</td>\n",
       "      <td>363.20</td>\n",
       "      <td>JSWSTEEL</td>\n",
       "      <td>15.76</td>\n",
       "      <td>127.12</td>\n",
       "      <td>55.997846</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>14.641731</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>0</td>\n",
       "      <td>18.548907</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Inverted Hammer</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>9.75</td>\n",
       "      <td>370.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>509.00</td>\n",
       "      <td>515.40</td>\n",
       "      <td>505.65</td>\n",
       "      <td>509.90</td>\n",
       "      <td>536.70</td>\n",
       "      <td>199.65</td>\n",
       "      <td>TATAMOTORS</td>\n",
       "      <td>18.33</td>\n",
       "      <td>122.84</td>\n",
       "      <td>61.974601</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>10.686055</td>\n",
       "      <td>Rising High</td>\n",
       "      <td>0</td>\n",
       "      <td>13.811799</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Inverted Hammer</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>8.38</td>\n",
       "      <td>388.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>769.00</td>\n",
       "      <td>795.00</td>\n",
       "      <td>763.65</td>\n",
       "      <td>780.10</td>\n",
       "      <td>901.00</td>\n",
       "      <td>500.10</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>23.97</td>\n",
       "      <td>203.62</td>\n",
       "      <td>64.408868</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>15.363095</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>0</td>\n",
       "      <td>21.053643</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>9.19</td>\n",
       "      <td>365.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1714.50</td>\n",
       "      <td>1746.80</td>\n",
       "      <td>1696.50</td>\n",
       "      <td>1737.75</td>\n",
       "      <td>1838.00</td>\n",
       "      <td>915.00</td>\n",
       "      <td>TECHM</td>\n",
       "      <td>41.86</td>\n",
       "      <td>-5.16</td>\n",
       "      <td>56.533617</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>18.147039</td>\n",
       "      <td>Rising High</td>\n",
       "      <td>0</td>\n",
       "      <td>44.400312</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Bullish Engulfing</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>6.15</td>\n",
       "      <td>376.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>506.00</td>\n",
       "      <td>509.50</td>\n",
       "      <td>503.00</td>\n",
       "      <td>506.35</td>\n",
       "      <td>551.85</td>\n",
       "      <td>224.55</td>\n",
       "      <td>HINDALCO</td>\n",
       "      <td>45.67</td>\n",
       "      <td>134.01</td>\n",
       "      <td>68.088941</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>21.098261</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>12.124316</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Inverted Hammer</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>4.45</td>\n",
       "      <td>397.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1213.00</td>\n",
       "      <td>1226.30</td>\n",
       "      <td>1206.10</td>\n",
       "      <td>1213.60</td>\n",
       "      <td>1534.50</td>\n",
       "      <td>596.00</td>\n",
       "      <td>TATASTEEL</td>\n",
       "      <td>52.05</td>\n",
       "      <td>200.25</td>\n",
       "      <td>60.147869</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>20.341697</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>34.090779</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Inverted Hammer</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>12.47</td>\n",
       "      <td>382.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>7634.00</td>\n",
       "      <td>7700.00</td>\n",
       "      <td>7566.90</td>\n",
       "      <td>7660.55</td>\n",
       "      <td>8269.00</td>\n",
       "      <td>5260.00</td>\n",
       "      <td>ULTRACEMCO</td>\n",
       "      <td>60.24</td>\n",
       "      <td>73.07</td>\n",
       "      <td>57.273652</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>12.441589</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>157.593387</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Green Doji</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>4.19</td>\n",
       "      <td>322.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1259.00</td>\n",
       "      <td>1272.25</td>\n",
       "      <td>1254.50</td>\n",
       "      <td>1263.60</td>\n",
       "      <td>1273.90</td>\n",
       "      <td>838.00</td>\n",
       "      <td>SBILIFE</td>\n",
       "      <td>76.71</td>\n",
       "      <td>125.91</td>\n",
       "      <td>71.857625</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>22.159275</td>\n",
       "      <td>Rising High</td>\n",
       "      <td>0</td>\n",
       "      <td>22.638524</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>4.52</td>\n",
       "      <td>373.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1320.00</td>\n",
       "      <td>1342.95</td>\n",
       "      <td>1293.00</td>\n",
       "      <td>1337.20</td>\n",
       "      <td>1377.75</td>\n",
       "      <td>891.00</td>\n",
       "      <td>HCLTECH</td>\n",
       "      <td>80.43</td>\n",
       "      <td>68.90</td>\n",
       "      <td>66.654850</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>34.585401</td>\n",
       "      <td>Rising High</td>\n",
       "      <td>0</td>\n",
       "      <td>31.892530</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>7.82</td>\n",
       "      <td>368.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>1882.00</td>\n",
       "      <td>1933.00</td>\n",
       "      <td>1881.00</td>\n",
       "      <td>1929.35</td>\n",
       "      <td>1933.00</td>\n",
       "      <td>1231.00</td>\n",
       "      <td>INFY</td>\n",
       "      <td>81.11</td>\n",
       "      <td>129.30</td>\n",
       "      <td>67.785232</td>\n",
       "      <td>Buy</td>\n",
       "      <td>22.538556</td>\n",
       "      <td>Rising High</td>\n",
       "      <td>0</td>\n",
       "      <td>37.595616</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Bullish Engulfing</td>\n",
       "      <td>Bullish</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>7.28</td>\n",
       "      <td>352.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>26830.00</td>\n",
       "      <td>27150.00</td>\n",
       "      <td>26577.25</td>\n",
       "      <td>27078.45</td>\n",
       "      <td>32048.00</td>\n",
       "      <td>22531.00</td>\n",
       "      <td>SHREECEM</td>\n",
       "      <td>82.78</td>\n",
       "      <td>59.78</td>\n",
       "      <td>54.205867</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>26.295460</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>614.935596</td>\n",
       "      <td>V Pattern</td>\n",
       "      <td>Bullish Engulfing</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>inf</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>2535.00</td>\n",
       "      <td>2567.30</td>\n",
       "      <td>2525.85</td>\n",
       "      <td>2539.00</td>\n",
       "      <td>2751.35</td>\n",
       "      <td>1830.00</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>101.27</td>\n",
       "      <td>165.85</td>\n",
       "      <td>63.772028</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>18.296688</td>\n",
       "      <td>Undeterministic</td>\n",
       "      <td>1</td>\n",
       "      <td>50.207076</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Inverted Hammer</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>4.98</td>\n",
       "      <td>383.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2022-01-14</td>\n",
       "      <td>2014.00</td>\n",
       "      <td>2049.95</td>\n",
       "      <td>2007.00</td>\n",
       "      <td>2044.75</td>\n",
       "      <td>2049.95</td>\n",
       "      <td>1306.00</td>\n",
       "      <td>LT</td>\n",
       "      <td>123.97</td>\n",
       "      <td>187.29</td>\n",
       "      <td>72.603972</td>\n",
       "      <td>No Signal</td>\n",
       "      <td>19.174605</td>\n",
       "      <td>Rising High</td>\n",
       "      <td>0</td>\n",
       "      <td>38.620992</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown Green</td>\n",
       "      <td>Nifty 50</td>\n",
       "      <td>7.64</td>\n",
       "      <td>392.13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         DATE      OPEN      HIGH       LOW     CLOSE     52W H     52W L  \\\n",
       "19 2022-01-14    121.50    124.40    121.35    123.30    141.50     86.75   \n",
       "13 2022-01-14    730.20    777.00    727.00    762.50    889.00    554.25   \n",
       "7  2022-01-14    395.00    399.95    392.50    398.45    503.00    357.40   \n",
       "8  2022-01-14   1909.00   1945.00   1898.00   1938.20   2253.00   1626.00   \n",
       "3  2022-01-14    134.40    136.15    133.30    135.35    152.10     88.15   \n",
       "9  2022-01-14   1530.00   1548.70   1519.00   1545.15   1725.00   1342.00   \n",
       "12 2022-01-14    164.75    166.15    163.25    164.75    203.80    123.40   \n",
       "11 2022-01-14    679.90    689.55    677.25    682.70    776.50    363.20   \n",
       "4  2022-01-14    509.00    515.40    505.65    509.90    536.70    199.65   \n",
       "6  2022-01-14    769.00    795.00    763.65    780.10    901.00    500.10   \n",
       "18 2022-01-14   1714.50   1746.80   1696.50   1737.75   1838.00    915.00   \n",
       "14 2022-01-14    506.00    509.50    503.00    506.35    551.85    224.55   \n",
       "0  2022-01-14   1213.00   1226.30   1206.10   1213.60   1534.50    596.00   \n",
       "2  2022-01-14   7634.00   7700.00   7566.90   7660.55   8269.00   5260.00   \n",
       "16 2022-01-14   1259.00   1272.25   1254.50   1263.60   1273.90    838.00   \n",
       "17 2022-01-14   1320.00   1342.95   1293.00   1337.20   1377.75    891.00   \n",
       "1  2022-01-14   1882.00   1933.00   1881.00   1929.35   1933.00   1231.00   \n",
       "5  2022-01-14  26830.00  27150.00  26577.25  27078.45  32048.00  22531.00   \n",
       "15 2022-01-14   2535.00   2567.30   2525.85   2539.00   2751.35   1830.00   \n",
       "10 2022-01-14   2014.00   2049.95   2007.00   2044.75   2049.95   1306.00   \n",
       "\n",
       "        SYMBOL    Diff  CCI Value  RSI Value MACD Signal        ADX  \\\n",
       "19         IOC    2.50     156.07  65.401471   No Signal  25.582498   \n",
       "13  TATACONSUM    2.71     176.90  57.600282   No Signal  26.459180   \n",
       "7         BPCL    2.97      95.75  57.207319   No Signal  16.331214   \n",
       "8    KOTAKBANK    3.25      85.08  57.769626   No Signal  24.591789   \n",
       "3         NTPC    4.49     111.33  64.151473   No Signal  24.508930   \n",
       "9     HDFCBANK    9.50      58.74  56.424449   No Signal  27.511609   \n",
       "12   COALINDIA   10.06     146.05  66.073250   No Signal  25.071845   \n",
       "11    JSWSTEEL   15.76     127.12  55.997846   No Signal  14.641731   \n",
       "4   TATAMOTORS   18.33     122.84  61.974601   No Signal  10.686055   \n",
       "6   ADANIPORTS   23.97     203.62  64.408868   No Signal  15.363095   \n",
       "18       TECHM   41.86      -5.16  56.533617   No Signal  18.147039   \n",
       "14    HINDALCO   45.67     134.01  68.088941   No Signal  21.098261   \n",
       "0    TATASTEEL   52.05     200.25  60.147869   No Signal  20.341697   \n",
       "2   ULTRACEMCO   60.24      73.07  57.273652   No Signal  12.441589   \n",
       "16     SBILIFE   76.71     125.91  71.857625   No Signal  22.159275   \n",
       "17     HCLTECH   80.43      68.90  66.654850   No Signal  34.585401   \n",
       "1         INFY   81.11     129.30  67.785232         Buy  22.538556   \n",
       "5     SHREECEM   82.78      59.78  54.205867   No Signal  26.295460   \n",
       "15    RELIANCE  101.27     165.85  63.772028   No Signal  18.296688   \n",
       "10          LT  123.97     187.29  72.603972   No Signal  19.174605   \n",
       "\n",
       "          Direction  Ichi         ATR      Triple Candle      Double Candle  \\\n",
       "19  Undeterministic     1    2.632577            Unknown            Unknown   \n",
       "13  Undeterministic     1   18.745219          V Pattern  Bullish Engulfing   \n",
       "7   Undeterministic     1    8.642031            Unknown            Unknown   \n",
       "8   Undeterministic     1   47.238806            Unknown            Unknown   \n",
       "3   Undeterministic     1    3.167456  Reverse V Pattern            Unknown   \n",
       "9   Undeterministic     1   28.712721            Unknown            Unknown   \n",
       "12  Undeterministic     1    3.948298            Unknown            Unknown   \n",
       "11  Undeterministic     0   18.548907            Unknown            Unknown   \n",
       "4       Rising High     0   13.811799            Unknown            Unknown   \n",
       "6   Undeterministic     0   21.053643            Unknown            Unknown   \n",
       "18      Rising High     0   44.400312            Unknown  Bullish Engulfing   \n",
       "14  Undeterministic     1   12.124316            Unknown            Unknown   \n",
       "0   Undeterministic     1   34.090779            Unknown            Unknown   \n",
       "2   Undeterministic     1  157.593387            Unknown            Unknown   \n",
       "16      Rising High     0   22.638524            Unknown            Unknown   \n",
       "17      Rising High     0   31.892530            Unknown            Unknown   \n",
       "1       Rising High     0   37.595616            Unknown  Bullish Engulfing   \n",
       "5   Undeterministic     1  614.935596          V Pattern  Bullish Engulfing   \n",
       "15  Undeterministic     1   50.207076            Unknown            Unknown   \n",
       "10      Rising High     0   38.620992            Unknown            Unknown   \n",
       "\n",
       "      Recent Candle     Index  Expected Change %  Max Config Risk  \n",
       "19    Unknown Green  Nifty 50               9.30           399.73  \n",
       "13    Unknown Green  Nifty 50              14.12           384.30  \n",
       "7     Unknown Green  Nifty 50               6.74           391.13  \n",
       "8     Unknown Green  Nifty 50               5.22           355.90  \n",
       "3     Unknown Green  Nifty 50               4.58           399.29  \n",
       "9     Unknown Green  Nifty 50               4.23           393.21  \n",
       "12             Doji  Nifty 50               8.99           396.18  \n",
       "11  Inverted Hammer  Nifty 50               9.75           370.11  \n",
       "4   Inverted Hammer  Nifty 50               8.38           388.98  \n",
       "6     Unknown Green  Nifty 50               9.19           365.55  \n",
       "18    Unknown Green  Nifty 50               6.15           376.20  \n",
       "14  Inverted Hammer  Nifty 50               4.45           397.55  \n",
       "0   Inverted Hammer  Nifty 50              12.47           382.64  \n",
       "2        Green Doji  Nifty 50               4.19           322.81  \n",
       "16    Unknown Green  Nifty 50               4.52           373.99  \n",
       "17    Unknown Green  Nifty 50               7.82           368.10  \n",
       "1           Bullish  Nifty 50               7.28           352.25  \n",
       "5     Unknown Green  Nifty 50                inf              inf  \n",
       "15  Inverted Hammer  Nifty 50               4.98           383.85  \n",
       "10    Unknown Green  Nifty 50               7.64           392.13  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "budget = 40000 # Total Budget\n",
    "risk = 400 # Risk per trade\n",
    "df = In.show_full_stats(budget = budget,risk=risk, diff = 150, nifty='nifty_50') # Show only stocks undder your budget and  whose recent candle's lowest is not more than 151 rupees above the moving average line\n",
    "df[(df['RSI Value'] < 80) & (df['CCI Value'] < 250)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b16b5f1",
   "metadata": {},
   "source": [
    "## Golden Crossover\n",
    "When 44 days `SMA` Crosses 200 days `SMA` from below and you find a `Green` candle within 15 days taking support on `44` days line set Risk to Reward ratio as 1:5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6b6dc881",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUB\n",
      "WHIRLPOOL\n",
      "SUNTV\n",
      "IDEA\n",
      "IRFC\n",
      "SRTRANSFIN\n",
      "VBL\n",
      "MARUTI\n",
      "TVSMOTOR\n"
     ]
    }
   ],
   "source": [
    "for name in In.data['nifty_200']:\n",
    "    df = In.open_downloaded_stock(name)\n",
    "    if In.has_golden_crossover(df,lookback=21):\n",
    "        print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d6c1d4d",
   "metadata": {},
   "source": [
    "## RSI Signal: Oversold / Overbought Stocks\n",
    "Buy when RSI is less than 30 sell when greater than 70"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6bd93e91",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ANGELBRKG\n",
      "VGUARD\n"
     ]
    }
   ],
   "source": [
    "for name in In.data['nifty_500']:\n",
    "    df = In.open_downloaded_stock(name)\n",
    "    if In.get_RSI(df,signal_only=True) == \"Buy\":\n",
    "        print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3b819d1",
   "metadata": {},
   "source": [
    "## MACD Signal\n",
    "It is the strategy when MACD (Blue) Line cuts the Signal (Red) line from below then it is a buy signal. When the blue line cuts from upside down, it is sell signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3f7071cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADANIPORTS\n",
      "JSWSTEEL\n"
     ]
    }
   ],
   "source": [
    "for name in In.data['nifty_50']:\n",
    "    df = In.open_downloaded_stock(name)\n",
    "    if In.macd_signal(df) == 'Buy':\n",
    "        print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09b8127e",
   "metadata": {},
   "source": [
    "## CCI Signal : Rally\n",
    "**Faster than MACD Signal works closely with Stochastic RSI**\n",
    "\n",
    "When CCI values comes from below  -100 to above -100, buy signal and when it comes from above +100 to below +100, sell signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "47e183a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('IOC', 'Nifty 50')\n",
      "('ICICIBANK', 'Nifty 50')\n",
      "('COALINDIA', 'Nifty 50')\n",
      "('HINDUNILVR', 'Nifty 50')\n",
      "('TCS', 'Nifty 50')\n",
      "('NTPC', 'Nifty 50')\n",
      "('SBILIFE', 'Nifty 50')\n",
      "('ONGC', 'Nifty 50')\n"
     ]
    }
   ],
   "source": [
    "for name in In.data['nifty_50']:\n",
    "    df = In.open_downloaded_stock(name)\n",
    "    if In.get_CCI(df, signal_only = True) == 'Buy':\n",
    "        print((name, In.get_index(name)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6435e7a6",
   "metadata": {},
   "source": [
    "# Stochastic Oscillator\n",
    "1. Buy when the fast line cuts the slow line from below in an OVERSOLD zone ( both are below 20). Wait for both lines to go above Oversold and then buy. Recent candle closing must be above 200-MA\n",
    "\n",
    "2. Sell when both lines reaches Overbought region (above 70) and fast line crosses slow from above. Wait for both lines to go below the threshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a8271cb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "for name in In.data['nifty_500']:\n",
    "    if In.Stochastic(In.open_downloaded_stock(name), signal_only = True) == \"Buy\":\n",
    "        print(name, In.get_index(name))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c6358c1",
   "metadata": {},
   "source": [
    "# Intraday \n",
    "## See documentations for Intraday strategies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27a27a4a",
   "metadata": {},
   "source": [
    "## Pivots Points\n",
    "As discusses in the book, [How to Make Money in Intraday Trading by Ashwani Gujral](https://www.amazon.in/How-Make-Money-Intraday-Trading/dp/9386268159) (go to `./ebooks` directory to find the annoted version of this book), this one is very important indicator. None of the online screening platforms have support for displaying [`CPR`](https://zerodha.com/varsity/chapter/the-central-pivot-range/) by default and most of these do not even show the Pivots, Support, Resistance until `9:15`. This one gives you the values of `Pivot with CPR, 3 Supports and Resistances` at the day end as long as the NSE updates the day end data so that you can plan your day in advance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "92bc92a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1800x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = In.open_live_stock_data('BSOFT')\n",
    "pivot_data = In.get_Pivot_Points(data, plot = True, num_days_back=5) # access pivot_data to see exact values of support resistances and pivots and pivots boundries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d776735e",
   "metadata": {},
   "source": [
    "## Narrow Range (Stock Selection)\n",
    "If recent candle's range is lowest among `X` other days then the future candle might break it's low/high"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "43fba55d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'SUPPETRO': {'Long Probability': 0.3, 'Short Probability': 1.0}} ['Nifty 500']\n",
      "{'INDHOTEL': {'Long Probability': 0.6, 'Short Probability': 1.0}} ['Nifty 200']\n",
      "{'CUB': {'Long Probability': 0.7, 'Short Probability': 0.9}} ['Nifty 200', 'NIFTY PRIVATE BANK']\n",
      "{'GUJALKALI': {'Long Probability': 0.6, 'Short Probability': 1.0}} ['Nifty 500']\n",
      "{'ZENSARTECH': {'Long Probability': 0.8, 'Short Probability': 0.8}} ['Nifty 500']\n",
      "{'ABFRL': {'Long Probability': 0.8, 'Short Probability': 0.9}} ['Nifty 200']\n",
      "{'GILLETTE': {'Long Probability': 0.3, 'Short Probability': 0.8}} ['Nifty 500']\n",
      "{'BEML': {'Long Probability': 0.7, 'Short Probability': 0.7}} ['Nifty 500']\n",
      "{'FLUOROCHEM': {'Long Probability': 0.6, 'Short Probability': 0.8}} ['Nifty 500']\n",
      "{'CUMMINSIND': {'Long Probability': 0.8, 'Short Probability': 0.6}} ['Nifty 200', 'NIFTY MNC']\n",
      "{'BIRLACORPN': {'Long Probability': 0.8, 'Short Probability': 0.7}} ['Nifty 500']\n"
     ]
    }
   ],
   "source": [
    "for name in In.data['nifty_500']:\n",
    "    if Intra.NR_strategy(name, range_ = 20):\n",
    "        print(Intra.prob_by_percent_change(symbol = [name], index = None, time_period = 10, change_percent=0.07),In.get_index(name,'all'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a6e2419",
   "metadata": {},
   "source": [
    "## Whole Number Open (Stock Selection + Strategy)\n",
    "When Open == Low / High in Whole number as `xxx.00` within 15 minutes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "246839a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long :\n",
      " Name - Change - ATR - Change% - Remaining Move - Index:\n",
      "\n",
      "('RELIANCE', 26.0, 64.5, '1.09%', -0.6, 'Nifty 50') \n",
      "\n",
      "('GRASIM', 29.9, 50.61, '1.74%', -0.41, 'Nifty 50') \n",
      "\n",
      "('NTPC', 2.45, 3.78, '1.96%', -0.35, 'Nifty 50') \n",
      "\n",
      "('ADANIGREEN', 66.85, 55.46, '4.82%', 0.21, 'Nifty 100') \n",
      "\n",
      "Short :\n",
      " Name - Change - ATR - Change% - Remaining Move - Index:\n",
      "\n",
      "('INDUSTOWER', 3.9, 11.78, '1.44%', -0.67, 'Nifty 100') \n",
      "\n",
      "('MUTHOOTFIN', 36.45, 43.24, '2.45%', -0.16, 'Nifty 100') \n",
      "\n",
      "('HDFCLIFE', 12.35, 13.99, '1.82%', -0.12, 'Nifty 50') \n",
      "\n"
     ]
    }
   ],
   "source": [
    "Intra.whole_number_strategy(nifty = 100, min_val=101, max_val=5000, print_results = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6098d58f",
   "metadata": {},
   "source": [
    "## `%` Change probability (Stock Selection)\n",
    "Gives the stock names which have the highest probability of providing you `x%` in intraday atleast on both long or short side based on the previous `N` days record"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b20b5b89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'BATAINDIA': {'Long Probability': 0.85, 'Short Probability': 0.5},\n",
       " 'SONACOMS': {'Long Probability': 0.8, 'Short Probability': 0.45},\n",
       " 'ADANIENT': {'Long Probability': 0.8, 'Short Probability': 0.4},\n",
       " 'HAL': {'Long Probability': 0.75, 'Short Probability': 0.6},\n",
       " 'MCDOWELL-N': {'Long Probability': 0.75, 'Short Probability': 0.5},\n",
       " 'LTTS': {'Long Probability': 0.75, 'Short Probability': 0.55},\n",
       " 'LTI': {'Long Probability': 0.75, 'Short Probability': 0.55},\n",
       " 'GUJGASLTD': {'Long Probability': 0.75, 'Short Probability': 0.7},\n",
       " 'BHARATFORG': {'Long Probability': 0.75, 'Short Probability': 0.55},\n",
       " 'FORTIS': {'Long Probability': 0.75, 'Short Probability': 0.7}}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Gives you top 10 stocks from Nifty 500 which have the highest probability of giving atleast 0.99% on your investment based on the Long/Buy position. Data is based on past 60 trading days\n",
    "# Test it for different time duration, index, % change and Long / Short criteria based on overall market trend\n",
    "Intra.prob_by_percent_change(symbol = None, index = 200, time_period = 20, change_percent=0.099, sort_by='Long Probability', top_k = 10) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74773862",
   "metadata": {},
   "source": [
    "## ATR \n",
    "If stock has crossed it's ATR on either side, it might reverse or if it hasn't, there is still a chance to move"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dd1a387d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>pChange</th>\n",
       "      <th>open</th>\n",
       "      <th>dayHigh</th>\n",
       "      <th>dayLow</th>\n",
       "      <th>lastPrice</th>\n",
       "      <th>absolute_change</th>\n",
       "      <th>ATR</th>\n",
       "      <th>remaining move %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>CUMMINSIND</td>\n",
       "      <td>0.13</td>\n",
       "      <td>897.00</td>\n",
       "      <td>901.90</td>\n",
       "      <td>892.20</td>\n",
       "      <td>896.95</td>\n",
       "      <td>0.13</td>\n",
       "      <td>27.016392</td>\n",
       "      <td>-0.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>IRCTC</td>\n",
       "      <td>-3.45</td>\n",
       "      <td>898.00</td>\n",
       "      <td>901.70</td>\n",
       "      <td>853.10</td>\n",
       "      <td>862.00</td>\n",
       "      <td>3.45</td>\n",
       "      <td>197.803641</td>\n",
       "      <td>-0.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>NAVINFLUOR</td>\n",
       "      <td>-0.33</td>\n",
       "      <td>3508.60</td>\n",
       "      <td>3543.00</td>\n",
       "      <td>3479.20</td>\n",
       "      <td>3505.00</td>\n",
       "      <td>0.33</td>\n",
       "      <td>142.066893</td>\n",
       "      <td>-0.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ESCORTS</td>\n",
       "      <td>0.41</td>\n",
       "      <td>1814.90</td>\n",
       "      <td>1831.00</td>\n",
       "      <td>1796.25</td>\n",
       "      <td>1810.00</td>\n",
       "      <td>0.41</td>\n",
       "      <td>75.096007</td>\n",
       "      <td>-0.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>HINDCOPPER</td>\n",
       "      <td>-0.46</td>\n",
       "      <td>120.70</td>\n",
       "      <td>121.65</td>\n",
       "      <td>119.10</td>\n",
       "      <td>119.35</td>\n",
       "      <td>0.46</td>\n",
       "      <td>5.743198</td>\n",
       "      <td>-0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>DIXON</td>\n",
       "      <td>-0.26</td>\n",
       "      <td>5120.00</td>\n",
       "      <td>5147.95</td>\n",
       "      <td>5051.00</td>\n",
       "      <td>5070.75</td>\n",
       "      <td>0.26</td>\n",
       "      <td>230.442496</td>\n",
       "      <td>-0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>2410.00</td>\n",
       "      <td>2428.25</td>\n",
       "      <td>2392.55</td>\n",
       "      <td>2400.00</td>\n",
       "      <td>0.16</td>\n",
       "      <td>61.300714</td>\n",
       "      <td>-0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>SHREECEM</td>\n",
       "      <td>-0.28</td>\n",
       "      <td>26895.00</td>\n",
       "      <td>27000.00</td>\n",
       "      <td>26665.00</td>\n",
       "      <td>26665.00</td>\n",
       "      <td>0.28</td>\n",
       "      <td>714.065296</td>\n",
       "      <td>-0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>SBICARD</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>1008.00</td>\n",
       "      <td>1016.30</td>\n",
       "      <td>998.00</td>\n",
       "      <td>1000.55</td>\n",
       "      <td>0.60</td>\n",
       "      <td>30.732185</td>\n",
       "      <td>-0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>SRTRANSFIN</td>\n",
       "      <td>-0.63</td>\n",
       "      <td>1588.80</td>\n",
       "      <td>1600.95</td>\n",
       "      <td>1570.00</td>\n",
       "      <td>1578.00</td>\n",
       "      <td>0.63</td>\n",
       "      <td>56.132333</td>\n",
       "      <td>-0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>PRESTIGE</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>440.00</td>\n",
       "      <td>448.00</td>\n",
       "      <td>432.50</td>\n",
       "      <td>435.70</td>\n",
       "      <td>1.25</td>\n",
       "      <td>24.451381</td>\n",
       "      <td>-0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>INDHOTEL</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>208.30</td>\n",
       "      <td>209.50</td>\n",
       "      <td>205.00</td>\n",
       "      <td>206.65</td>\n",
       "      <td>0.29</td>\n",
       "      <td>9.987298</td>\n",
       "      <td>-0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>DEEPAKNTR</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>2173.00</td>\n",
       "      <td>2187.00</td>\n",
       "      <td>2140.00</td>\n",
       "      <td>2148.75</td>\n",
       "      <td>0.18</td>\n",
       "      <td>99.186552</td>\n",
       "      <td>-0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>WHIRLPOOL</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>2220.90</td>\n",
       "      <td>2253.85</td>\n",
       "      <td>2186.25</td>\n",
       "      <td>2196.00</td>\n",
       "      <td>0.67</td>\n",
       "      <td>102.320678</td>\n",
       "      <td>-0.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>COROMANDEL</td>\n",
       "      <td>-0.56</td>\n",
       "      <td>761.55</td>\n",
       "      <td>768.40</td>\n",
       "      <td>754.20</td>\n",
       "      <td>757.30</td>\n",
       "      <td>0.56</td>\n",
       "      <td>21.620237</td>\n",
       "      <td>-0.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>HINDZINC</td>\n",
       "      <td>1.29</td>\n",
       "      <td>329.00</td>\n",
       "      <td>331.60</td>\n",
       "      <td>325.35</td>\n",
       "      <td>330.90</td>\n",
       "      <td>1.29</td>\n",
       "      <td>10.715640</td>\n",
       "      <td>-0.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>ASHOKLEY</td>\n",
       "      <td>0.11</td>\n",
       "      <td>136.30</td>\n",
       "      <td>137.35</td>\n",
       "      <td>134.40</td>\n",
       "      <td>135.20</td>\n",
       "      <td>0.11</td>\n",
       "      <td>5.631620</td>\n",
       "      <td>-0.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>PFC</td>\n",
       "      <td>0.00</td>\n",
       "      <td>125.00</td>\n",
       "      <td>126.40</td>\n",
       "      <td>123.70</td>\n",
       "      <td>124.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.842501</td>\n",
       "      <td>-0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>GODREJIND</td>\n",
       "      <td>0.79</td>\n",
       "      <td>620.00</td>\n",
       "      <td>626.00</td>\n",
       "      <td>612.45</td>\n",
       "      <td>623.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>20.807047</td>\n",
       "      <td>-0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>ASTRAL</td>\n",
       "      <td>-2.16</td>\n",
       "      <td>2200.00</td>\n",
       "      <td>2217.00</td>\n",
       "      <td>2170.85</td>\n",
       "      <td>2179.00</td>\n",
       "      <td>2.16</td>\n",
       "      <td>80.899648</td>\n",
       "      <td>-0.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         symbol  pChange      open   dayHigh    dayLow  lastPrice  \\\n",
       "52   CUMMINSIND     0.13    897.00    901.90    892.20     896.95   \n",
       "198       IRCTC    -3.45    898.00    901.70    853.10     862.00   \n",
       "78   NAVINFLUOR    -0.33   3508.60   3543.00   3479.20    3505.00   \n",
       "41      ESCORTS     0.41   1814.90   1831.00   1796.25    1810.00   \n",
       "83   HINDCOPPER    -0.46    120.70    121.65    119.10     119.35   \n",
       "70        DIXON    -0.26   5120.00   5147.95   5051.00    5070.75   \n",
       "66          ACC    -0.16   2410.00   2428.25   2392.55    2400.00   \n",
       "75     SHREECEM    -0.28  26895.00  27000.00  26665.00   26665.00   \n",
       "89      SBICARD    -0.60   1008.00   1016.30    998.00    1000.55   \n",
       "91   SRTRANSFIN    -0.63   1588.80   1600.95   1570.00    1578.00   \n",
       "129    PRESTIGE    -1.25    440.00    448.00    432.50     435.70   \n",
       "76     INDHOTEL    -0.29    208.30    209.50    205.00     206.65   \n",
       "68    DEEPAKNTR    -0.18   2173.00   2187.00   2140.00    2148.75   \n",
       "96    WHIRLPOOL    -0.67   2220.90   2253.85   2186.25    2196.00   \n",
       "85   COROMANDEL    -0.56    761.55    768.40    754.20     757.30   \n",
       "16     HINDZINC     1.29    329.00    331.60    325.35     330.90   \n",
       "53     ASHOKLEY     0.11    136.30    137.35    134.40     135.20   \n",
       "60          PFC     0.00    125.00    126.40    123.70     124.00   \n",
       "27    GODREJIND     0.79    620.00    626.00    612.45     623.00   \n",
       "177      ASTRAL    -2.16   2200.00   2217.00   2170.85    2179.00   \n",
       "\n",
       "     absolute_change         ATR  remaining move %  \n",
       "52              0.13   27.016392             -0.82  \n",
       "198             3.45  197.803641             -0.77  \n",
       "78              0.33  142.066893             -0.76  \n",
       "41              0.41   75.096007             -0.75  \n",
       "83              0.46    5.743198             -0.72  \n",
       "70              0.26  230.442496             -0.70  \n",
       "66              0.16   61.300714             -0.70  \n",
       "75              0.28  714.065296             -0.68  \n",
       "89              0.60   30.732185             -0.67  \n",
       "91              0.63   56.132333             -0.67  \n",
       "129             1.25   24.451381             -0.67  \n",
       "76              0.29    9.987298             -0.67  \n",
       "68              0.18   99.186552             -0.67  \n",
       "96              0.67  102.320678             -0.66  \n",
       "85              0.56   21.620237             -0.66  \n",
       "16              1.29   10.715640             -0.66  \n",
       "53              0.11    5.631620             -0.66  \n",
       "60              0.00    3.842501             -0.64  \n",
       "27              0.79   20.807047             -0.64  \n",
       "177             2.16   80.899648             -0.64  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = Intra.ATR_strategy(index = 'NIFTY 200', possible_reversal=False) # if possible_reversal is true, it'll just reverse the order of remaining move %\n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad616ab4",
   "metadata": {},
   "source": [
    "# [Live Market]()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b5eabab",
   "metadata": {},
   "source": [
    "## Minutes LIVE Data 🤯🤯🤯🤯🤑🤑🤑🤑🥳️🥳️🥳️\n",
    "Yup! Package now supports `[2,3,4,5,10,15,30,60]` minutes Live Data Too! Finally!!\n",
    "\n",
    "In order to access the data, there is a unique code associated with every name and is known only to them. You need to write the code for the stock you want to access. This is one time process per stock. You can find that code as follows:\n",
    "\n",
    "1. Login to `Kite` from your PC and open the chart of `5` minutes for any stock you want to analyse.\n",
    "2. Click `Ctrl + Shift + I` in Chrome. A new small panel will get opened on the right hand side of screen.\n",
    "3. Find **NETWORK** in the upper region of that panel. It'll be in the upper region only next to `Elements | Console | Sources | Network`. Click on **NETWORK**\n",
    "4. Click `CTRL+R` to reload. You'll find something that starts with `5minute?user_id=` under `Name`. [You'll be looking at something like this. Highlighted `holdings` is equal to your `5minute?user_id=`](https://marketsetup.in/posts/zerodha-login/portfolio.png). Click on it and see `Headers` just like in the picture.\n",
    "5. You'll see a Something like `Request URL: https://kite.zerodha.com/oms/instruments/historical/2513665/5minute?user_id=AB1234&oi=1&from=2022-01-09&to=2022-01-14`\n",
    "6. The number after `/historical/2513665` is the one you are looking for. So in this case, it is `HAVELLS` code. Save it for future purpose.\n",
    "\n",
    "### Please help me help you. I am trying to help more and more people. Not everyone can get this code easily and I can not get all the 1600 codes for everyone. If you are looking for a stock and find it's code, just send me a `feature request` or `raise an issue` and paste  the code along with scrip name there so that more and more people can be helped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4afc7677",
   "metadata": {},
   "outputs": [],
   "source": [
    "Kite = KiteZerodha(user_id = 'AB1234',password = \"password@123\",two_factor_pin = 123456) # You'll be logged out from your PC as much as I know\n",
    "df =  Kite.get_historical_minutes_data(name = 'HAVELLS', code = None, interval = 15, starting_from_date = None, no_days_back = 50, get_latest_only = False) # can also directly use code = 2513665\n",
    "# Get 15 minutes data of HINDPETRO starting from Today (including current candles) to the previous 50 days. If get_latest_only = True, it would give you 1 days day i.e Today\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29426149",
   "metadata": {},
   "source": [
    "## Market Sentiment: TICK, TRIN (Arm's Index) & 52W High-Low touching shares"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "788d8b74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Latest Updated on': '24/11/2021 16:14:59',\n",
       " 'Up': 934,\n",
       " 'Down': 690,\n",
       " 'TICK': 244,\n",
       " 'Volume Up': 1738.56,\n",
       " 'Volume Down': 739.87,\n",
       " 'TRIN': 0.576,\n",
       " '52W High': 63,\n",
       " '52W Low': 10}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MS.get_live_sentiment()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33ac5eb3",
   "metadata": {},
   "source": [
    "## [Volatility Index: VIX](https://www.motilaloswal.com/blog-details/6-things-that-the-Volatility-Index-(VIX)-indicates-to-you../1929)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d06d1f40",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current VIX: 17.0950\n"
     ]
    }
   ],
   "source": [
    "NSE.get_VIX()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8f41133",
   "metadata": {},
   "source": [
    "## MMI: [Market Mood Index](https://www.tickertape.in/market-mood-index)\n",
    "\n",
    "Please click on the link above to get the values. All credits to [Ticker Tape Website](https://www.tickertape.in/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b9aa6a4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'currentValue': 35.087171038762804,\n",
       " 'date': '2021-11-24T14:20:04.589Z',\n",
       " 'indicator': 35.087171038762804,\n",
       " 'lastDay': {'indicator': 33.86992310290614,\n",
       "  'date': '2021-11-23T00:00:00.000Z',\n",
       "  'nifty': 17503.35},\n",
       " 'lastWeek': {'indicator': 49.06614474165184,\n",
       "  'date': '2021-11-16T00:00:00.000Z',\n",
       "  'nifty': 17999.2},\n",
       " 'lastMonth': {'indicator': 49.81882013493076,\n",
       "  'date': '2021-10-20T00:00:00.000Z',\n",
       "  'nifty': 18266.6},\n",
       " 'nifty': 17415.05}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_mmi(raw = True) # True means a simple Json shows current, last week, last month MMI"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6f70e0d",
   "metadata": {},
   "source": [
    "## Current Index Performance\n",
    "Includes Nifty, Thematic and Sectoral indices and show `Top-N` sorted by change %"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7724448c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>percentChange</th>\n",
       "      <th>key</th>\n",
       "      <th>variation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>INDIA VIX</td>\n",
       "      <td>-5.10</td>\n",
       "      <td>BROAD MARKET INDICES</td>\n",
       "      <td>-0.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NIFTY MEDIA</td>\n",
       "      <td>2.00</td>\n",
       "      <td>SECTORAL INDICES</td>\n",
       "      <td>44.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>NIFTY CPSE</td>\n",
       "      <td>1.57</td>\n",
       "      <td>THEMATIC INDICES</td>\n",
       "      <td>36.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NIFTY IT</td>\n",
       "      <td>-1.52</td>\n",
       "      <td>SECTORAL INDICES</td>\n",
       "      <td>-538.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NIFTY AUTO</td>\n",
       "      <td>-1.28</td>\n",
       "      <td>SECTORAL INDICES</td>\n",
       "      <td>-146.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>NIFTY ALPHA LOW-VOLATILITY 30</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>STRATEGY INDICES</td>\n",
       "      <td>-215.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>NIFTY GROWTH SECTORS 15</td>\n",
       "      <td>-1.12</td>\n",
       "      <td>STRATEGY INDICES</td>\n",
       "      <td>-87.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>NIFTY200 QUALITY 30</td>\n",
       "      <td>-1.12</td>\n",
       "      <td>STRATEGY INDICES</td>\n",
       "      <td>-166.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>NIFTY50 PR 2X LEVERAGE</td>\n",
       "      <td>-1.02</td>\n",
       "      <td>STRATEGY INDICES</td>\n",
       "      <td>-92.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>NIFTY50 TR 2X LEVERAGE</td>\n",
       "      <td>-1.02</td>\n",
       "      <td>STRATEGY INDICES</td>\n",
       "      <td>-125.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            index  percentChange                   key  \\\n",
       "8                       INDIA VIX          -5.10  BROAD MARKET INDICES   \n",
       "21                    NIFTY MEDIA           2.00      SECTORAL INDICES   \n",
       "48                     NIFTY CPSE           1.57      THEMATIC INDICES   \n",
       "20                       NIFTY IT          -1.52      SECTORAL INDICES   \n",
       "16                     NIFTY AUTO          -1.28      SECTORAL INDICES   \n",
       "44  NIFTY ALPHA LOW-VOLATILITY 30          -1.25      STRATEGY INDICES   \n",
       "31        NIFTY GROWTH SECTORS 15          -1.12      STRATEGY INDICES   \n",
       "43            NIFTY200 QUALITY 30          -1.12      STRATEGY INDICES   \n",
       "35         NIFTY50 PR 2X LEVERAGE          -1.02      STRATEGY INDICES   \n",
       "34         NIFTY50 TR 2X LEVERAGE          -1.02      STRATEGY INDICES   \n",
       "\n",
       "    variation  \n",
       "8       -0.92  \n",
       "21      44.60  \n",
       "48      36.20  \n",
       "20    -538.15  \n",
       "16    -146.85  \n",
       "44    -215.30  \n",
       "31     -87.85  \n",
       "43    -166.50  \n",
       "35     -92.10  \n",
       "34    -125.20  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NSE.current_indices_status(10) # Live as of market is open. works post market also"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d71508aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>pChange</th>\n",
       "      <th>open</th>\n",
       "      <th>dayHigh</th>\n",
       "      <th>dayLow</th>\n",
       "      <th>lastPrice</th>\n",
       "      <th>absolute_change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ONGC</td>\n",
       "      <td>4.26</td>\n",
       "      <td>149.00</td>\n",
       "      <td>155.85</td>\n",
       "      <td>149.00</td>\n",
       "      <td>152.95</td>\n",
       "      <td>4.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>-1.84</td>\n",
       "      <td>1420.00</td>\n",
       "      <td>1429.00</td>\n",
       "      <td>1370.00</td>\n",
       "      <td>1381.10</td>\n",
       "      <td>1.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>-1.77</td>\n",
       "      <td>2380.00</td>\n",
       "      <td>2409.90</td>\n",
       "      <td>2343.55</td>\n",
       "      <td>2343.55</td>\n",
       "      <td>1.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NTPC</td>\n",
       "      <td>1.27</td>\n",
       "      <td>134.50</td>\n",
       "      <td>137.30</td>\n",
       "      <td>133.55</td>\n",
       "      <td>135.20</td>\n",
       "      <td>1.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GAIL</td>\n",
       "      <td>1.16</td>\n",
       "      <td>139.00</td>\n",
       "      <td>143.20</td>\n",
       "      <td>139.00</td>\n",
       "      <td>140.10</td>\n",
       "      <td>1.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BPCL</td>\n",
       "      <td>1.11</td>\n",
       "      <td>401.10</td>\n",
       "      <td>409.30</td>\n",
       "      <td>398.80</td>\n",
       "      <td>402.00</td>\n",
       "      <td>1.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>IOC</td>\n",
       "      <td>0.83</td>\n",
       "      <td>126.70</td>\n",
       "      <td>129.30</td>\n",
       "      <td>126.40</td>\n",
       "      <td>127.20</td>\n",
       "      <td>0.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ADANITRANS</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>1916.05</td>\n",
       "      <td>1985.00</td>\n",
       "      <td>1904.00</td>\n",
       "      <td>1940.05</td>\n",
       "      <td>0.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>TATAPOWER</td>\n",
       "      <td>0.57</td>\n",
       "      <td>240.00</td>\n",
       "      <td>246.70</td>\n",
       "      <td>237.30</td>\n",
       "      <td>238.30</td>\n",
       "      <td>0.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>0.50</td>\n",
       "      <td>202.20</td>\n",
       "      <td>207.45</td>\n",
       "      <td>202.00</td>\n",
       "      <td>202.85</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        symbol  pChange     open  dayHigh   dayLow  lastPrice  absolute_change\n",
       "1         ONGC     4.26   149.00   155.85   149.00     152.95             4.26\n",
       "10  ADANIGREEN    -1.84  1420.00  1429.00  1370.00    1381.10             1.84\n",
       "9     RELIANCE    -1.77  2380.00  2409.90  2343.55    2343.55             1.77\n",
       "2         NTPC     1.27   134.50   137.30   133.55     135.20             1.27\n",
       "3         GAIL     1.16   139.00   143.20   139.00     140.10             1.16\n",
       "4         BPCL     1.11   401.10   409.30   398.80     402.00             1.11\n",
       "5          IOC     0.83   126.70   129.30   126.40     127.20             0.83\n",
       "8   ADANITRANS    -0.74  1916.05  1985.00  1904.00    1940.05             0.74\n",
       "6    TATAPOWER     0.57   240.00   246.70   237.30     238.30             0.57\n",
       "7    POWERGRID     0.50   202.20   207.45   202.00     202.85             0.50"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NSE.open_nse_index('NIFTY ENERGY',) # Returns performance of stocks in a given index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f194c1e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>percentChange</th>\n",
       "      <th>key</th>\n",
       "      <th>variation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>NIFTY INDIA CONSUMPTION</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>THEMATIC INDICES</td>\n",
       "      <td>-55.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NIFTY 100</td>\n",
       "      <td>-0.51</td>\n",
       "      <td>BROAD MARKET INDICES</td>\n",
       "      <td>-90.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>NIFTY CONSUMER DURABLES</td>\n",
       "      <td>-0.46</td>\n",
       "      <td>SECTORAL INDICES</td>\n",
       "      <td>-131.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      index  percentChange                   key  variation\n",
       "47  NIFTY INDIA CONSUMPTION          -0.76      THEMATIC INDICES     -55.45\n",
       "2                 NIFTY 100          -0.51  BROAD MARKET INDICES     -90.50\n",
       "28  NIFTY CONSUMER DURABLES          -0.46      SECTORAL INDICES    -131.50"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "In.stock_current_index_performance('HAVELLS') # All the eligible indices (and their current performance) where this stock belongs to. Some stocks might not belong aywhere"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c782769b",
   "metadata": {},
   "source": [
    "## Stocks trading at their 52W Low / High"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6dcbfe3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>comapnyName</th>\n",
       "      <th>new52WHL</th>\n",
       "      <th>prev52WHL</th>\n",
       "      <th>prevHLDate</th>\n",
       "      <th>ltp</th>\n",
       "      <th>prevClose</th>\n",
       "      <th>change</th>\n",
       "      <th>pChange</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AIROLAM</td>\n",
       "      <td>Airo Lam limited</td>\n",
       "      <td>54.15</td>\n",
       "      <td>55.00</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>56.00</td>\n",
       "      <td>56.05</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>-0.089206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DFMFOODS</td>\n",
       "      <td>DFM Foods Limited</td>\n",
       "      <td>282.00</td>\n",
       "      <td>282.60</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>285.20</td>\n",
       "      <td>291.75</td>\n",
       "      <td>-6.55</td>\n",
       "      <td>-2.245073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DSPNEWETF</td>\n",
       "      <td>DSP  Mutual Fund - DSP Nifty 50 Equal Weight ETF</td>\n",
       "      <td>195.00</td>\n",
       "      <td>195.00</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>197.00</td>\n",
       "      <td>196.40</td>\n",
       "      <td>2.53</td>\n",
       "      <td>1.300972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FOCUS</td>\n",
       "      <td>Focus Lighting and Fixtures Limited</td>\n",
       "      <td>83.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-</td>\n",
       "      <td>85.30</td>\n",
       "      <td>81.25</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.984615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ICICICONSU</td>\n",
       "      <td>ICICI Prudential Mutual Fund - ICICI Prudentia...</td>\n",
       "      <td>58.05</td>\n",
       "      <td>71.10</td>\n",
       "      <td>03-Nov-2021</td>\n",
       "      <td>72.20</td>\n",
       "      <td>72.83</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.152123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>IHCL-RE</td>\n",
       "      <td>INDIAN HOTELS CO LTD-RE</td>\n",
       "      <td>52.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-</td>\n",
       "      <td>54.50</td>\n",
       "      <td>57.25</td>\n",
       "      <td>-2.75</td>\n",
       "      <td>-4.803493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MOGSEC</td>\n",
       "      <td>Motilal Oswal Mutual Fund - Motilal Oswal 5 Ye...</td>\n",
       "      <td>45.00</td>\n",
       "      <td>45.00</td>\n",
       "      <td>08-Nov-2021</td>\n",
       "      <td>49.14</td>\n",
       "      <td>49.24</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>-0.203087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MOL</td>\n",
       "      <td>Meghmani Organics Limited</td>\n",
       "      <td>81.10</td>\n",
       "      <td>83.90</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>81.10</td>\n",
       "      <td>84.50</td>\n",
       "      <td>-3.40</td>\n",
       "      <td>-4.023669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NXTDIG-RE</td>\n",
       "      <td>NXTDIGITAL LIMITED-RE</td>\n",
       "      <td>31.90</td>\n",
       "      <td>48.10</td>\n",
       "      <td>22-Nov-2021</td>\n",
       "      <td>31.90</td>\n",
       "      <td>53.10</td>\n",
       "      <td>-21.20</td>\n",
       "      <td>-39.924670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>SIGACHI</td>\n",
       "      <td>Sigachi Industries Limited</td>\n",
       "      <td>486.35</td>\n",
       "      <td>511.90</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>537.45</td>\n",
       "      <td>511.90</td>\n",
       "      <td>25.55</td>\n",
       "      <td>4.991209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SPANDANA</td>\n",
       "      <td>Spandana Sphoorty Financial Limited</td>\n",
       "      <td>430.50</td>\n",
       "      <td>435.65</td>\n",
       "      <td>22-Nov-2021</td>\n",
       "      <td>433.90</td>\n",
       "      <td>458.35</td>\n",
       "      <td>-24.45</td>\n",
       "      <td>-5.334351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>VERTOZ</td>\n",
       "      <td>Vertoz Advertising Limited</td>\n",
       "      <td>85.10</td>\n",
       "      <td>85.30</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>88.90</td>\n",
       "      <td>89.25</td>\n",
       "      <td>-0.35</td>\n",
       "      <td>-0.392157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RMCL</td>\n",
       "      <td>Radha Madhav Corporation Limited</td>\n",
       "      <td>1.90</td>\n",
       "      <td>1.90</td>\n",
       "      <td>23-Nov-2021</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.95</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2.564103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>VIKASPROP</td>\n",
       "      <td>Vikas Proppant &amp; Granite Limited</td>\n",
       "      <td>1.55</td>\n",
       "      <td>1.55</td>\n",
       "      <td>18-Nov-2021</td>\n",
       "      <td>1.60</td>\n",
       "      <td>1.70</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>-5.882353</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        symbol                                        comapnyName  new52WHL  \\\n",
       "0      AIROLAM                                   Airo Lam limited     54.15   \n",
       "1     DFMFOODS                                  DFM Foods Limited    282.00   \n",
       "2    DSPNEWETF   DSP  Mutual Fund - DSP Nifty 50 Equal Weight ETF    195.00   \n",
       "3        FOCUS                Focus Lighting and Fixtures Limited     83.05   \n",
       "4   ICICICONSU  ICICI Prudential Mutual Fund - ICICI Prudentia...     58.05   \n",
       "5      IHCL-RE                            INDIAN HOTELS CO LTD-RE     52.05   \n",
       "6       MOGSEC  Motilal Oswal Mutual Fund - Motilal Oswal 5 Ye...     45.00   \n",
       "7          MOL                          Meghmani Organics Limited     81.10   \n",
       "8    NXTDIG-RE                              NXTDIGITAL LIMITED-RE     31.90   \n",
       "9      SIGACHI                         Sigachi Industries Limited    486.35   \n",
       "10    SPANDANA                Spandana Sphoorty Financial Limited    430.50   \n",
       "11      VERTOZ                         Vertoz Advertising Limited     85.10   \n",
       "12        RMCL                   Radha Madhav Corporation Limited      1.90   \n",
       "13   VIKASPROP                   Vikas Proppant & Granite Limited      1.55   \n",
       "\n",
       "    prev52WHL   prevHLDate     ltp   prevClose  change    pChange  \n",
       "0       55.00  23-Nov-2021   56.00       56.05   -0.05  -0.089206  \n",
       "1      282.60  23-Nov-2021  285.20      291.75   -6.55  -2.245073  \n",
       "2      195.00  23-Nov-2021  197.00      196.40    2.53   1.300972  \n",
       "3        0.00            -   85.30       81.25    4.05   4.984615  \n",
       "4       71.10  03-Nov-2021   72.20       72.83   -0.11  -0.152123  \n",
       "5        0.00            -   54.50       57.25   -2.75  -4.803493  \n",
       "6       45.00  08-Nov-2021   49.14       49.24   -0.10  -0.203087  \n",
       "7       83.90  23-Nov-2021   81.10       84.50   -3.40  -4.023669  \n",
       "8       48.10  22-Nov-2021   31.90       53.10  -21.20 -39.924670  \n",
       "9      511.90  23-Nov-2021  537.45      511.90   25.55   4.991209  \n",
       "10     435.65  22-Nov-2021  433.90      458.35  -24.45  -5.334351  \n",
       "11      85.30  23-Nov-2021   88.90       89.25   -0.35  -0.392157  \n",
       "12       1.90  23-Nov-2021    2.00        1.95    0.05   2.564103  \n",
       "13       1.55  18-Nov-2021    1.60        1.70   -0.10  -5.882353  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NSE.stocks_at_52W(direction = 'low') # set direction = 'high' for stocks going up"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04a660ec",
   "metadata": {},
   "source": [
    "# Futures and Options"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a23be0ce",
   "metadata": {},
   "source": [
    "## [Analyse Option Chain](https://www.quora.com/How-do-I-read-analyse-the-option-chain-of-a-stock-to-intraday-trade-with-clarity-NSE). Very helpful"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "159e84ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1512x964.8 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "filtered_df = analyse_option_chain('TATACHEM', plot = True, fig_size=(21,6.7)) # Read the Doc String. Manually compare other parameters such as openInterest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f731a459",
   "metadata": {},
   "source": [
    "# [Back Testing](https://www.investopedia.com/terms/b/backtesting.asp)\n",
    "## Back Testing Stratagies to get the best Win %, Max Return Investment etc\n",
    "Pass in the parameters dict for all. Check Docstring of each individual function for how a strategy works in buying or selling."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81e6fd1d",
   "metadata": {},
   "source": [
    "## CCI\n",
    "`BT.backtest('cci', stocks=['DIVISLAB'])` , for individual stock data performance to tell how much a stock would have gained or lost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "15867546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>win%</th>\n",
       "      <th>wins</th>\n",
       "      <th>losses</th>\n",
       "      <th>ROI</th>\n",
       "      <th>p&amp;l</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>hold_period</th>\n",
       "      <th>buys</th>\n",
       "      <th>sells</th>\n",
       "      <th>days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ALEMBICLTD</th>\n",
       "      <td>1.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>5.85</td>\n",
       "      <td>[15.299999999999997, 0.9500000000000028, 4.049...</td>\n",
       "      <td>[2020-07-31 00:00:00, 2020-10-14 00:00:00, 202...</td>\n",
       "      <td>[2020-08-07 00:00:00, 2020-11-25 00:00:00, 202...</td>\n",
       "      <td>[79.65, 103.7, 101.95, 101.95, 105.1, 127.25, ...</td>\n",
       "      <td>[94.95, 104.65, 106.0, 114.0, 109.5, 128.55, 1...</td>\n",
       "      <td>[7, 42, 7, 1, 7, 17, 13]</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IEX</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>9.50</td>\n",
       "      <td>[17.100000000000023, 3.8000000000000114, 14.59...</td>\n",
       "      <td>[2020-02-05 00:00:00, 2020-07-30 00:00:00, 202...</td>\n",
       "      <td>[2020-02-18 00:00:00, 2020-08-17 00:00:00, 202...</td>\n",
       "      <td>[170.95, 183.0, 214.35, 335.1, 370.15, 410.0]</td>\n",
       "      <td>[188.05, 186.8, 228.95, 378.75, 373.0, 488.0]</td>\n",
       "      <td>[13, 18, 8, 12, 28, 15]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIINDIA</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>9.25</td>\n",
       "      <td>[26.0, 185.20000000000005, 20.100000000000023,...</td>\n",
       "      <td>[2020-02-24 00:00:00, 2020-09-29 00:00:00, 202...</td>\n",
       "      <td>[2020-03-02 00:00:00, 2020-12-02 00:00:00, 202...</td>\n",
       "      <td>[504.0, 624.8, 817.0, 1110.0, 1195.0, 1330.0]</td>\n",
       "      <td>[530.0, 810.0, 837.1, 1274.9, 1230.1, 1415.0]</td>\n",
       "      <td>[7, 64, 21, 11, 7, 24]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VTL</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>9.24</td>\n",
       "      <td>[50.0, 30.75, 50.34999999999991, 89.25, 221.0,...</td>\n",
       "      <td>[2020-02-18 00:00:00, 2021-02-03 00:00:00, 202...</td>\n",
       "      <td>[2020-02-24 00:00:00, 2021-02-09 00:00:00, 202...</td>\n",
       "      <td>[1030.0, 1054.15, 1075.0, 1234.0, 1777.0, 1841.0]</td>\n",
       "      <td>[1080.0, 1084.9, 1125.35, 1323.25, 1998.0, 214...</td>\n",
       "      <td>[6, 6, 1, 15, 12, 12]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CYIENT</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>7.76</td>\n",
       "      <td>[22.5, 41.0, 113.94999999999999, 2.79999999999...</td>\n",
       "      <td>[2020-09-11 00:00:00, 2020-09-28 00:00:00, 202...</td>\n",
       "      <td>[2020-09-16 00:00:00, 2020-10-23 00:00:00, 202...</td>\n",
       "      <td>[393.5, 389.0, 505.45, 655.0, 652.05, 950.0]</td>\n",
       "      <td>[416.0, 430.0, 619.4, 657.8, 660.0, 1036.85]</td>\n",
       "      <td>[5, 25, 4, 6, 12, 25]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASF</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>7.45</td>\n",
       "      <td>[17.200000000000045, 370.0, 73.40000000000009,...</td>\n",
       "      <td>[2020-04-24 00:00:00, 2020-08-13 00:00:00, 202...</td>\n",
       "      <td>[2020-06-05 00:00:00, 2020-08-24 00:00:00, 202...</td>\n",
       "      <td>[1097.8, 1324.0, 1447.6, 1540.0, 2080.0, 3489.9]</td>\n",
       "      <td>[1115.0, 1694.0, 1521.0, 1719.7, 2247.8, 3500.0]</td>\n",
       "      <td>[42, 11, 50, 10, 18, 22]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMBUJACEM</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6.09</td>\n",
       "      <td>[1.6999999999999886, 21.850000000000023, 6.100...</td>\n",
       "      <td>[2020-02-05 00:00:00, 2020-09-11 00:00:00, 202...</td>\n",
       "      <td>[2020-03-02 00:00:00, 2020-10-08 00:00:00, 202...</td>\n",
       "      <td>[206.9, 212.95, 258.9, 263.7, 303.95, 398.0]</td>\n",
       "      <td>[208.6, 234.8, 265.0, 273.0, 326.55, 436.55]</td>\n",
       "      <td>[26, 27, 30, 3, 28, 19]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MFSL</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>5.37</td>\n",
       "      <td>[71.39999999999998, 6.899999999999977, 21.2999...</td>\n",
       "      <td>[2020-08-19 00:00:00, 2020-09-28 00:00:00, 202...</td>\n",
       "      <td>[2020-08-26 00:00:00, 2020-10-08 00:00:00, 202...</td>\n",
       "      <td>[548.6, 603.1, 597.0, 709.9, 865.0, 1085.15]</td>\n",
       "      <td>[620.0, 610.0, 618.3, 778.0, 925.0, 1094.0]</td>\n",
       "      <td>[7, 10, 22, 9, 30, 31]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIMKEN</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>10.19</td>\n",
       "      <td>[156.0, 46.0, 93.65000000000009, 131.599999999...</td>\n",
       "      <td>[2020-07-29 00:00:00, 2020-09-29 00:00:00, 202...</td>\n",
       "      <td>[2020-08-26 00:00:00, 2020-11-17 00:00:00, 202...</td>\n",
       "      <td>[982.0, 1118.0, 1150.0, 1252.0, 1773.0]</td>\n",
       "      <td>[1138.0, 1164.0, 1243.65, 1383.6, 1985.0]</td>\n",
       "      <td>[28, 49, 9, 12, 15]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GRINDWELL</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>9.10</td>\n",
       "      <td>[22.0, 130.5, 124.0, 139.0, 5.2999999999999545]</td>\n",
       "      <td>[2020-11-17 00:00:00, 2021-01-27 00:00:00, 202...</td>\n",
       "      <td>[2020-11-19 00:00:00, 2021-02-18 00:00:00, 202...</td>\n",
       "      <td>[550.0, 720.0, 906.0, 1182.0, 1263.75]</td>\n",
       "      <td>[572.0, 850.5, 1030.0, 1321.0, 1269.05]</td>\n",
       "      <td>[2, 22, 36, 15, 28]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            win%  wins  losses    ROI  \\\n",
       "ALEMBICLTD   1.0     7       0   5.85   \n",
       "IEX          1.0     6       0   9.50   \n",
       "TIINDIA      1.0     6       0   9.25   \n",
       "VTL          1.0     6       0   9.24   \n",
       "CYIENT       1.0     6       0   7.76   \n",
       "BASF         1.0     6       0   7.45   \n",
       "AMBUJACEM    1.0     6       0   6.09   \n",
       "MFSL         1.0     6       0   5.37   \n",
       "TIMKEN       1.0     5       0  10.19   \n",
       "GRINDWELL    1.0     5       0   9.10   \n",
       "\n",
       "                                                          p&l  \\\n",
       "ALEMBICLTD  [15.299999999999997, 0.9500000000000028, 4.049...   \n",
       "IEX         [17.100000000000023, 3.8000000000000114, 14.59...   \n",
       "TIINDIA     [26.0, 185.20000000000005, 20.100000000000023,...   \n",
       "VTL         [50.0, 30.75, 50.34999999999991, 89.25, 221.0,...   \n",
       "CYIENT      [22.5, 41.0, 113.94999999999999, 2.79999999999...   \n",
       "BASF        [17.200000000000045, 370.0, 73.40000000000009,...   \n",
       "AMBUJACEM   [1.6999999999999886, 21.850000000000023, 6.100...   \n",
       "MFSL        [71.39999999999998, 6.899999999999977, 21.2999...   \n",
       "TIMKEN      [156.0, 46.0, 93.65000000000009, 131.599999999...   \n",
       "GRINDWELL     [22.0, 130.5, 124.0, 139.0, 5.2999999999999545]   \n",
       "\n",
       "                                                     buy_date  \\\n",
       "ALEMBICLTD  [2020-07-31 00:00:00, 2020-10-14 00:00:00, 202...   \n",
       "IEX         [2020-02-05 00:00:00, 2020-07-30 00:00:00, 202...   \n",
       "TIINDIA     [2020-02-24 00:00:00, 2020-09-29 00:00:00, 202...   \n",
       "VTL         [2020-02-18 00:00:00, 2021-02-03 00:00:00, 202...   \n",
       "CYIENT      [2020-09-11 00:00:00, 2020-09-28 00:00:00, 202...   \n",
       "BASF        [2020-04-24 00:00:00, 2020-08-13 00:00:00, 202...   \n",
       "AMBUJACEM   [2020-02-05 00:00:00, 2020-09-11 00:00:00, 202...   \n",
       "MFSL        [2020-08-19 00:00:00, 2020-09-28 00:00:00, 202...   \n",
       "TIMKEN      [2020-07-29 00:00:00, 2020-09-29 00:00:00, 202...   \n",
       "GRINDWELL   [2020-11-17 00:00:00, 2021-01-27 00:00:00, 202...   \n",
       "\n",
       "                                                    sell_date  \\\n",
       "ALEMBICLTD  [2020-08-07 00:00:00, 2020-11-25 00:00:00, 202...   \n",
       "IEX         [2020-02-18 00:00:00, 2020-08-17 00:00:00, 202...   \n",
       "TIINDIA     [2020-03-02 00:00:00, 2020-12-02 00:00:00, 202...   \n",
       "VTL         [2020-02-24 00:00:00, 2021-02-09 00:00:00, 202...   \n",
       "CYIENT      [2020-09-16 00:00:00, 2020-10-23 00:00:00, 202...   \n",
       "BASF        [2020-06-05 00:00:00, 2020-08-24 00:00:00, 202...   \n",
       "AMBUJACEM   [2020-03-02 00:00:00, 2020-10-08 00:00:00, 202...   \n",
       "MFSL        [2020-08-26 00:00:00, 2020-10-08 00:00:00, 202...   \n",
       "TIMKEN      [2020-08-26 00:00:00, 2020-11-17 00:00:00, 202...   \n",
       "GRINDWELL   [2020-11-19 00:00:00, 2021-02-18 00:00:00, 202...   \n",
       "\n",
       "                                                    buy_price  \\\n",
       "ALEMBICLTD  [79.65, 103.7, 101.95, 101.95, 105.1, 127.25, ...   \n",
       "IEX             [170.95, 183.0, 214.35, 335.1, 370.15, 410.0]   \n",
       "TIINDIA         [504.0, 624.8, 817.0, 1110.0, 1195.0, 1330.0]   \n",
       "VTL         [1030.0, 1054.15, 1075.0, 1234.0, 1777.0, 1841.0]   \n",
       "CYIENT           [393.5, 389.0, 505.45, 655.0, 652.05, 950.0]   \n",
       "BASF         [1097.8, 1324.0, 1447.6, 1540.0, 2080.0, 3489.9]   \n",
       "AMBUJACEM        [206.9, 212.95, 258.9, 263.7, 303.95, 398.0]   \n",
       "MFSL             [548.6, 603.1, 597.0, 709.9, 865.0, 1085.15]   \n",
       "TIMKEN                [982.0, 1118.0, 1150.0, 1252.0, 1773.0]   \n",
       "GRINDWELL              [550.0, 720.0, 906.0, 1182.0, 1263.75]   \n",
       "\n",
       "                                                   sell_price  \\\n",
       "ALEMBICLTD  [94.95, 104.65, 106.0, 114.0, 109.5, 128.55, 1...   \n",
       "IEX             [188.05, 186.8, 228.95, 378.75, 373.0, 488.0]   \n",
       "TIINDIA         [530.0, 810.0, 837.1, 1274.9, 1230.1, 1415.0]   \n",
       "VTL         [1080.0, 1084.9, 1125.35, 1323.25, 1998.0, 214...   \n",
       "CYIENT           [416.0, 430.0, 619.4, 657.8, 660.0, 1036.85]   \n",
       "BASF         [1115.0, 1694.0, 1521.0, 1719.7, 2247.8, 3500.0]   \n",
       "AMBUJACEM        [208.6, 234.8, 265.0, 273.0, 326.55, 436.55]   \n",
       "MFSL              [620.0, 610.0, 618.3, 778.0, 925.0, 1094.0]   \n",
       "TIMKEN              [1138.0, 1164.0, 1243.65, 1383.6, 1985.0]   \n",
       "GRINDWELL             [572.0, 850.5, 1030.0, 1321.0, 1269.05]   \n",
       "\n",
       "                         hold_period buys sells days  \n",
       "ALEMBICLTD  [7, 42, 7, 1, 7, 17, 13]    7     7  511  \n",
       "IEX          [13, 18, 8, 12, 28, 15]    6     6  510  \n",
       "TIINDIA       [7, 64, 21, 11, 7, 24]    6     6  511  \n",
       "VTL            [6, 6, 1, 15, 12, 12]    6     6  511  \n",
       "CYIENT         [5, 25, 4, 6, 12, 25]    6     6  511  \n",
       "BASF        [42, 11, 50, 10, 18, 22]    6     6  509  \n",
       "AMBUJACEM    [26, 27, 30, 3, 28, 19]    6     6  511  \n",
       "MFSL          [7, 10, 22, 9, 30, 31]    6     6  511  \n",
       "TIMKEN           [28, 49, 9, 12, 15]    5     5  511  \n",
       "GRINDWELL        [2, 22, 36, 15, 28]    5     5  511  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cci_parameters = {'buying_thresh':-100, 'selling_thresh':100, 'window':20, 'cols':('OPEN','CLOSE','LOW','HIGH', 'DATE')} # check documentation of BT.cci()\n",
    "\n",
    "# Using the CCI strategy, Return top gaining stocks which have traded atleast 365 recent days and are currently in nifty-500\n",
    "BT.backtest('cci', min_days = 365, top_n=10, stocks = 'nifty_500', **cci_parameters)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8012cb9a",
   "metadata": {},
   "source": [
    "## MA\n",
    "Moving Average Strategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "535c01aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>win%</th>\n",
       "      <th>wins</th>\n",
       "      <th>losses</th>\n",
       "      <th>ROI</th>\n",
       "      <th>p&amp;l</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>hold_period</th>\n",
       "      <th>buys</th>\n",
       "      <th>sells</th>\n",
       "      <th>days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INFY</th>\n",
       "      <td>0.82</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>3.89</td>\n",
       "      <td>[43.68050000000005, 64.476, 28.45699999999988,...</td>\n",
       "      <td>[2019-12-05 00:00:00, 2020-06-24 00:00:00, 202...</td>\n",
       "      <td>[2020-01-13 00:00:00, 2020-07-07 00:00:00, 202...</td>\n",
       "      <td>[710.5, 724.5, 926.4, 1144.8, 1140.25, 1277.95...</td>\n",
       "      <td>[754.1805, 788.976, 954.8569999999999, 1091.1,...</td>\n",
       "      <td>[39, 13, 12, 3, 21, 36, 17, 26, 1, 21, 5]</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TATAMOTORS</th>\n",
       "      <td>0.80</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4.56</td>\n",
       "      <td>[-14.0, 8.158999999999992, 7.960000000000008, ...</td>\n",
       "      <td>[2020-01-30 00:00:00, 2020-10-01 00:00:00, 202...</td>\n",
       "      <td>[2020-02-01 00:00:00, 2020-10-07 00:00:00, 202...</td>\n",
       "      <td>[188.9, 134.4, 138.0, 315.7, 302.0]</td>\n",
       "      <td>[174.9, 142.559, 145.96, 345.948, 318.8155]</td>\n",
       "      <td>[2, 6, 4, 27, 9]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TATASTEEL</th>\n",
       "      <td>0.78</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>5.24</td>\n",
       "      <td>[40.89449999999988, -33.64999999999998, 36.615...</td>\n",
       "      <td>[2019-12-13 00:00:00, 2020-09-10 00:00:00, 202...</td>\n",
       "      <td>[2019-12-20 00:00:00, 2020-09-21 00:00:00, 202...</td>\n",
       "      <td>[420.9, 420.15, 408.0, 663.5, 697.9, 729.95, 7...</td>\n",
       "      <td>[461.79449999999986, 386.5, 444.616, 715.7375,...</td>\n",
       "      <td>[7, 11, 19, 4, 8, 5, 9, 0, 1]</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IOC</th>\n",
       "      <td>0.75</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3.98</td>\n",
       "      <td>[8.556999999999988, -5.199999999999989, 6.4675...</td>\n",
       "      <td>[2020-12-23 00:00:00, 2021-02-19 00:00:00, 202...</td>\n",
       "      <td>[2021-01-12 00:00:00, 2021-03-24 00:00:00, 202...</td>\n",
       "      <td>[88.5, 99.85, 95.25, 108.2]</td>\n",
       "      <td>[97.05699999999999, 94.65, 101.7175, 113.97100...</td>\n",
       "      <td>[20, 33, 1, 9]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAJAJFINSV</th>\n",
       "      <td>0.71</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3.35</td>\n",
       "      <td>[439.7900000000009, -522.7000000000007, 902.5,...</td>\n",
       "      <td>[2019-12-12 00:00:00, 2020-02-06 00:00:00, 202...</td>\n",
       "      <td>[2020-01-14 00:00:00, 2020-02-28 00:00:00, 202...</td>\n",
       "      <td>[9100.0, 9684.0, 9025.0, 9911.9, 11942.0, 1310...</td>\n",
       "      <td>[9539.79, 9161.3, 9927.5, 10532.580999999998, ...</td>\n",
       "      <td>[33, 22, 12, 5, 3, 6, 13]</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            win%  wins  losses   ROI  \\\n",
       "INFY        0.82     9       2  3.89   \n",
       "TATAMOTORS  0.80     4       1  4.56   \n",
       "TATASTEEL   0.78     7       2  5.24   \n",
       "IOC         0.75     3       1  3.98   \n",
       "BAJAJFINSV  0.71     5       2  3.35   \n",
       "\n",
       "                                                          p&l  \\\n",
       "INFY        [43.68050000000005, 64.476, 28.45699999999988,...   \n",
       "TATAMOTORS  [-14.0, 8.158999999999992, 7.960000000000008, ...   \n",
       "TATASTEEL   [40.89449999999988, -33.64999999999998, 36.615...   \n",
       "IOC         [8.556999999999988, -5.199999999999989, 6.4675...   \n",
       "BAJAJFINSV  [439.7900000000009, -522.7000000000007, 902.5,...   \n",
       "\n",
       "                                                     buy_date  \\\n",
       "INFY        [2019-12-05 00:00:00, 2020-06-24 00:00:00, 202...   \n",
       "TATAMOTORS  [2020-01-30 00:00:00, 2020-10-01 00:00:00, 202...   \n",
       "TATASTEEL   [2019-12-13 00:00:00, 2020-09-10 00:00:00, 202...   \n",
       "IOC         [2020-12-23 00:00:00, 2021-02-19 00:00:00, 202...   \n",
       "BAJAJFINSV  [2019-12-12 00:00:00, 2020-02-06 00:00:00, 202...   \n",
       "\n",
       "                                                    sell_date  \\\n",
       "INFY        [2020-01-13 00:00:00, 2020-07-07 00:00:00, 202...   \n",
       "TATAMOTORS  [2020-02-01 00:00:00, 2020-10-07 00:00:00, 202...   \n",
       "TATASTEEL   [2019-12-20 00:00:00, 2020-09-21 00:00:00, 202...   \n",
       "IOC         [2021-01-12 00:00:00, 2021-03-24 00:00:00, 202...   \n",
       "BAJAJFINSV  [2020-01-14 00:00:00, 2020-02-28 00:00:00, 202...   \n",
       "\n",
       "                                                    buy_price  \\\n",
       "INFY        [710.5, 724.5, 926.4, 1144.8, 1140.25, 1277.95...   \n",
       "TATAMOTORS                [188.9, 134.4, 138.0, 315.7, 302.0]   \n",
       "TATASTEEL   [420.9, 420.15, 408.0, 663.5, 697.9, 729.95, 7...   \n",
       "IOC                               [88.5, 99.85, 95.25, 108.2]   \n",
       "BAJAJFINSV  [9100.0, 9684.0, 9025.0, 9911.9, 11942.0, 1310...   \n",
       "\n",
       "                                                   sell_price  \\\n",
       "INFY        [754.1805, 788.976, 954.8569999999999, 1091.1,...   \n",
       "TATAMOTORS        [174.9, 142.559, 145.96, 345.948, 318.8155]   \n",
       "TATASTEEL   [461.79449999999986, 386.5, 444.616, 715.7375,...   \n",
       "IOC         [97.05699999999999, 94.65, 101.7175, 113.97100...   \n",
       "BAJAJFINSV  [9539.79, 9161.3, 9927.5, 10532.580999999998, ...   \n",
       "\n",
       "                                          hold_period buys sells days  \n",
       "INFY        [39, 13, 12, 3, 21, 36, 17, 26, 1, 21, 5]   12    11  511  \n",
       "TATAMOTORS                           [2, 6, 4, 27, 9]    5     5  510  \n",
       "TATASTEEL               [7, 11, 19, 4, 8, 5, 9, 0, 1]    9     9  511  \n",
       "IOC                                    [20, 33, 1, 9]    4     4  511  \n",
       "BAJAJFINSV                  [33, 22, 12, 5, 3, 6, 13]    7     7  511  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BT.backtest('ma',stocks='nifty_50',top_n=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8de259c1",
   "metadata": {},
   "source": [
    "## RSI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "effc86b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>win%</th>\n",
       "      <th>wins</th>\n",
       "      <th>losses</th>\n",
       "      <th>ROI</th>\n",
       "      <th>p&amp;l</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>hold_period</th>\n",
       "      <th>buys</th>\n",
       "      <th>sells</th>\n",
       "      <th>days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CEATLTD</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.38</td>\n",
       "      <td>[5.0, 148.0999999999999, 31.450000000000045]</td>\n",
       "      <td>[2019-12-06 00:00:00, 2020-12-23 00:00:00, 202...</td>\n",
       "      <td>[2020-06-15 00:00:00, 2021-01-19 00:00:00, 202...</td>\n",
       "      <td>[965.0, 1070.75, 1394.0]</td>\n",
       "      <td>[970.0, 1218.85, 1425.45]</td>\n",
       "      <td>[192, 27, 89]</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GMMPFAUDLR</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>33.26</td>\n",
       "      <td>[1750.0, 242.10000000000036]</td>\n",
       "      <td>[2020-03-23 00:00:00, 2020-10-01 00:00:00, 202...</td>\n",
       "      <td>[2020-04-27 00:00:00, 2021-02-22 00:00:00]</td>\n",
       "      <td>[1890.0, 4099.0, 4239.4]</td>\n",
       "      <td>[3640.0, 4341.1]</td>\n",
       "      <td>[35, 144]</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EIHOTEL</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>29.79</td>\n",
       "      <td>[21.099999999999994, 37.0]</td>\n",
       "      <td>[2021-04-15 00:00:00, 2021-08-13 00:00:00]</td>\n",
       "      <td>[2021-06-01 00:00:00, 2021-09-28 00:00:00]</td>\n",
       "      <td>[89.0, 106.0]</td>\n",
       "      <td>[110.1, 143.0]</td>\n",
       "      <td>[47, 46]</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALKEM</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>28.03</td>\n",
       "      <td>[1038.7, 244.05000000000018]</td>\n",
       "      <td>[2020-03-23 00:00:00, 2020-10-28 00:00:00, 202...</td>\n",
       "      <td>[2020-08-05 00:00:00, 2020-12-09 00:00:00]</td>\n",
       "      <td>[1881.3, 2694.95, 3730.8]</td>\n",
       "      <td>[2920.0, 2939.0]</td>\n",
       "      <td>[135, 42]</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BSE</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>26.05</td>\n",
       "      <td>[70.0, 203.29999999999995]</td>\n",
       "      <td>[2020-11-06 00:00:00, 2021-03-30 00:00:00]</td>\n",
       "      <td>[2020-11-25 00:00:00, 2021-05-17 00:00:00]</td>\n",
       "      <td>[495.0, 554.0]</td>\n",
       "      <td>[565.0, 757.3]</td>\n",
       "      <td>[19, 48]</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            win%  wins  losses    ROI  \\\n",
       "CEATLTD      1.0     3       0   5.38   \n",
       "GMMPFAUDLR   1.0     2       0  33.26   \n",
       "EIHOTEL      1.0     2       0  29.79   \n",
       "ALKEM        1.0     2       0  28.03   \n",
       "BSE          1.0     2       0  26.05   \n",
       "\n",
       "                                                     p&l  \\\n",
       "CEATLTD     [5.0, 148.0999999999999, 31.450000000000045]   \n",
       "GMMPFAUDLR                  [1750.0, 242.10000000000036]   \n",
       "EIHOTEL                       [21.099999999999994, 37.0]   \n",
       "ALKEM                       [1038.7, 244.05000000000018]   \n",
       "BSE                           [70.0, 203.29999999999995]   \n",
       "\n",
       "                                                     buy_date  \\\n",
       "CEATLTD     [2019-12-06 00:00:00, 2020-12-23 00:00:00, 202...   \n",
       "GMMPFAUDLR  [2020-03-23 00:00:00, 2020-10-01 00:00:00, 202...   \n",
       "EIHOTEL            [2021-04-15 00:00:00, 2021-08-13 00:00:00]   \n",
       "ALKEM       [2020-03-23 00:00:00, 2020-10-28 00:00:00, 202...   \n",
       "BSE                [2020-11-06 00:00:00, 2021-03-30 00:00:00]   \n",
       "\n",
       "                                                    sell_date  \\\n",
       "CEATLTD     [2020-06-15 00:00:00, 2021-01-19 00:00:00, 202...   \n",
       "GMMPFAUDLR         [2020-04-27 00:00:00, 2021-02-22 00:00:00]   \n",
       "EIHOTEL            [2021-06-01 00:00:00, 2021-09-28 00:00:00]   \n",
       "ALKEM              [2020-08-05 00:00:00, 2020-12-09 00:00:00]   \n",
       "BSE                [2020-11-25 00:00:00, 2021-05-17 00:00:00]   \n",
       "\n",
       "                            buy_price                 sell_price  \\\n",
       "CEATLTD      [965.0, 1070.75, 1394.0]  [970.0, 1218.85, 1425.45]   \n",
       "GMMPFAUDLR   [1890.0, 4099.0, 4239.4]           [3640.0, 4341.1]   \n",
       "EIHOTEL                 [89.0, 106.0]             [110.1, 143.0]   \n",
       "ALKEM       [1881.3, 2694.95, 3730.8]           [2920.0, 2939.0]   \n",
       "BSE                    [495.0, 554.0]             [565.0, 757.3]   \n",
       "\n",
       "              hold_period buys sells days  \n",
       "CEATLTD     [192, 27, 89]    3     3  511  \n",
       "GMMPFAUDLR      [35, 144]    3     2  511  \n",
       "EIHOTEL          [47, 46]    2     2  511  \n",
       "ALKEM           [135, 42]    3     2  511  \n",
       "BSE              [19, 48]    2     2  510  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BT.backtest('rsi',stocks='nifty_500', top_n = 5) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a352d2c3",
   "metadata": {},
   "source": [
    "## MACD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9897c91f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>win%</th>\n",
       "      <th>wins</th>\n",
       "      <th>losses</th>\n",
       "      <th>ROI</th>\n",
       "      <th>p&amp;l</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>hold_period</th>\n",
       "      <th>buys</th>\n",
       "      <th>sells</th>\n",
       "      <th>days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BAJFINANCE</th>\n",
       "      <td>0.47</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>5.44</td>\n",
       "      <td>[-67.0, 570.1000000000004, 660.0, -58.0, -132....</td>\n",
       "      <td>[2020-01-16 00:00:00, 2020-01-29 00:00:00, 202...</td>\n",
       "      <td>[2020-01-23 00:00:00, 2020-02-27 00:00:00, 202...</td>\n",
       "      <td>[4190.0, 4244.9, 2520.0, 3665.0, 3400.0, 3368....</td>\n",
       "      <td>[4123.0, 4815.0, 3180.0, 3607.0, 3268.0, 3236....</td>\n",
       "      <td>[7, 29, 94, 12, 7, 1, 42, 1, 20, 34, 7, 12, 11...</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COALINDIA</th>\n",
       "      <td>0.44</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>0.56</td>\n",
       "      <td>[-10.0, -20.650000000000006, -5.90000000000000...</td>\n",
       "      <td>[2020-01-14 00:00:00, 2020-02-24 00:00:00, 202...</td>\n",
       "      <td>[2020-01-21 00:00:00, 2020-03-11 00:00:00, 202...</td>\n",
       "      <td>[211.15, 178.75, 138.75, 127.25, 144.95, 133.7...</td>\n",
       "      <td>[201.15, 158.1, 132.85, 134.5, 132.85, 129.9, ...</td>\n",
       "      <td>[7, 16, 37, 20, 8, 12, 23, 37, 21, 7, 11, 25, ...</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SHREECEM</th>\n",
       "      <td>0.43</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>1.36</td>\n",
       "      <td>[-114.0, 1811.0999999999985, -728.0, 1451.0499...</td>\n",
       "      <td>[2019-12-31 00:00:00, 2020-01-03 00:00:00, 202...</td>\n",
       "      <td>[2020-01-01 00:00:00, 2020-01-24 00:00:00, 202...</td>\n",
       "      <td>[20489.0, 21200.0, 25048.0, 16900.0, 19156.0, ...</td>\n",
       "      <td>[20375.0, 23011.1, 24320.0, 18351.05, 21840.0,...</td>\n",
       "      <td>[1, 21, 11, 37, 29, 2, 1, 2, 8, 5, 28, 42, 10,...</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            win%  wins  losses   ROI  \\\n",
       "BAJFINANCE  0.47     7       8  5.44   \n",
       "COALINDIA   0.44     7       9  0.56   \n",
       "SHREECEM    0.43     9      12  1.36   \n",
       "\n",
       "                                                          p&l  \\\n",
       "BAJFINANCE  [-67.0, 570.1000000000004, 660.0, -58.0, -132....   \n",
       "COALINDIA   [-10.0, -20.650000000000006, -5.90000000000000...   \n",
       "SHREECEM    [-114.0, 1811.0999999999985, -728.0, 1451.0499...   \n",
       "\n",
       "                                                     buy_date  \\\n",
       "BAJFINANCE  [2020-01-16 00:00:00, 2020-01-29 00:00:00, 202...   \n",
       "COALINDIA   [2020-01-14 00:00:00, 2020-02-24 00:00:00, 202...   \n",
       "SHREECEM    [2019-12-31 00:00:00, 2020-01-03 00:00:00, 202...   \n",
       "\n",
       "                                                    sell_date  \\\n",
       "BAJFINANCE  [2020-01-23 00:00:00, 2020-02-27 00:00:00, 202...   \n",
       "COALINDIA   [2020-01-21 00:00:00, 2020-03-11 00:00:00, 202...   \n",
       "SHREECEM    [2020-01-01 00:00:00, 2020-01-24 00:00:00, 202...   \n",
       "\n",
       "                                                    buy_price  \\\n",
       "BAJFINANCE  [4190.0, 4244.9, 2520.0, 3665.0, 3400.0, 3368....   \n",
       "COALINDIA   [211.15, 178.75, 138.75, 127.25, 144.95, 133.7...   \n",
       "SHREECEM    [20489.0, 21200.0, 25048.0, 16900.0, 19156.0, ...   \n",
       "\n",
       "                                                   sell_price  \\\n",
       "BAJFINANCE  [4123.0, 4815.0, 3180.0, 3607.0, 3268.0, 3236....   \n",
       "COALINDIA   [201.15, 158.1, 132.85, 134.5, 132.85, 129.9, ...   \n",
       "SHREECEM    [20375.0, 23011.1, 24320.0, 18351.05, 21840.0,...   \n",
       "\n",
       "                                                  hold_period buys sells days  \n",
       "BAJFINANCE  [7, 29, 94, 12, 7, 1, 42, 1, 20, 34, 7, 12, 11...   15    15  511  \n",
       "COALINDIA   [7, 16, 37, 20, 8, 12, 23, 37, 21, 7, 11, 25, ...   16    16  511  \n",
       "SHREECEM    [1, 21, 11, 37, 29, 2, 1, 2, 8, 5, 28, 42, 10,...   21    21  511  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BT.backtest('macd', top_n=5, stocks=['BAJFINANCE','SHREECEM',\"COALINDIA\"]) # Individual stocks. If no sells have been made, it'll be empty"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef633b46",
   "metadata": {},
   "source": [
    "## Stochastic Oscillator\n",
    "Faster signal than MACD. Pass in the paramerters to change results and modify to your ease"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b6fa4cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "BT.backtest('stochastic_osc',stocks='nifty_50', top_n = 15) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86f357f0",
   "metadata": {},
   "source": [
    "# [Risk Management](https://www.youtube.com/watch?v=v3lfIdpKSiU)\n",
    "\n",
    "You have a total budget of 40K, and a risk apetite of rs 400 per trade, You can set manual such as `entry = 3980.1` and `stop_loss=3780.5`. If intraday, set `leverage` parameter to `>1` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "be70b877",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Buying Price': 420.42,\n",
       " 'Stop-Loss %': 13.27,\n",
       " 'Target %': 26.54,\n",
       " 'Quantity': 7.0,\n",
       " 'Stop-Loss Price': 364.635,\n",
       " 'Trigger Price': 531.99,\n",
       " 'investment_required': 2942.94,\n",
       " 'Risk Per Share': 55.79,\n",
       " 'Profit Per Share': 111.57,\n",
       " 'Max loss on this config': 390.5,\n",
       " 'Max Gain on this config': 780.99,\n",
       " 'Index': []}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "In.get_particulars('NIITLTD',budget = 40000, risk = 400,)  #manually set parameters for entry, exit etc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "021391e4",
   "metadata": {},
   "source": [
    "# Connect to Online Brokers\n",
    "First step towards Algo trading"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72c96b27",
   "metadata": {},
   "source": [
    "## Zerodha / Kite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d4bdf5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "Kite = KiteZerodha(user_id = 'AB1234',password = \"password@123\",two_factor_pin = 123456)\n",
    "Kite.check_basic_info('holdings') # can check user info, positions, margins etc "
   ]
  }
 ],
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