趋势类策略入门- 4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 趋势策略入门"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 关键函数：\n",
    " - 1 交易函数（接收一个交易字典，包含交易价格，交易量，币种，交易方向等）\n",
    " - 2 持仓计算函数（根据仓位情况和风险设定，计算限制交易量以及交易价格）\n",
    " - 3 趋势条件计算函数（根据品种价格情况，判断是否执行交易，交易方向，交易量，以及交易价格）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'PERIOD_M5' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-b479206ff9fa>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[1;32mclass\u001b[0m \u001b[0mmid_class\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mthis_exchange\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m         '''\n\u001b[1;32m      4\u001b[0m         \u001b[0m初始化数据填充交易所的信息\u001b[0m\u001b[0;31m，\u001b[0m\u001b[0m首次获取价格\u001b[0m\u001b[0;31m，\u001b[0m\u001b[0m首次获取account信息\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m         \u001b[0m设定好密钥\u001b[0m\u001b[0;31m…\u001b[0m\u001b[0;31m…\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-1-b479206ff9fa>\u001b[0m in \u001b[0;36mmid_class\u001b[0;34m()\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     86\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m---> 87\u001b[0;31m     \u001b[1;32mdef\u001b[0m \u001b[0mget_ohlc_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mperiod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPERIOD_M5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     88\u001b[0m         '''\n\u001b[1;32m     89\u001b[0m         \u001b[0m获取K线信息\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'PERIOD_M5' is not defined"
     ]
    }
   ],
   "source": [
    "class mid_class():\n",
    "    def __init__(self, this_exchange):\n",
    "        '''\n",
    "        初始化数据填充交易所的信息，首次获取价格，首次获取account信息\n",
    "        设定好密钥……\n",
    "        \n",
    "        Args:\n",
    "            this_exchange: FMZ的交易所结构\n",
    "        \n",
    "        '''\n",
    "        self.init_timestamp = time.time()\n",
    "        self.exchange = this_exchange\n",
    "        self.name = self.exchange.GetName()\n",
    "        self.jyd = self.exchange.GetCurrency()        \n",
    "    \n",
    "    def get_account(self):\n",
    "        '''\n",
    "        获取账户信息\n",
    "        \n",
    "        Returns:\n",
    "            获取信息成功返回True，获取信息失败返回False\n",
    "        '''\n",
    "        self.Balance = '---'\n",
    "        self.Amount = '---'\n",
    "        self.FrozenBalance = '---'\n",
    "        self.FrozenStocks = '---'\n",
    "        \n",
    "        try:\n",
    "            self.account = self.exchange.GetAccount()\n",
    "\n",
    "            self.Balance =  self.account['Balance']\n",
    "            self.Amount = self.account['Stocks']\n",
    "            self.FrozenBalance =  self.account['FrozenBalance']\n",
    "            self.FrozenStocks = self.account['FrozenStocks']\n",
    "            return True\n",
    "        except:\n",
    "            return False\n",
    "    \n",
    "    def get_ticker(self):\n",
    "        '''\n",
    "        获取市价信息\n",
    "        \n",
    "        Returns:\n",
    "            获取信息成功返回True，获取信息失败返回False\n",
    "        '''\n",
    "        self.high = '---'\n",
    "        self.low = '---'\n",
    "        self.Sell =  '---'\n",
    "        self.Buy =  '---'\n",
    "        self.last =  '---'\n",
    "        self.Volume = '---'\n",
    "        \n",
    "        try:\n",
    "            self.ticker = self.exchange.GetTicker()\n",
    "        \n",
    "            self.high = self.ticker['High']\n",
    "            self.low = self.ticker['Low']\n",
    "            self.Sell =  self.ticker['Sell']\n",
    "            self.Buy =  self.ticker['Buy']\n",
    "            self.last =  self.ticker['Last']\n",
    "            self.Volume = self.ticker['Volume']\n",
    "            return True\n",
    "        except:\n",
    "            return False\n",
    "        \n",
    "        \n",
    "    def get_depth(self):\n",
    "        '''\n",
    "        获取深度信息\n",
    "        \n",
    "        Returns:\n",
    "            获取信息成功返回True，获取信息失败返回False\n",
    "        '''\n",
    "        self.Ask = '---'\n",
    "        self.Bids = '---'\n",
    "        \n",
    "        try:\n",
    "            self.Depth = self.exchange.GetDepth()\n",
    "            self.Ask = self.Depth['Asks']\n",
    "            self.Bids = self.Depth ['Bids']\n",
    "            return True\n",
    "        except:\n",
    "            return False\n",
    "        \n",
    "        \n",
    "    \n",
    "    def get_ohlc_data(self, period = PERIOD_M5):\n",
    "        '''\n",
    "        获取K线信息\n",
    "        \n",
    "        Args:\n",
    "            period: K线周期，PERIOD_M1 指1分钟, PERIOD_M5 指5分钟, PERIOD_M15 指15分钟,\n",
    "            PERIOD_M30 指30分钟, PERIOD_H1 指1小时, PERIOD_D1 指一天。\n",
    "        '''\n",
    "        self.ohlc_data = exchange.GetRecords(period)\n",
    "        \n",
    "        \n",
    "    \n",
    "    def create_order(self, order_type, price, amount):\n",
    "        '''\n",
    "        post一个挂单信息\n",
    "        \n",
    "        Args:\n",
    "            order_type：挂单类型，'buy'指挂买单，'sell'指挂卖单\n",
    "            price：挂单价格\n",
    "            amount:挂单数量\n",
    "            \n",
    "        Returns:\n",
    "            挂单Id号，可用以取消挂单\n",
    "        '''\n",
    "        if order_type == 'buy':\n",
    "            try:\n",
    "                order_id = self.exchange.Buy( price, amount)\n",
    "            except:\n",
    "                return False\n",
    "            \n",
    "        elif order_type == 'sell':\n",
    "            try:\n",
    "                order_id = self.exchange.Sell( price, amount)\n",
    "            except:\n",
    "                return False\n",
    "        \n",
    "        return order_id\n",
    "    \n",
    "    def get_orders(self):\n",
    "        self.undo_ordes = self.exchange.GetOrders()\n",
    "        return self.undo_ordes\n",
    "    \n",
    "    def cancel_order(self, order_id):\n",
    "        '''\n",
    "        取消一个挂单信息\n",
    "        \n",
    "        Args:\n",
    "            order_id：希望取消的挂单ID号\n",
    "            \n",
    "        Returns:\n",
    "            取消挂单成功返回True，取消挂单失败返回False\n",
    "        '''\n",
    "        return self.exchange.CancelOrder(order_id)\n",
    "        \n",
    "    def refreash_data(self):\n",
    "        '''\n",
    "        刷新信息\n",
    "        \n",
    "        Returns:\n",
    "            刷新信息成功返回 'refreash_data_finish!' 否则返回相应刷新失败的信息提示\n",
    "        '''\n",
    "\n",
    "        if not self.get_account():\n",
    "            return 'false_get_account'\n",
    "        \n",
    "        if not self.get_ticker():\n",
    "            return 'false_get_ticker'\n",
    "        if not self.get_depth():\n",
    "            return 'false_get_depth'\n",
    "        try:\n",
    "            self.get_ohlc_data()\n",
    "        except:\n",
    "            return 'false_get_K_line_info'\n",
    "        \n",
    "        return 'refreash_data_finish!'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def make_MACD(Kline, short_period, long_period, mid_period):\n",
    "    DIFF = make_DIF(Kline, short_period, long_period)\n",
    "    DEA = make_DEA(DIFF, mid_period)\n",
    "    MACDs = []\n",
    "    for i in range(len(DEA)):\n",
    "        MACDs.append( 2*(DEA[i] - DIFF[i]) )\n",
    "    return MACDs\n",
    "    \n",
    "def make_DIF(Kline, short_period, long_period):\n",
    "    EMA_short = make_EMA(Kline, short_period)\n",
    "    EMA_long = make_EMA(Kline, long_period)\n",
    "    DIFs = []\n",
    "    the_len = len(EMA_short)\n",
    "    for i in range( the_len ):\n",
    "        DIFs.append( EMA_short[ i - the_len ] - EMA_long[ i-the_len ])\n",
    "    return DIFs\n",
    "\n",
    "def make_DEA(DIFF, mid_period):\n",
    "    return make_EMA(DIFF, mid_period)\n",
    "    \n",
    "def make_EMA(Kline, period):\n",
    "    this_Kline = Kline[-period:]\n",
    "    Log(this_Kline)\n",
    "    EMAs = []\n",
    "    try:\n",
    "        EMAs.append( this_Kline[0]['Close'] )\n",
    "        for i in range(len(this_Kline) -1 ):\n",
    "            EMAs.append( ( 2*this_Kline[i+1]['Close'] + (period -1)*EMAs[i] )/(period + 1) )\n",
    "    except:\n",
    "        EMAs.append( this_Kline[0] )\n",
    "        for i in range(len(this_Kline) -1 ):\n",
    "            EMAs.append( ( 2*this_Kline[i+1] + (period -1)*EMAs[i] )/(period + 1) )\n",
    "            \n",
    "    return EMAs\n",
    "\n",
    "class qushi_class():\n",
    "    def __init__(self, mid_class, amount_N, price_N):\n",
    "        '''\n",
    "        设定好初始需要考虑的参数\n",
    "        Args:\n",
    "            mid_class: 所使用的交易所中间层\n",
    "            amount_N：数量小数点限制\n",
    "            price_N：价格小数点限制\n",
    "            \n",
    "        Attributes：\n",
    "            amount_N：数量小数点限制\n",
    "            price_N：价格小数点限制\n",
    "            init_time：初始时间\n",
    "            last_time：上一次执行操作的时间\n",
    "            trade_list:交易请求的id\n",
    "        '''\n",
    "        self.jys = mid_class\n",
    "        \n",
    "        self.init_time = time.time()\n",
    "        self.last_time = time.time()\n",
    "        \n",
    "        self.amount_N = amount_N\n",
    "        self.price_N = price_N\n",
    "        \n",
    "        self.trade_list = []\n",
    "    \n",
    "    def refreash_data(self):\n",
    "        '''\n",
    "        用来从交易所获取最新的价格和数量信息\n",
    "        \n",
    "        Attributes：\n",
    "            B：商品币数量\n",
    "            money：计价币数量\n",
    "            can_buy_B：当前理论可购买商品币数量\n",
    "            Buy_price:当前市场上最近的一单挂单买价\n",
    "            Sell_price：当前市场上最近的一单挂单卖价\n",
    "        '''\n",
    "        \n",
    "        self.jys.refreash_data()\n",
    "        self.B = self.jys.Amount\n",
    "        self.money = self.jys.Balance\n",
    "        self.Buy_price = self.jys.Buy\n",
    "        self.Sell_price = self.jys.Sell\n",
    "        self.can_buy_B = self.money/ self.Sell_price\n",
    "        self.can_buy_B = _N(self.can_buy_B, self.amount_N )\n",
    "        self.can_sell_B = _N(self.B, self.amount_N )\n",
    "        \n",
    "    def make_trade_by_dict(self, trade_dicts):\n",
    "        '''\n",
    "        用来批量完成交易订单\n",
    "        \n",
    "        Attributes：\n",
    "            trade_list:已提交的交易请求的id\n",
    "        '''\n",
    "        for this_trade in trade_dicts:\n",
    "            this_price = _N(this_trade['price'], self.price_N )\n",
    "            this_amount = _N(this_trade['amount'], self.amount_N )\n",
    "            \n",
    "            this_trade_id = self.jys.create_order( this_trade['side'], this_price , this_amount ) \n",
    "            self.trade_list.append( this_trade_id )\n",
    "    \n",
    "    def condition_chicang(self, hands_num):\n",
    "        '''\n",
    "        根据持仓情况来做交易判定的条件\n",
    "        Args:\n",
    "            hands_num：表示交易一共几手（我们假设当前每次交易不高于一手）\n",
    "            \n",
    "        Attributes：\n",
    "            min_trade_B: 一手最多交易的商品币数量\n",
    "            min_trade_money: 一手最多交易的计价币数量\n",
    "        \n",
    "        '''\n",
    "        self.min_trade_B = (self.can_buy_B + self.B) / hands_num\n",
    "        self.min_buy_B = min(self.min_trade_B, self.can_buy_B)\n",
    "        self.min_sell_B = min(self.min_trade_B, self.B)\n",
    "        \n",
    "        self.min_trade_money = self.min_trade_B* self.jys.Buy\n",
    "\n",
    "\n",
    "    \n",
    "    def condition_qushi(self, macd_threshold, short_period = 12, long_period = 26, mid_period = 9 ):\n",
    "        '''\n",
    "        根据市场价格情况来做交易判定的条件\n",
    "        Args:\n",
    "            short_period：MACD的EMA短周期\n",
    "            long_period:MACD的EMA长周期\n",
    "            mid_period:DIF的EMA周期\n",
    "            macd_threshold:MACD预计变化百分之多少取信\n",
    "        Returns：\n",
    "            min_trade_B: 一手最多交易的商品币数量\n",
    "            min_trade_money: 一手最多交易的计价币数量\n",
    "        \n",
    "        '''\n",
    "        Kline = self.jys.ohlc_data\n",
    "        MACD = make_MACD(Kline, short_period, long_period, mid_period)\n",
    "        X = [[x+1,x+1] for x in range(mid_period)]\n",
    "        y = MACD\n",
    "        reg = LinearRegression().fit(X, y)\n",
    "        next_macd = reg.predict( [[ mid_period + 1,mid_period + 1]] )\n",
    "        mean_macd = sum(MACD)/len(MACD)\n",
    "        \n",
    "        more_than = (100+macd_threshold)/100\n",
    "        less_than = (100-macd_threshold)/100\n",
    "        \n",
    "        rt = False\n",
    "        if  next_macd> macd_threshold and MACD [0] <0 :\n",
    "            rt = 'Buy'\n",
    "        elif next_macd< -macd_threshold and MACD [0] >0:\n",
    "            rt = 'Sell'\n",
    "        \n",
    "        return rt\n",
    "    \n",
    "    \n",
    "    def make_trade_dicts(self, hands_num, change_pct ):\n",
    "        '''\n",
    "        制作交易用字典表单\n",
    "        Args:\n",
    "            hands_num：一共交易多少手\n",
    "            change_pct：价格变化多少交易一手\n",
    "            \n",
    "        Returns：\n",
    "            this_trade_dicts: 根据当前价格变化，制作出需交易的字典的列表\n",
    "        \n",
    "        '''\n",
    "        self.condition_chicang(hands_num)\n",
    "        rt = self.condition_qushi( change_pct )\n",
    "        this_trade_dicts = []\n",
    "        if rt:\n",
    "            if rt == 'Buy':\n",
    "                if self.min_buy_B > 10**-self.amount_N:\n",
    "                    this_trade_dicts.append({\n",
    "                        'side':'buy',\n",
    "                        'price':self.jys.Buy,\n",
    "                        'amount':self.min_buy_B\n",
    "                    })\n",
    "            else:\n",
    "                if self.min_sell_B > 10**-self.amount_N:\n",
    "                    this_trade_dicts.append({\n",
    "                        'side':'sell',\n",
    "                        'price':self.jys.Sell,\n",
    "                        'amount':self.min_sell_B\n",
    "                    })\n",
    "            return this_trade_dicts\n",
    "        else:\n",
    "            return False\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main():\n",
    "    \n",
    "    Set_amount_N = 4\n",
    "    Set_price_N = 4\n",
    "    \n",
    "    hands_num = 20\n",
    "    macd_threshold = 10\n",
    "    \n",
    "    test_mid = mid_class(exchange)\n",
    "    Log(test_mid.refreash_data())\n",
    "    test_qushi = qushi_class(test_mid , Set_amount_N, Set_price_N)\n",
    "    \n",
    "    while True:\n",
    "        \n",
    "        Sleep(1000)\n",
    "        try:\n",
    "            test_qushi.refreash_data()\n",
    "\n",
    "            now_trade_dicts = test_qushi.make_trade_dicts(hands_num, macd_threshold)\n",
    "            if now_trade_dicts:\n",
    "                test_qushi.make_trade_by_dict(now_trade_dicts)\n",
    "                now_trade_dicts = False\n",
    "        except:\n",
    "            pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 优化策略的思路\n",
    "    作出假设 --> 验证假设 --> 写成函数投入策略\n",
    "    \n",
    "## 优化策略的方法\n",
    "    1、优化价格判定条件\n",
    "    2、优化持仓判定条件\n",
    "    3、优化交易表单的制作函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_MACD(Kline, short_period, long_period, mid_period):\n",
    "    DIFF = make_DIF(Kline, short_period, long_period)\n",
    "    DEA = make_DEA(DIFF, mid_period)\n",
    "    MACDs = []\n",
    "    for i in range(len(DEA)):\n",
    "        MACDs.append( 2*(DEA[i] - DIFF[i]) )\n",
    "    return MACDs\n",
    "    \n",
    "def make_DIF(Kline, short_period, long_period):\n",
    "    EMA_short = make_EMA(Kline, short_period)\n",
    "    EMA_long = make_EMA(Kline, long_period)\n",
    "    DIFs = []\n",
    "    the_len = len(EMA_short)\n",
    "    for i in range( the_len ):\n",
    "        DIFs.append( EMA_short[ i - the_len ] - EMA_long[ i-the_len ])\n",
    "    return DIFs\n",
    "\n",
    "def make_DEA(DIFF, mid_period):\n",
    "    return make_EMA(DIFF, mid_period)\n",
    "    \n",
    "def make_EMA(Kline, period):\n",
    "    EMAs = Kline[0]['Close']\n",
    "    for i in range(len(Kline) -1 ):\n",
    "        EMAs.append( 2*Kline(i+1)['Close'] + (period -1)*EMAs[i] )/(period + 1)\n",
    "    return EMAs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 4, 5, 6, 7, 8]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 所有看起来有效的网格策略，都是在用长期风险换取短期收益 （看起来一直在赚钱，突然有一天本都亏没了）\n",
    "## 大部分的趋势策略（诸如MACD，EMA这类的简单判定）用近期风险换取长期收益 （看起来一直在亏钱，突然有一天赚了一点点，然后继续亏）\n",
    "\n",
    "# 人们都容易忽略长期风险，因为短期收益而欢喜"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 作出假设 --> 验证假设 --> 写成函数投入策略\n"
   ]
  }
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