vnpy/examples/CtaBacktesting/backtesting.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, OptimizationSetting, MINUTE_DB_NAME\n",
    "from vnpy.trader.app.ctaStrategy.strategy.strategyAtrRsi import AtrRsiStrategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 创建回测引擎对象\n",
    "engine = BacktestingEngine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 设置回测使用的数据\n",
    "engine.setBacktestingMode(engine.BAR_MODE)    # 设置引擎的回测模式为K线\n",
    "engine.setDatabase(MINUTE_DB_NAME, 'IF0000')  # 设置使用的历史数据库\n",
    "engine.setStartDate('20120101')               # 设置回测用的数据起始日期"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 配置回测引擎参数\n",
    "engine.setSlippage(0.2)     # 设置滑点为股指1跳\n",
    "engine.setRate(0.3/10000)   # 设置手续费万0.3\n",
    "engine.setSize(300)         # 设置股指合约大小 \n",
    "engine.setPriceTick(0.2)    # 设置股指最小价格变动   \n",
    "engine.setCapital(1000000)  # 设置回测本金"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 在引擎中创建策略对象\n",
    "d = {'atrLength': 11}                     # 策略参数配置\n",
    "engine.initStrategy(AtrRsiStrategy, d)    # 创建策略对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2017-08-23 22:46:29.700000\t开始载入数据\n",
      "2017-08-23 22:46:29.790000\t载入完成，数据量：31455\n",
      "2017-08-23 22:46:29.790000\t开始回测\n",
      "2017-08-23 22:46:29.809000\t策略初始化完成\n",
      "2017-08-23 22:46:29.809000\t策略启动完成\n",
      "2017-08-23 22:46:29.809000\t开始回放数据\n",
      "2017-08-23 22:46:31.487000\t数据回放结束\n"
     ]
    }
   ],
   "source": [
    "# 运行回测\n",
    "engine.runBacktesting()          # 运行回测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2017-08-23 22:46:33.876000\t计算按日统计结果\n",
      "2017-08-23 22:46:33.907000\t------------------------------\n",
      "2017-08-23 22:46:33.907000\t首个交易日：\t2012-01-11\n",
      "2017-08-23 22:46:33.907000\t最后交易日：\t2012-06-29\n",
      "2017-08-23 22:46:33.907000\t总交易日：\t112\n",
      "2017-08-23 22:46:33.907000\t盈利交易日\t48\n",
      "2017-08-23 22:46:33.907000\t亏损交易日：\t64\n",
      "2017-08-23 22:46:33.907000\t起始资金：\t1000000\n",
      "2017-08-23 22:46:33.907000\t结束资金：\t879,365.29\n",
      "2017-08-23 22:46:33.907000\t总收益率：\t-12.06\n",
      "2017-08-23 22:46:33.907000\t总盈亏：\t-120,634.71\n",
      "2017-08-23 22:46:33.907000\t最大回撤: \t-138,853.38\n",
      "2017-08-23 22:46:33.907000\t总手续费：\t9,934.71\n",
      "2017-08-23 22:46:33.907000\t总滑点：\t25,980.0\n",
      "2017-08-23 22:46:33.907000\t总成交金额：\t331,156,920.0\n",
      "2017-08-23 22:46:33.907000\t总成交笔数：\t433.0\n",
      "2017-08-23 22:46:33.907000\t日均盈亏：\t-1,077.1\n",
      "2017-08-23 22:46:33.907000\t日均手续费：\t88.7\n",
      "2017-08-23 22:46:33.907000\t日均滑点：\t231.96\n",
      "2017-08-23 22:46:33.907000\t日均成交金额：\t2,956,758.21\n",
      "2017-08-23 22:46:33.907000\t日均成交笔数：\t3.87\n",
      "2017-08-23 22:46:33.908000\t日均收益率：\t-0.1%\n",
      "2017-08-23 22:46:33.908000\t收益标准差：\t0.98%\n",
      "2017-08-23 22:46:33.908000\tSharpe Ratio：\t-1.66\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAn8AAAOlCAYAAAAcnIEGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nNWoUly9fBiAxMZFBgwY
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd28bc90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 显示逐日回测结果\n",
    "df = engine.showDailyResult()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2017-08-23 22:46:39.856000\t计算回测结果\n",
      "2017-08-23 22:46:39.863000\t------------------------------\n",
      "2017-08-23 22:46:39.863000\t第一笔交易：\t2012-01-11 10:18:00\n",
      "2017-08-23 22:46:39.863000\t最后一笔交易：\t2012-06-29 11:30:00\n",
      "2017-08-23 22:46:39.863000\t总交易次数：\t217.0\n",
      "2017-08-23 22:46:39.863000\t总盈亏：\t-120,716.82\n",
      "2017-08-23 22:46:39.863000\t最大回撤: \t-135,300.01\n",
      "2017-08-23 22:46:39.863000\t平均每笔盈利：\t-556.3\n",
      "2017-08-23 22:46:39.863000\t平均每笔滑点：\t120.0\n",
      "2017-08-23 22:46:39.863000\t平均每笔佣金：\t45.88\n",
      "2017-08-23 22:46:39.863000\t胜率\t\t33.18%\n",
      "2017-08-23 22:46:39.863000\t盈利交易平均值\t6,203.36\n",
      "2017-08-23 22:46:39.863000\t亏损交易平均值\t-3,912.82\n",
      "2017-08-23 22:46:39.863000\t盈亏比：\t1.59\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0xbf31950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 显示逐笔回测结果\n",
    "engine.showBacktestingResult()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'orderID': '1', 'direction': u'\\u591a', 'gatewayName': '', 'tradeID': '1', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '09:18:00', 'rawData': None, 'vtTradeID': '1', 'offset': u'\\u5f00\\u4ed3', 'vtOrderID': '1', 'dt': datetime.datetime(2012, 1, 11, 9, 18), 'price': 2464.4, 'vtSymbol': ''}\n",
      "{'orderID': '2', 'direction': u'\\u7a7a', 'gatewayName': '', 'tradeID': '2', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '10:18:00', 'rawData': None, 'vtTradeID': '2', 'offset': u'\\u5e73\\u4ed3', 'vtOrderID': '2', 'dt': datetime.datetime(2012, 1, 11, 10, 18), 'price': 2448.8, 'vtSymbol': ''}\n",
      "{'orderID': '3', 'direction': u'\\u7a7a', 'gatewayName': '', 'tradeID': '3', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '10:19:00', 'rawData': None, 'vtTradeID': '3', 'offset': u'\\u5f00\\u4ed3', 'vtOrderID': '3', 'dt': datetime.datetime(2012, 1, 11, 10, 19), 'price': 2448.4, 'vtSymbol': ''}\n",
      "{'orderID': '4', 'direction': u'\\u591a', 'gatewayName': '', 'tradeID': '4', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '14:21:00', 'rawData': None, 'vtTradeID': '4', 'offset': u'\\u5e73\\u4ed3', 'vtOrderID': '4', 'dt': datetime.datetime(2012, 1, 11, 14, 21), 'price': 2456.2000000000003, 'vtSymbol': ''}\n",
      "{'orderID': '5', 'direction': u'\\u591a', 'gatewayName': '', 'tradeID': '5', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '14:22:00', 'rawData': None, 'vtTradeID': '5', 'offset': u'\\u5f00\\u4ed3', 'vtOrderID': '5', 'dt': datetime.datetime(2012, 1, 11, 14, 22), 'price': 2455.6, 'vtSymbol': ''}\n",
      "{'orderID': '6', 'direction': u'\\u7a7a', 'gatewayName': '', 'tradeID': '6', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '14:57:00', 'rawData': None, 'vtTradeID': '6', 'offset': u'\\u5e73\\u4ed3', 'vtOrderID': '6', 'dt': datetime.datetime(2012, 1, 11, 14, 57), 'price': 2444.0, 'vtSymbol': ''}\n",
      "{'orderID': '7', 'direction': u'\\u7a7a', 'gatewayName': '', 'tradeID': '7', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '14:58:00', 'rawData': None, 'vtTradeID': '7', 'offset': u'\\u5f00\\u4ed3', 'vtOrderID': '7', 'dt': datetime.datetime(2012, 1, 11, 14, 58), 'price': 2445.8, 'vtSymbol': ''}\n",
      "{'orderID': '8', 'direction': u'\\u591a', 'gatewayName': '', 'tradeID': '8', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '09:51:00', 'rawData': None, 'vtTradeID': '8', 'offset': u'\\u5e73\\u4ed3', 'vtOrderID': '8', 'dt': datetime.datetime(2012, 1, 12, 9, 51), 'price': 2452.8, 'vtSymbol': ''}\n",
      "{'orderID': '9', 'direction': u'\\u591a', 'gatewayName': '', 'tradeID': '9', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '09:52:00', 'rawData': None, 'vtTradeID': '9', 'offset': u'\\u5f00\\u4ed3', 'vtOrderID': '9', 'dt': datetime.datetime(2012, 1, 12, 9, 52), 'price': 2452.0, 'vtSymbol': ''}\n",
      "{'orderID': '10', 'direction': u'\\u7a7a', 'gatewayName': '', 'tradeID': '10', 'exchange': '', 'symbol': '', 'volume': 1, 'tradeTime': '10:31:00', 'rawData': None, 'vtTradeID': '10', 'offset': u'\\u5e73\\u4ed3', 'vtOrderID': '10', 'dt': datetime.datetime(2012, 1, 12, 10, 31), 'price': 2455.2000000000003, 'vtSymbol': ''}\n"
     ]
    }
   ],
   "source": [
    "# 显示前10条成交记录\n",
    "for i in range(10):\n",
    "    print engine.tradeDict[str(i+1)].__dict__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 优化配置\n",
    "setting = OptimizationSetting()                 # 新建一个优化任务设置对象\n",
    "setting.setOptimizeTarget('capital')            # 设置优化排序的目标是策略净盈利\n",
    "setting.addParameter('atrLength', 12, 20, 2)    # 增加第一个优化参数atrLength，起始12，结束20，步进2\n",
    "setting.addParameter('atrMa', 20, 30, 5)        # 增加第二个优化参数atrMa，起始20，结束30，步进5\n",
    "setting.addParameter('rsiLength', 5)            # 增加一个固定数值的参数\n",
    "\n",
    "# 执行多进程优化\n",
    "import time\n",
    "engine.runParallelOptimization(AtrRsiStrategy, setting)\n",
    "print u'耗时：%s' %(time.time()-start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 2",
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  "language_info": {
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   "file_extension": ".py",
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