{
 "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.strategyBollChannel import BollChannelStrategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "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, 'rb0000')  # 设置使用的历史数据库\n",
    "engine.setStartDate('20110101')               # 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(1)      # 设置滑点为1跳\n",
    "engine.setRate(1/10000)    # 设置手续费万1\n",
    "engine.setSize(10)         # 设置合约大小 \n",
    "engine.setPriceTick(1)     # 设置最小价格变动   \n",
    "engine.setCapital(30000)   # 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 = {}                                         # 策略参数配置\n",
    "engine.initStrategy(BollChannelStrategy, d)    # 创建策略对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-01-07 15:25:16.799000\t开始载入数据\n",
      "2018-01-07 15:25:16.805000\t载入完成，数据量：0\n",
      "2018-01-07 15:25:16.805000\t开始回测\n",
      "2018-01-07 15:25:16.805000\t策略初始化完成\n",
      "2018-01-07 15:25:16.805000\t策略启动完成\n",
      "2018-01-07 15:25:16.805000\t开始回放数据\n",
      "2018-01-07 15:25:16.806000\t数据回放结束\n"
     ]
    }
   ],
   "source": [
    "# 运行回测\n",
    "engine.runBacktesting()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 显示逐日回测结果\n",
    "engine.showDailyResult()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 显示逐笔回测结果\n",
    "engine.showBacktestingResult()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 显示前10条成交记录\n",
    "for i in range(10):\n",
    "    d = engine.tradeDict[str(i+1)].__dict__\n",
    "    print 'TradeID: %s, Time: %s, Direction: %s, Price: %s, Volume: %s' %(d['tradeID'], d['dt'], d['direction'], d['price'], d['volume'])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}