{ "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\n", "#from vnpy.trader.app.ctaStrategy.strategy.strategyMultiTimeframe import MultiTimeframeStrategy\n", "from vnpy.trader.app.ctaStrategy.strategy.strategyMultiSignal import MultiSignalStrategy" ] }, { "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('20130101') # 设置回测用的数据起始日期" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "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": null, "metadata": { "collapsed": false }, "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\n", "#ngine.initStrategy(MultiTimeframeStrategy, d) \n", "#engine.initStrategy(MultiSignalStrategy, {}) " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# 运行回测\n", "engine.runBacktesting() # 运行回测" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "scrolled": 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'])" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2018-02-16 22:15:18.251000\t------------------------------\n", "2018-02-16 22:15:18.251000\tsetting: {'atrLength': 12}\n", "2018-02-16 22:15:18.256000\t开始载入数据\n", "2018-02-16 22:15:18.319000\t载入完成，数据量：91381\n", "2018-02-16 22:15:18.319000\t开始回测\n", "2018-02-16 22:15:18.361000\t策略初始化完成\n", "2018-02-16 22:15:18.361000\t策略启动完成\n", "2018-02-16 22:15:18.361000\t开始回放数据\n", "2018-02-16 22:15:25.992000\t数据回放结束\n", "2018-02-16 22:15:25.992000\t计算按日统计结果\n", "2018-02-16 22:15:26.085000\t------------------------------\n", "2018-02-16 22:15:26.085000\tsetting: {'atrLength': 14}\n", "2018-02-16 22:15:26.087000\t开始载入数据\n", "2018-02-16 22:15:26.142000\t载入完成，数据量：91381\n", "2018-02-16 22:15:26.142000\t开始回测\n", "2018-02-16 22:15:26.183000\t策略初始化完成\n", "2018-02-16 22:15:26.183000\t策略启动完成\n", "2018-02-16 22:15:26.183000\t开始回放数据\n", "2018-02-16 22:15:34.799000\t数据回放结束\n", "2018-02-16 22:15:34.799000\t计算按日统计结果\n", "2018-02-16 22:15:34.881000\t------------------------------\n", "2018-02-16 22:15:34.881000\tsetting: {'atrLength': 16}\n", "2018-02-16 22:15:34.883000\t开始载入数据\n", "2018-02-16 22:15:34.935000\t载入完成，数据量：91381\n", "2018-02-16 22:15:34.935000\t开始回测\n", "2018-02-16 22:15:34.981000\t策略初始化完成\n", "2018-02-16 22:15:34.981000\t策略启动完成\n", "2018-02-16 22:15:34.981000\t开始回放数据\n", "2018-02-16 22:15:43.120000\t数据回放结束\n", "2018-02-16 22:15:43.120000\t计算按日统计结果\n", "2018-02-16 22:15:43.151000\t------------------------------\n", "2018-02-16 22:15:43.151000\t优化结果：\n", "2018-02-16 22:15:43.151000\t参数：[\"{'atrLength': 16}\"]，目标：819765.66\n", "2018-02-16 22:15:43.151000\t参数：[\"{'atrLength': 14}\"]，目标：534310.005\n", "2018-02-16 22:15:43.151000\t参数：[\"{'atrLength': 12}\"]，目标：278612.3988\n", "耗时：24.9000000954\n" ] } ], "source": [ "# 优化配置\n", "setting = OptimizationSetting() # 新建一个优化任务设置对象\n", "setting.setOptimizeTarget('totalNetPnl') # 设置优化排序的目标是策略净盈利\n", "setting.addParameter('atrLength', 12, 16, 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", "start = time.time()\n", "#resultList = engine.runParallelOptimization(AtrRsiStrategy, setting)\n", "resultList = engine.runOptimization(AtrRsiStrategy, setting)\n", "print u'耗时：%s' %(time.time()-start)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# 显示优化的所有统计数据\n", "for result in resultList:\n", " print '-' * 30\n", " print u'参数：%s，目标：%s' %(result[0], result[1])\n", " print u'统计数据：'\n", " for k, v in result[2].items():\n", " print u'%s：%s' %(k, v)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "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 }