diff --git a/vn.trader/ctaAlgo/ctaBacktesting.py b/vn.trader/ctaAlgo/ctaBacktesting.py index 35220f1b..aa880f70 100644 --- a/vn.trader/ctaAlgo/ctaBacktesting.py +++ b/vn.trader/ctaAlgo/ctaBacktesting.py @@ -7,15 +7,21 @@ from datetime import datetime, timedelta from collections import OrderedDict +from itertools import product import pymongo +import MySQLdb +import json +import os +import cPickle + from ctaBase import * from ctaSetting import * from vtConstant import * from vtGateway import VtOrderData, VtTradeData from vtFunction import loadMongoSetting - +import logging ######################################################################## class BacktestingEngine(object): @@ -23,6 +29,10 @@ class BacktestingEngine(object): CTA回测引擎 函数接口和策略引擎保持一样， 从而实现同一套代码从回测到实盘。 + # modified by IncenseLee： + 1.增加Mysql数据库的支持； + 2.修改装载数据为批量式后加载模式。 + """ TICK_MODE = 'tick' @@ -51,10 +61,13 @@ class BacktestingEngine(object): self.dbClient = None # 数据库客户端 self.dbCursor = None # 数据库指针 - #self.historyData = [] # 历史数据的列表，回测用 + self.historyData = [] # 历史数据的列表，回测用 self.initData = [] # 初始化用的数据 - #self.backtestingData = [] # 回测用的数据 + self.backtestingData = [] # 回测用的数据 + self.dbName = '' # 回测数据库名 + self.symbol = '' # 回测集合名 + self.dataStartDate = None # 回测数据开始日期，datetime对象 self.dataEndDate = None # 回测数据结束日期，datetime对象 self.strategyStartDate = None # 策略启动日期（即前面的数据用于初始化），datetime对象 @@ -72,33 +85,49 @@ class BacktestingEngine(object): self.tick = None self.bar = None self.dt = None # 最新的时间 + self.gatewayName = u'BackTest' #---------------------------------------------------------------------- def setStartDate(self, startDate='20100416', initDays=10): """设置回测的启动日期""" self.dataStartDate = datetime.strptime(startDate, '%Y%m%d') - + + # 初始化天数 initTimeDelta = timedelta(initDays) + self.strategyStartDate = self.dataStartDate + initTimeDelta #---------------------------------------------------------------------- def setEndDate(self, endDate=''): """设置回测的结束日期""" if endDate: - self.dataEndDate= datetime.strptime(endDate, '%Y%m%d') - + self.dataEndDate = datetime.strptime(endDate, '%Y%m%d') + + else: + self.dataEndDate = datetime.now() + + def setMinDiff(self, minDiff): + """设置回测品种的最小跳价，用于修正数据""" + self.minDiff = minDiff + #---------------------------------------------------------------------- def setBacktestingMode(self, mode): """设置回测模式""" self.mode = mode - + #---------------------------------------------------------------------- - def loadHistoryData(self, dbName, symbol): + def setDatabase(self, dbName, symbol): + """设置历史数据所用的数据库""" + self.dbName = dbName + self.symbol = symbol + + #---------------------------------------------------------------------- + def loadHistoryDataFromMongo(self): """载入历史数据""" host, port = loadMongoSetting() self.dbClient = pymongo.MongoClient(host, port) - collection = self.dbClient[dbName][symbol] + collection = self.dbClient[self.dbName][self.symbol] self.output(u'开始载入数据') @@ -130,10 +159,370 @@ class BacktestingEngine(object): self.dbCursor = collection.find(flt) self.output(u'载入完成，数据量：%s' %(initCursor.count() + self.dbCursor.count())) - + + #---------------------------------------------------------------------- + def connectMysql(self): + """连接MysqlDB""" + + # 载入json文件 + fileName = 'mysql_connect.json' + try: + f = file(fileName) + except IOError: + self.writeCtaLog(u'回测引擎读取Mysql_connect.json失败') + return + + # 解析json文件 + setting = json.load(f) + try: + mysql_host = str(setting['host']) + mysql_port = int(setting['port']) + mysql_user = str(setting['user']) + mysql_passwd = str(setting['passwd']) + mysql_db = str(setting['db']) + + + except IOError: + self.writeCtaLog(u'回测引擎读取Mysql_connect.json,连接配置缺少字段，请检查') + return + + try: + self.__mysqlConnection = MySQLdb.connect(host=mysql_host, user=mysql_user, + passwd=mysql_passwd, db=mysql_db, port=mysql_port) + self.__mysqlConnected = True + self.writeCtaLog(u'回测引擎连接MysqlDB成功') + except ConnectionFailure: + self.writeCtaLog(u'回测引擎连接MysqlDB失败') + + #---------------------------------------------------------------------- + def loadDataHistoryFromMysql(self, symbol, startDate, endDate): + """载入历史TICK数据 + 如果加载过多数据会导致加载失败,间隔不要超过半年 + """ + + if not endDate: + endDate = datetime.today() + + # 看本地缓存是否存在 + if self.__loadDataHistoryFromLocalCache(symbol, startDate, endDate): + self.writeCtaLog(u'历史TICK数据从Cache载入') + return + + # 每次获取日期周期 + intervalDays = 10 + + for i in range (0,(endDate - startDate).days +1, intervalDays): + d1 = startDate + timedelta(days = i ) + + if (endDate - d1).days > 10: + d2 = startDate + timedelta(days = i + intervalDays -1 ) + else: + d2 = endDate + + # 从Mysql 提取数据 + self.__qryDataHistoryFromMysql(symbol, d1, d2) + + self.writeCtaLog(u'历史TICK数据共载入{0}条'.format(len(self.historyData))) + + # 保存本地cache文件 + self.__saveDataHistoryToLocalCache(symbol, startDate, endDate) + + + def __loadDataHistoryFromLocalCache(self, symbol, startDate, endDate): + """看本地缓存是否存在 + added by IncenseLee + """ + + # 运行路径下cache子目录 + cacheFolder = os.getcwd()+'/cache' + + # cache文件 + cacheFile = u'{0}/{1}_{2}_{3}.pickle'.\ + format(cacheFolder, symbol, startDate.strftime('%Y-%m-%d'), endDate.strftime('%Y-%m-%d')) + + if not os.path.isfile(cacheFile): + return False + + else: + # 从cache文件加载 + cache = open(cacheFile,mode='r') + self.historyData = cPickle.load(cache) + cache.close() + return True + + def __saveDataHistoryToLocalCache(self, symbol, startDate, endDate): + """保存本地缓存 + added by IncenseLee + """ + + # 运行路径下cache子目录 + cacheFolder = os.getcwd()+'/cache' + + # 创建cache子目录 + if not os.path.isdir(cacheFolder): + os.mkdir(cacheFolder) + + # cache 文件名 + cacheFile = u'{0}/{1}_{2}_{3}.pickle'.\ + format(cacheFolder, symbol, startDate.strftime('%Y-%m-%d'), endDate.strftime('%Y-%m-%d')) + + # 重复存在 返回 + if os.path.isfile(cacheFile): + return False + + else: + # 写入cache文件 + cache = open(cacheFile, mode='w') + cPickle.dump(self.historyData,cache) + cache.close() + return True + + #---------------------------------------------------------------------- + def __qryDataHistoryFromMysql(self, symbol, startDate, endDate): + """从Mysql载入历史TICK数据 + added by IncenseLee + """ + + try: + self.connectMysql() + if self.__mysqlConnected: + + # 获取指针 + cur = self.__mysqlConnection.cursor(MySQLdb.cursors.DictCursor) + + if endDate: + + # 开始日期 ~ 结束日期 + sqlstring = ' select \'{0}\' as InstrumentID, str_to_date(concat(ndate,\' \', ntime),' \ + '\'%Y-%m-%d %H:%i:%s\') as UpdateTime,price as LastPrice,vol as Volume,' \ + 'position_vol as OpenInterest,bid1_price as BidPrice1,bid1_vol as BidVolume1, ' \ + 'sell1_price as AskPrice1, sell1_vol as AskVolume1 from TB_{0}MI ' \ + 'where ndate between cast(\'{1}\' as date) and cast(\'{2}\' as date) order by UpdateTime'.\ + format(symbol, startDate, endDate) + + elif startDate: + + # 开始日期 - 当前 + sqlstring = ' select \'{0}\' as InstrumentID,str_to_date(concat(ndate,\' \', ntime),' \ + '\'%Y-%m-%d %H:%i:%s\') as UpdateTime,price as LastPrice,vol as Volume,' \ + 'position_vol as OpenInterest,bid1_price as BidPrice1,bid1_vol as BidVolume1, ' \ + 'sell1_price as AskPrice1, sell1_vol as AskVolume1 from TB__{0}MI ' \ + 'where ndate > cast(\'{1}\' as date) order by UpdateTime'.\ + format( symbol, startDate) + + else: + + # 所有数据 + sqlstring =' select \'{0}\' as InstrumentID,str_to_date(concat(ndate,\' \', ntime),' \ + '\'%Y-%m-%d %H:%i:%s\') as UpdateTime,price as LastPrice,vol as Volume,' \ + 'position_vol as OpenInterest,bid1_price as BidPrice1,bid1_vol as BidVolume1, ' \ + 'sell1_price as AskPrice1, sell1_vol as AskVolume1 from TB__{0}MI order by UpdateTime'.\ + format(symbol) + + self.writeCtaLog(sqlstring) + + # 执行查询 + count = cur.execute(sqlstring) + self.writeCtaLog(u'历史TICK数据共{0}条'.format(count)) + + + # 分批次读取 + fetch_counts = 0 + fetch_size = 1000 + + while True: + results = cur.fetchmany(fetch_size) + + if not results: + break + + fetch_counts = fetch_counts + len(results) + + if not self.historyData: + self.historyData =results + + else: + self.historyData = self.historyData + results + + self.writeCtaLog(u'{1}~{2}历史TICK数据载入共{0}条'.format(fetch_counts,startDate,endDate)) + + + else: + self.writeCtaLog(u'MysqlDB未连接，请检查') + + except MySQLdb.Error, e: + + self.writeCtaLog(u'MysqlDB载入数据失败，请检查.Error {0}'.format(e)) + + def __dataToTick(self, data): + """ + 数据库查询返回的data结构，转换为tick对象 + added by IncenseLee + """ + tick = CtaTickData() + symbol = data['InstrumentID'] + tick.symbol = symbol + + # 创建TICK数据对象并更新数据 + tick.vtSymbol = symbol + # tick.openPrice = data['OpenPrice'] + # tick.highPrice = data['HighestPrice'] + # tick.lowPrice = data['LowestPrice'] + tick.lastPrice = float(data['LastPrice']) + + tick.volume = data['Volume'] + tick.openInterest = data['OpenInterest'] + + # tick.upperLimit = data['UpperLimitPrice'] + # tick.lowerLimit = data['LowerLimitPrice'] + + tick.datetime = data['UpdateTime'] + tick.date = tick.datetime.strftime('%Y-%m-%d') + tick.time = tick.datetime.strftime('%H:%M:%S') + + tick.bidPrice1 = float(data['BidPrice1']) + # tick.bidPrice2 = data['BidPrice2'] + # tick.bidPrice3 = data['BidPrice3'] + # tick.bidPrice4 = data['BidPrice4'] + # tick.bidPrice5 = data['BidPrice5'] + + tick.askPrice1 = float(data['AskPrice1']) + # tick.askPrice2 = data['AskPrice2'] + # tick.askPrice3 = data['AskPrice3'] + # tick.askPrice4 = data['AskPrice4'] + # tick.askPrice5 = data['AskPrice5'] + + tick.bidVolume1 = data['BidVolume1'] + # tick.bidVolume2 = data['BidVolume2'] + # tick.bidVolume3 = data['BidVolume3'] + # tick.bidVolume4 = data['BidVolume4'] + # tick.bidVolume5 = data['BidVolume5'] + + tick.askVolume1 = data['AskVolume1'] + # tick.askVolume2 = data['AskVolume2'] + # tick.askVolume3 = data['AskVolume3'] + # tick.askVolume4 = data['AskVolume4'] + # tick.askVolume5 = data['AskVolume5'] + + return tick + + #---------------------------------------------------------------------- + def getMysqlDeltaDate(self,symbol, startDate, decreaseDays): + """从mysql库中获取交易日前若干天 + added by IncenseLee + """ + try: + if self.__mysqlConnected: + + # 获取mysql指针 + cur = self.__mysqlConnection.cursor() + + sqlstring='select distinct ndate from TB_{0}MI where ndate < ' \ + 'cast(\'{1}\' as date) order by ndate desc limit {2},1'.format(symbol, startDate, decreaseDays-1) + + # self.writeCtaLog(sqlstring) + + count = cur.execute(sqlstring) + + if count > 0: + + # 提取第一条记录 + result = cur.fetchone() + + return result[0] + + else: + self.writeCtaLog(u'MysqlDB没有查询结果，请检查日期') + + else: + self.writeCtaLog(u'MysqlDB未连接，请检查') + + except MySQLdb.Error, e: + + self.writeCtaLog(u'MysqlDB载入数据失败，请检查.Error {0}: {1}'.format(e.arg[0],e.arg[1])) + + # 出错后缺省返回 + return startDate-timedelta(days=3) + + #---------------------------------------------------------------------- + def runBacktestingWithMysql(self): + """运行回测(使用Mysql数据） + added by IncenseLee + """ + + if not self.dataStartDate: + self.writeCtaLog(u'回测开始日期未设置。') + return + + if not self.dataEndDate: + self.dataEndDate = datetime.today() + + if len(self.symbol)<1: + self.writeCtaLog(u'回测对象未设置。') + return + + + # 首先根据回测模式，确认要使用的数据类 + if self.mode == self.BAR_MODE: + dataClass = CtaBarData + func = self.newBar + else: + dataClass = CtaTickData + func = self.newTick + + self.output(u'开始回测') + + #self.strategy.inited = True + self.strategy.onInit() + self.output(u'策略初始化完成') + + self.strategy.trading = True + self.strategy.onStart() + self.output(u'策略启动完成') + + self.output(u'开始回放数据') + + + # 每次获取日期周期 + intervalDays = 10 + + for i in range (0,(self.dataEndDate - self.dataStartDate).days +1, intervalDays): + d1 = self.dataStartDate + timedelta(days = i ) + + if (self.dataEndDate - d1).days > intervalDays: + d2 = self.dataStartDate + timedelta(days = i + intervalDays -1 ) + else: + d2 = self.dataEndDate + + # 提取历史数据 + self.loadDataHistoryFromMysql(self.symbol, d1, d2) + + self.output(u'数据日期:{0} => {1}'.format(d1,d2)) + # 将逐笔数据推送 + for data in self.historyData: + + # 记录最新的TICK数据 + self.tick = self.__dataToTick(data) + self.dt = self.tick.datetime + + # 处理限价单 + self.crossLimitOrder() + self.crossStopOrder() + + # 推送到策略引擎中 + self.strategy.onTick(self.tick) + + # 清空历史数据 + self.historyData = [] + + self.output(u'数据回放结束') + #---------------------------------------------------------------------- def runBacktesting(self): """运行回测""" + # 载入历史数据 + self.loadHistoryData() + # 首先根据回测模式，确认要使用的数据类 if self.mode == self.BAR_MODE: dataClass = CtaBarData @@ -160,7 +549,7 @@ class BacktestingEngine(object): func(data) self.output(u'数据回放结束') - + #---------------------------------------------------------------------- def newBar(self, bar): """新的K线""" @@ -191,6 +580,8 @@ class BacktestingEngine(object): #---------------------------------------------------------------------- def sendOrder(self, vtSymbol, orderType, price, volume, strategy): """发单""" + + self.writeCtaLog(u'{0},{1},{2}@{3}'.format(vtSymbol,orderType,price,volume)) self.limitOrderCount += 1 orderID = str(self.limitOrderCount) @@ -202,6 +593,9 @@ class BacktestingEngine(object): order.orderID = orderID order.vtOrderID = orderID order.orderTime = str(self.dt) + + # added by IncenseLee + order.gatewayName = self.gatewayName # CTA委托类型映射 if orderType == CTAORDER_BUY: @@ -220,8 +614,9 @@ class BacktestingEngine(object): # 保存到限价单字典中 self.workingLimitOrderDict[orderID] = order self.limitOrderDict[orderID] = order - - return orderID + + # modified by IncenseLee + return u'{0}.{1}'.format(order.gatewayName, orderID) #---------------------------------------------------------------------- def cancelOrder(self, vtOrderID): @@ -279,13 +674,15 @@ class BacktestingEngine(object): """基于最新数据撮合限价单""" # 先确定会撮合成交的价格 if self.mode == self.BAR_MODE: - buyCrossPrice = self.bar.low # 若买入方向限价单价格高于该价格，则会成交 - sellCrossPrice = self.bar.high # 若卖出方向限价单价格低于该价格，则会成交 - bestCrossPrice = self.bar.open # 在当前时间点前发出的委托可能的最优成交价 + buyCrossPrice = self.bar.low # 若买入方向限价单价格高于该价格，则会成交 + sellCrossPrice = self.bar.high # 若卖出方向限价单价格低于该价格，则会成交 + buyBestCrossPrice = self.bar.open # 在当前时间点前发出的买入委托可能的最优成交价 + sellBestCrossPrice = self.bar.open # 在当前时间点前发出的卖出委托可能的最优成交价 else: - buyCrossPrice = self.tick.lastPrice - sellCrossPrice = self.tick.lastPrice - bestCrossPrice = self.tick.lastPrice + buyCrossPrice = self.tick.askPrice1 + sellCrossPrice = self.tick.bidPrice1 + buyBestCrossPrice = self.tick.askPrice1 + sellBestCrossPrice = self.tick.bidPrice1 # 遍历限价单字典中的所有限价单 for orderID, order in self.workingLimitOrderDict.items(): @@ -312,10 +709,10 @@ class BacktestingEngine(object): # 2. 假设在上一根K线结束(也是当前K线开始)的时刻，策略发出的委托为限价105 # 3. 则在实际中的成交价会是100而不是105，因为委托发出时市场的最优价格是100 if buyCross: - trade.price = min(order.price, bestCrossPrice) + trade.price = min(order.price, buyBestCrossPrice) self.strategy.pos += order.totalVolume else: - trade.price = max(order.price, bestCrossPrice) + trade.price = max(order.price, sellBestCrossPrice) self.strategy.pos -= order.totalVolume trade.volume = order.totalVolume @@ -425,27 +822,27 @@ class BacktestingEngine(object): """记录日志""" log = str(self.dt) + ' ' + content self.logList.append(log) + + # 写入本地log日志 + logging.info(content) #---------------------------------------------------------------------- def output(self, content): """输出内容""" - print content - + print str(datetime.now()) + "\t" + content + #---------------------------------------------------------------------- - def showBacktestingResult(self): + def calculateBacktestingResult(self): """ - 显示回测结果 + 计算回测结果 """ - self.output(u'显示回测结果') + self.output(u'计算回测结果') # 首先基于回测后的成交记录，计算每笔交易的盈亏 - pnlDict = OrderedDict() # 每笔盈亏的记录 + resultDict = OrderedDict() # 交易结果记录 longTrade = [] # 未平仓的多头交易 shortTrade = [] # 未平仓的空头交易 - - # 计算滑点，一个来回包括两次 - totalSlippage = self.slippage * 2 - + for trade in self.tradeDict.values(): # 多头交易 if trade.direction == DIRECTION_LONG: @@ -455,12 +852,15 @@ class BacktestingEngine(object): # 当前多头交易为平空 else: entryTrade = shortTrade.pop(0) - # 计算比例佣金 - commission = (trade.price+entryTrade.price) * self.rate - # 计算盈亏 - pnl = ((trade.price - entryTrade.price)*(-1) - totalSlippage - commission) \ - * trade.volume * self.size - pnlDict[trade.dt] = pnl + + result = TradingResult(entryTrade.price, trade.price, -trade.volume, + self.rate, self.slippage, self.size) + + resultDict[trade.dt] = result + + self.output(u'{0},short:{1},{2},cover:{3},vol:{4},{5}' + .format(entryTrade.tradeTime, entryTrade.price,trade.tradeTime,trade.price, trade.volume,result.pnl)) + # 空头交易 else: # 如果尚无多头交易 @@ -469,58 +869,101 @@ class BacktestingEngine(object): # 当前空头交易为平多 else: entryTrade = longTrade.pop(0) - # 计算比例佣金 - commission = (trade.price+entryTrade.price) * self.rate - # 计算盈亏 - pnl = ((trade.price - entryTrade.price) - totalSlippage - commission) \ - * trade.volume * self.size - pnlDict[trade.dt] = pnl + + result = TradingResult(entryTrade.price, trade.price, trade.volume, + self.rate, self.slippage, self.size) + resultDict[trade.dt] = result + + self.output(u'{0},buy:{1},{2},sell:{3},vol:{4},{5}' + .format(entryTrade.tradeTime, entryTrade.price,trade.tradeTime,trade.price, trade.volume,result.pnl)) + + # 检查是否有交易 + if not resultDict: + self.output(u'无交易结果') + return {} # 然后基于每笔交易的结果，我们可以计算具体的盈亏曲线和最大回撤等 - timeList = pnlDict.keys() - pnlList = pnlDict.values() + capital = 0 # 资金 + maxCapital = 0 # 资金最高净值 + drawdown = 0 # 回撤 - capital = 0 - maxCapital = 0 - drawdown = 0 + totalResult = 0 # 总成交数量 + totalTurnover = 0 # 总成交金额（合约面值） + totalCommission = 0 # 总手续费 + totalSlippage = 0 # 总滑点 + timeList = [] # 时间序列 + pnlList = [] # 每笔盈亏序列 capitalList = [] # 盈亏汇总的时间序列 - maxCapitalList = [] # 最高盈利的时间序列 drawdownList = [] # 回撤的时间序列 - for pnl in pnlList: - capital += pnl + for time, result in resultDict.items(): + capital += result.pnl maxCapital = max(capital, maxCapital) drawdown = capital - maxCapital + pnlList.append(result.pnl) + timeList.append(time) capitalList.append(capital) - maxCapitalList.append(maxCapital) drawdownList.append(drawdown) + totalResult += 1 + totalTurnover += result.turnover + totalCommission += result.commission + totalSlippage += result.slippage + + # 返回回测结果 + d = {} + d['capital'] = capital + d['maxCapital'] = maxCapital + d['drawdown'] = drawdown + d['totalResult'] = totalResult + d['totalTurnover'] = totalTurnover + d['totalCommission'] = totalCommission + d['totalSlippage'] = totalSlippage + d['timeList'] = timeList + d['pnlList'] = pnlList + d['capitalList'] = capitalList + d['drawdownList'] = drawdownList + return d + + #---------------------------------------------------------------------- + def showBacktestingResult(self): + """显示回测结果""" + d = self.calculateBacktestingResult() + + if len(d)== 0: + self.output(u'无交易结果') + return # 输出 - self.output('-' * 50) - self.output(u'第一笔交易时间：%s' % timeList[0]) - self.output(u'最后一笔交易时间：%s' % timeList[-1]) - self.output(u'总交易次数：%s' % len(pnlList)) - self.output(u'总盈亏：%s' % capitalList[-1]) - self.output(u'最大回撤: %s' % min(drawdownList)) + self.output('-' * 30) + self.output(u'第一笔交易：\t%s' % d['timeList'][0]) + self.output(u'最后一笔交易：\t%s' % d['timeList'][-1]) + + self.output(u'总交易次数：\t%s' % formatNumber(d['totalResult'])) + self.output(u'总盈亏：\t%s' % formatNumber(d['capital'])) + self.output(u'最大回撤: \t%s' % formatNumber(min(d['drawdownList']))) + + self.output(u'平均每笔盈利：\t%s' %formatNumber(d['capital']/d['totalResult'])) + self.output(u'平均每笔滑点：\t%s' %formatNumber(d['totalSlippage']/d['totalResult'])) + self.output(u'平均每笔佣金：\t%s' %formatNumber(d['totalCommission']/d['totalResult'])) # 绘图 - import matplotlib.pyplot as plt + #import matplotlib.pyplot as plt - pCapital = plt.subplot(3, 1, 1) - pCapital.set_ylabel("capital") - pCapital.plot(capitalList) + #pCapital = plt.subplot(3, 1, 1) + #pCapital.set_ylabel("capital") + #pCapital.plot(d['capitalList']) - pDD = plt.subplot(3, 1, 2) - pDD.set_ylabel("DD") - pDD.bar(range(len(drawdownList)), drawdownList) + #pDD = plt.subplot(3, 1, 2) + #pDD.set_ylabel("DD") + #pDD.bar(range(len(d['drawdownList'])), d['drawdownList']) - pPnl = plt.subplot(3, 1, 3) - pPnl.set_ylabel("pnl") - pPnl.hist(pnlList, bins=20) + #pPnl = plt.subplot(3, 1, 3) + #pPnl.set_ylabel("pnl") + #pPnl.hist(d['pnlList'], bins=50) - plt.show() + #plt.show() #---------------------------------------------------------------------- def putStrategyEvent(self, name): @@ -529,7 +972,7 @@ class BacktestingEngine(object): #---------------------------------------------------------------------- def setSlippage(self, slippage): - """设置滑点""" + """设置滑点点数""" self.slippage = slippage #---------------------------------------------------------------------- @@ -542,6 +985,136 @@ class BacktestingEngine(object): """设置佣金比例""" self.rate = rate + #---------------------------------------------------------------------- + def runOptimization(self, strategyClass, optimizationSetting): + """优化参数""" + # 获取优化设置 + settingList = optimizationSetting.generateSetting() + targetName = optimizationSetting.optimizeTarget + + # 检查参数设置问题 + if not settingList or not targetName: + self.output(u'优化设置有问题，请检查') + + # 遍历优化 + resultList = [] + for setting in settingList: + self.clearBacktestingResult() + self.output('-' * 30) + self.output('setting: %s' %str(setting)) + self.initStrategy(strategyClass, setting) + self.runBacktesting() + d = self.calculateBacktestingResult() + try: + targetValue = d[targetName] + except KeyError: + targetValue = 0 + resultList.append(([str(setting)], targetValue)) + + # 显示结果 + resultList.sort(reverse=True, key=lambda result:result[1]) + self.output('-' * 30) + self.output(u'优化结果：') + for result in resultList: + self.output(u'%s: %s' %(result[0], result[1])) + + #---------------------------------------------------------------------- + def clearBacktestingResult(self): + """清空之前回测的结果""" + # 清空限价单相关 + self.limitOrderCount = 0 + self.limitOrderDict.clear() + self.workingLimitOrderDict.clear() + + # 清空停止单相关 + self.stopOrderCount = 0 + self.stopOrderDict.clear() + self.workingStopOrderDict.clear() + + # 清空成交相关 + self.tradeCount = 0 + self.tradeDict.clear() + + +######################################################################## +class TradingResult(object): + """每笔交易的结果""" + + #---------------------------------------------------------------------- + def __init__(self, entry, exit, volume, rate, slippage, size): + """Constructor""" + self.entry = entry # 开仓价格 + self.exit = exit # 平仓价格 + self.volume = volume # 交易数量（+/-代表方向） + + self.turnover = (self.entry+self.exit)*size # 成交金额 + self.commission = self.turnover*rate # 手续费成本 + self.slippage = slippage*2*size # 滑点成本 + self.pnl = ((self.exit - self.entry) * volume * size + - self.commission - self.slippage) # 净盈亏 + + +######################################################################## +class OptimizationSetting(object): + """优化设置""" + + #---------------------------------------------------------------------- + def __init__(self): + """Constructor""" + self.paramDict = OrderedDict() + + self.optimizeTarget = '' # 优化目标字段 + + #---------------------------------------------------------------------- + def addParameter(self, name, start, end, step): + """增加优化参数""" + if end <= start: + print u'参数起始点必须小于终止点' + return + + if step <= 0: + print u'参数布进必须大于0' + return + + l = [] + param = start + + while param <= end: + l.append(param) + param += step + + self.paramDict[name] = l + + #---------------------------------------------------------------------- + def generateSetting(self): + """生成优化参数组合""" + # 参数名的列表 + nameList = self.paramDict.keys() + paramList = self.paramDict.values() + + # 使用迭代工具生产参数对组合 + productList = list(product(*paramList)) + + # 把参数对组合打包到一个个字典组成的列表中 + settingList = [] + for p in productList: + d = dict(zip(nameList, p)) + settingList.append(d) + + return settingList + + #---------------------------------------------------------------------- + def setOptimizeTarget(self, target): + """设置优化目标字段""" + self.optimizeTarget = target + + +#---------------------------------------------------------------------- +def formatNumber(n): + """格式化数字到字符串""" + n = round(n, 2) # 保留两位小数 + return format(n, ',') # 加上千分符 + if __name__ == '__main__': @@ -560,7 +1133,7 @@ if __name__ == '__main__': engine.setStartDate('20110101') # 载入历史数据到引擎中 - engine.loadHistoryData(MINUTE_DB_NAME, 'IF0000') + engine.setDatabase(MINUTE_DB_NAME, 'IF0000') # 设置产品相关参数 engine.setSlippage(0.2) # 股指1跳