diff --git a/vn.trader/ctaAlgo/ctaBacktesting.py b/vn.trader/ctaAlgo/ctaBacktesting.py index b21ef1cf..44a35bee 100644 --- a/vn.trader/ctaAlgo/ctaBacktesting.py +++ b/vn.trader/ctaAlgo/ctaBacktesting.py @@ -22,6 +22,7 @@ from vtConstant import * from vtGateway import VtOrderData, VtTradeData from vtFunction import loadMongoSetting import logging +import copy ######################################################################## class BacktestingEngine(object): @@ -86,6 +87,8 @@ class BacktestingEngine(object): self.bar = None self.dt = None # 最新的时间 self.gatewayName = u'BackTest' + + self.usageCompounding = False # 是否使用简单复利 #---------------------------------------------------------------------- def setStartDate(self, startDate='20100416', initDays=10): @@ -903,6 +906,12 @@ class BacktestingEngine(object): def calculateBacktestingResult(self): """ 计算回测结果 + Modified by Incense Lee + 增加了支持逐步加仓的计算： + 例如，前面共有6次开仓（1手开仓+5次加仓，每次1手），平仓只有1次（六手）。那么，交易次数是6次（开仓+平仓）。 + 暂不支持每次加仓数目不一致的核对（因为比较复杂） + + 增加组合的支持。 """ self.output(u'计算回测结果') @@ -911,7 +920,9 @@ class BacktestingEngine(object): longTrade = [] # 未平仓的多头交易 shortTrade = [] # 未平仓的空头交易 - i = 0 + i = 1 + + tradeUnit = 1 longid = EMPTY_STRING shortid = EMPTY_STRING @@ -920,9 +931,6 @@ class BacktestingEngine(object): trade = self.tradeDict[tradeid] - if tradeid == '127': - pass - # 多头交易 if trade.direction == DIRECTION_LONG: # 如果尚无空头交易 @@ -931,18 +939,46 @@ class BacktestingEngine(object): longid = tradeid # 当前多头交易为平空 else: - entryTrade = shortTrade.pop(0) + gId = i # 交易组（多个平仓数为一组） + gt = 1 # 组合的交易次数 + gr = None # 组合的交易结果 - result = TradingResult(entryTrade.price, trade.price, -trade.volume, - self.rate, self.slippage, self.size) + if trade.volume >tradeUnit: + self.writeCtaLog(u'平仓数{0},组合编号:{1}'.format(trade.volume,gId)) + gt = int(trade.volume/tradeUnit) - resultDict[trade.dt] = result + for tv in range(gt): - i = i+1 - self.writeCtaLog(u'{6}.{7}.开空{0},short:{1},{8}.平空{2},cover:{3},vol:{4},净盈亏:{5}' - .format(entryTrade.tradeTime, entryTrade.price, - trade.tradeTime,trade.price, trade.volume,result.pnl, - i,shortid,tradeid)) + entryTrade = shortTrade.pop(0) + result = TradingResult(entryTrade.price, trade.price, -tradeUnit, + self.rate, self.slippage, self.size, groupId=gId) + + if tv == 0: + if gt==1: + resultDict[entryTrade.dt] = result + else: + gr = copy.deepcopy(result) + else: + gr.turnover = gr.turnover + result.turnover + gr.commission = gr.commission + result.commission + gr.slippage = gr.slippage + result.slippage + gr.pnl = gr.pnl + result.pnl + + if tv == gt -1: + gr.volume = trade.volume + resultDict[entryTrade.dt] = gr + + + self.writeCtaLog(u'{9}@{6} [{7}:开空{0},short:{1}]-[{8}:平空{2},cover:{3},vol:{4}],净盈亏:{5}' + .format(entryTrade.tradeTime, entryTrade.price, + trade.tradeTime, trade.price, tradeUnit, result.pnl, + i, shortid, tradeid,gId)) + i = i+1 + + if type(gr) != type(None): + self.writeCtaLog(u'组合净盈亏:{0}'.format(gr.pnl)) + + self.writeCtaLog(u'-------------') # 空头交易 else: @@ -952,17 +988,47 @@ class BacktestingEngine(object): shortid = tradeid # 当前空头交易为平多 else: - entryTrade = longTrade.pop(0) + gId = i # 交易组（多个平仓数为一组） + gt = 1 # 组合的交易次数 + gr = None # 组合的交易结果 - result = TradingResult(entryTrade.price, trade.price, trade.volume, - self.rate, self.slippage, self.size) - resultDict[trade.dt] = result + if trade.volume >tradeUnit: + self.writeCtaLog(u'平仓数{0},组合编号:{1}'.format(trade.volume,gId)) + gt = int(trade.volume/tradeUnit) - i = i+1 - self.writeCtaLog(u'{6}.{7}开多{0},buy:{1},{8}.平多{2},sell:{3},vol:{4},净盈亏：{5}' - .format(entryTrade.tradeTime, entryTrade.price, - trade.tradeTime,trade.price, trade.volume,result.pnl, - i,longid,tradeid)) + for tv in range(gt): + + entryTrade = longTrade.pop(0) + + result = TradingResult(entryTrade.price, trade.price, tradeUnit, + self.rate, self.slippage, self.size, groupId= gId) + + if tv == 0: + if gt==1: + resultDict[entryTrade.dt] = result + else: + gr = copy.deepcopy(result) + else: + gr.turnover = gr.turnover + result.turnover + gr.commission = gr.commission + result.commission + gr.slippage = gr.slippage + result.slippage + gr.pnl = gr.pnl + result.pnl + + if tv == gt -1: + gr.volume = trade.volume + resultDict[entryTrade.dt] = gr + + + self.writeCtaLog(u'{9}@{6} [{7}:开多{0},buy:{1}]-[{8}.平多{2},sell:{3},vol:{4}],净盈亏：{5}' + .format(entryTrade.tradeTime, entryTrade.price, + trade.tradeTime,trade.price, tradeUnit, result.pnl, + i, longid, tradeid, gId)) + i = i+1 + + if type(gr) != type(None): + self.writeCtaLog(u'组合净盈亏:{0}'.format(gr.pnl)) + + self.writeCtaLog(u'-------------') # 检查是否有交易 if not resultDict: @@ -970,9 +1036,15 @@ class BacktestingEngine(object): 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 - capital = 0 # 资金 - maxCapital = 0 # 资金最高净值 + initCapital = 40000 # 期初资金 + capital = initCapital # 资金 + maxCapital = initCapital # 资金最高净值 drawdown = 0 # 回撤 + maxPnl = 0 # 最高盈利 + minPnl = 0 # 最大亏损 + maxVolume = 1 # 最大仓位数 + compounding = 1 # 简单的复利基数（如果资金是期初资金的x倍，就扩大开仓比例,例如3w开1手，6w开2手，12w开4手) + wins = 0 totalResult = 0 # 总成交数量 totalTurnover = 0 # 总成交金额（合约面值） @@ -983,27 +1055,42 @@ class BacktestingEngine(object): pnlList = [] # 每笔盈亏序列 capitalList = [] # 盈亏汇总的时间序列 drawdownList = [] # 回撤的时间序列 + drawdownRateList = [] # 最大回撤比例的时间序列 for time, result in resultDict.items(): - capital += result.pnl + + # 是否使用简单复利 + if self.usageCompounding: + compounding = int(capital/initCapital) + + if result.pnl > 0: + wins += 1 + capital += result.pnl*compounding maxCapital = max(capital, maxCapital) + maxVolume = max(maxVolume, result.volume*compounding) drawdown = capital - maxCapital + drawdownRate = round(float(drawdown*100/maxCapital),4) - pnlList.append(result.pnl) + pnlList.append(result.pnl*compounding) timeList.append(time) capitalList.append(capital) drawdownList.append(drawdown) + drawdownRateList.append(drawdownRate) totalResult += 1 - totalTurnover += result.turnover - totalCommission += result.commission - totalSlippage += result.slippage + totalTurnover += result.turnover*compounding + totalCommission += result.commission*compounding + totalSlippage += result.slippage*compounding # 返回回测结果 d = {} - d['capital'] = capital + d['initCapital'] = initCapital + d['capital'] = capital - initCapital d['maxCapital'] = maxCapital d['drawdown'] = drawdown + d['maxPnl'] = max(pnlList) + d['minPnl'] = min(pnlList) + d['maxVolume'] = maxVolume d['totalResult'] = totalResult d['totalTurnover'] = totalTurnover d['totalCommission'] = totalCommission @@ -1012,6 +1099,8 @@ class BacktestingEngine(object): d['pnlList'] = pnlList d['capitalList'] = capitalList d['drawdownList'] = drawdownList + d['drawdownRateList'] = drawdownRateList + d['winRate'] = round(100*wins/len(pnlList),4) return d #---------------------------------------------------------------------- @@ -1028,8 +1117,17 @@ class BacktestingEngine(object): 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'期初资金：\t%s' % formatNumber(d['initCapital'])) 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'资金最高净值：\t%s' % formatNumber(d['maxCapital'])) + + self.output(u'每笔最大盈利：\t%s' % formatNumber(d['maxPnl'])) + self.output(u'每笔最大亏损：\t%s' % formatNumber(d['minPnl'])) + self.output(u'净值最大回撤: \t%s' % formatNumber(min(d['drawdownList']))) + self.output(u'净值最大回撤率: \t%s' % formatNumber(min(d['drawdownRateList']))) + self.output(u'胜率：\t%s' % formatNumber(d['winRate'])) + + self.output(u'最大持仓：\t%s' % formatNumber(d['maxVolume'])) self.output(u'平均每笔盈利：\t%s' %formatNumber(d['capital']/d['totalResult'])) self.output(u'平均每笔滑点成本：\t%s' %formatNumber(d['totalSlippage']/d['totalResult'])) @@ -1128,11 +1226,12 @@ class TradingResult(object): """每笔交易的结果""" #---------------------------------------------------------------------- - def __init__(self, entry, exit, volume, rate, slippage, size): + def __init__(self, entry, exit, volume, rate, slippage, size, groupId): """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.groupId = groupId # 主交易ID（针对多手平仓） self.turnover = (self.entry+self.exit)*size # 成交金额 self.commission =round(float(self.turnover*rate),4) # 手续费成本