From 941908687b7adc709e9496e2729d51f462d4259f Mon Sep 17 00:00:00 2001 From: chenxy123 Date: Sat, 2 Apr 2016 12:33:41 +0800 Subject: [PATCH] =?UTF-8?q?=E6=94=B9=E8=BF=9B=E4=BA=86CTA=E5=BC=95?= =?UTF-8?q?=E6=93=8E=E6=A8=A1=E5=9D=97=EF=BC=8C=E5=A2=9E=E5=8A=A0=E4=BA=86?= =?UTF-8?q?=E5=90=88=E7=BA=A6=E5=A4=A7=E5=B0=8F=E3=80=81=E7=99=BE=E5=88=86?= =?UTF-8?q?=E6=AF=94=E6=89=8B=E7=BB=AD=E8=B4=B9=E7=9A=84=E6=94=AF=E6=8C=81?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- vn.trader/ctaAlgo/IF0000_1min.csv | 21095 ++++++++++++++++++++++++++ vn.trader/ctaAlgo/ctaBacktesting.py | 76 +- vn.trader/ctaAlgo/ctaDemo.py | 1 - 3 files changed, 21146 insertions(+), 26 deletions(-) diff --git a/vn.trader/ctaAlgo/IF0000_1min.csv b/vn.trader/ctaAlgo/IF0000_1min.csv index d9e62bf5..d74a5a4f 100644 --- a/vn.trader/ctaAlgo/IF0000_1min.csv +++ b/vn.trader/ctaAlgo/IF0000_1min.csv @@ -367735,3 +367735,21098 @@ 2015/11/25,15:13:00,3695.8,3696.6,3695.2,3695.2,95 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数据库指针 @@ -283,14 +285,13 @@ class BacktestingEngine(object): # 1. 假设当根K线的OHLC分别为：100, 125, 90, 110 # 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 - # 同时更新策略对象的持仓情况 if buyCross: trade.price = min(order.price, bestCrossPrice) self.strategy.pos += order.totalVolume else: trade.price = max(order.price, bestCrossPrice) self.strategy.pos -= order.totalVolume - + trade.volume = order.totalVolume trade.tradeTime = str(self.dt) trade.dt = self.dt @@ -313,9 +314,11 @@ class BacktestingEngine(object): if self.mode == self.BAR_MODE: buyCrossPrice = self.bar.high # 若买入方向停止单价格低于该价格，则会成交 sellCrossPrice = self.bar.low # 若卖出方向限价单价格高于该价格，则会成交 + bestCrossPrice = self.bar.open # 最优成交价，买入停止单不能低于，卖出停止单不能高于 else: buyCrossPrice = self.tick.lastPrice sellCrossPrice = self.tick.lastPrice + bestCrossPrice = self.tick.lastPrice # 遍历停止单字典中的所有停止单 for stopOrderID, so in self.workingStopOrderDict.items(): @@ -325,12 +328,6 @@ class BacktestingEngine(object): # 如果发生了成交 if buyCross or sellCross: - # 更新策略对象的持仓情况 - if buyCross: - self.strategy.pos += order.totalVolume - else: - self.strategy.pos -= order.totalVolume - # 推送成交数据 self.tradeCount += 1 # 成交编号自增1 tradeID = str(self.tradeCount) @@ -339,6 +336,13 @@ class BacktestingEngine(object): trade.tradeID = tradeID trade.vtTradeID = tradeID + if buyCross: + self.strategy.pos += so.volume + trade.price = max(bestCrossPrice, so.price) + else: + self.strategy.pos -= so.volume + trade.price = min(bestCrossPrice, so.price) + self.limitOrderCount += 1 orderID = str(self.limitOrderCount) trade.orderID = orderID @@ -346,7 +350,6 @@ class BacktestingEngine(object): trade.direction = so.direction trade.offset = so.offset - trade.price = so.price trade.volume = so.volume trade.tradeTime = str(self.dt) trade.dt = self.dt @@ -414,6 +417,9 @@ class BacktestingEngine(object): 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: @@ -423,8 +429,11 @@ class BacktestingEngine(object): # 当前多头交易为平空 else: entryTrade = shortTrade.pop(0) - # 滑点对于交易而言永远是不利的方向，因此每笔交易开平需要减去两倍的滑点 - pnl = (trade.price - entryTrade.price - self.slippage * 2) * trade.volume * (-1) + # 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 # 空头交易 else: @@ -434,7 +443,11 @@ class BacktestingEngine(object): # 当前空头交易为平多 else: entryTrade = longTrade.pop(0) - pnl = (trade.price - entryTrade.price - self.slippage * 2) * trade.volume + # 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 # 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 @@ -458,6 +471,14 @@ class BacktestingEngine(object): maxCapitalList.append(maxCapital) drawdownList.append(drawdown) + # 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)) + # 绘图 import matplotlib.pyplot as plt @@ -474,14 +495,6 @@ class BacktestingEngine(object): pPnl.hist(pnlList, bins=20) plt.show() - - # 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)) #---------------------------------------------------------------------- def putStrategyEvent(self, name): @@ -492,6 +505,17 @@ class BacktestingEngine(object): def setSlippage(self, slippage): """设置滑点""" self.slippage = slippage + + #---------------------------------------------------------------------- + def setSize(self, size): + """设置合约大小""" + self.size = size + + #---------------------------------------------------------------------- + def setRate(self, rate): + """设置佣金比例""" + self.rate = rate + if __name__ == '__main__': @@ -505,16 +529,18 @@ if __name__ == '__main__': # 设置引擎的回测模式为K线 engine.setBacktestingMode(engine.BAR_MODE) - - # 设置滑点 - engine.setSlippage(0.2) # 股指1跳 - + # 设置回测用的数据起始日期 - engine.setStartDate('20100416') + engine.setStartDate('20120101') # 载入历史数据到引擎中 engine.loadHistoryData(MINUTE_DB_NAME, 'IF0000') + # 设置产品相关参数 + engine.setSlippage(0.2) # 股指1跳 + engine.setRate(0.3/10000) # 万0.3 + engine.setSize(300) # 股指合约大小 + # 在引擎中创建策略对象 engine.initStrategy(DoubleEmaDemo, {}) diff --git a/vn.trader/ctaAlgo/ctaDemo.py b/vn.trader/ctaAlgo/ctaDemo.py index 660c6667..4391fb21 100644 --- a/vn.trader/ctaAlgo/ctaDemo.py +++ b/vn.trader/ctaAlgo/ctaDemo.py @@ -285,4 +285,3 @@ class OrderManagementDemo(CtaTemplate): """收到成交推送（必须由用户继承实现）""" # 对于无需做细粒度委托控制的策略，可以忽略onOrder pass -