diff --git a/examples/DataService/RqdataDataService/downloadData.py b/examples/DataService/RqdataDataService/downloadData.py index ca654770..f0263ffc 100644 --- a/examples/DataService/RqdataDataService/downloadData.py +++ b/examples/DataService/RqdataDataService/downloadData.py @@ -8,10 +8,7 @@ from dataService import * if __name__ == '__main__': - #downloadMinuteBarBySymbol('IF1812') - #downloadAllMinuteBar() - #downloadMinuteBarBySymbol('CU99') - downloadDailyBarBySymbol('CU99') + downloadMinuteBarBySymbol('CU99') downloadDailyBarBySymbol('IF99') downloadDailyBarBySymbol('TA99') downloadDailyBarBySymbol('I99') \ No newline at end of file diff --git a/examples/TurtleStrategy/000300.csv b/examples/TurtleStrategy/000300.csv new file mode 100644 index 00000000..2c17dc32 --- /dev/null +++ b/examples/TurtleStrategy/000300.csv @@ -0,0 +1,1424 @@ +date,close,high,low,open,volume +2013/1/4,2524.409,2558.529,2498.892,2551.814,9798818200 +2013/1/7,2535.985,2545.969,2511.603,2518.047,7516799300 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b/examples/TurtleStrategy/README.MD new file mode 100644 index 00000000..fdd79cb0 --- /dev/null +++ b/examples/TurtleStrategy/README.MD @@ -0,0 +1,15 @@ +## 海龟交易策略（完整版） + +使用说明： +1. 在cmd中运行python loadCsv.py，将000300.csv中的沪深300指数数据加载到MongoDB数据库中 +2. 使用Jupyter Notebook打开run.ipynb，并执行相应的回测分析 + +开发进度 +1. 海龟交易信号（负责判断具体的买卖位置）：已完成 +2. 海龟投资组合（负责根据信号执行具体交易）：已完成 +3. 回测引擎配置组合和信号：已完成 +4. 回测引擎加载历史数据：已完成 +5. 回测引擎回放历史数据：已完成 +6. 回测引擎计算每日盈亏情况：已完成 +7. 回测引擎统计整体回测结果和画图：未完成 + diff --git a/examples/TurtleStrategy/loadCsv.py b/examples/TurtleStrategy/loadCsv.py new file mode 100644 index 00000000..7b3d7bc2 --- /dev/null +++ b/examples/TurtleStrategy/loadCsv.py @@ -0,0 +1,37 @@ +# encoding: UTF-8 + +from csv import DictReader +from datetime import datetime +from pymongo import MongoClient + +from vnpy.trader.vtObject import VtBarData + +from turtleEngine import DAILY_DB_NAME + + +#---------------------------------------------------------------------- +def loadCsv(filename): + """""" + symbol = filename.split('.')[0] + + mc = MongoClient() + db = mc[DAILY_DB_NAME] + collection = db[symbol] + + with open(filename) as f: + r = DictReader(f) + for d in r: + bar = VtBarData() + bar.datetime = datetime.strptime(d['date'], '%Y/%m/%d') + bar.vtSymbol = symbol + bar.open = float(d['open']) + bar.high = float(d['high']) + bar.low = float(d['low']) + bar.close = float(d['close']) + bar.volume= int(d['volume']) + + collection.insert(bar.__dict__) + +if __name__ == '__main__': + loadCsv('000300.csv') + loadCsv('000905.csv') \ No newline at end of file diff --git a/examples/TurtleStrategy/run.ipynb b/examples/TurtleStrategy/run.ipynb index 2f34f25b..8eb32e4c 100644 --- a/examples/TurtleStrategy/run.ipynb +++ b/examples/TurtleStrategy/run.ipynb @@ -20,11 +20,20 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "16:03:53.281000:\t投资组合的合约代码['000300', '000905']\n", + "16:03:53.281000:\t投资组合的初始价值10000000\n" + ] + } + ], "source": [ "engine = BacktestingEngine()\n", "engine.setPeriod(datetime(2015, 1, 1), datetime(2018, 11, 9))\n", - "engine.initPortfolio('setting.csv', 10000000)" + "engine.initPortfolio('test.csv', 10000000)" ] }, { @@ -38,11 +47,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "15:23:05.294000:IF99数据加载完成，总数据量：940\n", - "15:23:05.323000:I99数据加载完成，总数据量：940\n", - "15:23:05.348000:CU99数据加载完成，总数据量：940\n", - "15:23:05.375000:TA99数据加载完成，总数据量：940\n", - "15:23:05.375000:全部数据加载完成\n" + "16:03:53.421000:\t000300数据加载完成，总数据量：2820\n", + "16:03:53.455000:\t000905数据加载完成，总数据量：940\n", + "16:03:53.455000:\t全部数据加载完成\n", + "16:03:53.457000:\t开始回放K线数据\n", + "16:03:53.575000:\tK线数据回放结束\n", + "16:03:53.576000:\t开始统计回测结果\n", + "16:03:53.582000:\t回测结果统计结束\n" ] } ], @@ -52,44 +63,15 @@ "engine.calculateResult()" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "for dt, l in engine.tradeDict.items():\n", - " print dt\n", - " for trade in l:\n", - " print trade.vtSymbol, trade.direction, trade.offset, trade.price, trade.volume" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "for result in engine.resultList:\n", - " if result.totalPnl:\n", - " print result.date, result.totalPnl" - ] - }, { "cell_type": "code", "execution_count": 4, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 4, @@ -98,9 +80,9 @@ }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -108,6 +90,7 @@ } ], "source": [ + "# 汇总每日盈亏，绘制简单资金曲线\n", "l = [result.totalPnl for result in engine.resultList]\n", "equity = np.cumsum(l)\n", "plt.plot(equity)" @@ -115,10 +98,1192 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] + "execution_count": 5, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2015-04-07 00:00:00\n", + "000300 多 开仓 4213.8 1216\n", + "000300 多 开仓 4213.8 1216\n", + "000300 多 开仓 4252.8 1216\n", + "000905 多 开仓 7728.9 831\n", + "000905 多 开仓 7742.9 831\n", + "000905 多 开仓 7803.1 831\n", + "000905 多 开仓 7863.3 831\n", + "2015-04-08 00:00:00\n", + "000300 多 开仓 4294.0 1216\n", + "2015-04-09 00:00:00\n", + "000905 空 平仓 7622.5 3324\n", + "2015-04-10 00:00:00\n", + "000905 多 开仓 7921.0 712\n", + "2015-04-13 00:00:00\n", + "000905 多 开仓 7994.3 712\n", + "000905 多 开仓 8061.4 712\n", + "000905 多 开仓 8131.6 712\n", + "2015-04-15 00:00:00\n", + "000905 空 平仓 7850.8 2848\n", + "2015-04-22 00:00:00\n", + "000905 多 开仓 8192.2 570\n", + "000905 多 开仓 8280.0 570\n", + "2015-04-23 00:00:00\n", + "000905 多 开仓 8371.9 570\n", + "2015-04-27 00:00:00\n", + "000905 多 开仓 8503.6 570\n", + "2015-05-06 00:00:00\n", + "000905 空 平仓 8152.6 2280\n", + "2015-05-07 00:00:00\n", + "000300 空 平仓 4511.8 4864\n", + "2015-05-12 00:00:00\n", + "000905 多 开仓 8595.1 472\n", + "000905 多 开仓 8682.4 472\n", + "2015-05-13 00:00:00\n", + "000905 多 开仓 8788.3 472\n", + "000905 多 开仓 8894.2 472\n", + "2015-06-05 00:00:00\n", + "000300 多 开仓 5255.0 691\n", + "2015-06-08 00:00:00\n", + "000300 多 开仓 5299.2 691\n", + "2015-06-09 00:00:00\n", + "000300 多 开仓 5379.4 691\n", + "2015-06-16 00:00:00\n", + "000300 空 平仓 5090.0 2073\n", + "2015-06-19 00:00:00\n", + "000300 空 开仓 4665.6 657\n", + "000905 空 平仓 10475.9 1888\n", + "2015-06-23 00:00:00\n", + "000300 空 开仓 4589.4 657\n", + "000300 空 开仓 4513.2 657\n", + "2015-06-24 00:00:00\n", + 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+ "000300 空 开仓 3179.6 1692\n", + "000300 空 开仓 3161.8 1692\n", + "000300 空 开仓 3132.2 1692\n", + "000300 空 开仓 3102.8 1692\n", + "000905 空 开仓 4483.3 1237\n", + "000905 空 开仓 4483.3 1237\n", + "000905 空 开仓 4483.3 1237\n", + "000905 空 开仓 4463.1 1237\n", + "2018-10-22 00:00:00\n", + "000300 多 平仓 3221.0 6768\n", + "2018-11-02 00:00:00\n", + "000905 多 平仓 4375.6 4948\n" + ] + } + ], + "source": [ + "# 查看逐笔的交易记录\n", + "for dt, l in engine.tradeDict.items():\n", + " print dt\n", + " for trade in l:\n", + " print trade.vtSymbol, trade.direction, trade.offset, trade.price, trade.volume" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2015-04-03 00:00:00 -556058.736\n", + "2015-04-07 00:00:00 -41290.496\n", + "2015-04-08 00:00:00 -669917.184\n", + "2015-04-09 00:00:00 -493815.152\n", + "2015-04-10 00:00:00 164718.296\n", + "2015-04-13 00:00:00 494400.896\n", + 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00:00:00 300093.824\n", + "2015-05-25 00:00:00 494503.072\n", + "2015-05-26 00:00:00 629629.12\n", + "2015-05-27 00:00:00 233658.88\n", + "2015-05-28 00:00:00 -1187393.408\n", + "2015-05-29 00:00:00 185818.848\n", + "2015-06-01 00:00:00 984525.92\n", + "2015-06-02 00:00:00 751593.92\n", + "2015-06-03 00:00:00 176697.92\n", + "2015-06-04 00:00:00 -78373.584\n", + "2015-06-05 00:00:00 290723.912\n", + "2015-06-08 00:00:00 -147075.994\n", + "2015-06-09 00:00:00 -82588.984\n", + "2015-06-10 00:00:00 349570.9486\n", + "2015-06-11 00:00:00 293520.3292\n", + "2015-06-12 00:00:00 398212.6123\n", + "2015-06-15 00:00:00 -910264.9591\n", + "2015-06-16 00:00:00 -1179473.9125\n", + "2015-06-17 00:00:00 416700.1024\n", + "2015-06-18 00:00:00 -1353402.4515\n", + "2015-06-19 00:00:00 -1517295.5482\n", + "2015-06-23 00:00:00 -160417.7847\n", + "2015-06-24 00:00:00 -185343.9705\n", + "2015-06-25 00:00:00 -922472.4249\n", + "2015-06-26 00:00:00 -204613.1811\n", + "2015-06-29 00:00:00 545817.2343\n", + 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192475.14\n", + "2015-09-01 00:00:00 402709.2984\n", + "2015-09-02 00:00:00 35671.6116\n", + "2015-09-07 00:00:00 248993.596\n", + "2015-09-08 00:00:00 -415007.4876\n", + "2015-09-09 00:00:00 -319934.6564\n", + "2015-09-10 00:00:00 202732.3416\n", + "2015-09-11 00:00:00 -26275.0272\n", + "2015-09-14 00:00:00 576282.1476\n", + "2015-09-15 00:00:00 625950.3296\n", + "2015-09-16 00:00:00 -724882.5516\n", + "2015-09-17 00:00:00 282181.704\n", + "2015-09-18 00:00:00 -101330.092\n", + "2015-09-21 00:00:00 -336169.3228\n", + "2015-09-22 00:00:00 -115089.8036\n", + "2015-09-23 00:00:00 245139.4204\n", + "2015-09-24 00:00:00 -137402.8152\n", + "2015-09-25 00:00:00 320517.7188\n", + "2015-09-28 00:00:00 -131160.0976\n", + "2015-09-29 00:00:00 259523.9128\n", + "2015-09-30 00:00:00 -302176.3876\n", + "2015-10-08 00:00:00 -454946.734\n", + "2015-10-09 00:00:00 -303435.176\n", + "2015-10-12 00:00:00 -250870.73\n", + "2015-11-19 00:00:00 -44606.452\n", + "2015-11-23 00:00:00 -27316.652\n", + 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"2018-09-27 00:00:00 -47314.7126\n", + "2018-09-28 00:00:00 -255063.6332\n", + "2018-10-08 00:00:00 -512850.5026\n", + "2018-10-10 00:00:00 -1680888.45\n", + "2018-10-12 00:00:00 -170072.5924\n", + "2018-10-15 00:00:00 689959.1236\n", + "2018-10-16 00:00:00 664611.8052\n", + "2018-10-17 00:00:00 -283648.3748\n", + "2018-10-18 00:00:00 1068480.3224\n", + "2018-10-19 00:00:00 -1737209.0496\n", + "2018-10-22 00:00:00 -1931025.1004\n", + "2018-10-23 00:00:00 393803.4032\n", + "2018-10-24 00:00:00 39918.9796\n", + "2018-10-25 00:00:00 54762.4848\n", + "2018-10-26 00:00:00 2287.4604\n", + "2018-10-29 00:00:00 353450.484\n", + "2018-10-30 00:00:00 -207899.6212\n", + "2018-10-31 00:00:00 -336510.5112\n", + "2018-11-01 00:00:00 -509882.4936\n", + "2018-11-02 00:00:00 -687583.4812\n" + ] + } + ], + "source": [ + "# 查看每日的盈亏统计\n", + "for result in engine.resultList:\n", + " if result.totalPnl:\n", + " print result.date, result.totalPnl" + ] }, { "cell_type": "code", diff --git a/examples/TurtleStrategy/test.csv b/examples/TurtleStrategy/test.csv new file mode 100644 index 00000000..dbf865b3 --- /dev/null +++ b/examples/TurtleStrategy/test.csv @@ -0,0 +1,3 @@ +vtSymbol,size,priceTick,variableCommission,fixedCommission,slippage +000300,1,0.2,0,0,0 +000905,1,0.1,0,0,0 diff --git a/examples/TurtleStrategy/turtleEngine.py b/examples/TurtleStrategy/turtleEngine.py index 129f3590..001dd819 100644 --- a/examples/TurtleStrategy/turtleEngine.py +++ b/examples/TurtleStrategy/turtleEngine.py @@ -72,6 +72,9 @@ class BacktestingEngine(object): self.portfolio = TurtlePortfolio(self) self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT) + + self.writeLog(u'投资组合的合约代码%s' %(self.vtSymbolList)) + self.writeLog(u'投资组合的初始价值%s' %(portfolioValue)) #---------------------------------------------------------------------- def loadData(self): @@ -100,6 +103,8 @@ class BacktestingEngine(object): #---------------------------------------------------------------------- def runBacktesting(self): """""" + self.writeLog(u'开始回放K线数据') + for dt, barDict in self.dataDict.items(): self.currentDt = dt @@ -115,12 +120,18 @@ class BacktestingEngine(object): self.resultList.append(result) self.result = result + + self.writeLog(u'K线数据回放结束') #---------------------------------------------------------------------- def calculateResult(self): """""" + self.writeLog(u'开始统计回测结果') + for result in self.resultList: result.calculatePnl() + + self.writeLog(u'回测结果统计结束') #---------------------------------------------------------------------- def sendOrder(self, vtSymbol, direction, offset, price, volume): @@ -139,7 +150,7 @@ class BacktestingEngine(object): #---------------------------------------------------------------------- def writeLog(self, content): """""" - print '%s:%s' %(datetime.now().strftime('%H:%M:%S.%f'), content) + print '%s:\t%s' %(datetime.now().strftime('%H:%M:%S.%f'), content) ######################################################################## diff --git a/examples/TurtleStrategy/turtleStrategy.py b/examples/TurtleStrategy/turtleStrategy.py index 1b138a9c..1996c9fc 100644 --- a/examples/TurtleStrategy/turtleStrategy.py +++ b/examples/TurtleStrategy/turtleStrategy.py @@ -75,7 +75,7 @@ class TurtleSignal(object): self.shortEntry4 = 0 self.shortStop = 0 # 空头止损位 - self.unit = 0 # 信号持仓 + self.unit = 0 # 信号持仓 self.result = None # 当前的交易 self.resultList = [] # 交易列表 self.bar = None # 最新K线