[Add]增加多策略组合回测的Jupyter Notebook
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vn.py
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%matplotlib inline\n",
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"\n",
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"from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, MINUTE_DB_NAME\n",
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"\n",
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"def runBacktesting(strategyClass, settingDict, symbol, \n",
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" startDate, endDate, slippage, \n",
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" rate, size, priceTick):\n",
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" \"\"\"运行单标的回测\"\"\"\n",
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" engine = BacktestingEngine()\n",
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" engine.setBacktestingMode(engine.BAR_MODE)\n",
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" engine.setDatabase(MINUTE_DB_NAME, symbol)\n",
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" engine.setStartDate(startDate)\n",
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" engine.setEndDate(endDate)\n",
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" engine.setSlippage(slippage)\n",
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" engine.setRate(rate) \n",
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" engine.setSize(size) \n",
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" engine.setPriceTick(priceTick)\n",
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" \n",
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" engine.initStrategy(strategyClass, settingDict)\n",
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" engine.runBacktesting()\n",
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" df = engine.calculateDailyResult()\n",
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" return df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "EOL while scanning string literal (<ipython-input-2-50e7df42c47d>, line 4)",
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"output_type": "error",
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"traceback": [
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"\u001b[1;36m File \u001b[1;32m\"<ipython-input-2-50e7df42c47d>\"\u001b[1;36m, line \u001b[1;32m4\u001b[0m\n\u001b[1;33m '20120101', '20170630, 0.2,\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m EOL while scanning string literal\n"
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]
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}
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],
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"source": [
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"# 运行IF回测，交易1手\n",
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"from vnpy.trader.app.ctaStrategy.strategy.strategyAtrRsi import AtrRsiStrategy\n",
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"df1 = runBacktesting(AtrRsiStrategy, {}, 'IF0000', \n",
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" '20120101', '20170630', 0.2, \n",
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" 0.3/10000, 300, 0.2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2017-10-07 23:23:57.497000\t开始载入数据\n",
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"2017-10-07 23:23:57.617000\t载入完成，数据量：300224\n",
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"2017-10-07 23:23:57.617000\t开始回测\n",
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"2017-10-07 23:23:57.625000\t策略初始化完成\n",
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"2017-10-07 23:23:57.625000\t策略启动完成\n",
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"2017-10-07 23:23:57.625000\t开始回放数据\n"
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]
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}
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],
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"source": [
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"# 运行rb回测，交易16手\n",
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"from vnpy.trader.app.ctaStrategy.strategy.strategyBollChannel import BollChannelStrategy\n",
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"settingDict = {'fixedSize': 16}\n",
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"df2 = runBacktesting(BollChannelStrategy, settingDict, 'rb0000', \n",
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" '20120101', '20170630', 1, \n",
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" 1/10000, 10, 1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# 合并获得组合回测结果\n",
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"dfp = df1 + df2\n",
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"\n",
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"# 注意如果被抛弃的交易日位于回测的前后，即两者不重合的日期中，则不会影响组合曲线正确性\n",
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"# 但是如果被抛弃的交易日位于回测的中部，即两者重合的日期中，组合曲线会出现错误（丢失交易日）\n",
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"dfp = dfp.dropna() \n",
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"\n",
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"# 创建回测引擎，并设置组合回测初始资金后，显示结果\n",
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"engine = BacktestingEngine()\n",
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"engine.setCapital(1000000)\n",
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"engine.showDailyResult(dfp)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -90,7 +90,7 @@
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"outputs": [],
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"source": [
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"# 显示逐日回测结果\n",
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"df = engine.showDailyResult()"
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"engine.showDailyResult()"
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]
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},
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{
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@ -90,7 +90,7 @@
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"outputs": [],
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"source": [
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"# 显示逐日回测结果\n",
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"df = engine.showDailyResult()"
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"engine.showDailyResult()"
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]
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},
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{
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188
examples/CtaBacktesting/backtesting_portfolio.ipynb
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188
examples/CtaBacktesting/backtesting_portfolio.ipynb
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File diff suppressed because one or more lines are too long
@ -90,7 +90,7 @@
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"outputs": [],
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"source": [
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"# 显示逐日回测结果\n",
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"df = engine.showDailyResult()"
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"engine.showDailyResult()"
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]
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},
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{
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@ -948,7 +948,7 @@ class BacktestingEngine(object):
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#----------------------------------------------------------------------
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def showDailyResult(self, df=None):
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"""显示按日统计的交易结果"""
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if not df:
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if df is None:
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df = self.calculateDailyResult()
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df['balance'] = df['netPnl'].cumsum() + self.capital
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