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vnpy/examples/CtaBacktesting/backtesting_portfolio.ipynb

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[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, MINUTE_DB_NAME\n",
"\n",
"def runBacktesting(strategyClass, settingDict, symbol, \n",
" startDate, endDate, slippage, \n",
" rate, size, priceTick):\n",
" \"\"\"运行单标的回测\"\"\"\n",
" engine = BacktestingEngine()\n",
" engine.setBacktestingMode(engine.BAR_MODE)\n",
" engine.setDatabase(MINUTE_DB_NAME, symbol)\n",
" engine.setStartDate(startDate)\n",
" engine.setEndDate(endDate)\n",
" engine.setSlippage(slippage)\n",
" engine.setRate(rate) \n",
" engine.setSize(size) \n",
" engine.setPriceTick(priceTick)\n",
" \n",
" engine.initStrategy(strategyClass, settingDict)\n",
" engine.runBacktesting()\n",
" df = engine.calculateDailyResult()\n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
"2018-01-07 17:18:45.507000\t开始载入数据\n",
"2018-01-07 17:18:45.654000\t载入完成，数据量：348690\n",
"2018-01-07 17:18:45.654000\t开始回测\n",
"2018-01-07 17:18:45.694000\t策略初始化完成\n",
"2018-01-07 17:18:45.694000\t策略启动完成\n",
"2018-01-07 17:18:45.694000\t开始回放数据\n",
"2018-01-07 17:19:17.327000\t数据回放结束\n",
"2018-01-07 17:19:17.327000\t计算按日统计结果\n"
[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
]
}
],
"source": [
"# 运行IF回测，交易1手\n",
"from vnpy.trader.app.ctaStrategy.strategy.strategyAtrRsi import AtrRsiStrategy\n",
"df1 = runBacktesting(AtrRsiStrategy, {}, 'IF0000', \n",
" '20120101', '20170630', 0.2, \n",
" 0.3/10000, 300, 0.2)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
"2018-01-07 17:19:26.235000\t开始载入数据\n",
"2018-01-07 17:19:26.396000\t载入完成，数据量：370838\n",
"2018-01-07 17:19:26.396000\t开始回测\n",
"2018-01-07 17:19:26.404000\t策略初始化完成\n",
"2018-01-07 17:19:26.404000\t策略启动完成\n",
"2018-01-07 17:19:26.404000\t开始回放数据\n",
"2018-01-07 17:19:43.626000\t数据回放结束\n",
"2018-01-07 17:19:43.627000\t计算按日统计结果\n"
[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
]
}
],
"source": [
"# 运行rb回测，交易16手\n",
"from vnpy.trader.app.ctaStrategy.strategy.strategyBollChannel import BollChannelStrategy\n",
"settingDict = {'fixedSize': 16}\n",
"df2 = runBacktesting(BollChannelStrategy, settingDict, 'rb0000', \n",
" '20120101', '20170630', 1, \n",
" 1/10000, 10, 1)"
]
},
{
"cell_type": "code",
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
"execution_count": 4,
[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
"2018-01-07 17:23:24.218000\t------------------------------\n",
"2018-01-07 17:23:24.218000\t首个交易日：\t2012-01-11\n",
"2018-01-07 17:23:24.218000\t最后交易日：\t2017-06-30\n",
"2018-01-07 17:23:24.218000\t总交易日：\t1328\n",
"2018-01-07 17:23:24.218000\t盈利交易日\t675\n",
"2018-01-07 17:23:24.218000\t亏损交易日：\t653\n",
"2018-01-07 17:23:24.218000\t起始资金：\t1000000\n",
"2018-01-07 17:23:24.218000\t结束资金：\t2,495,104.82\n",
"2018-01-07 17:23:24.218000\t总收益率：\t149.51\n",
"2018-01-07 17:23:24.218000\t总盈亏：\t1,495,104.82\n",
"2018-01-07 17:23:24.218000\t最大回撤: \t-151,844.23\n",
"2018-01-07 17:23:24.218000\t总手续费：\t216,395.18\n",
"2018-01-07 17:23:24.218000\t总滑点：\t556,780.0\n",
"2018-01-07 17:23:24.218000\t总成交金额：\t7,521,413,620.0\n",
"2018-01-07 17:23:24.218000\t总成交笔数：\t8,168.0\n",
"2018-01-07 17:23:24.218000\t日均盈亏：\t1,125.83\n",
"2018-01-07 17:23:24.218000\t日均手续费：\t162.95\n",
"2018-01-07 17:23:24.218000\t日均滑点：\t419.26\n",
"2018-01-07 17:23:24.218000\t日均成交金额：\t5,663,715.08\n",
"2018-01-07 17:23:24.218000\t日均成交笔数：\t6.15\n",
"2018-01-07 17:23:24.218000\t日均收益率：\t0.07%\n",
"2018-01-07 17:23:24.218000\t收益标准差：\t0.97%\n",
"2018-01-07 17:23:24.218000\tSharpe Ratio：\t1.11\n"
[Add]增加多策略组合回测的Jupyter Notebook
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]
},
{
"data": {
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
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[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
"text/plain": [
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
"<matplotlib.figure.Figure at 0x1543a7f0>"
[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# 合并获得组合回测结果\n",
"dfp = df1 + df2\n",
"\n",
"# 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",
"# 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",
"dfp = dfp.dropna() \n",
"\n",
"# 创建回测引擎，并设置组合回测初始资金后，显示结果\n",
"engine = BacktestingEngine()\n",
"engine.setCapital(1000000)\n",
[Fix]修复 #618
2017-11-30 01:44:09 +00:00
"dfp, result = engine.calculateDailyStatistics(dfp)\n",
"engine.showDailyResult(dfp, result)"
[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
]
},
[Mod]修改CTA_Setting.json配置
2018-01-11 08:03:42 +00:00
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2018-01-07 17:24:26.175000\t------------------------------\n",
"2018-01-07 17:24:26.175000\t首个交易日：\t2012-01-11\n",
"2018-01-07 17:24:26.175000\t最后交易日：\t2017-06-30\n",
"2018-01-07 17:24:26.175000\t总交易日：\t1328\n",
"2018-01-07 17:24:26.175000\t盈利交易日\t648\n",
"2018-01-07 17:24:26.175000\t亏损交易日：\t679\n",
"2018-01-07 17:24:26.175000\t起始资金：\t1000000\n",
"2018-01-07 17:24:26.175000\t结束资金：\t1,815,424.82\n",
"2018-01-07 17:24:26.175000\t总收益率：\t81.54\n",
"2018-01-07 17:24:26.175000\t总盈亏：\t815,424.82\n",
"2018-01-07 17:24:26.175000\t最大回撤: \t-193,351.02\n",
"2018-01-07 17:24:26.175000\t总手续费：\t216,395.18\n",
"2018-01-07 17:24:26.175000\t总滑点：\t450,060.0\n",
"2018-01-07 17:24:26.175000\t总成交金额：\t7,213,172,820.0\n",
"2018-01-07 17:24:26.175000\t总成交笔数：\t7,501.0\n",
"2018-01-07 17:24:26.175000\t日均盈亏：\t614.02\n",
"2018-01-07 17:24:26.176000\t日均手续费：\t162.95\n",
"2018-01-07 17:24:26.176000\t日均滑点：\t338.9\n",
"2018-01-07 17:24:26.176000\t日均成交金额：\t5,431,606.04\n",
"2018-01-07 17:24:26.176000\t日均成交笔数：\t5.65\n",
"2018-01-07 17:24:26.176000\t日均收益率：\t0.05%\n",
"2018-01-07 17:24:26.176000\t收益标准差：\t1.07%\n",
"2018-01-07 17:24:26.176000\tSharpe Ratio：\t0.66\n"
]
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAoEAAAOlCAYAAAASGT0sAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3X18zXX/wPHX7Abb2Z17a0XuU4StcjWW6hJCxI8xVlGK\nWnRJ10i5DxXpxlQidQkhuUr35WLLSpibyU0pd2PLTYad4Wycz++Pt7OzMQzbzrG9n4+Hx/d8v+d7\nvudzztd47/35fN4fD2OMQSmllFJKlSnlXN0ApZRSSilV8jQIVEoppZQqgzQIVEoppZQqgzQIVEop\npZQqgzQIVEoppZQqgzQIVEoppZQqg7xc3QCllCpK+/fvp23btjRs2BBjDGfOnMHX15e4uDhatGhx\nwdeNGDGCBg0a0K9fvxJsrVJKuY4GgUqpUqdChQosXbo0d//rr79mxIgRfPvtty5slVJKuRcNApVS\npV5GRgbVqlUDYMKECWzevJmsrCyMMUyYMIHmzZvnO/+TTz5h0aJFnD59mqNHj/L444/Tq1cvli5d\nyvfff0+5cuXYs2cP3t7evPLKK9SrV4/Dhw8zevRodu7ciaenJ1FRUcTExGC1WnnppZf4/fffOX36\nNP/4xz/497//TblyOhpHKeVaGgQqpUqdU6dO8eCDD2KM4fjx4xw6dIgZM2awceNGDh8+zMKFCwGY\nOXMmM2fO5O2338597YkTJ/jkk0947733CAwMZNOmTfTr149evXoBsG7dOr744guqVavGhAkTmD17\nNpMmTWLMmDHceOONxMfHY7Va6d27N23atOHtt9/mlltuYdKkSdjtdoYPH87777/PY4895pLvRiml\nHDQIVEqVOud2B2/YsIEBAwbw2WefMWTIEBYsWMDevXtZs2YNFosl32t9fX155513WLFiBXv27GHb\ntm2cPHky9/mbb745N6vYuHFjvv/+ewB+/vln4uLiALBYLCxbtgyAlStXsnnzZhYvXgyAzWbDw8Oj\n+D68UkoVkgaBSqlSr3nz5tx4442sXbuWGTNm0L9/f/75z39Sp06d3GDN4cCBA0RFRREVFUV4eDjt\n2rUjISEh9/ny5cvnPvbw8MCx/LqXV/5/TlNTUwkODsZut/PGG29Qp04dAKxWa3F9TKWUuiw6KEUp\nVeo4AjOHXbt2sXv3br7++mvuueceevXqxS233MLy5cux2+35zt28eTOVKlVi0KBBREREsGLFigKv\nea4777yTTz/9FIDMzEweeeQR9u7dS6tWrfjggw8AyM7OZuDAgcybN6+IPqlSSl05zQQqpUqd7Oxs\nHnzwQUCCN8cEkAYNGvDss8/SpUsXPD09CQ8P57vvvsv32tatW7NkyRLatWuHn58fTZo0oVKlSuzZ\ns+ei7/niiy8yZswYHnjgAYwxDBw4kMaNGzNy5EgmTpxI586dOX36NBEREToeUCnlFjzMpX69VUop\npZRSpc4lM4GnT5/m+eefZ//+/eTk5DBw4EDq1avH8OHDKVeuHPXr12f06NEALFq0iIULF+Lt7c3A\ngQNp06YNNpuN5557jr///huLxcLkyZMJDg5m48aNTJw4ES8vL+68805iY2MBmD59OgkJCXh5eTFi\nxAiaNm1KRkYGw4YNw2azUa1aNSZNmpRvXI5SSimllLo8lxwT+PnnnxMcHMy8efOYNWsW48ePZ9Kk\nSQwdOpSPPvoIu93ODz/8wOHDh5k7dy4LFy5k1qxZTJ06lZycHBYsWECDBg2YN28eXbp0YcaMGQCM\nGTOG1157jfnz55OSksL27dvZunUr69atY/Hixbz22muMGzcOgPj4eDp37sxHH31Eo0aNWLBgQfF+\nK0oppZRSpdwlg8AOHTowZMgQAM6cOYOnpydbt24lPDwcgMjISH766SdSUlIICwvDy8sLi8VC7dq1\n2b59O8nJyURGRuaeu3r1aqxWKzk5OYSGhgLQqlUrkpKSSE5OJiIiAoCaNWtit9s5cuQI69evp3Xr\n1vmuoZRSSimlrtwlg8CKFSvi6+uL1WplyJAh/Otf/8o3S87Pzw+r1UpWVhb+/v65xx2vycrKyq3D\n5efnR2ZmZr5j5x7Pe42Cru04VymllFJKXblCzQ5OT08nNjaWvn370rFjR1599dXc57KysggICMBi\nseSrf5X3eFZWVu4xf3//3OAu77mBgYF4e3vnngtSTysgICD3/EqVKp0XKOaVnJx8eZ9eKaWUUsqF\nwsLCXPbelwwCDx8+zKOPPsqoUaNo2bIlADfddBNr167ltttuIzExkZYtW9KkSROmTZtGdnY2NpuN\nnTt3Ur9+fZo3b05CQgJNmjQhISGB8PBwLBYLPj4+pKamEhoayqpVq4iNjcXT05MpU6bQv39/0tPT\nMcYQFBREixYtSExMpGvXriQmJuZ2RRfElV+mckpLSyMkJMTVzVDn0PvinvS+uCfHfTl5Ek6fhgvk\nH5QLlJafGVcnry4ZBL777rscP36cGTNmEB8fj4eHByNHjmTChAnk5ORQt25d2rdvj4eHBzExMURH\nR2OMYejQofj4+NC7d2/i4uKIjo7Gx8eHqVOnAjB27FiGDRuG3W4nIiKCpk2bAhLERUVFYYxh1KhR\nAAwaNIi4uDgWLVpEcHBw7jWUUkqp4vbWW3DwIEyZ4uqWKFW0SlWdwOTkZM0EuonS8ltaaaP3xT3p\nfXFPjvsyYAAYA7NmubpFyqG0/My4Om7RZeOUUkqpi9i5E44ehUOHXN0SpYqWBoFKKaXURezaBUuW\nQLVqUL8+2GywZYurW6XU1dMgUCmllLqA06dh717n/h9/wAcfwC23wIkTMHcuHD5c8Gv//BM6dcp/\nLDVVrqmUO9AgUCmllLqA1FQ4c0YeO+YkVqgg21tugYcekqCwIMuXw5df5j92ww3w4ovF0lSlLpsG\ngUoppdQF/O9/UKWKPA4Ph1q1YM0aaN0aPD2hdm347DNnoOjwxhvwxBPy2G6XrWMa5vLlJdJ0pS5J\ng0CllFLqAtavh0cekccBAdCuHXz9tQSEmzfD9u3g7Q0vvQTffguvvCLnzpwJDRrI4yNHZHv0KHh5\nwW+/wbFjJf5R1EU47lFZo0GgUkopdQE2mzOY8/CQTOCuXRAYKN3C5cvDRx/BjBnQvj3Excm5hw7B\njz9CaKiMHQRIT4d69eDGG2W8oCoZeRYiK9DhwzLpx8MD/vrLefzHH2HChNIdIGoQ6GJr1qyhc+fO\nl/WaRo0acfTo0WJqkVJKKYfsbAn0EhKgSRNo2RI6dIA+fZznhITA7Nn5X2e1gsUigeKpU3IsLQ1q\n1IDrroN9+0ruM5RlixbJffj4YxgxQgL2mBgYOxbGjYNVq2TGd61acn69evDhh5CZCXfdJeffcYez\nS7+0KdTawcq9eHh4uLoJSilVJths4OMDkZGyf8898udcHTvC4MHw5psyPtBmg4oV5Y8jCPzhB7jp\nJnl+//6S+wyl2eHD0sX+/ffQo0f+54yBZ56Rx717F/z6iRPlXv32G/TqBStWSPf/iBHQs6cEj3Xr\nSrd/48bF+lFcQoNAN5CVlcXgwYPZu3cvAQEBjBs3DoBx48Zx4sQJDh48yE033cS0adPw8fHBscjL\nyZMnGTNmDHv27OHo0aP4+fkxdepUateuTUxMDM2bN2f9+vWkpaURHh7OK2cHq6xYsYI33ngDYwwV\nK1ZkzJgxNGrUiPXr1zN16lROnjxJuXLliI2NpU2bNq76WpRSyuVsNskEFsarr0rmaeNG8POT7sUK\nFSAxUcrCzJ4N//kPrF2rQeDVsNthwwZvqlaFqlXh6adlaT+7Xb7XEydknOYXX0DlylLse+5c6NZN\nJuzYbJLpe+45qFNHun2rVZNu/xUrYPRoyRSOHi3vFxEh9/WJJ6BmTdd+9iJnSpF169a5ugmX7Zdf\nfjGNGzc2GzduNMYYs3DhQtOjRw/zyiuvmM8//9wYY0xOTo7p3Lmz+e6774wxxjRs2NBkZGSYb775\nxkyYMCH3WqNGjTLjx48
"text/plain": [
"<matplotlib.figure.Figure at 0x1498ad30>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"engine = BacktestingEngine()\n",
"engine.setCapital(1000000)\n",
"df1, result = engine.calculateDailyStatistics(df1)\n",
"engine.showDailyResult(df1, result)"
]
},
[Add]增加多策略组合回测的Jupyter Notebook
2017-10-07 15:25:59 +00:00
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Reference in New Issue Copy Permalink