{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#%%\n", "from vnpy.app.cta_strategy.backtesting import BacktestingEngine, OptimizationSetting\n", "from vnpy.app.cta_strategy.strategies.atr_rsi_strategy import (\n", " AtrRsiStrategy,\n", ")\n", "from datetime import datetime" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "#%%\n", "engine = BacktestingEngine()\n", "engine.set_parameters(\n", " vt_symbol=\"IF88.CFFEX\",\n", " interval=\"1m\",\n", " start=datetime(2019, 1, 1),\n", " end=datetime(2019, 4, 30),\n", " rate=0.3/10000,\n", " slippage=0.2,\n", " size=300,\n", " pricetick=0.2,\n", " capital=1_000_000,\n", ")\n", "engine.add_strategy(AtrRsiStrategy, {})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": false }, "outputs": [], "source": [ "#%%\n", "engine.load_data()\n", "engine.run_backtesting()\n", "df = engine.calculate_result()\n", "engine.calculate_statistics()\n", "engine.show_chart()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2019-04-15 22:19:49.696835\t参数:{'atr_length': 22}, 目标:121.19996051999999\n", "2019-04-15 22:19:49.709531\t参数:{'atr_length': 23}, 目标:116.54901966000013\n", "2019-04-15 22:19:49.710507\t参数:{'atr_length': 24}, 目标:113.29820520000014\n" ] }, { "data": { "text/plain": [ "[(\"{'atr_length': 22}\",\n", " 121.19996051999999,\n", " {'start_date': datetime.date(2013, 1, 18),\n", " 'end_date': datetime.date(2019, 4, 11),\n", " 'total_days': 1514,\n", " 'profit_days': 763,\n", " 'loss_days': 750,\n", " 'capital': 1000000,\n", " 'end_balance': 2211999.6052,\n", " 'max_drawdown': -248787.6971999996,\n", " 'max_ddpercent': -12.636908338002794,\n", " 'total_net_pnl': 1211999.6052000003,\n", " 'daily_net_pnl': 800.5281408190227,\n", " 'total_commission': 242400.39479999998,\n", " 'daily_commission': 160.10594108322323,\n", " 'total_slippage': 481860.0,\n", " 'daily_slippage': 318.2694848084544,\n", " 'total_turnover': 8080013160.0,\n", " 'daily_turnover': 5336864.702774108,\n", " 'total_trade_count': 8031,\n", " 'daily_trade_count': 5.30449141347424,\n", " 'total_return': 121.19996051999999,\n", " 'annual_return': 19.212675379656538,\n", " 'daily_return': 0.052348808029058974,\n", " 'return_std': 0.9487639654919149,\n", " 'sharpe_ratio': 0.854779772691872,\n", " 'return_drawdown_ratio': 9.590950355754112}),\n", " (\"{'atr_length': 23}\",\n", " 116.54901966000013,\n", " {'start_date': datetime.date(2013, 1, 18),\n", " 'end_date': datetime.date(2019, 4, 11),\n", " 'total_days': 1514,\n", " 'profit_days': 759,\n", " 'loss_days': 754,\n", " 'capital': 1000000,\n", " 'end_balance': 2165490.1966000013,\n", " 'max_drawdown': -232904.1239999996,\n", " 'max_ddpercent': -13.536251422505968,\n", " 'total_net_pnl': 1165490.1966000004,\n", " 'daily_net_pnl': 769.8085842800531,\n", " 'total_commission': 242769.80339999998,\n", " 'daily_commission': 160.34993619550858,\n", " 'total_slippage': 482700.0,\n", " 'daily_slippage': 318.82430647291943,\n", " 'total_turnover': 8092326780.0,\n", " 'daily_turnover': 5344997.873183619,\n", " 'total_trade_count': 8045,\n", " 'daily_trade_count': 5.313738441215324,\n", " 'total_return': 116.54901966000013,\n", " 'annual_return': 18.475406022721288,\n", " 'daily_return': 0.0509452313711608,\n", " 'return_std': 0.961380153488665,\n", " 'sharpe_ratio': 0.8209448965768181,\n", " 'return_drawdown_ratio': 8.610139987960078}),\n", " (\"{'atr_length': 24}\",\n", " 113.29820520000014,\n", " {'start_date': datetime.date(2013, 1, 18),\n", " 'end_date': datetime.date(2019, 4, 11),\n", " 'total_days': 1514,\n", " 'profit_days': 760,\n", " 'loss_days': 753,\n", " 'capital': 1000000,\n", " 'end_balance': 2132982.0520000015,\n", " 'max_drawdown': -236503.9475999996,\n", " 'max_ddpercent': -13.23872340727957,\n", " 'total_net_pnl': 1132982.0520000013,\n", " 'daily_net_pnl': 748.3368903566719,\n", " 'total_commission': 242817.948,\n", " 'daily_commission': 160.3817357992074,\n", " 'total_slippage': 482700.0,\n", " 'daily_slippage': 318.82430647291943,\n", " 'total_turnover': 8093931600.0,\n", " 'daily_turnover': 5346057.85997358,\n", " 'total_trade_count': 8045,\n", " 'daily_trade_count': 5.313738441215324,\n", " 'total_return': 113.29820520000014,\n", " 'annual_return': 17.96008536856013,\n", " 'daily_return': 0.049946173936258026,\n", " 'return_std': 0.959328411709829,\n", " 'sharpe_ratio': 0.8065671672003681,\n", " 'return_drawdown_ratio': 8.558091419728651})]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "setting = OptimizationSetting()\n", "setting.set_target(\"total_return\")\n", "setting.add_parameter(\"atr_length\", 22, 24, 1)\n", "\n", "engine.run_optimization(setting)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.1" } }, "nbformat": 4, "nbformat_minor": 2 }