vnpy/tests/backtesting/turtle.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%\n",
    "from vnpy.app.cta_strategy.backtesting import BacktestingEngine\n",
    "from vnpy.app.cta_strategy.strategies.turtle_signal_strategy import (\n",
    "    TurtleSignalStrategy,\n",
    ")\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%\n",
    "engine = BacktestingEngine()\n",
    "engine.set_parameters(\n",
    "    vt_symbol=\"IF99.CFFEX\",\n",
    "    interval=\"1m\",\n",
    "    start=datetime(2013, 1, 1),\n",
    "    end=datetime(2019, 3, 30),\n",
    "    rate=0,\n",
    "    slippage=0,\n",
    "    size=300,\n",
    "    pricetick=0.2,\n",
    "    capital=1_000_000,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-01-30 12:25:59.002493\t开始加载历史数据\n",
      "2019-01-30 12:26:34.081621\t历史数据加载完成，数据量：376572\n",
      "2019-01-30 12:26:34.332922\t策略初始化完成\n",
      "2019-01-30 12:26:34.333896\t开始回放历史数据\n",
      "2019-01-30 12:27:21.518437\t历史数据回放结束\n",
      "2019-01-30 12:27:21.518437\t开始计算逐日盯市盈亏\n",
      "2019-01-30 12:27:21.898312\t逐日盯市盈亏计算完成\n",
      "2019-01-30 12:27:21.898312\t开始计算策略统计指标\n",
      "2019-01-30 12:27:21.929482\t------------------------------\n",
      "2019-01-30 12:27:21.929482\t首个交易日：\t2013-02-01\n",
      "2019-01-30 12:27:21.929482\t最后交易日：\t2019-01-30\n",
      "2019-01-30 12:27:21.929482\t总交易日：\t1459\n",
      "2019-01-30 12:27:21.929482\t盈利交易日：\t805\n",
      "2019-01-30 12:27:21.929482\t亏损交易日：\t654\n",
      "2019-01-30 12:27:21.929482\t起始资金：\t1,000,000.00\n",
      "2019-01-30 12:27:21.929482\t结束资金：\t220,899,784.04\n",
      "2019-01-30 12:27:21.929482\t总收益率：\t21,989.98%\n",
      "2019-01-30 12:27:21.929482\t年化收益：\t3,617.27%\n",
      "2019-01-30 12:27:21.929482\t最大回撤: \t-57,892,062.00%\n",
      "2019-01-30 12:27:21.929482\t百分比最大回撤: -1,199.55%\n",
      "2019-01-30 12:27:21.929482\t总盈亏：\t219,899,784.04%\n",
      "2019-01-30 12:27:21.929482\t总手续费：\t0.00\n",
      "2019-01-30 12:27:21.929482\t总滑点：\t0.00\n",
      "2019-01-30 12:27:21.929482\t总成交金额：\t96,983,115,547.79\n",
      "2019-01-30 12:27:21.929482\t总成交笔数：\t68478\n",
      "2019-01-30 12:27:21.929482\t日均盈亏：\t150,719.52\n",
      "2019-01-30 12:27:21.929482\t日均手续费：\t0.00\n",
      "2019-01-30 12:27:21.929482\t日均滑点：\t0.00\n",
      "2019-01-30 12:27:21.929482\t日均成交金额：\t66,472,320.46\n",
      "2019-01-30 12:27:21.929482\t日均成交笔数：\t46.93488690884167\n",
      "2019-01-30 12:27:21.929482\t日均收益率：\t1,322.46%\n",
      "2019-01-30 12:27:21.929482\t收益标准差：\t828.67%\n",
      "2019-01-30 12:27:21.929482\tSharpe Ratio：\t24.72\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Github\\vnpy\\vnpy\\app\\cta_strategy\\backtesting.py:306: RuntimeWarning: invalid value encountered in log\n",
      "  df[\"return\"] = (np.log(df[\"balance\"] - np.log(df[\"balance\"].shift(1)))).fillna(\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 720x1152 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%%\n",
    "engine.add_strategy(TurtleSignalStrategy, {})\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": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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