6_4_網格歷史回測最佳化.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "載入必要套件與類別"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mplfinance as mpf\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "from grid_backtest import trade\n",
    "plt.rcParams['font.sans-serif'] = ['Microsoft JhengHei']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "網格交易最佳化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  1 of 1 completed\n",
      "C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_15768\\1659100453.py:5: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "  data = data1.ffill()\n"
     ]
    }
   ],
   "source": [
    "# 取得要回測的歷史資料\n",
    "symbol = '0050' \n",
    "data = yf.download(f'{symbol}.TW')\n",
    "data1 = data.replace(0, None)\n",
    "data = data1.ffill()\n",
    "data.columns = [i.lower() for i in data.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.08, 25, 1.8 年化報酬率:0.06400663406382412\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.08, 25, 2 年化報酬率:0.0691316677665561\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.08, 25, 2.2 年化報酬率:0.07018673303006384\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '5.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 5, 1.6 年化報酬率:0.0872949454150318\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '5.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 5, 1.8 年化報酬率:0.08684045828299047\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '5.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 5, 2 年化報酬率:0.08219485730749598\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '5.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 5, 2.2 年化報酬率:0.08481625143116411\n",
      "錯誤！初始部位要可以被交易單位整除\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 20, 1.6 年化報酬率:0.06816276160443335\n",
      "錯誤！初始部位要可以被交易單位整除\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 20, 1.8 年化報酬率:0.07476490859869944\n",
      "錯誤！初始部位要可以被交易單位整除\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '5.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 20, 2 年化報酬率:0.05810568368090774\n",
      "錯誤！初始部位要可以被交易單位整除\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '5.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 20, 2.2 年化報酬率:0.07796132862640248\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 25, 1.6 年化報酬率:0.0668558239564705\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 25, 1.8 年化報酬率:0.07170432553125616\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1, 25, 2 年化報酬率:0.050839671467195924\n",
      "0.1, 25, 2.2 年化報酬率:0.07440538419555698\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:86: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dividend_table_one[\"西元日期\"] = pd.to_datetime(\n",
      "d:\\pythonProject\\台股網格自動化交易書\\grid_backtest.py:100: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value '3.2' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  self.position_table.loc[index, \"還原除權息\"] += row1[\"權值+息值\"]\n"
     ]
    }
   ],
   "source": [
    "# 紀錄最佳化績效\n",
    "trade_performance = []\n",
    "for i, j, k in [[i/100, j, k]\n",
    "                for i in range(2, 11, 2)\n",
    "                for j in [5, 20, 25]\n",
    "                for k in [1.6, 1.8, 2, 2.2]]:\n",
    "    # 設定初始部位(%數)\n",
    "    init_ratio = 50\n",
    "    # 設定網格間距\n",
    "    grid_gap = round(i, 2)\n",
    "    # 設定交易單位(%數)\n",
    "    grid_unit = j\n",
    "    # 初始部位是幾個交易單位\n",
    "    if init_ratio % grid_unit != 0:\n",
    "        print('錯誤！初始部位要可以被交易單位整除')\n",
    "    init_unit = int(init_ratio / grid_unit)\n",
    "    # 上漲跟下跌網格差距比率\n",
    "    up_down_grid_gap_diff = k\n",
    "\n",
    "    # 期初買入張數\n",
    "    init_time = data.index[0]\n",
    "    init_price = data.loc[data.index[0], 'open']\n",
    "    trade_position = trade(init_time, init_price, init_unit)\n",
    "    # 依照迴圈來跑網格\n",
    "    for index, row in data.iterrows():\n",
    "        # 優先執行比較差的狀況(賣出) 至少不會回測過度優化導致結果失真\n",
    "        while row['open'] >= init_price * (1+grid_gap*up_down_grid_gap_diff):\n",
    "            init_price *= (1+grid_gap*up_down_grid_gap_diff)\n",
    "            trade_position.cover(index, row['open'])\n",
    "        while row['high'] >= init_price * (1+grid_gap*up_down_grid_gap_diff):\n",
    "            init_price *= (1+grid_gap*up_down_grid_gap_diff)\n",
    "            trade_position.cover(index, init_price)\n",
    "        # 再考慮(買進)的情況\n",
    "        while row['open'] <= init_price * (1-grid_gap):\n",
    "            init_price *= (1-grid_gap)\n",
    "            if trade_position.position() < 100/grid_unit:\n",
    "                trade_position.order(index, row['open'])\n",
    "        while row['low'] <= init_price * (1-grid_gap):\n",
    "            init_price *= (1-grid_gap)\n",
    "            if trade_position.position() < 100/grid_unit:\n",
    "                trade_position.order(index, init_price)\n",
    "\n",
    "    # 最後一天的資料 要把所有部位先出場 檢查總績效\n",
    "    while trade_position.position() > 0:\n",
    "        trade_position.cover(index, row['close'])\n",
    "    # 報酬率計算\n",
    "    trade_position.restoreReturn(symbol)\n",
    "    position_table = trade_position.position_table\n",
    "    position_table['單筆報酬'] = (position_table['出場價格'] - position_table['進場價格'] +\n",
    "                              position_table['還原除權息'])\n",
    "    position_table['單筆報酬率'] = position_table['單筆報酬'] / \\\n",
    "        position_table['進場價格'] * (grid_unit/100)\n",
    "    total_return = (position_table['單筆報酬率']).sum() + 1\n",
    "    yearly_return = total_return ** (1/(data.shape[0]/252))-1\n",
    "    # 紀錄最佳化參數與績效\n",
    "    trade_performance.append([i, j, k, yearly_return])\n",
    "\n",
    "    print(f'{i}, {j}, {k} 年化報酬率:{yearly_return}')\n",
    "\n",
    "# 最佳化績效檢視\n",
    "pdf = pd.DataFrame(trade_performance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>網格間距</th>\n",
       "      <th>交易單位</th>\n",
       "      <th>上下網格差距比率</th>\n",
       "      <th>年化報酬率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.08</td>\n",
       "      <td>5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.099338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.08</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.096877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.08</td>\n",
       "      <td>5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.095890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.02</td>\n",
       "      <td>25</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.094901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.02</td>\n",
       "      <td>25</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.093953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.02</td>\n",
       "      <td>25</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.092275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.08</td>\n",
       "      <td>5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.092085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.06</td>\n",
       "      <td>5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.089348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.02</td>\n",
       "      <td>20</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.088372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.02</td>\n",
       "      <td>20</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.087899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.02</td>\n",
       "      <td>25</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.087778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.02</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.087393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.10</td>\n",
       "      <td>5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.087295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.06</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.087228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.10</td>\n",
       "      <td>5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.086840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.06</td>\n",
       "      <td>5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.085615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.10</td>\n",
       "      <td>5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.084816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.02</td>\n",
       "      <td>20</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.084690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.06</td>\n",
       "      <td>5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.083153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.10</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.082195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.10</td>\n",
       "      <td>20</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.077961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.04</td>\n",
       "      <td>5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.077753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.04</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.076023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.04</td>\n",
       "      <td>5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.075428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02</td>\n",
       "      <td>5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.075010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.02</td>\n",
       "      <td>5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.074914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02</td>\n",
       "      <td>5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.074833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.074765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.04</td>\n",
       "      <td>25</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.074740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.04</td>\n",
       "      <td>5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.074610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.08</td>\n",
       "      <td>25</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.074459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.10</td>\n",
       "      <td>25</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.074405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.08</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.074139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.08</td>\n",
       "      <td>20</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.073572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.08</td>\n",
       "      <td>20</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.073210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.04</td>\n",
       "      <td>25</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.072199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.06</td>\n",
       "      <td>20</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.072173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.02</td>\n",
       "      <td>5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.072030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.10</td>\n",
       "      <td>25</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.071704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.04</td>\n",
       "      <td>20</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.071136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.04</td>\n",
       "      <td>25</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.071105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.04</td>\n",
       "      <td>20</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.070655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.06</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.070537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.08</td>\n",
       "      <td>25</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.070187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.04</td>\n",
       "      <td>25</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.069933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.06</td>\n",
       "      <td>20</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.069864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.06</td>\n",
       "      <td>25</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.069727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.08</td>\n",
       "      <td>25</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.069132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.04</td>\n",
       "      <td>20</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.068935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.08</td>\n",
       "      <td>20</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.068914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.068163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.06</td>\n",
       "      <td>25</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.067921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.04</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.067888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.06</td>\n",
       "      <td>20</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.067754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.06</td>\n",
       "      <td>25</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.067136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.10</td>\n",
       "      <td>25</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.066856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.06</td>\n",
       "      <td>25</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.066045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.08</td>\n",
       "      <td>25</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.064007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.10</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.058106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.10</td>\n",
       "      <td>25</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.050840</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    網格間距  交易單位  上下網格差距比率     年化報酬率\n",
       "39  0.08     5       2.2  0.099338\n",
       "38  0.08     5       2.0  0.096877\n",
       "37  0.08     5       1.8  0.095890\n",
       "9   0.02    25       1.8  0.094901\n",
       "8   0.02    25       1.6  0.093953\n",
       "10  0.02    25       2.0  0.092275\n",
       "36  0.08     5       1.6  0.092085\n",
       "27  0.06     5       2.2  0.089348\n",
       "5   0.02    20       1.8  0.088372\n",
       "4   0.02    20       1.6  0.087899\n",
       "11  0.02    25       2.2  0.087778\n",
       "6   0.02    20       2.0  0.087393\n",
       "48  0.10     5       1.6  0.087295\n",
       "26  0.06     5       2.0  0.087228\n",
       "49  0.10     5       1.8  0.086840\n",
       "25  0.06     5       1.8  0.085615\n",
       "51  0.10     5       2.2  0.084816\n",
       "7   0.02    20       2.2  0.084690\n",
       "24  0.06     5       1.6  0.083153\n",
       "50  0.10     5       2.0  0.082195\n",
       "55  0.10    20       2.2  0.077961\n",
       "15  0.04     5       2.2  0.077753\n",
       "14  0.04     5       2.0  0.076023\n",
       "13  0.04     5       1.8  0.075428\n",
       "2   0.02     5       2.0  0.075010\n",
       "3   0.02     5       2.2  0.074914\n",
       "1   0.02     5       1.8  0.074833\n",
       "53  0.10    20       1.8  0.074765\n",
       "20  0.04    25       1.6  0.074740\n",
       "12  0.04     5       1.6  0.074610\n",
       "44  0.08    25       1.6  0.074459\n",
       "59  0.10    25       2.2  0.074405\n",
       "42  0.08    20       2.0  0.074139\n",
       "40  0.08    20       1.6  0.073572\n",
       "43  0.08    20       2.2  0.073210\n",
       "23  0.04    25       2.2  0.072199\n",
       "31  0.06    20       2.2  0.072173\n",
       "0   0.02     5       1.6  0.072030\n",
       "57  0.10    25       1.8  0.071704\n",
       "16  0.04    20       1.6  0.071136\n",
       "21  0.04    25       1.8  0.071105\n",
       "19  0.04    20       2.2  0.070655\n",
       "30  0.06    20       2.0  0.070537\n",
       "47  0.08    25       2.2  0.070187\n",
       "22  0.04    25       2.0  0.069933\n",
       "28  0.06    20       1.6  0.069864\n",
       "35  0.06    25       2.2  0.069727\n",
       "46  0.08    25       2.0  0.069132\n",
       "17  0.04    20       1.8  0.068935\n",
       "41  0.08    20       1.8  0.068914\n",
       "52  0.10    20       1.6  0.068163\n",
       "34  0.06    25       2.0  0.067921\n",
       "18  0.04    20       2.0  0.067888\n",
       "29  0.06    20       1.8  0.067754\n",
       "32  0.06    25       1.6  0.067136\n",
       "56  0.10    25       1.6  0.066856\n",
       "33  0.06    25       1.8  0.066045\n",
       "45  0.08    25       1.8  0.064007\n",
       "54  0.10    20       2.0  0.058106\n",
       "58  0.10    25       2.0  0.050840"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m在目前儲存格或上一個儲存格中執行程式碼時，Kernel 已損毀。\n",
      "\u001b[1;31m請檢閱儲存格中的程式碼，找出失敗的可能原因。\n",
      "\u001b[1;31m如需詳細資訊，請按一下<a href='https://aka.ms/vscodeJupyterKernelCrash'>這裡</a>。\n",
      "\u001b[1;31m如需詳細資料，請檢視 Jupyter <a href='command:jupyter.viewOutput'>記錄</a>。"
     ]
    }
   ],
   "source": [
    "pdf.columns = ['網格間距', '交易單位', '上下網格差距比率', '年化報酬率']\n",
    "pdf.sort_values(by='年化報酬率', ascending=False, inplace=True)\n",
    "pdf"
   ]
  }
 ],
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