example/TQ_布林通道交易策略.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "85743b0c",
   "metadata": {},
   "source": [
    "# 布林通道實戰\n",
    "\n",
    "## 交易邏輯\n",
    "\n",
    "* 根據統計學的常態分佈理論，有 95.44% 的樣本都會位於正負兩個標準差這個區間，因此當股價超出這區間時，產生反轉的機率會大幅上升。\n",
    "* 我們可以把移動平均、正二標準差、負二標準差，轉換成中軌、上軌、下軌\n",
    "\n",
    "## 交易策略\n",
    "\n",
    "* 當今天的收盤價觸碰到上軌且持有部位時，隔日賣出。\n",
    "* 當今天的收盤價觸碰到下軌且現金部位大於零時，隔日買入。\n",
    "* 當今天的收盤價觸碰到下軌、現金部位大於零且當日收盤價低於上次買入訊號收盤價時，隔日加碼一單位。\n",
    "\n",
    "## 資料來源\n",
    "\n",
    "[布林通道交易策略](https://www.tejwin.com/insight/%e5%b8%83%e6%9e%97%e9%80%9a%e9%81%93%e4%ba%a4%e6%98%93%e7%ad%96%e7%95%a5/)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ad4d0b7",
   "metadata": {},
   "source": [
    "## 編輯交易策略\n",
    "\n",
    "### 載入所需套件與輸入資料"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "af2cb3dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Merging daily equity files:\n",
      "Currently used TEJ API key call quota 495/9223372036854775807 (0.0%)\n",
      "Currently used TEJ API key data quota 61089856/9223372036854775807 (0.0%)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2024-02-07 03:24:48.623366] INFO: zipline.data.bundles.core: Ingesting tquant.\n",
      "[2024-02-07 03:24:52.381719] INFO: zipline.data.bundles.core: Ingest tquant successfully.\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "import tejapi\n",
    "import os \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "os.environ['TEJAPI_BASE'] = 'https://api.tej.com.tw'\n",
    "os.environ['TEJAPI_KEY'] = 'YOUR KEY'\n",
    "os.environ['mdate'] = '20210401 20221231'\n",
    "os.environ['ticker'] = '2409'\n",
    "\n",
    "# 使用 ingest 將股價資料導入暫存，並且命名該股票組合 (bundle) 為 tquant\n",
    "!zipline ingest -b tquant "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "defc2ee8",
   "metadata": {},
   "source": [
    "### 載入所需套件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a491743c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.api import set_slippage, set_commission, set_benchmark, attach_pipeline, order, order_target, symbol, pipeline_output, record\n",
    "from zipline.finance import commission, slippage\n",
    "from zipline.data import bundles\n",
    "from zipline import run_algorithm\n",
    "from zipline.pipeline import Pipeline\n",
    "from zipline.pipeline.filters import StaticAssets\n",
    "from zipline.pipeline.factors import BollingerBands\n",
    "from zipline.pipeline.data import EquityPricing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "863bf5f4",
   "metadata": {},
   "source": [
    "### 建立 Pipeline 函式\n",
    "\n",
    "`Pipeline()` 提供使用者快速處理多檔標的的量化指標與價量資料的功能，於本次案例我們用以處理:\n",
    "\n",
    "* 過去 20 日布林通道上軌\n",
    "* 過去 20 日布林通道中軌\n",
    "* 過去 20 日布林通道下軌\n",
    "* 當期收盤價"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ff0d96fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_pipeline():\n",
    "    \n",
    "    perf = BollingerBands(inputs=[EquityPricing.close], window_length=20, k=2)\n",
    "    upper,middle,lower = perf.upper,perf.middle, perf.lower\n",
    "    curr_price = EquityPricing.close.latest\n",
    "     \n",
    "    return Pipeline(\n",
    "        columns = {\n",
    "            'upper':  upper,\n",
    "            'middle':  middle,\n",
    "            'lower':  lower,\n",
    "            'curr_price':curr_price\n",
    "        }\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71a457f6",
   "metadata": {},
   "source": [
    "### 建立 initialize 函式\n",
    "\n",
    "`inintialize` 函式用於定義交易開始前的每日交易環境，與此例中我們設置:\n",
    "\n",
    "* 流動性滑價\n",
    "* 交易手續費\n",
    "* 買入持有友達的報酬作為基準\n",
    "* 將 Pipeline 導入交易流程中\n",
    "* 設定 __context.last_signal_price__ 紀錄上次買入訊號的收盤價"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bfe9965e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def initialize(context):\n",
    "    context.last_buy_price = 0\n",
    "    set_slippage(slippage.VolumeShareSlippage())\n",
    "    set_commission(commission.PerShare(cost=0.00285))\n",
    "    set_benchmark(symbol('2409'))\n",
    "    attach_pipeline(make_pipeline(), 'mystrategy')\n",
    "    context.last_signal_price = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce1d1f77",
   "metadata": {},
   "source": [
    "### 建立 handle_date 函式\n",
    "\n",
    "`handle_data` 函式用於處理每天的交易策略或行動。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "28f5019c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def handle_data(context, data):\n",
    "    out_dir = pipeline_output('mystrategy')\n",
    "    for i in out_dir.index: \n",
    "        upper = out_dir.loc[i, 'upper']\n",
    "        middle = out_dir.loc[i, 'middle']\n",
    "        lower = out_dir.loc[i, 'lower']\n",
    "        curr_price = out_dir.loc[i, 'curr_price']\n",
    "        cash_position = context.portfolio.cash\n",
    "        stock_position = context.portfolio.positions[i].amount\n",
    "        \n",
    "        buy, sell = False, False\n",
    "        record(price = curr_price, upper = upper, lower = lower, buy = buy, sell = sell)\n",
    "        \n",
    "        if stock_position == 0:\n",
    "            if (curr_price <= lower) and (cash_position >= curr_price * 1000):\n",
    "                order(i, 1000)\n",
    "                context.last_signal_price = curr_price\n",
    "                buy = True\n",
    "                record(buy = buy)\n",
    "        elif stock_position > 0:\n",
    "            if (curr_price <= lower) and (curr_price <= context.last_signal_price) and (cash_position >= curr_price * 1000):\n",
    "                order(i, 1000)\n",
    "                context.last_signal_price = curr_price\n",
    "                buy = True\n",
    "                record(buy = buy)\n",
    "            elif (curr_price >= upper):\n",
    "                order_target(i, 0)\n",
    "                context.last_signal_price = 0\n",
    "                sell = True\n",
    "                record(sell = sell)\n",
    "            else:\n",
    "                pass\n",
    "        else:\n",
    "            pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "538c14e2",
   "metadata": {},
   "source": [
    "### 建立 analyze 函式\n",
    "\n",
    "多半用於繪製績效圖表，於本案例使用 matplotlib 將視覺化買賣點與投組價值變化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "82a399a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def analyze(context, perf):\n",
    "    fig = plt.figure()\n",
    "    ax1 = fig.add_subplot(211)\n",
    "    perf.portfolio_value.plot(ax=ax1)\n",
    "    ax1.set_ylabel(\"Portfolio value (NTD)\")\n",
    "    ax2 = fig.add_subplot(212)\n",
    "    ax2.set_ylabel(\"Price (NTD)\")\n",
    "    perf.price.plot(ax=ax2)\n",
    "    perf.upper.plot(ax=ax2)\n",
    "    perf.lower.plot(ax=ax2)\n",
    "    ax2.plot( # 繪製買入訊號\n",
    "        perf.index[perf.buy],\n",
    "        perf.loc[perf.buy, 'price'],\n",
    "        '^',\n",
    "        markersize=5,\n",
    "        color='red'\n",
    "    )\n",
    "    ax2.plot( # 繪製賣出訊號\n",
    "        perf.index[perf.sell],\n",
    "        perf.loc[perf.sell, 'price'],\n",
    "        'v',\n",
    "        markersize=5,\n",
    "        color='green'\n",
    "    )\n",
    "    plt.legend(loc=0)\n",
    "    plt.gcf().set_size_inches(18,8)\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36336fc8",
   "metadata": {},
   "source": [
    "## 執行交易策略\n",
    "\n",
    "使用 `run_algorithm` 執行上述所編撰的交易策略，設置交易期間為 2021-06-01 到 2022-12-31，所使用資料集為 *tquant*，初始資金為 500,000 元。其中輸出的 __results__ 就是每日績效與交易的明細表。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4afa5e8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<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>period_open</th>\n",
       "      <th>period_close</th>\n",
       "      <th>positions</th>\n",
       "      <th>shorts_count</th>\n",
       "      <th>long_value</th>\n",
       "      <th>returns</th>\n",
       "      <th>short_value</th>\n",
       "      <th>ending_exposure</th>\n",
       "      <th>long_exposure</th>\n",
       "      <th>starting_exposure</th>\n",
       "      <th>...</th>\n",
       "      <th>sharpe</th>\n",
       "      <th>sortino</th>\n",
       "      <th>benchmark_period_return</th>\n",
       "      <th>excess_return</th>\n",
       "      <th>benchmark_volatility</th>\n",
       "      <th>max_drawdown</th>\n",
       "      <th>max_leverage</th>\n",
       "      <th>trading_days</th>\n",
       "      <th>period_label</th>\n",
       "      <th>treasury_period_return</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-06-01 13:30:00+08:00</th>\n",
       "      <td>2021-06-01 09:01:00+08:00</td>\n",
       "      <td>2021-06-01 13:30:00+08:00</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.005791</td>\n",
       "      <td>0.005791</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-02 13:30:00+08:00</th>\n",
       "      <td>2021-06-02 09:01:00+08:00</td>\n",
       "      <td>2021-06-02 13:30:00+08:00</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.034823</td>\n",
       "      <td>0.034823</td>\n",
       "      <td>0.262782</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-03 13:30:00+08:00</th>\n",
       "      <td>2021-06-03 09:01:00+08:00</td>\n",
       "      <td>2021-06-03 13:30:00+08:00</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.038671</td>\n",
       "      <td>0.038671</td>\n",
       "      <td>0.223289</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-04 13:30:00+08:00</th>\n",
       "      <td>2021-06-04 09:01:00+08:00</td>\n",
       "      <td>2021-06-04 13:30:00+08:00</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.056082</td>\n",
       "      <td>0.056082</td>\n",
       "      <td>0.186788</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-07 13:30:00+08:00</th>\n",
       "      <td>2021-06-07 09:01:00+08:00</td>\n",
       "      <td>2021-06-07 13:30:00+08:00</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.021259</td>\n",
       "      <td>0.021259</td>\n",
       "      <td>0.397626</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5</td>\n",
       "      <td>2021-06</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-26 13:30:00+08:00</th>\n",
       "      <td>2022-12-26 09:01:00+08:00</td>\n",
       "      <td>2022-12-26 13:30:00+08:00</td>\n",
       "      <td>[{'sid': Equity(0 [2409]), 'amount': 6000, 'co...</td>\n",
       "      <td>0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>0.001169</td>\n",
       "      <td>0.0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>92400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.420172</td>\n",
       "      <td>0.647045</td>\n",
       "      <td>-0.397590</td>\n",
       "      <td>0.425293</td>\n",
       "      <td>0.413922</td>\n",
       "      <td>-0.056005</td>\n",
       "      <td>0.270017</td>\n",
       "      <td>391</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-27 13:30:00+08:00</th>\n",
       "      <td>2022-12-27 09:01:00+08:00</td>\n",
       "      <td>2022-12-27 13:30:00+08:00</td>\n",
       "      <td>[{'sid': Equity(0 [2409]), 'amount': 6000, 'co...</td>\n",
       "      <td>0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.419636</td>\n",
       "      <td>0.646220</td>\n",
       "      <td>-0.397590</td>\n",
       "      <td>0.425293</td>\n",
       "      <td>0.413393</td>\n",
       "      <td>-0.056005</td>\n",
       "      <td>0.270017</td>\n",
       "      <td>392</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-28 13:30:00+08:00</th>\n",
       "      <td>2022-12-28 09:01:00+08:00</td>\n",
       "      <td>2022-12-28 13:30:00+08:00</td>\n",
       "      <td>[{'sid': Equity(0 [2409]), 'amount': 6000, 'co...</td>\n",
       "      <td>0</td>\n",
       "      <td>90900.0</td>\n",
       "      <td>-0.004087</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90900.0</td>\n",
       "      <td>90900.0</td>\n",
       "      <td>93000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.358691</td>\n",
       "      <td>0.550359</td>\n",
       "      <td>-0.411193</td>\n",
       "      <td>0.434696</td>\n",
       "      <td>0.413228</td>\n",
       "      <td>-0.056005</td>\n",
       "      <td>0.270017</td>\n",
       "      <td>393</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-29 13:30:00+08:00</th>\n",
       "      <td>2022-12-29 09:01:00+08:00</td>\n",
       "      <td>2022-12-29 13:30:00+08:00</td>\n",
       "      <td>[{'sid': Equity(0 [2409]), 'amount': 6000, 'co...</td>\n",
       "      <td>0</td>\n",
       "      <td>90600.0</td>\n",
       "      <td>-0.000586</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90600.0</td>\n",
       "      <td>90600.0</td>\n",
       "      <td>90900.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.349728</td>\n",
       "      <td>0.536571</td>\n",
       "      <td>-0.413136</td>\n",
       "      <td>0.436039</td>\n",
       "      <td>0.412706</td>\n",
       "      <td>-0.056005</td>\n",
       "      <td>0.270017</td>\n",
       "      <td>394</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-30 13:30:00+08:00</th>\n",
       "      <td>2022-12-30 09:01:00+08:00</td>\n",
       "      <td>2022-12-30 13:30:00+08:00</td>\n",
       "      <td>[{'sid': Equity(0 [2409]), 'amount': 6000, 'co...</td>\n",
       "      <td>0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>-0.001173</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>90600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.332247</td>\n",
       "      <td>0.509606</td>\n",
       "      <td>-0.417023</td>\n",
       "      <td>0.438726</td>\n",
       "      <td>0.412207</td>\n",
       "      <td>-0.056005</td>\n",
       "      <td>0.270017</td>\n",
       "      <td>395</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>395 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        period_open              period_close  \\\n",
       "2021-06-01 13:30:00+08:00 2021-06-01 09:01:00+08:00 2021-06-01 13:30:00+08:00   \n",
       "2021-06-02 13:30:00+08:00 2021-06-02 09:01:00+08:00 2021-06-02 13:30:00+08:00   \n",
       "2021-06-03 13:30:00+08:00 2021-06-03 09:01:00+08:00 2021-06-03 13:30:00+08:00   \n",
       "2021-06-04 13:30:00+08:00 2021-06-04 09:01:00+08:00 2021-06-04 13:30:00+08:00   \n",
       "2021-06-07 13:30:00+08:00 2021-06-07 09:01:00+08:00 2021-06-07 13:30:00+08:00   \n",
       "...                                             ...                       ...   \n",
       "2022-12-26 13:30:00+08:00 2022-12-26 09:01:00+08:00 2022-12-26 13:30:00+08:00   \n",
       "2022-12-27 13:30:00+08:00 2022-12-27 09:01:00+08:00 2022-12-27 13:30:00+08:00   \n",
       "2022-12-28 13:30:00+08:00 2022-12-28 09:01:00+08:00 2022-12-28 13:30:00+08:00   \n",
       "2022-12-29 13:30:00+08:00 2022-12-29 09:01:00+08:00 2022-12-29 13:30:00+08:00   \n",
       "2022-12-30 13:30:00+08:00 2022-12-30 09:01:00+08:00 2022-12-30 13:30:00+08:00   \n",
       "\n",
       "                                                                   positions  \\\n",
       "2021-06-01 13:30:00+08:00                                                 []   \n",
       "2021-06-02 13:30:00+08:00                                                 []   \n",
       "2021-06-03 13:30:00+08:00                                                 []   \n",
       "2021-06-04 13:30:00+08:00                                                 []   \n",
       "2021-06-07 13:30:00+08:00                                                 []   \n",
       "...                                                                      ...   \n",
       "2022-12-26 13:30:00+08:00  [{'sid': Equity(0 [2409]), 'amount': 6000, 'co...   \n",
       "2022-12-27 13:30:00+08:00  [{'sid': Equity(0 [2409]), 'amount': 6000, 'co...   \n",
       "2022-12-28 13:30:00+08:00  [{'sid': Equity(0 [2409]), 'amount': 6000, 'co...   \n",
       "2022-12-29 13:30:00+08:00  [{'sid': Equity(0 [2409]), 'amount': 6000, 'co...   \n",
       "2022-12-30 13:30:00+08:00  [{'sid': Equity(0 [2409]), 'amount': 6000, 'co...   \n",
       "\n",
       "                           shorts_count  long_value   returns  short_value  \\\n",
       "2021-06-01 13:30:00+08:00             0         0.0  0.000000          0.0   \n",
       "2021-06-02 13:30:00+08:00             0         0.0  0.000000          0.0   \n",
       "2021-06-03 13:30:00+08:00             0         0.0  0.000000          0.0   \n",
       "2021-06-04 13:30:00+08:00             0         0.0  0.000000          0.0   \n",
       "2021-06-07 13:30:00+08:00             0         0.0  0.000000          0.0   \n",
       "...                                 ...         ...       ...          ...   \n",
       "2022-12-26 13:30:00+08:00             0     93000.0  0.001169          0.0   \n",
       "2022-12-27 13:30:00+08:00             0     93000.0  0.000000          0.0   \n",
       "2022-12-28 13:30:00+08:00             0     90900.0 -0.004087          0.0   \n",
       "2022-12-29 13:30:00+08:00             0     90600.0 -0.000586          0.0   \n",
       "2022-12-30 13:30:00+08:00             0     90000.0 -0.001173          0.0   \n",
       "\n",
       "                           ending_exposure  long_exposure  starting_exposure  \\\n",
       "2021-06-01 13:30:00+08:00              0.0            0.0                0.0   \n",
       "2021-06-02 13:30:00+08:00              0.0            0.0                0.0   \n",
       "2021-06-03 13:30:00+08:00              0.0            0.0                0.0   \n",
       "2021-06-04 13:30:00+08:00              0.0            0.0                0.0   \n",
       "2021-06-07 13:30:00+08:00              0.0            0.0                0.0   \n",
       "...                                    ...            ...                ...   \n",
       "2022-12-26 13:30:00+08:00          93000.0        93000.0            92400.0   \n",
       "2022-12-27 13:30:00+08:00          93000.0        93000.0            93000.0   \n",
       "2022-12-28 13:30:00+08:00          90900.0        90900.0            93000.0   \n",
       "2022-12-29 13:30:00+08:00          90600.0        90600.0            90900.0   \n",
       "2022-12-30 13:30:00+08:00          90000.0        90000.0            90600.0   \n",
       "\n",
       "                           ...    sharpe   sortino benchmark_period_return  \\\n",
       "2021-06-01 13:30:00+08:00  ...       NaN       NaN               -0.005791   \n",
       "2021-06-02 13:30:00+08:00  ...       NaN       NaN               -0.034823   \n",
       "2021-06-03 13:30:00+08:00  ...       NaN       NaN               -0.038671   \n",
       "2021-06-04 13:30:00+08:00  ...       NaN       NaN               -0.056082   \n",
       "2021-06-07 13:30:00+08:00  ...       NaN       NaN               -0.021259   \n",
       "...                        ...       ...       ...                     ...   \n",
       "2022-12-26 13:30:00+08:00  ...  0.420172  0.647045               -0.397590   \n",
       "2022-12-27 13:30:00+08:00  ...  0.419636  0.646220               -0.397590   \n",
       "2022-12-28 13:30:00+08:00  ...  0.358691  0.550359               -0.411193   \n",
       "2022-12-29 13:30:00+08:00  ...  0.349728  0.536571               -0.413136   \n",
       "2022-12-30 13:30:00+08:00  ...  0.332247  0.509606               -0.417023   \n",
       "\n",
       "                           excess_return  benchmark_volatility  max_drawdown  \\\n",
       "2021-06-01 13:30:00+08:00       0.005791                   NaN      0.000000   \n",
       "2021-06-02 13:30:00+08:00       0.034823              0.262782      0.000000   \n",
       "2021-06-03 13:30:00+08:00       0.038671              0.223289      0.000000   \n",
       "2021-06-04 13:30:00+08:00       0.056082              0.186788      0.000000   \n",
       "2021-06-07 13:30:00+08:00       0.021259              0.397626      0.000000   \n",
       "...                                  ...                   ...           ...   \n",
       "2022-12-26 13:30:00+08:00       0.425293              0.413922     -0.056005   \n",
       "2022-12-27 13:30:00+08:00       0.425293              0.413393     -0.056005   \n",
       "2022-12-28 13:30:00+08:00       0.434696              0.413228     -0.056005   \n",
       "2022-12-29 13:30:00+08:00       0.436039              0.412706     -0.056005   \n",
       "2022-12-30 13:30:00+08:00       0.438726              0.412207     -0.056005   \n",
       "\n",
       "                           max_leverage  trading_days  period_label  \\\n",
       "2021-06-01 13:30:00+08:00      0.000000             1       2021-06   \n",
       "2021-06-02 13:30:00+08:00      0.000000             2       2021-06   \n",
       "2021-06-03 13:30:00+08:00      0.000000             3       2021-06   \n",
       "2021-06-04 13:30:00+08:00      0.000000             4       2021-06   \n",
       "2021-06-07 13:30:00+08:00      0.000000             5       2021-06   \n",
       "...                                 ...           ...           ...   \n",
       "2022-12-26 13:30:00+08:00      0.270017           391       2022-12   \n",
       "2022-12-27 13:30:00+08:00      0.270017           392       2022-12   \n",
       "2022-12-28 13:30:00+08:00      0.270017           393       2022-12   \n",
       "2022-12-29 13:30:00+08:00      0.270017           394       2022-12   \n",
       "2022-12-30 13:30:00+08:00      0.270017           395       2022-12   \n",
       "\n",
       "                           treasury_period_return  \n",
       "2021-06-01 13:30:00+08:00                     0.0  \n",
       "2021-06-02 13:30:00+08:00                     0.0  \n",
       "2021-06-03 13:30:00+08:00                     0.0  \n",
       "2021-06-04 13:30:00+08:00                     0.0  \n",
       "2021-06-07 13:30:00+08:00                     0.0  \n",
       "...                                           ...  \n",
       "2022-12-26 13:30:00+08:00                     0.0  \n",
       "2022-12-27 13:30:00+08:00                     0.0  \n",
       "2022-12-28 13:30:00+08:00                     0.0  \n",
       "2022-12-29 13:30:00+08:00                     0.0  \n",
       "2022-12-30 13:30:00+08:00                     0.0  \n",
       "\n",
       "[395 rows x 44 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = run_algorithm(\n",
    "    start = pd.Timestamp('2021-06-01', tz='UTC'),\n",
    "    end = pd.Timestamp('2022-12-31', tz ='UTC'),\n",
    "    initialize=initialize,\n",
    "    bundle='tquant',\n",
    "    analyze=analyze,\n",
    "    capital_base=5e5,\n",
    "    handle_data = handle_data\n",
    ")\n",
    "\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77a2f011",
   "metadata": {},
   "source": [
    "## 績效評估\n",
    "\n",
    "使用 `extract_rets_pos_txn_from_zipline()` 計算報酬、部位與交易紀錄。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aa8a20fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyfolio as pf \n",
    "returns, positions, transactions = pf.utils.extract_rets_pos_txn_from_zipline(results)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85468ce9",
   "metadata": {},
   "source": [
    "### 報酬紀錄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0b3362a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2022-12-26 00:00:00+00:00    0.001169\n",
       "2022-12-27 00:00:00+00:00    0.000000\n",
       "2022-12-28 00:00:00+00:00   -0.004087\n",
       "2022-12-29 00:00:00+00:00   -0.000586\n",
       "2022-12-30 00:00:00+00:00   -0.001173\n",
       "Name: returns, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75de1559",
   "metadata": {},
   "source": [
    "### 部位紀錄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "76af3c51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>sid</th>\n",
       "      <th>Equity(0 [2409])</th>\n",
       "      <th>cash</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-07-16 00:00:00+00:00</th>\n",
       "      <td>21350.0</td>\n",
       "      <td>478647.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-19 00:00:00+00:00</th>\n",
       "      <td>20900.0</td>\n",
       "      <td>478647.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-20 00:00:00+00:00</th>\n",
       "      <td>20100.0</td>\n",
       "      <td>478647.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-21 00:00:00+00:00</th>\n",
       "      <td>19150.0</td>\n",
       "      <td>478647.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-22 00:00:00+00:00</th>\n",
       "      <td>39400.0</td>\n",
       "      <td>458944.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sid                        Equity(0 [2409])       cash\n",
       "index                                                 \n",
       "2021-07-16 00:00:00+00:00           21350.0  478647.15\n",
       "2021-07-19 00:00:00+00:00           20900.0  478647.15\n",
       "2021-07-20 00:00:00+00:00           20100.0  478647.15\n",
       "2021-07-21 00:00:00+00:00           19150.0  478647.15\n",
       "2021-07-22 00:00:00+00:00           39400.0  458944.30"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "positions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b938283",
   "metadata": {},
   "source": [
    "### 交易紀錄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "db0908ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sid</th>\n",
       "      <th>symbol</th>\n",
       "      <th>price</th>\n",
       "      <th>order_id</th>\n",
       "      <th>amount</th>\n",
       "      <th>commission</th>\n",
       "      <th>dt</th>\n",
       "      <th>txn_dollars</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-07-16 05:30:00+00:00</th>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>21.35</td>\n",
       "      <td>a9664465c62b48c9b2be0f059620d1e5</td>\n",
       "      <td>1000</td>\n",
       "      <td>None</td>\n",
       "      <td>2021-07-16 13:30:00+08:00</td>\n",
       "      <td>-21350.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-22 05:30:00+00:00</th>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>19.70</td>\n",
       "      <td>c0cd13a325f846d2aee3ed09fe88f554</td>\n",
       "      <td>1000</td>\n",
       "      <td>None</td>\n",
       "      <td>2021-07-22 13:30:00+08:00</td>\n",
       "      <td>-19700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-23 05:30:00+00:00</th>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>20.70</td>\n",
       "      <td>ee53128741e44b6089ac5a342713a8df</td>\n",
       "      <td>1000</td>\n",
       "      <td>None</td>\n",
       "      <td>2021-07-23 13:30:00+08:00</td>\n",
       "      <td>-20700.000000</td>\n",
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       "    <tr>\n",
       "      <th>2021-08-06 05:30:00+00:00</th>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>21.60</td>\n",
       "      <td>680e5c45e8c948a8998c0b1defbb5aac</td>\n",
       "      <td>-3000</td>\n",
       "      <td>None</td>\n",
       "      <td>2021-08-06 13:30:00+08:00</td>\n",
       "      <td>64799.999998</td>\n",
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       "    <tr>\n",
       "      <th>2021-08-24 05:30:00+00:00</th>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>Equity(0 [2409])</td>\n",
       "      <td>17.80</td>\n",
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       "      <td>1000</td>\n",
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       "      <td>2021-08-24 13:30:00+08:00</td>\n",
       "      <td>-17800.000000</td>\n",
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      "text/plain": [
       "                                        sid            symbol  price  \\\n",
       "2021-07-16 05:30:00+00:00  Equity(0 [2409])  Equity(0 [2409])  21.35   \n",
       "2021-07-22 05:30:00+00:00  Equity(0 [2409])  Equity(0 [2409])  19.70   \n",
       "2021-07-23 05:30:00+00:00  Equity(0 [2409])  Equity(0 [2409])  20.70   \n",
       "2021-08-06 05:30:00+00:00  Equity(0 [2409])  Equity(0 [2409])  21.60   \n",
       "2021-08-24 05:30:00+00:00  Equity(0 [2409])  Equity(0 [2409])  17.80   \n",
       "\n",
       "                                                   order_id  amount  \\\n",
       "2021-07-16 05:30:00+00:00  a9664465c62b48c9b2be0f059620d1e5    1000   \n",
       "2021-07-22 05:30:00+00:00  c0cd13a325f846d2aee3ed09fe88f554    1000   \n",
       "2021-07-23 05:30:00+00:00  ee53128741e44b6089ac5a342713a8df    1000   \n",
       "2021-08-06 05:30:00+00:00  680e5c45e8c948a8998c0b1defbb5aac   -3000   \n",
       "2021-08-24 05:30:00+00:00  c334592463f34ad9b9dac1f4aa91862b    1000   \n",
       "\n",
       "                          commission                        dt   txn_dollars  \n",
       "2021-07-16 05:30:00+00:00       None 2021-07-16 13:30:00+08:00 -21350.000000  \n",
       "2021-07-22 05:30:00+00:00       None 2021-07-22 13:30:00+08:00 -19700.000000  \n",
       "2021-07-23 05:30:00+00:00       None 2021-07-23 13:30:00+08:00 -20700.000000  \n",
       "2021-08-06 05:30:00+00:00       None 2021-08-06 13:30:00+08:00  64799.999998  \n",
       "2021-08-24 05:30:00+00:00       None 2021-08-24 13:30:00+08:00 -17800.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16d05987",
   "metadata": {},
   "source": [
    "### 繪製基準 (benchmark) 與投組累積報酬率\n",
    "\n",
    "使用 `plot_rolling_returns()` 繪製，本案例的基準為友達買入持有。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0d612a0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "benchmark_rets = results['benchmark_return'] "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e27b36b",
   "metadata": {},
   "source": [
    "### 製作績效表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c2ecd3a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\"><th>Start date</th><td colspan=2>2021-06-01</td></tr>\n",
       "    <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2022-12-30</td></tr>\n",
       "    <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>18</td></tr>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Backtest</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Annual return</th>\n",
       "      <td>1.379%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cumulative returns</th>\n",
       "      <td>2.17%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Annual volatility</th>\n",
       "      <td>4.415%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sharpe ratio</th>\n",
       "      <td>0.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Calmar ratio</th>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stability</th>\n",
       "      <td>0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Max drawdown</th>\n",
       "      <td>-5.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Omega ratio</th>\n",
       "      <td>1.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sortino ratio</th>\n",
       "      <td>0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Skew</th>\n",
       "      <td>0.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kurtosis</th>\n",
       "      <td>9.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tail ratio</th>\n",
       "      <td>1.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily value at risk</th>\n",
       "      <td>-0.55%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gross leverage</th>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily turnover</th>\n",
       "      <td>5.361%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alpha</th>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beta</th>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "perf_stats = pf.plotting.show_perf_stats(\n",
    "        returns,\n",
    "        benchmark_rets,\n",
    "        positions=positions,\n",
    "        transactions=transactions)"
   ]
  }
 ],
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