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tej87681088/Google Colab 教學.ipynb

Last active July 31, 2024 01:56
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Google Colab 教學.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kgkWnkM7I4DO",
"outputId": "9e726e14-0995-48ac-ccf3-de1187161b10"
},
"outputs": [],
"source": [
"!pip install zipline-tej"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Q8OeTtQ5Rv4M"
},
"source": [
"### **因為版本相容問題，我們必須將 pandas 的版本改成1.5.3版，並且無須理會安裝完的 Error 。**\n",
"**（因應近期 Google Colab 改版，需要新增 dask 降版指令）**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Y5JqL6aPV7__",
"outputId": "e9155ba6-500d-4003-8390-0a7b8d9a6ea2"
},
"outputs": [],
"source": [
"!pip install pandas==1.5.3\n",
"!pip install dask==2.30.0 # dask降版"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "p7bkvcMqSLJP"
},
"source": [
"### **到這個步驟已經可以正常使用了，我們會用一個簡單的小例子來展示結果，先載入常用套件，並輸入 TEJAPI_KEY 。**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "2XHMhXbEGwN3"
},
"outputs": [],
"source": [
"import os\n",
"os.environ['TEJAPI_BASE'] = 'https://api.tej.com.tw'\n",
"os.environ['TEJAPI_KEY'] = 'Your_Key'\n",
"\n",
"import datetime\n",
"\n",
"import tejapi\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "LoGeXgKWa5qF"
},
"outputs": [],
"source": [
"from zipline.sources.TEJ_Api_Data import get_universe"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "U4k_hhOmTCsa"
},
"source": [
"### **選出有興趣的公司，這邊先篩選為半導體或電腦產業別的上市公司**"
]
},
{
"cell_type": "code",
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"outputId": "58a3de1e-1b1e-4a2e-eb11-f1153f315063"
},
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{
"name": "stdout",
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"Currently used TEJ API key call quota 5/9223372036854775807 (0.0%)\n",
"Currently used TEJ API key data quota 41888/9223372036854775807 (0.0%)\n"
]
},
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"source": [
"pool = get_universe(start = '2023-07-02',\n",
" end = '2024-07-02',\n",
" mkt_bd_e = 'TSE', # 已上市之股票\n",
" stktp_e = 'Common Stock', # 普通股\n",
" sub_ind_e=['M2324 Semiconductor', 'M2325 Computer and Peripheral Equipment'])\n",
"pool"
]
},
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"0 2301 2024-07-02 M2300 電子工業 20.8186 20.32 -8539994.0 54.57 \n",
"1 2302 2024-07-02 M2300 電子工業 35.6755 37.43 2849.0 25.93 \n",
"2 2303 2024-07-02 M2300 電子工業 11.8023 30.93 -29914635.0 33.30 \n",
"3 2305 2024-07-02 M2300 電子工業 243.9021 32.48 126270.0 21.83 \n",
"4 2324 2024-07-02 M2300 電子工業 17.8337 4.91 -2205331.0 70.01 \n",
".. ... ... ... ... ... ... ... \n",
"131 8163 2024-07-02 M2300 電子工業 212.9516 19.12 429411.0 55.27 \n",
"132 8210 2024-07-02 M2300 電子工業 24.9009 24.83 -305706.0 54.81 \n",
"133 8261 2024-07-02 M2300 電子工業 29.1586 18.19 -421234.0 8.40 \n",
"134 8271 2024-07-02 M2300 電子工業 14.7692 20.03 18409.0 25.87 \n",
"135 9912 2024-07-02 M2300 電子工業 NaN 42.38 -40.0 42.48 \n",
"\n",
" 營業總收入_Q 常續ROE_Q 營運產生現金流量_Q \n",
"0 28775904.0 1.23 1595764.0 \n",
"1 147257.0 0.73 14978.0 \n",
"2 54632099.0 2.94 20819871.0 \n",
"3 173649.0 -0.09 10878.0 \n",
"4 199571114.0 1.69 8250149.0 \n",
".. ... ... ... \n",
"131 5111173.0 1.23 594704.0 \n",
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"\n",
"[136 rows x 10 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import TejToolAPI\n",
"\n",
"start_time = pd.Timestamp('2023-07-02')\n",
"end_time = pd.Timestamp('2024-07-02')\n",
"\n",
"data = TejToolAPI.get_history_data(start = start_time,\n",
" end = end_time,\n",
" ticker = pool,\n",
" fin_type = 'Q', # 為累計資料，舉例來說，Q3累計：1月～9月的資料。\n",
" columns = ['主產業別_中文', '常續ROE', '營業毛利率', '營運產生現金流量', '投資產生現金流量', '負債比率', 'per_tej', '營業總收入'],\n",
" transfer_to_chinese = True)\n",
"\n",
"data = data.drop_duplicates(subset=['股票代碼'], keep='last').reset_index(drop=True)\n",
"\n",
"data\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "4ls7y1vuTaSi"
},
"source": [
"### **篩選營收最高的五間公司，紀錄其股票代碼。**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "qG_8G2Xsilaz",
"outputId": "eb67f5eb-dc12-4442-962f-2bf7fff88719"
},
"outputs": [
{
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" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
" --disabled-bg-color: #3B4455;\n",
" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
" box-shadow: none;\n",
" }\n",
"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-20529d42-f36f-4b3e-a8eb-50ca28c9c210 button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
"\n",
" <div id=\"id_1937543d-9111-4ca5-a193-7d250aa40cfb\">\n",
" <style>\n",
" .colab-df-generate {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-generate:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-generate {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-generate:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
" <button class=\"colab-df-generate\" onclick=\"generateWithVariable('data')\"\n",
" title=\"Generate code using this dataframe.\"\n",
" style=\"display:none;\">\n",
"\n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
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" </button>\n",
" <script>\n",
" (() => {\n",
" const buttonEl =\n",
" document.querySelector('#id_1937543d-9111-4ca5-a193-7d250aa40cfb button.colab-df-generate');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" buttonEl.onclick = () => {\n",
" google.colab.notebook.generateWithVariable('data');\n",
" }\n",
" })();\n",
" </script>\n",
" </div>\n",
"\n",
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" </div>\n"
],
"text/plain": [
" 股票代碼 日期 主產業別_中文 本益比_TEJ 營業毛利率_Q 投資產生現金流量_Q 負債比率_Q \\\n",
"6 2330 2024-07-02 M2300 電子工業 29.1046 53.07 -159806991.0 36.67 \n",
"27 2382 2024-07-02 M2300 電子工業 26.0091 8.48 22640275.0 76.20 \n",
"86 4938 2024-07-02 M2300 電子工業 18.0987 4.23 -2946059.0 57.42 \n",
"64 3231 2024-07-02 M2300 電子工業 21.5123 7.20 -2693302.0 69.48 \n",
"4 2324 2024-07-02 M2300 電子工業 17.8337 4.91 -2205331.0 70.01 \n",
"\n",
" 營業總收入_Q 常續ROE_Q 營運產生現金流量_Q \n",
"6 592644201.0 6.40 436311108.0 \n",
"27 258939378.0 6.50 23733615.0 \n",
"86 250399656.0 1.54 20958867.0 \n",
"64 239325146.0 4.39 3127081.0 \n",
"4 199571114.0 1.69 8250149.0 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = data.nlargest(5, '營業總收入_Q')\n",
"\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "xFk-3n-klB6p",
"outputId": "a1134b77-8368-4cbb-ef38-24b2e6a1b19e"
},
"outputs": [
{
"data": {
"text/plain": [
"array(['2330', '2382', '4938', '3231', '2324'], dtype=object)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tickers = data['股票代碼'].unique()\n",
"\n",
"tickers"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Nan3f7DLUBH6"
},
"source": [
"### **將資料載入本地電腦，方便運行**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "lKnzkMTBmZib",
"outputId": "8b88595d-3e09-4ea0-c773-12161d936800"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2024-07-04 01:21:13.785539] INFO: zipline.data.bundles.core: Ingesting tquant.\n",
"\u001b[?25lMerging daily equity files: [####################################] \u001b[?25h\n",
"Currently used TEJ API key call quota 34/9223372036854775807 (0.0%)\n",
"Currently used TEJ API key data quota 337912/9223372036854775807 (0.0%)\n",
"[2024-07-04 01:21:28.543091] INFO: zipline.data.bundles.core: Ingest tquant successfully.\n"
]
}
],
"source": [
"start = '2023-01-01'\n",
"end = '2024-07-02'\n",
"\n",
"os.environ['mdate'] = start + ' ' + end\n",
"os.environ['ticker'] = ' '.join(tickers) + ' ' + 'IR0001'\n",
"\n",
"!zipline ingest -b tquant"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "M6JFFHTDm0P1"
},
"outputs": [],
"source": [
"from zipline.data import bundles\n",
"\n",
"bundle_data = bundles.load('tquant')"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "BPkpJPkAVbCP"
},
"source": [
"### **採用與『巴菲特選股策略回測』後半部分相同的分析方法**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "iTMZ9iaxoHHg"
},
"outputs": [],
"source": [
"from zipline.api import *\n",
"from zipline.finance import commission, slippage\n",
"\n",
"def initialize(context):\n",
" context.day = 0\n",
" context.tickers = tickers\n",
" set_slippage(slippage.VolumeShareSlippage(volume_limit = 0.025, price_impact = 0.1))\n",
" set_commission(commission.Custom_TW_Commission(min_trade_cost = 20, discount = 1.0, tax = 0.003))\n",
" set_benchmark(symbol('IR0001'))\n",
" set_liquidity_risk_management_rule(['全額交割股票(Full-Cash Delivery Securities)', '漲停股票(Limit Up)', '跌停股票(Limit Down)', '開盤即鎖死(Limited Whole Day)'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "0kEd-6gNtVac"
},
"outputs": [],
"source": [
"def handle_data(context, data):\n",
"\n",
" #回測第一天買進\n",
" if context.day == 0:\n",
" for ticker in context.tickers:\n",
" order_percent(symbol(ticker), 1 / len(tickers))\n",
"\n",
" context.day += 1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "n2yoYeVStZNY"
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"capital_base = 1e6 # 設定初始資金\n",
"\n",
"def analyze(context, results):\n",
"\n",
" fig = plt.figure()\n",
" ax1 = fig.add_subplot(111)\n",
" results['benchmark_cum'] = results.benchmark_return.add(1).cumprod() * capital_base\n",
" results[['portfolio_value', 'benchmark_cum']].plot(ax = ax1, label = 'Portfolio Value($)')\n",
" ax1.set_ylabel('Portfolio value (TWD)')\n",
"\n",
" plt.legend(loc = 'upper left')\n",
"\n",
" plt.gcf().set_size_inches(18, 8)\n",
" plt.grid()\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "tMrOhjh2X28L"
},
"source": [
"### **可以看出，策略有成功運行**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "yzpz7fHYtcj-",
"outputId": "e063a8cd-e6fe-4b93-bf65-65533dee5b7a"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1800x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "results"
},
"text/html": [
"\n",
" <div id=\"df-f9852b15-1516-42dd-b525-cebac4bfe2e1\" class=\"colab-df-container\">\n",
" <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>gross_leverage</th>\n",
" <th>positions</th>\n",
" <th>net_leverage</th>\n",
" <th>short_exposure</th>\n",
" <th>starting_cash</th>\n",
" <th>treasury_return</th>\n",
" <th>ending_cash</th>\n",
" <th>portfolio_value</th>\n",
" <th>...</th>\n",
" <th>max_leverage</th>\n",
" <th>treasury_period_return</th>\n",
" <th>trading_days</th>\n",
" <th>period_label</th>\n",
" <th>algorithm_period_return</th>\n",
" <th>algo_volatility</th>\n",
" <th>benchmark_period_return</th>\n",
" <th>excess_return</th>\n",
" <th>benchmark_volatility</th>\n",
" <th>benchmark_cum</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2023-01-03 13:30:00+08:00</th>\n",
" <td>2023-01-03 09:01:00+08:00</td>\n",
" <td>2023-01-03 13:30:00+08:00</td>\n",
" <td>0.000000</td>\n",
" <td>[]</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1000000.000000</td>\n",
" <td>0.0</td>\n",
" <td>1000000.000000</td>\n",
" <td>1.000000e+06</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>2023-01</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-01-04 13:30:00+08:00</th>\n",
" <td>2023-01-04 09:01:00+08:00</td>\n",
" <td>2023-01-04 13:30:00+08:00</td>\n",
" <td>0.998963</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.998963</td>\n",
" <td>0.0</td>\n",
" <td>1000000.000000</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>9.985759e+05</td>\n",
" <td>...</td>\n",
" <td>0.998963</td>\n",
" <td>0.0</td>\n",
" <td>2</td>\n",
" <td>2023-01</td>\n",
" <td>-0.001424</td>\n",
" <td>0.015985</td>\n",
" <td>-0.001741</td>\n",
" <td>0.000317</td>\n",
" <td>NaN</td>\n",
" <td>9.982590e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-01-05 13:30:00+08:00</th>\n",
" <td>2023-01-05 09:01:00+08:00</td>\n",
" <td>2023-01-05 13:30:00+08:00</td>\n",
" <td>0.998966</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.998966</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>1.001245e+06</td>\n",
" <td>...</td>\n",
" <td>0.998966</td>\n",
" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>2023-01</td>\n",
" <td>0.001245</td>\n",
" <td>0.033017</td>\n",
" <td>0.005424</td>\n",
" <td>-0.004180</td>\n",
" <td>0.100115</td>\n",
" <td>1.005424e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-01-06 13:30:00+08:00</th>\n",
" <td>2023-01-06 09:01:00+08:00</td>\n",
" <td>2023-01-06 13:30:00+08:00</td>\n",
" <td>0.998968</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.998968</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>1.002598e+06</td>\n",
" <td>...</td>\n",
" <td>0.998968</td>\n",
" <td>0.0</td>\n",
" <td>4</td>\n",
" <td>2023-01</td>\n",
" <td>0.002598</td>\n",
" <td>0.027961</td>\n",
" <td>0.010506</td>\n",
" <td>-0.007909</td>\n",
" <td>0.073959</td>\n",
" <td>1.010506e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-01-09 13:30:00+08:00</th>\n",
" <td>2023-01-09 09:01:00+08:00</td>\n",
" <td>2023-01-09 13:30:00+08:00</td>\n",
" <td>0.998992</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.998992</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>0.0</td>\n",
" <td>1035.035448</td>\n",
" <td>1.026972e+06</td>\n",
" <td>...</td>\n",
" <td>0.998992</td>\n",
" <td>0.0</td>\n",
" <td>5</td>\n",
" <td>2023-01</td>\n",
" <td>0.026972</td>\n",
" <td>0.169715</td>\n",
" <td>0.037143</td>\n",
" <td>-0.010171</td>\n",
" <td>0.191248</td>\n",
" <td>1.037143e+06</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>2024-06-26 13:30:00+08:00</th>\n",
" <td>2024-06-26 09:01:00+08:00</td>\n",
" <td>2024-06-26 13:30:00+08:00</td>\n",
" <td>0.963874</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.963874</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>2.777073e+06</td>\n",
" <td>...</td>\n",
" <td>0.999162</td>\n",
" <td>0.0</td>\n",
" <td>354</td>\n",
" <td>2024-06</td>\n",
" <td>1.777073</td>\n",
" <td>0.328169</td>\n",
" <td>0.687501</td>\n",
" <td>1.089572</td>\n",
" <td>0.138582</td>\n",
" <td>1.687501e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024-06-27 13:30:00+08:00</th>\n",
" <td>2024-06-27 09:01:00+08:00</td>\n",
" <td>2024-06-27 13:30:00+08:00</td>\n",
" <td>0.963122</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.963122</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>2.720485e+06</td>\n",
" <td>...</td>\n",
" <td>0.999162</td>\n",
" <td>0.0</td>\n",
" <td>355</td>\n",
" <td>2024-06</td>\n",
" <td>1.720485</td>\n",
" <td>0.328302</td>\n",
" <td>0.683184</td>\n",
" <td>1.037301</td>\n",
" <td>0.138428</td>\n",
" <td>1.683184e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024-06-28 13:30:00+08:00</th>\n",
" <td>2024-06-28 09:01:00+08:00</td>\n",
" <td>2024-06-28 13:30:00+08:00</td>\n",
" <td>0.963446</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.963446</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>2.744534e+06</td>\n",
" <td>...</td>\n",
" <td>0.999162</td>\n",
" <td>0.0</td>\n",
" <td>356</td>\n",
" <td>2024-06</td>\n",
" <td>1.744534</td>\n",
" <td>0.327876</td>\n",
" <td>0.692644</td>\n",
" <td>1.051890</td>\n",
" <td>0.138276</td>\n",
" <td>1.692644e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024-07-01 13:30:00+08:00</th>\n",
" <td>2024-07-01 09:01:00+08:00</td>\n",
" <td>2024-07-01 13:30:00+08:00</td>\n",
" <td>0.963398</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.963398</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>2.740965e+06</td>\n",
" <td>...</td>\n",
" <td>0.999162</td>\n",
" <td>0.0</td>\n",
" <td>357</td>\n",
" <td>2024-07</td>\n",
" <td>1.740965</td>\n",
" <td>0.327435</td>\n",
" <td>0.696368</td>\n",
" <td>1.044597</td>\n",
" <td>0.138082</td>\n",
" <td>1.696368e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024-07-02 13:30:00+08:00</th>\n",
" <td>2024-07-02 09:01:00+08:00</td>\n",
" <td>2024-07-02 13:30:00+08:00</td>\n",
" <td>0.963197</td>\n",
" <td>[{'sid': Equity(1 [2330]), 'amount': 441, 'cos...</td>\n",
" <td>0.963197</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>0.0</td>\n",
" <td>100324.969410</td>\n",
" <td>2.726012e+06</td>\n",
" <td>...</td>\n",
" <td>0.999162</td>\n",
" <td>0.0</td>\n",
" <td>358</td>\n",
" <td>2024-07</td>\n",
" <td>1.726012</td>\n",
" <td>0.327054</td>\n",
" <td>0.686006</td>\n",
" <td>1.040006</td>\n",
" <td>0.138037</td>\n",
" <td>1.686006e+06</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>358 rows × 40 columns</p>\n",
"</div>\n",
" <div class=\"colab-df-buttons\">\n",
"\n",
" <div class=\"colab-df-container\">\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f9852b15-1516-42dd-b525-cebac4bfe2e1')\"\n",
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" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-f9852b15-1516-42dd-b525-cebac4bfe2e1 button.colab-df-convert');\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-f9852b15-1516-42dd-b525-cebac4bfe2e1');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
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" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
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"<div id=\"df-3b33e2ee-e658-4fb1-99bd-9e976a9e90b3\">\n",
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"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
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" [theme=dark] .colab-df-quickchart {\n",
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" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
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" border: none;\n",
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" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
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"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
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" fill: var(--button-hover-fill-color);\n",
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" .colab-df-quickchart-complete:disabled,\n",
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" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
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" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-3b33e2ee-e658-4fb1-99bd-9e976a9e90b3 button');\n",
" quickchartButtonEl.style.display =\n",
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" })();\n",
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"</div>\n",
"\n",
" <div id=\"id_80e67354-38d5-4771-ae6b-4a1d8dbfdcf6\">\n",
" <style>\n",
" .colab-df-generate {\n",
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" .colab-df-generate:hover {\n",
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"text/plain": [
" period_open period_close \\\n",
"2023-01-03 13:30:00+08:00 2023-01-03 09:01:00+08:00 2023-01-03 13:30:00+08:00 \n",
"2023-01-04 13:30:00+08:00 2023-01-04 09:01:00+08:00 2023-01-04 13:30:00+08:00 \n",
"2023-01-05 13:30:00+08:00 2023-01-05 09:01:00+08:00 2023-01-05 13:30:00+08:00 \n",
"2023-01-06 13:30:00+08:00 2023-01-06 09:01:00+08:00 2023-01-06 13:30:00+08:00 \n",
"2023-01-09 13:30:00+08:00 2023-01-09 09:01:00+08:00 2023-01-09 13:30:00+08:00 \n",
"... ... ... \n",
"2024-06-26 13:30:00+08:00 2024-06-26 09:01:00+08:00 2024-06-26 13:30:00+08:00 \n",
"2024-06-27 13:30:00+08:00 2024-06-27 09:01:00+08:00 2024-06-27 13:30:00+08:00 \n",
"2024-06-28 13:30:00+08:00 2024-06-28 09:01:00+08:00 2024-06-28 13:30:00+08:00 \n",
"2024-07-01 13:30:00+08:00 2024-07-01 09:01:00+08:00 2024-07-01 13:30:00+08:00 \n",
"2024-07-02 13:30:00+08:00 2024-07-02 09:01:00+08:00 2024-07-02 13:30:00+08:00 \n",
"\n",
" gross_leverage \\\n",
"2023-01-03 13:30:00+08:00 0.000000 \n",
"2023-01-04 13:30:00+08:00 0.998963 \n",
"2023-01-05 13:30:00+08:00 0.998966 \n",
"2023-01-06 13:30:00+08:00 0.998968 \n",
"2023-01-09 13:30:00+08:00 0.998992 \n",
"... ... \n",
"2024-06-26 13:30:00+08:00 0.963874 \n",
"2024-06-27 13:30:00+08:00 0.963122 \n",
"2024-06-28 13:30:00+08:00 0.963446 \n",
"2024-07-01 13:30:00+08:00 0.963398 \n",
"2024-07-02 13:30:00+08:00 0.963197 \n",
"\n",
" positions \\\n",
"2023-01-03 13:30:00+08:00 [] \n",
"2023-01-04 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2023-01-05 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2023-01-06 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2023-01-09 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"... ... \n",
"2024-06-26 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2024-06-27 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2024-06-28 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2024-07-01 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"2024-07-02 13:30:00+08:00 [{'sid': Equity(1 [2330]), 'amount': 441, 'cos... \n",
"\n",
" net_leverage short_exposure starting_cash \\\n",
"2023-01-03 13:30:00+08:00 0.000000 0.0 1000000.000000 \n",
"2023-01-04 13:30:00+08:00 0.998963 0.0 1000000.000000 \n",
"2023-01-05 13:30:00+08:00 0.998966 0.0 1035.035448 \n",
"2023-01-06 13:30:00+08:00 0.998968 0.0 1035.035448 \n",
"2023-01-09 13:30:00+08:00 0.998992 0.0 1035.035448 \n",
"... ... ... ... \n",
"2024-06-26 13:30:00+08:00 0.963874 0.0 100324.969410 \n",
"2024-06-27 13:30:00+08:00 0.963122 0.0 100324.969410 \n",
"2024-06-28 13:30:00+08:00 0.963446 0.0 100324.969410 \n",
"2024-07-01 13:30:00+08:00 0.963398 0.0 100324.969410 \n",
"2024-07-02 13:30:00+08:00 0.963197 0.0 100324.969410 \n",
"\n",
" treasury_return ending_cash portfolio_value \\\n",
"2023-01-03 13:30:00+08:00 0.0 1000000.000000 1.000000e+06 \n",
"2023-01-04 13:30:00+08:00 0.0 1035.035448 9.985759e+05 \n",
"2023-01-05 13:30:00+08:00 0.0 1035.035448 1.001245e+06 \n",
"2023-01-06 13:30:00+08:00 0.0 1035.035448 1.002598e+06 \n",
"2023-01-09 13:30:00+08:00 0.0 1035.035448 1.026972e+06 \n",
"... ... ... ... \n",
"2024-06-26 13:30:00+08:00 0.0 100324.969410 2.777073e+06 \n",
"2024-06-27 13:30:00+08:00 0.0 100324.969410 2.720485e+06 \n",
"2024-06-28 13:30:00+08:00 0.0 100324.969410 2.744534e+06 \n",
"2024-07-01 13:30:00+08:00 0.0 100324.969410 2.740965e+06 \n",
"2024-07-02 13:30:00+08:00 0.0 100324.969410 2.726012e+06 \n",
"\n",
" ... max_leverage treasury_period_return \\\n",
"2023-01-03 13:30:00+08:00 ... 0.000000 0.0 \n",
"2023-01-04 13:30:00+08:00 ... 0.998963 0.0 \n",
"2023-01-05 13:30:00+08:00 ... 0.998966 0.0 \n",
"2023-01-06 13:30:00+08:00 ... 0.998968 0.0 \n",
"2023-01-09 13:30:00+08:00 ... 0.998992 0.0 \n",
"... ... ... ... \n",
"2024-06-26 13:30:00+08:00 ... 0.999162 0.0 \n",
"2024-06-27 13:30:00+08:00 ... 0.999162 0.0 \n",
"2024-06-28 13:30:00+08:00 ... 0.999162 0.0 \n",
"2024-07-01 13:30:00+08:00 ... 0.999162 0.0 \n",
"2024-07-02 13:30:00+08:00 ... 0.999162 0.0 \n",
"\n",
" trading_days period_label \\\n",
"2023-01-03 13:30:00+08:00 1 2023-01 \n",
"2023-01-04 13:30:00+08:00 2 2023-01 \n",
"2023-01-05 13:30:00+08:00 3 2023-01 \n",
"2023-01-06 13:30:00+08:00 4 2023-01 \n",
"2023-01-09 13:30:00+08:00 5 2023-01 \n",
"... ... ... \n",
"2024-06-26 13:30:00+08:00 354 2024-06 \n",
"2024-06-27 13:30:00+08:00 355 2024-06 \n",
"2024-06-28 13:30:00+08:00 356 2024-06 \n",
"2024-07-01 13:30:00+08:00 357 2024-07 \n",
"2024-07-02 13:30:00+08:00 358 2024-07 \n",
"\n",
" algorithm_period_return algo_volatility \\\n",
"2023-01-03 13:30:00+08:00 0.000000 NaN \n",
"2023-01-04 13:30:00+08:00 -0.001424 0.015985 \n",
"2023-01-05 13:30:00+08:00 0.001245 0.033017 \n",
"2023-01-06 13:30:00+08:00 0.002598 0.027961 \n",
"2023-01-09 13:30:00+08:00 0.026972 0.169715 \n",
"... ... ... \n",
"2024-06-26 13:30:00+08:00 1.777073 0.328169 \n",
"2024-06-27 13:30:00+08:00 1.720485 0.328302 \n",
"2024-06-28 13:30:00+08:00 1.744534 0.327876 \n",
"2024-07-01 13:30:00+08:00 1.740965 0.327435 \n",
"2024-07-02 13:30:00+08:00 1.726012 0.327054 \n",
"\n",
" benchmark_period_return excess_return \\\n",
"2023-01-03 13:30:00+08:00 0.000000 0.000000 \n",
"2023-01-04 13:30:00+08:00 -0.001741 0.000317 \n",
"2023-01-05 13:30:00+08:00 0.005424 -0.004180 \n",
"2023-01-06 13:30:00+08:00 0.010506 -0.007909 \n",
"2023-01-09 13:30:00+08:00 0.037143 -0.010171 \n",
"... ... ... \n",
"2024-06-26 13:30:00+08:00 0.687501 1.089572 \n",
"2024-06-27 13:30:00+08:00 0.683184 1.037301 \n",
"2024-06-28 13:30:00+08:00 0.692644 1.051890 \n",
"2024-07-01 13:30:00+08:00 0.696368 1.044597 \n",
"2024-07-02 13:30:00+08:00 0.686006 1.040006 \n",
"\n",
" benchmark_volatility benchmark_cum \n",
"2023-01-03 13:30:00+08:00 NaN NaN \n",
"2023-01-04 13:30:00+08:00 NaN 9.982590e+05 \n",
"2023-01-05 13:30:00+08:00 0.100115 1.005424e+06 \n",
"2023-01-06 13:30:00+08:00 0.073959 1.010506e+06 \n",
"2023-01-09 13:30:00+08:00 0.191248 1.037143e+06 \n",
"... ... ... \n",
"2024-06-26 13:30:00+08:00 0.138582 1.687501e+06 \n",
"2024-06-27 13:30:00+08:00 0.138428 1.683184e+06 \n",
"2024-06-28 13:30:00+08:00 0.138276 1.692644e+06 \n",
"2024-07-01 13:30:00+08:00 0.138082 1.696368e+06 \n",
"2024-07-02 13:30:00+08:00 0.138037 1.686006e+06 \n",
"\n",
"[358 rows x 40 columns]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from zipline import run_algorithm\n",
"\n",
"start_date = pd.Timestamp('20230101', tz = 'utc')\n",
"end_date = pd.Timestamp('20240702', tz = 'utc') # 轉換成時間序列格式\n",
"\n",
"results = run_algorithm(\n",
" start = start_date,\n",
" end = end_date,\n",
" initialize = initialize,\n",
" handle_data = handle_data,\n",
" analyze = analyze,\n",
" bundle = 'tquant',\n",
" capital_base = capital_base,\n",
")\n",
"\n",
"results"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Z_eGVZCRZ2dS"
},
"source": [
"### **在繪製夏普比率圖時使用 Pyfolio 的套件，雖然圖有成功跑出來，但會出現無法找到對應字型的警告**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "8jO_H7LzuQJE"
},
"outputs": [],
"source": [
"from pyfolio.utils import extract_rets_pos_txn_from_zipline\n",
"import pyfolio as pf\n",
"\n",
"# 從 results 資料表中取出 returns, positions & transactions\n",
"returns, positions, transactions = extract_rets_pos_txn_from_zipline(results) # 從 results 資料表中取出 returns, positions & transactions\n",
"benchmark_rets = results.benchmark_return # 取出 benchmark 的報酬率"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "eGYUTP6ouS4D",
"outputId": "bc0e37f4-68b3-4ddc-b606-d6b09af73cfc"
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: title={'center': 'Rolling Sharpe ratio (6-month)'}, ylabel='Sharpe ratio'>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
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"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
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"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
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"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n",
"WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft JhengHei\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# 繪製夏普比率圖\n",
"from pyfolio.plotting import plot_rolling_sharpe\n",
"\n",
"plot_rolling_sharpe(returns,\n",
" factor_returns=benchmark_rets)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "M3GJighraJJb"
},
"source": [
"### **所以在這邊我們手動安裝字型，再試一次之後會發現沒有警告了**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "d40QryfVug4L",
"outputId": "ffecaa0e-b974-411e-dec0-dba70a0c5bcf"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2024-07-04 01:43:42-- https://drive.google.com/uc?id=1nMlvxPOPUGkHxYD5kuP8Ur37EmKlZAW_\n",
"Resolving drive.google.com (drive.google.com)... 173.194.210.102, 173.194.210.113, 173.194.210.100, ...\n",
"Connecting to drive.google.com (drive.google.com)|173.194.210.102|:443... connected.\n",
"HTTP request sent, awaiting response... 303 See Other\n",
"Location: https://drive.usercontent.google.com/download?id=1nMlvxPOPUGkHxYD5kuP8Ur37EmKlZAW_ [following]\n",
"--2024-07-04 01:43:42-- https://drive.usercontent.google.com/download?id=1nMlvxPOPUGkHxYD5kuP8Ur37EmKlZAW_\n",
"Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 74.125.141.132, 2607:f8b0:400c:c06::84\n",
"Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|74.125.141.132|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 21663376 (21M) [application/octet-stream]\n",
"Saving to: ‘MicrosoftJhengHei.ttf’\n",
"\n",
"MicrosoftJhengHei.t 100%[===================>] 20.66M 58.5MB/s in 0.4s \n",
"\n",
"2024-07-04 01:43:45 (58.5 MB/s) - ‘MicrosoftJhengHei.ttf’ saved [21663376/21663376]\n",
"\n",
"--2024-07-04 01:43:45-- https://drive.google.com/uc?id=1Y4O8Flv7lfrzHqOE8dkFTSctyYOpAJ0N\n",
"Resolving drive.google.com (drive.google.com)... 173.194.210.102, 173.194.210.113, 173.194.210.100, ...\n",
"Connecting to drive.google.com (drive.google.com)|173.194.210.102|:443... connected.\n",
"HTTP request sent, awaiting response... 303 See Other\n",
"Location: https://drive.usercontent.google.com/download?id=1Y4O8Flv7lfrzHqOE8dkFTSctyYOpAJ0N [following]\n",
"--2024-07-04 01:43:45-- https://drive.usercontent.google.com/download?id=1Y4O8Flv7lfrzHqOE8dkFTSctyYOpAJ0N\n",
"Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 74.125.141.132, 2607:f8b0:400c:c06::84\n",
"Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|74.125.141.132|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 24131012 (23M) [application/octet-stream]\n",
"Saving to: ‘ArialUnicodeMS.ttf’\n",
"\n",
"ArialUnicodeMS.ttf 100%[===================>] 23.01M 36.9MB/s in 0.6s \n",
"\n",
"2024-07-04 01:43:48 (36.9 MB/s) - ‘ArialUnicodeMS.ttf’ saved [24131012/24131012]\n",
"\n"
]
}
],
"source": [
"import matplotlib\n",
"!wget -O MicrosoftJhengHei.ttf https://drive.google.com/uc?id=1nMlvxPOPUGkHxYD5kuP8Ur37EmKlZAW_&export=download\n",
"!wget -O ArialUnicodeMS.ttf https://drive.google.com/uc?id=1Y4O8Flv7lfrzHqOE8dkFTSctyYOpAJ0N&export=download\n",
"matplotlib.font_manager.fontManager.addfont('MicrosoftJhengHei.ttf')\n",
"matplotlib.rc('font', family='sans-serif')\n",
"\n",
"matplotlib.font_manager.fontManager.addfont('ArialUnicodeMS.ttf')\n",
"matplotlib.rc('font', family='sans-serif')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 454
},
"id": "4tSfYIv8um_i",
"outputId": "28b77385-8f75-48b4-bde0-729978cba295"
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: title={'center': 'Rolling Sharpe ratio (6-month)'}, ylabel='Sharpe ratio'>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# 再繪製一次夏普比率圖，看是否跳出warning\n",
"plot_rolling_sharpe(returns,\n",
" factor_returns=benchmark_rets)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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