{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 准备数据" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "xtquant文档地址：http://dict.thinktrader.net/nativeApi/start_now.html\n" ] } ], "source": [ "# 加载模块\n", "from datetime import datetime\n", "\n", "from tqdm import tqdm\n", "from xtquant import xtdata\n", "\n", "from vnpy.trader.database import DB_TZ\n", "from vnpy.trader.datafeed import get_datafeed\n", "from vnpy.trader.constant import Exchange, Interval\n", "from vnpy.trader.object import HistoryRequest\n", "\n", "from vnpy.alpha import AlphaLab, logger" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# 设置下载参数\n", "task_name = \"csi300\"\n", "index_symbol = \"000300.SSE\"\n", "xt_index_symbol = \"000300.SH\"\n", "\n", "start_date = \"20070101\"\n", "end_date = \"20231231\"\n", "\n", "intervals = [\n", " Interval.DAILY,\n", "]" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# 创建投研实验室\n", "lab = AlphaLab(f\"./lab/{task_name}\") # 指定数据文件夹" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 初始化数据服务（这里配置使用的迅投研）\n", "datafeed = get_datafeed()\n", "datafeed.init()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "{'000001.BKZS': {'start_time': datetime.datetime(2011, 9, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n", " 'count': 377},\n", " '000002.BKZS': {'start_time': datetime.datetime(2011, 9, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n", " 'count': 313},\n", " '000003.BKZS': {'start_time': datetime.datetime(2011, 9, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 5, 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0, 0),\n", " 'end_time': datetime.datetime(2022, 1, 27, 0, 0),\n", " 'count': 58},\n", " '101765.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2024, 9, 5, 20, 0, 0, 2000),\n", " 'count': 82},\n", " '101766.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2024, 9, 5, 20, 0, 0, 2000),\n", " 'count': 86},\n", " '101767.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 6, 5, 8, 0, 0, 3000),\n", " 'count': 345},\n", " '101768.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2024, 8, 23, 20, 0, 0, 16000),\n", " 'count': 60},\n", " '101769.BKZS': {'start_time': datetime.datetime(2016, 5, 6, 0, 0),\n", " 'end_time': datetime.datetime(2022, 9, 22, 0, 0),\n", " 'count': 103},\n", " '101770.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2019, 3, 19, 0, 0),\n", " 'count': 4},\n", " '101771.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n", " 'count': 78},\n", " '101772.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 5, 4, 8, 0, 0, 3000),\n", " 'count': 115},\n", " '101773.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2021, 11, 26, 0, 0),\n", " 'count': 5},\n", " '101774.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2022, 9, 22, 0, 0),\n", " 'count': 36},\n", " '101775.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 3, 11, 8, 50, 0, 16000),\n", " 'count': 108},\n", " '101776.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n", " 'count': 139},\n", " '101777.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n", " 'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n", " 'count': 146},\n", " ...}" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 下载历史成分股信息\n", "xtdata.download_sector_data()\n", "\n", "xtdata.download_history_data(\"\", \"stocklistchange\", \"\", \"\")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# 查询交易日历\n", "days = xtdata.get_trading_calendar(market=\"SZ\", start_time=start_date, end_time=end_date)\n", "\n", "# 轮询获取指数成本股\n", "index_components = {}\n", "end_datetime = datetime.strptime(end_date, \"%Y%m%d\")\n", "for i in days:\n", " dt = datetime.strptime(i, \"%Y%m%d\")\n", " if dt > end_datetime:\n", " continue\n", "\n", " xt_symbols = xtdata.get_stock_list_in_sector(xt_index_symbol, i)\n", "\n", " vt_symbols: list = []\n", " for xt_symbol in xt_symbols:\n", " vt_symbol = xt_symbol.replace(\"SH\", \"SSE\").replace(\"SZ\", \"SZSE\")\n", " vt_symbols.append(vt_symbol)\n", "\n", " index_components[dt.strftime(\"%Y-%m-%d\")] = vt_symbols\n", "\n", "# 保存到数据中心\n", "lab.save_component_data(index_symbol, index_components)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# 加载指数成分股代码\n", "component_symbols = lab.load_component_symbols(index_symbol, start_date, end_date)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|████████████████████████████████████████| 854/854 [01:21<00:00, 10.54it/s]\n" ] } ], "source": [ "# 转换时间格式\n", "start = datetime.strptime(start_date, \"%Y%m%d\")\n", "start.replace(tzinfo=DB_TZ)\n", "\n", "end = datetime.strptime(end_date, \"%Y%m%d\")\n", "end.replace(tzinfo=DB_TZ)\n", "\n", "# 除了成分股，还要下载指数数据\n", "task_symbols = component_symbols + [index_symbol]\n", "\n", "# 遍历下载数据\n", "for vt_symbol in tqdm(task_symbols):\n", " symbol, exchange_str = vt_symbol.split(\".\")\n", "\n", " for interval in intervals:\n", " req = HistoryRequest(symbol, Exchange(exchange_str), start, end, interval)\n", " bars = datafeed.query_bar_history(req)\n", "\n", " if bars:\n", " lab.save_bar_data(bars)\n", " else:\n", " logger(interval, vt_symbol)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# 添加回测参数配置\n", "for vt_symbol in component_symbols:\n", " lab.add_contract_setting(\n", " vt_symbol,\n", " long_rate=5/10000,\n", " short_rate=10/10000,\n", " size=1,\n", " pricetick=0.0001,\n", " )" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.2" } }, "nbformat": 4, "nbformat_minor": 4 }