{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hikyuu pyecharts绘图\n",
"=============="
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1、引入交互式工具\n",
"-----------------\n",
"需从hikyuu.interactive引入，而不是直接从hikyuu库中引入（hikyuu是一个库，可用于编制其他的工具，而hikyuu.interactive.interactive是基于hikyuu库实现的交互式探索工具）"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2023-10-03 22:29:18,639 [INFO] Note: NumExpr detected 12 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8. [numexpr.utils::_init_num_threads]\n",
"2023-10-03 22:29:18,640 [INFO] NumExpr defaulting to 8 threads. [numexpr.utils::_init_num_threads]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"std::cout are redirected to python::stdout\n",
"std::cerr are redirected to python::stderr\n",
"2023-10-03 22:29:19.362 [HKU-I] - Using SQLITE3 BaseInfoDriver (BaseInfoDriver.cpp:58)\n",
"2023-10-03 22:29:19.362 [HKU-T] - SQLITE3: D:/Hikyuu_data/stock.db (SQLiteBaseInfoDriver.cpp:32)\n",
"2023-10-03 22:29:19.363 [HKU-I] - Loading market information... (StockManager.cpp:503)\n",
"2023-10-03 22:29:19.364 [HKU-I] - Loading stock type information... (StockManager.cpp:516)\n",
"2023-10-03 22:29:19.364 [HKU-I] - Loading stock information... (StockManager.cpp:427)\n",
"2023-10-03 22:29:19.673 [HKU-I] - Loading stock weight... (StockManager.cpp:533)\n",
"2023-10-03 22:29:20.218 [HKU-I] - Loading KData... (StockManager.cpp:135)\n",
"2023-10-03 22:29:20.227 [HKU-I] - Preloading all day kdata to buffer! (StockManager.cpp:158)\n",
"2023-10-03 22:29:20.308 [HKU-I] - 0.09s Loaded Data. (StockManager.cpp:146)\n",
"CPU times: total: 1.3 s\n",
"Wall time: 3.18 s\n"
]
}
],
"source": [
"%matplotlib inline\n",
"\n",
"%time from hikyuu.interactive import *\n",
"# 设置绘图引擎为echarts\n",
"use_draw_engine('echarts')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2、创建交易系统并运行\n",
"--------------------"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#创建模拟交易账户进行回测，初始资金30万\n",
"my_tm = crtTM(init_cash = 300000)\n",
"\n",
"#创建信号指示器（相对强弱信号）\n",
"ind = RSI(C, 24)\n",
"my_sg = SG_Band(ind, 30, 70)\n",
"\n",
"#固定每次买入1股\n",
"my_mm = MM_FixedCount(1)\n",
"\n",
"#创建交易系统并运行\n",
"sys = SYS_Simple(tm = my_tm, sg = my_sg, mm = my_mm)\n",
"sys.set_param(\"buy_delay\", False)\n",
"sys.set_param(\"sell_delay\", False)\n",
"#日线信号\n",
"candle_num = 500\n",
"q = Query(-candle_num, constant.null_int64, Query.DAY)\n",
"symbol = 'sh000001'\n",
"sys.run(sm[symbol], q)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"3、绘制曲线观察\n",
"---------------"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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" \n",
"\n",
"\n"
],
"text/plain": [
""
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},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chart = sys.plot()\n",
"k = sm[symbol].get_kdata(q)\n",
"c = CLOSE(k)\n",
"chart.render_notebook()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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"text/html": [
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"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k.plot()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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""
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},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind(c).plot(kref=k)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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],
"text/plain": [
""
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},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind(c).bar(kref=k)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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],
"text/plain": [
""
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},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind1 = TA_RSI(timeperiod=24)\n",
"ind2 = RSI(24)\n",
"chart = ind1(c).plot(kref=k)\n",
"ind2(c).plot(kref=k, chart=chart)\n",
"chart"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"4、绘制资金收益曲线\n",
"---------------------"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#绘制资金收益曲线\n",
"x = my_tm.get_profit_curve(k.get_datetime_list(), q.ktype) # datetime is lost there\n",
"x = PRICELIST(x)\n",
"x.plot(kref=k).render_notebook()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"5、回测统计报告\n",
"----------------------"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"帐户初始金额: 300000.00\n",
"累计投入本金: 300000.00\n",
"累计投入资产: 0.00\n",
"累计借入现金: 0.00\n",
"累计借入资产: 0.00\n",
"累计红利: 0.00\n",
"现金余额: 296372.56\n",
"未平仓头寸净值: 3276.68\n",
"当前总资产: 299649.24\n",
"已平仓交易总成本: 0.00\n",
"已平仓净利润总额: -399.85\n",
"单笔交易最大占用现金比例%: 1.18\n",
"交易平均占用现金比例%: 1.13\n",
"已平仓帐户收益率%: -0.13\n",
"帐户年复合收益率%: -0.05\n",
"帐户平均年收益率%: -0.05\n",
"赢利交易赢利总额: 0.00\n",
"亏损交易亏损总额: -399.85\n",
"已平仓交易总数: 2.00\n",
"赢利交易数: 0.00\n",
"亏损交易数: 2.00\n",
"赢利交易比例%: 0.00\n",
"赢利期望值: -199.92\n",
"赢利交易平均赢利: 0.00\n",
"亏损交易平均亏损: -199.92\n",
"平均赢利/平均亏损比例: 0.00\n",
"净赢利/亏损比例: 0.00\n",
"最大单笔赢利: 0.00\n",
"最大单笔亏损: -293.61\n",
"赢利交易平均持仓时间: 0.00\n",
"赢利交易最大持仓时间: 0.00\n",
"亏损交易平均持仓时间: 138.00\n",
"亏损交易最大持仓时间: 193.00\n",
"空仓总时间: 534.00\n",
"空仓时间/总时间%: 65.00\n",
"平均空仓时间: 267.00\n",
"最长空仓时间: 379.00\n",
"最大连续赢利笔数: 0.00\n",
"最大连续亏损笔数: 2.00\n",
"最大连续赢利金额: 0.00\n",
"最大连续亏损金额: -399.85\n",
"R乘数期望值: -0.06\n",
"交易机会频率/年: 0.90\n",
"年度期望R乘数: -0.05\n",
"赢利交易平均R乘数: 0.00\n",
"亏损交易平均R乘数: -0.06\n",
"最大单笔赢利R乘数: 0.00\n",
"最大单笔亏损R乘数: -0.09\n",
"最大连续赢利R乘数: 0.00\n",
"最大连续亏损R乘数: -0.06\n",
"\n"
]
}
],
"source": [
"#回测统计\n",
"from datetime import datetime\n",
"\n",
"per = Performance()\n",
"print(per.report(my_tm, Datetime(datetime.today())))\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "hikyuu_env",
"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": "3.9.18"
}
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"nbformat": 4,
"nbformat_minor": 4
}