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310
backtest_outputs/charts/bb_backtest_2026_full_visualization.html
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310
backtest_outputs/charts/bb_backtest_2026_full_visualization.html
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310
backtest_outputs/charts/bb_backtest_visualization.html
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310
backtest_outputs/charts/bb_backtest_visualization.html
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145
backtest_outputs/charts/bb_chart_2026_03_02.html
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145
backtest_outputs/charts/bb_chart_2026_03_02.html
Normal file
@@ -0,0 +1,145 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<title>ETHUSDT 2026-03-02 K线 + 布林带</title>
|
||||
<style>
|
||||
html,
|
||||
body {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: #111;
|
||||
color: #eee;
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
|
||||
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
|
||||
}
|
||||
#chart {
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
}
|
||||
</style>
|
||||
<script src="https://cdn.jsdelivr.net/npm/echarts@5/dist/echarts.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div id="chart"></div>
|
||||
<script>
|
||||
async function main() {
|
||||
// 从同目录加载由 Python 导出的 JSON 数据
|
||||
const resp = await fetch("bb_chart_2026_03_02_data.json");
|
||||
const raw = await resp.json();
|
||||
|
||||
const categoryData = [];
|
||||
const klineData = [];
|
||||
const upper = [];
|
||||
const mid = [];
|
||||
const lower = [];
|
||||
|
||||
for (const k of raw) {
|
||||
const d = new Date(k.timestamp);
|
||||
const label = `${d.getHours().toString().padStart(2, "0")}:${d
|
||||
.getMinutes()
|
||||
.toString()
|
||||
.padStart(2, "0")}`;
|
||||
categoryData.push(label);
|
||||
klineData.push([k.open, k.close, k.low, k.high]);
|
||||
upper.push(k.bb_upper);
|
||||
mid.push(k.bb_mid);
|
||||
lower.push(k.bb_lower);
|
||||
}
|
||||
|
||||
const chartDom = document.getElementById("chart");
|
||||
const chart = echarts.init(chartDom, null, { renderer: "canvas" });
|
||||
|
||||
const option = {
|
||||
backgroundColor: "#111",
|
||||
tooltip: {
|
||||
trigger: "axis",
|
||||
axisPointer: { type: "cross" },
|
||||
},
|
||||
axisPointer: {
|
||||
link: [{ xAxisIndex: "all" }],
|
||||
},
|
||||
grid: {
|
||||
left: "3%",
|
||||
right: "3%",
|
||||
top: "6%",
|
||||
bottom: "5%",
|
||||
containLabel: true,
|
||||
},
|
||||
xAxis: {
|
||||
type: "category",
|
||||
data: categoryData,
|
||||
scale: true,
|
||||
boundaryGap: true,
|
||||
axisLine: { lineStyle: { color: "#888" } },
|
||||
axisLabel: { color: "#ccc" },
|
||||
},
|
||||
yAxis: {
|
||||
scale: true,
|
||||
axisLine: { lineStyle: { color: "#888" } },
|
||||
splitLine: { lineStyle: { color: "#333" } },
|
||||
axisLabel: { color: "#ccc" },
|
||||
},
|
||||
dataZoom: [
|
||||
{
|
||||
type: "inside",
|
||||
start: 0,
|
||||
end: 100,
|
||||
},
|
||||
{
|
||||
type: "slider",
|
||||
start: 0,
|
||||
end: 100,
|
||||
height: 20,
|
||||
},
|
||||
],
|
||||
series: [
|
||||
{
|
||||
name: "K线",
|
||||
type: "candlestick",
|
||||
data: klineData,
|
||||
itemStyle: {
|
||||
color: "#26a69a",
|
||||
color0: "#ef5350",
|
||||
borderColor: "#26a69a",
|
||||
borderColor0: "#ef5350",
|
||||
},
|
||||
},
|
||||
{
|
||||
name: "BB上轨",
|
||||
type: "line",
|
||||
data: upper,
|
||||
symbol: "none",
|
||||
lineStyle: { color: "#ff9800", width: 1 },
|
||||
},
|
||||
{
|
||||
name: "BB中轨",
|
||||
type: "line",
|
||||
data: mid,
|
||||
symbol: "none",
|
||||
lineStyle: { color: "#fff", width: 1, type: "dashed" },
|
||||
},
|
||||
{
|
||||
name: "BB下轨",
|
||||
type: "line",
|
||||
data: lower,
|
||||
symbol: "none",
|
||||
lineStyle: { color: "#ff9800", width: 1 },
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
chart.setOption(option);
|
||||
window.addEventListener("resize", () => chart.resize());
|
||||
}
|
||||
|
||||
main().catch((e) => {
|
||||
console.error(e);
|
||||
alert("加载数据失败，请确认 bb_chart_2026_03_02_data.json 已生成并与本 HTML 同目录。");
|
||||
});
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
17941
backtest_outputs/logs/backtest_result.txt
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17941
backtest_outputs/logs/backtest_result.txt
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File diff suppressed because it is too large
Load Diff
142073
backtest_outputs/reports/bb_sweep_results.csv
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142073
backtest_outputs/reports/bb_sweep_results.csv
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43
backtest_outputs/reports/bb_sweep_results_snapshot.csv
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43
backtest_outputs/reports/bb_sweep_results_snapshot.csv
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@@ -0,0 +1,43 @@
|
||||
178.5,305.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,305.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,306.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,306.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,307.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,307.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,308.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,308.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,309.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,309.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,310.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,310.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,311.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,311.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,312.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,312.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,313.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,313.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,314.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,314.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,315.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,315.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,316.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,316.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,317.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,317.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,318.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,318.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,319.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,319.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,320.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,320.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,321.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,321.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,322.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,322.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,323.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,323.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,324.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,324.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,325.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,325.5,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
178.5,326.0,5.2791790570783465e+19,2.6395895285391733e+19,33680,56.24109263657957,21.175874581988747,4.8783963655773225e+19
|
||||
|
42500
backtest_outputs/trades/bb_backtest_20250101_20251231_trades.csv
Normal file
42500
backtest_outputs/trades/bb_backtest_20250101_20251231_trades.csv
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19004
backtest_outputs/trades/bb_backtest_2025_15m_trades.csv
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19004
backtest_outputs/trades/bb_backtest_2025_15m_trades.csv
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Load Diff
247966
backtest_outputs/trades/bb_backtest_2025_1m_trades.csv
Normal file
247966
backtest_outputs/trades/bb_backtest_2025_1m_trades.csv
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File diff suppressed because it is too large
Load Diff
88456
backtest_outputs/trades/bb_backtest_2025_3m_trades.csv
Normal file
88456
backtest_outputs/trades/bb_backtest_2025_3m_trades.csv
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Load Diff
54689
backtest_outputs/trades/bb_backtest_2025_5m_trades.csv
Normal file
54689
backtest_outputs/trades/bb_backtest_2025_5m_trades.csv
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Load Diff
7346
backtest_outputs/trades/bb_backtest_20260101_20260228_trades.csv
Normal file
7346
backtest_outputs/trades/bb_backtest_20260101_20260228_trades.csv
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File diff suppressed because it is too large
Load Diff
17941
backtest_outputs/trades/bb_backtest_20260101_20261231_trades.csv
Normal file
17941
backtest_outputs/trades/bb_backtest_20260101_20261231_trades.csv
Normal file
File diff suppressed because it is too large
Load Diff
157
backtest_outputs/trades/bb_backtest_march_2026_trades.csv
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157
backtest_outputs/trades/bb_backtest_march_2026_trades.csv
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@@ -0,0 +1,157 @@
|
||||
timestamp,action,price,size,margin,fee,capital,reason,pnl
|
||||
2026-03-01 01:35,开short,1970.895742,0.02536917551471376,1.0,0.0024999999999999996,98.9975,触上轨开空,
|
||||
2026-03-01 01:50,平仓100%,2022.33,0.02536917551471376,,0.0025652422359335528,98.690090039093,止损,-1.3048447186710703
|
||||
2026-03-01 03:50,开long,2019.4038,0.02443545219611179,0.9869009003909299,0.0024672522509773245,97.70072188645109,触下轨开多,
|
||||
2026-03-01 03:55,加long,2018.383596,0.04840542802670058,1.9540144377290218,0.004885036094322554,95.74182241262774,触下轨加多,
|
||||
2026-03-01 04:00,平仓50%,2028.348,0.03642044011140619,,0.0036936663429545246,97.55902982143648,触中轨平50%-1m(04:02)回踩中轨,0.35044340609171903
|
||||
2026-03-01 04:05,平仓100%,2018.7258371425564,0.03642044011140619,,0.003676144172649939,99.0258113463238,回开仓价全平,0.0
|
||||
2026-03-01 04:15,开long,1999.6626196004338,0.02476062971215385,0.9902581134632381,0.0024756452836580947,98.03307758757691,触下轨开多,
|
||||
2026-03-01 04:35,平仓50%,2014.6299999999999,0.012380314856076925,,0.0012470876859249124,98.71226043853991,触中轨平50%-1m(04:39)回踩中轨,0.18530088191730254
|
||||
2026-03-01 05:10,平仓100%,2017.8250206638015,0.012380314856076925,,0.0012490654540143892,99.43099667352436,延迟反转-同K回调确认-平多,0.22485624370683877
|
||||
2026-03-01 05:10,开short,2017.4214556596687,0.02464308991920873,0.9943099667352436,0.0024857749168381085,98.43420093187228,延迟反转-同K回调确认-开空,
|
||||
2026-03-01 05:15,平仓50%,2014.157,0.012321544959604365,,0.0012408763015600921,98.9703381761176,触中轨平50%-1m(05:16)反抽中轨,0.04022313717924384
|
||||
2026-03-01 05:20,平仓100%,2017.4214556596687,0.012321544959604365,,0.0012428874584190543,99.4662502720268,回开仓价全平,0.0
|
||||
2026-03-01 05:20,开short,2020.9165042134857,0.0246091934190863,0.994662502720268,0.0024866562568006696,98.46910111304973,触上轨开空,
|
||||
2026-03-01 05:35,平仓50%,2016.4740000000002,0.01230459670954315,,0.0012405949672639653,99.01985499216998,触中轨平50%-1m(05:38)反抽中轨,0.05466322272738604
|
||||
2026-03-01 06:10,平仓100%,1993.0582785593572,0.01230459670954315,,0.0012261889168144599,99.8587442863308,延迟反转-同K反弹确认-平空,0.34278423171750066
|
||||
2026-03-01 06:10,开long,1993.456890215069,0.02504662748828175,0.998587442863308,0.00249646860715827,98.85766037486034,延迟反转-同K反弹确认-开多,
|
||||
2026-03-01 07:00,平仓50%,1996.611,0.012523313744140875,,0.0012502092989001429,99.39520379341326,触中轨平50%-1m(07:01)回踩中轨,0.03949990642015626
|
||||
2026-03-01 07:05,平仓100%,1993.456890215069,0.012523313744140875,,0.001248234303579135,99.89324928054134,回开仓价全平,0.0
|
||||
2026-03-01 07:10,开short,2002.49942,0.024942141876011462,0.9989324928054134,0.002497331232013533,98.89181945650391,触上轨开空,
|
||||
2026-03-01 07:25,平仓50%,1997.67,0.012471070938005731,,0.0012456542140362953,99.450268088102,触中轨平50%-1m(07:26)反抽中轨,0.06022803940942398
|
||||
2026-03-01 07:35,平仓100%,2002.49942,0.012471070938005731,,0.0012486656160067666,99.94848566888871,回开仓价全平,0.0
|
||||
2026-03-01 08:50,开long,1983.9752370436452,0.02518894485241248,0.9994848566888871,0.0024987121417222175,98.9465021000581,触下轨开多,
|
||||
2026-03-01 09:00,加long,1984.6668539999998,0.049855471662982744,1.978930042001162,0.004947325105002905,96.96262473295194,触下轨加多,
|
||||
2026-03-01 09:15,平仓50%,1992.7069999999999,0.037522208257697615,,0.003738538352528591,98.75848822726503,触中轨平50%-1m(09:18)回踩中轨,0.31039458332059994
|
||||
2026-03-01 09:30,平仓100%,1984.4347101286562,0.037522208257697615,,0.003723018623362561,100.24397265798669,回开仓价全平,0.0
|
||||
2026-03-01 09:35,开long,1977.5454880734026,0.025345554188907188,1.0024397265798668,0.0025060993164496663,99.23902683209037,触下轨开多,
|
||||
2026-03-01 10:15,平仓50%,1979.625,0.012672777094453594,,0.0012543673177803846,99.76534551917355,触中轨平50%-1m(10:17)回踩中轨,0.02635319111102702
|
||||
2026-03-01 10:15,平仓100%,1977.5454880734026,0.012672777094453594,,0.0012530496582248331,100.26531233280527,回开仓价全平,0.0
|
||||
2026-03-01 10:25,开short,1983.593202,0.02527365798383223,1.0026531233280527,0.0025066328083201313,99.26015257666889,触上轨开空,
|
||||
2026-03-01 10:35,加short,1987.0210368714647,0.049954253495449914,1.9852030515333778,0.004963007628833443,97.26998651750668,触上轨加空,
|
||||
2026-03-01 10:40,平仓50%,1980.9359999999997,0.037613955739641075,,0.0037255419513530803,98.94575440746019,触中轨平50%-1m(10:41)反抽中轨,0.18556534447413794
|
||||
2026-03-01 11:00,平仓100%,1985.8694174198158,0.037613955739641075,,0.0037348202185767876,100.43594767467232,回开仓价全平,0.0
|
||||
2026-03-01 13:20,开long,1971.0811861410878,0.02547737464617128,1.0043594767467232,0.0025108986918668075,99.42907729923373,触下轨开多,
|
||||
2026-03-01 13:25,平仓50%,1977.221,0.01273868732308564,,0.0012593600043819353,100.00821084657333,触中轨平50%-1m(13:27)回踩中轨,0.07821316897063098
|
||||
2026-03-01 13:50,平仓100%,2012.7953226137352,0.01273868732308564,,0.0012820185130072825,101.04049190791126,延迟反转-同K回调确认-平多,0.5313833414775777
|
||||
2026-03-01 13:50,开short,2012.3927635492125,0.025104565504824317,1.0104049190791127,0.002526012297697781,100.02756097653445,延迟反转-同K回调确认-开空,
|
||||
2026-03-01 14:25,平仓50%,2004.753,0.012552282752412158,,0.0012582113252373262,100.62740169698006,触中轨平50%-1m(14:28)反抽中轨,0.09589647223128844
|
||||
2026-03-01 14:40,平仓100%,1994.9544227315625,0.012552282752412158,,0.0012520615996150872,101.35024307959607,延迟反转-同K反弹确认-平空,0.21889098467607288
|
||||
2026-03-01 14:40,开long,1995.3534136161088,0.025396564435150013,1.0135024307959608,0.0025337560769899017,100.33420689272312,延迟反转-同K反弹确认-开多,
|
||||
2026-03-01 15:00,平仓50%,2004.636,0.012698282217575007,,0.0012727716835755343,100.95755823804919,触中轨平50%-1m(15:03)回踩中轨,0.11787290161166897
|
||||
2026-03-01 15:20,平仓100%,2012.645228772288,0.012698282217575007,,0.0012778568559403158,101.68260794549853,延迟反转-同K回调确认-平多,0.21957634890730374
|
||||
2026-03-01 15:20,开short,2012.2426997265336,0.02526599002180933,1.0168260794549853,0.002542065198637463,100.6632398008449,延迟反转-同K回调确认-开空,
|
||||
2026-03-01 15:50,平仓50%,2008.9260000000002,0.012632995010904665,,0.0012689376067638331,101.2122837540636,触中轨平50%-1m(15:52)反抽中轨,0.04189985109796585
|
||||
2026-03-01 15:50,平仓100%,2012.2426997265336,0.012632995010904665,,0.0012710325993187314,101.71942576119179,回开仓价全平,0.0
|
||||
2026-03-01 15:55,开long,1992.6786162417027,0.025523289338307855,1.017194257611918,0.0025429856440297945,100.69968851793584,触下轨开多,
|
||||
2026-03-01 16:00,加long,1991.1565538891698,0.050573466120103445,2.013993770358717,0.005034984425896792,98.68065976315123,触下轨加多,
|
||||
2026-03-01 16:25,平仓50%,2002.4759999999999,0.03804837772920565,,0.00380954816208344,100.60370677137739,触中轨平50%-1m(16:26)回踩中轨,0.41126254240293536
|
||||
2026-03-01 16:45,平仓100%,1967.62,0.03804837772920565,,0.00374323744937698,101.20060583618708,止损,-0.9149517117262566
|
||||
2026-03-01 16:50,开long,1965.2229659999998,0.02574786871185666,1.0120060583618709,0.0025300151459046764,100.18606976267931,触下轨开多,
|
||||
2026-03-01 17:35,平仓50%,1967.5260000000003,0.01287393435592833,,0.001266490028379112,100.72045541036735,触中轨平50%-1m(17:36)回踩中轨,0.029649108535477225
|
||||
2026-03-01 17:45,平仓100%,1965.2229659999998,0.01287393435592833,,0.0012650075729523382,101.22519343197533,回开仓价全平,0.0
|
||||
2026-03-01 18:00,开short,1982.393442,0.025531055361505614,1.0122519343197534,0.002530629835799383,100.21041086781977,触上轨开空,
|
||||
2026-03-01 18:05,加short,1991.233970955805,0.05032578407635248,2.0042082173563953,0.005010520543390987,98.20119212991999,触上轨加空,
|
||||
2026-03-01 18:30,平仓50%,1977.5280000000002,0.037928419718929046,,0.0037502255994967156,100.11266378212795,触中轨平50%-1m(18:33)反抽中轨,0.4069918019693819
|
||||
2026-03-01 18:55,平仓100%,1972.9829470185493,0.037928419718929046,,0.0037416062656404534,102.196530730795,延迟反转-同K反弹确认-平空,0.5793784790946218
|
||||
2026-03-01 18:55,开long,1973.377543607953,0.025893811111265538,1.02196530730795,0.0025549132682698744,101.17201051021878,延迟反转-同K反弹确认-开多,
|
||||
2026-03-01 19:05,加long,1968.973716,0.051383118874614164,2.0234402102043756,0.0050586005255109385,99.1435116994889,触下轨加多,
|
||||
2026-03-01 19:40,平仓100%,1946.27,0.0772769299858797,,0.007520088526180904,100.31289177647686,止损,-1.8685053519981858
|
||||
2026-03-01 20:10,开long,1933.526628,0.025940395731771856,1.0031289177647686,0.002507822294411921,99.30725503641769,触下轨开多,
|
||||
2026-03-01 20:35,平仓100%,1911.05,0.025940395731771856,,0.00247866966316013,99.72485265948347,止损,-0.5830526250358269
|
||||
2026-03-01 22:10,开short,1943.1708021370632,0.025660341476366342,0.9972485265948348,0.002493121316487086,98.72511101157215,触上轨开空,
|
||||
2026-03-01 22:25,平仓50%,1933.2939999999999,0.012830170738183171,,0.0012402246053552545,99.34921610802999,触中轨平50%-1m(22:28)反抽中轨,0.12672105776577522
|
||||
2026-03-01 22:25,平仓100%,1943.1708021370632,0.012830170738183171,,0.001246560658243543,99.84659381066916,回开仓价全平,0.0
|
||||
2026-03-02 00:10,开short,1947.900342,0.025629286996313172,0.9984659381066916,0.0024961648452667285,98.8456317077172,触上轨开空,
|
||||
2026-03-02 00:15,平仓50%,1940.6370000000002,0.012814643498156586,,0.001243428565716605,99.43669838654002,触中轨平50%-1m(00:17)反抽中轨,0.0930771383351843
|
||||
2026-03-02 00:20,平仓100%,1947.900342,0.012814643498156586,,0.0012480824226333643,99.93468327317073,回开仓价全平,0.0
|
||||
2026-03-02 00:40,开short,1961.187684,0.02547810290888272,0.9993468327317073,0.002498367081829268,98.9328380733572,触上轨开空,
|
||||
2026-03-02 00:45,加short,1959.7479720000001,0.050482429111735394,1.9786567614671442,0.004946641903667859,96.9492346699864,触上轨加空,
|
||||
2026-03-02 01:10,平仓100%,1988.21,0.07596053202061812,,0.007551274468435656,97.79437733094622,止损,-2.1253096587705884
|
||||
2026-03-02 02:05,开long,1949.6071946200707,0.02508053355588993,0.9779437733094622,0.002444859433273655,96.81398869820349,触下轨开多,
|
||||
2026-03-02 02:10,加long,1940.8287934851146,0.049882807295102104,1.9362797739640698,0.004840699434910173,94.8728682248045,触下轨加多,
|
||||
2026-03-02 02:30,平仓50%,1953.676,0.037481670425496015,,0.0036613519975100665,96.69776991480681,触中轨平50%-1m(02:34)回踩中轨,0.371451268363048
|
||||
2026-03-02 03:10,平仓100%,1966.7001436494575,0.037481670425496015,,0.0036857603305022308,99.0108138563194,延迟反转-同K回调确认-平多,0.859617928206332
|
||||
2026-03-02 03:10,开short,1966.3068036207276,0.025176847700979926,0.990108138563194,0.0024752703464079847,98.0182304474098,延迟反转-同K回调确认-开空,
|
||||
2026-03-02 03:55,平仓50%,1971.86,0.012588423850489963,,0.0012411304726913566,98.44213739647142,触中轨平50%-1m(03:57)反抽中轨,-0.0699059897472862
|
||||
2026-03-02 03:55,平仓100%,1966.3068036207276,0.012588423850489963,,0.0012376351732039923,98.93595383057982,回开仓价全平,0.0
|
||||
2026-03-02 04:15,开long,1969.413804,0.025118122364541886,0.9893595383057983,0.002473398845764495,97.94412089342826,触下轨开多,
|
||||
2026-03-02 04:20,平仓50%,1971.578,0.012559061182270943,,0.001238058436380969,98.46474287411921,触中轨平50%-1m(04:22)回踩中轨,0.02718026997442538
|
||||
2026-03-02 04:20,平仓100%,1969.413804,0.012559061182270943,,0.0012366994228822474,98.95818594384923,回开仓价全平,0.0
|
||||
2026-03-02 05:05,开long,1964.19276,0.025190548493786637,0.9895818594384923,0.0024739546485962305,97.96613012976213,触下轨开多,
|
||||
2026-03-02 05:15,平仓50%,1970.2719999999997,0.012595274246893318,,0.0012408058090487492,98.53624994868501,触中轨平50%-1m(05:17)回踩中轨,0.07656969501268121
|
||||
2026-03-02 05:20,平仓100%,1964.19276,0.012595274246893318,,0.0012369773242981153,99.02980390107996,回开仓价全平,0.0
|
||||
2026-03-02 05:40,开short,1979.524016,0.025013539391451352,0.9902980390107996,0.0024757450975269983,98.03703011697164,触上轨开空,
|
||||
2026-03-02 07:20,平仓50%,1937.3039999999996,0.012506769695725676,,0.0012114707479304063,99.05900368239097,触中轨平50%-1m(07:24)反抽中轨,0.5280360166618587
|
||||
2026-03-02 08:10,平仓100%,1928.936186384675,0.012506769695725676,,0.0012062380320432252,100.1856367982698,延迟反转-同K反弹确认-平空,0.6326903344054814
|
||||
2026-03-02 08:10,开long,1929.3219736219519,0.025963949555342865,1.001856367982698,0.0025046409199567447,99.18127578936715,延迟反转-同K反弹确认-开多,
|
||||
2026-03-02 08:15,加long,1930.6160459999999,0.051372864114984755,1.983625515787343,0.004959063789468357,97.19269120979034,触下轨加多,
|
||||
2026-03-02 08:50,平仓100%,1948.7595882760102,0.07733681367032762,,0.007535542858338308,101.60740052896617,延迟反转-同K回调确认-平多,1.4367629782641276
|
||||
2026-03-02 08:50,开short,1948.369836358355,0.026074977818091708,1.0160740052896617,0.0025401850132241535,100.58878633866328,延迟反转-同K回调确认-开空,
|
||||
2026-03-02 09:40,平仓50%,1955.359,0.013037488909045854,,0.0012746485637851492,101.00442754928288,触中轨平50%-1m(09:43)反抽中轨,-0.09112114346145109
|
||||
2026-03-02 09:40,平仓100%,1948.369836358355,0.013037488909045854,,0.0012700925066120767,101.5111944594211,回开仓价全平,0.0
|
||||
2026-03-02 11:05,开long,1939.03773,0.02617566251777399,1.0151119445942112,0.0025377798614855274,100.49354473496541,触下轨开多,
|
||||
2026-03-02 12:00,平仓50%,1943.6330000000003,0.013087831258886995,,0.0012718970366602154,101.05997092857488,触中轨平50%-1m(12:02)回踩中轨,0.06014211834902898
|
||||
2026-03-02 12:20,平仓100%,1939.03773,0.013087831258886995,,0.0012688899307427637,101.56625801094124,回开仓价全平,0.0
|
||||
2026-03-02 12:20,开long,1936.8878482318667,0.026218931081543613,1.0156625801094123,0.0025391564502735306,100.54805627438155,触下轨开多,
|
||||
2026-03-02 12:35,加long,1930.6260479999999,0.05208054474274946,2.010961125487631,0.005027402813719077,98.5320677460802,触下轨加多,
|
||||
2026-03-02 12:50,平仓50%,1939.3809999999999,0.039149737912146536,,0.003796312893089832,100.30224850785619,触中轨平50%-1m(12:51)回踩中轨,0.26066522187056274
|
||||
2026-03-02 13:05,平仓100%,1932.7228399260932,0.039149737912146536,,0.0037832796319963034,101.81177708102271,回开仓价全平,0.0
|
||||
2026-03-02 13:05,开long,1930.4860199999998,0.026369467591643766,1.0181177708102271,0.0025452944270255673,100.79111401578545,触下轨开多,
|
||||
2026-03-02 13:15,平仓50%,1935.7879999999998,0.013184733795821883,,0.001276142473257322,101.36880195360808,触中轨平50%-1m(13:16)回踩中轨,0.06990519489077116
|
||||
2026-03-02 13:25,平仓100%,1930.4860199999998,0.013184733795821883,,0.0012726472135127836,101.87658819179968,回开仓价全平,0.0
|
||||
2026-03-02 14:25,开long,1922.6183440503523,0.02649423077311791,1.0187658819179968,0.002546914704794992,100.85527539517689,触下轨开多,
|
||||
2026-03-02 14:30,平仓100%,1950.3106548105818,0.02649423077311791,,0.0025835990283911126,102.60514414998892,延迟反转-同K回调确认-平多,0.733686471922416
|
||||
2026-03-02 14:30,开short,1949.9205926796196,0.02631008271187774,1.0260514414998891,0.0025651286037497224,101.57652757988528,延迟反转-同K回调确认-开空,
|
||||
2026-03-02 14:45,平仓100%,1977.81,0.02631008271187774,,0.002601817234418945,101.8662045907663,止损,-0.7337726133844545
|
||||
2026-03-02 17:40,开long,2025.7860592669192,0.025142389573859815,1.018662045907663,0.002546655114769157,100.84499588974387,触下轨开多,
|
||||
2026-03-02 18:15,平仓50%,2037.0170000000003,0.012571194786929907,,0.00128038687456438,101.49423286941916,触中轨平50%-1m(18:15)回踩中轨,0.1411863435960275
|
||||
2026-03-02 18:40,加long,2027.0190691607734,0.05007068478711442,2.0298846573883833,0.005074711643470957,99.45927350038731,触下轨加多,
|
||||
2026-03-02 18:45,平仓50%,2033.3019999999997,0.03132093978702216,,0.0031842464755415857,100.93023459635924,触中轨平50%-1m(18:47)回踩中轨,0.20453750227635803
|
||||
2026-03-02 18:50,平仓100%,2026.7716243577877,0.03132093978702216,,0.003174019600427768,102.19666841692992,回开仓价全平,0.0
|
||||
2026-03-02 18:50,开long,2028.895698,0.02518529378264026,1.0219666841692994,0.002554916710423248,101.1721468160502,触下轨开多,
|
||||
2026-03-02 18:55,加long,2027.7254639999999,0.049894400702781824,2.023442936321004,0.005058607340802509,99.1436452723884,触下轨加多,
|
||||
2026-03-02 19:05,平仓50%,2031.3199999999997,0.03753984724271104,,0.003812772125053188,100.78273929931468,触中轨平50%-1m(19:05)回踩中轨,0.1202019888061939
|
||||
2026-03-02 19:05,平仓100%,2028.1180160380236,0.03753984724271104,,0.003806762025612878,102.30163734753422,回开仓价全平,0.0
|
||||
2026-03-02 19:05,开long,2026.35519,0.025242770332760428,1.0230163734753424,0.0025575409336883554,101.27606343312519,触下轨开多,
|
||||
2026-03-02 19:10,加long,2023.6443782356102,0.05004637401825834,2.0255212686625037,0.005063803171656258,99.24547836129103,触下轨加多,
|
||||
2026-03-02 19:15,平仓50%,2030.7600000000002,0.037644572175509386,,0.0038223545695568717,100.99957516548169,触中轨平50%-1m(19:18)回踩中轨,0.23365033769128954
|
||||
2026-03-02 19:35,平仓100%,2038.953388071054,0.037644572175509386,,0.003837776398987009,103.06209313644565,延迟反转-同K回调确认-平多,0.5420869262940294
|
||||
2026-03-02 19:35,开short,2038.5455973934397,0.025278338946213584,1.0306209313644565,0.002576552328411141,102.02889565275278,延迟反转-同K回调确认-开空,
|
||||
2026-03-02 19:45,平仓50%,2031.934,0.012639169473106792,,0.0012840979092083886,102.62648712046943,触中轨平50%-1m(19:45)反抽中轨,0.08356509994363615
|
||||
2026-03-02 19:50,平仓100%,2038.5455973934397,0.012639169473106792,,0.0012882761642055705,103.14050930998745,回开仓价全平,0.0
|
||||
2026-03-02 19:50,开short,2043.2612660000002,0.025239187720692457,1.0314050930998746,0.0025785127327496863,102.10652570415482,触上轨开空,
|
||||
2026-03-02 19:55,加short,2042.021514,0.05000266892592338,2.0421305140830963,0.00510532628520774,100.05928986378652,触上轨加空,
|
||||
2026-03-02 20:05,平仓50%,2037.4699999999998,0.03762092832330792,,0.003832575641544508,101.77910244042056,触中轨平50%-1m(20:09)反抽中轨,0.18687734868409472
|
||||
2026-03-02 20:05,平仓100%,2042.4373773884072,0.03762092832330792,,0.003841919508978713,103.31202832450306,回开仓价全平,0.0
|
||||
2026-03-02 20:50,开short,2045.370844,0.02525508482424204,1.0331202832450306,0.002582800708112576,102.27632524054992,触上轨开空,
|
||||
2026-03-02 20:55,平仓50%,2038.2310000000002,0.01262754241212102,,0.0012868924199099917,102.88175717267845,触中轨平50%-1m(20:59)反抽中轨,0.09015868292592541
|
||||
2026-03-02 21:45,平仓100%,2045.370844,0.01262754241212102,,0.001291400354056288,103.3970259139469,回开仓价全平,0.0
|
||||
2026-03-02 22:05,开short,2047.470424,0.025249943711506063,1.033970259139469,0.002584925647848672,102.36047072915959,触上轨开空,
|
||||
2026-03-02 22:15,平仓50%,2043.7830000000001,0.012624971855753031,,0.0012901351427133249,102.92271934780683,触中轨平50%-1m(22:15)反抽中轨,0.04655362422022782
|
||||
2026-03-02 22:25,平仓100%,2047.470424,0.012624971855753031,,0.001292462823924336,103.43841201455264,回开仓价全平,0.0
|
||||
2026-03-02 22:30,开short,2051.5995980000002,0.025209210441303816,1.0343841201455264,0.0025859603003638154,102.40144193410674,触上轨开空,
|
||||
2026-03-02 22:50,平仓50%,2049.2699999999995,0.012604605220651908,,0.001291511967026266,102.94670614532531,触中轨平50%-1m(22:54)反抽中轨,0.029363663112829255
|
||||
2026-03-02 22:50,平仓100%,2051.5995980000002,0.012604605220651908,,0.0012929801501819077,103.46260522524788,回开仓价全平,0.0
|
||||
2026-03-03 00:30,开long,2020.584036,0.02560215348183813,1.0346260522524788,0.0025865651306311967,102.42539260786478,触下轨开多,
|
||||
2026-03-03 00:45,平仓50%,2029.438,0.012801076740919065,,0.001298949578946865,103.05474695703741,触中轨平50%-1m(00:47)回踩中轨,0.11334027262533643
|
||||
2026-03-03 01:30,加long,2025.1515544797203,0.05088742456290541,2.061094939140748,0.005152737347851869,100.98849928054881,触下轨加多,
|
||||
2026-03-03 02:15,平仓100%,2002.4,0.06368850130382447,,0.0063764927505389046,102.16998750049402,止损,-1.390543252571244
|
||||
2026-03-03 02:45,开short,2019.206078,0.025299544363914604,1.0216998750049402,0.00255424968751235,101.14573337580157,触上轨开空,
|
||||
2026-03-03 03:10,平仓50%,2012.1740000000002,0.012649772181957302,,0.0012726771345228875,101.74426482083527,触中轨平50%-1m(03:13)反抽中轨,0.0889541846657505
|
||||
2026-03-03 04:35,平仓100%,2003.7637516585983,0.012649772181957302,,0.0012673577482472664,102.44918931076766,延迟反转-同K反弹确认-平空,0.1953419101781693
|
||||
2026-03-03 04:35,开long,2004.16450440893,0.025559076883507146,1.0244918931076767,0.0025612297327691916,101.42213618792722,延迟反转-同K反弹确认-开多,
|
||||
2026-03-03 04:40,加long,2002.570434,0.05064597702331163,2.0284427237585443,0.0050711068093963595,99.38862235735928,触下轨加多,
|
||||
2026-03-03 05:05,平仓50%,2003.5459999999998,0.03810252695340939,,0.0038170082733697775,100.92807270325906,触中轨平50%-1m(05:09)回踩中轨,0.016800045740044088
|
||||
2026-03-03 05:05,平仓100%,2003.1050831610567,0.03810252695340939,,0.003816168271082775,102.45072384342109,回开仓价全平,0.0
|
||||
2026-03-03 05:15,开short,2013.5872020000002,0.02543985275176105,1.0245072384342109,0.0025612680960855265,101.42365533689079,触上轨开空,
|
||||
2026-03-03 05:20,平仓50%,2003.975,0.012719926375880526,,0.0012745207229552585,102.05690093713504,触中轨平50%-1m(05:24)反抽中轨,0.12226650175009475
|
||||
2026-03-03 06:35,加short,1993.821156,0.0511865874379031,2.041138018742701,0.005102845046856751,100.01066007334548,触上轨加空,
|
||||
2026-03-03 06:40,平仓50%,1992.6649999999997,0.03195325690689181,,0.0031836068337185775,101.44682656011526,触中轨平50%-1m(06:41)反抽中轨,0.1626542746235937
|
||||
2026-03-03 06:45,平仓100%,1988.3703092642115,0.03195325690689181,,0.003176745365897763,103.02022926476914,延迟反转-同K反弹确认-平空,0.2998836310398825
|
||||
2026-03-03 06:45,开long,1988.7679833260643,0.025900514823372103,1.0302022926476915,0.002575505731619228,101.98745146638983,延迟反转-同K反弹确认-开多,
|
||||
2026-03-03 06:50,平仓50%,1992.611,0.012950257411686051,,0.0012902412685678573,102.55103042660998,触中轨平50%-1m(06:51)回踩中轨,0.04976805516487063
|
||||
2026-03-03 06:55,平仓100%,1999.2593560774471,0.012950257411686051,,0.0012945461646962318,103.20070300450149,延迟反转-同K回调确认-平多,0.1358659777323571
|
||||
2026-03-03 06:55,开short,1998.8595042062318,0.025814896641643555,1.032007030045015,0.002580017575112537,102.16611595688137,延迟反转-同K回调确认-开空,
|
||||
2026-03-03 07:05,平仓50%,1993.9159999999997,0.012907448320821777,,0.0012868183863029834,102.74464067858328,触中轨平50%-1m(07:08)反抽中轨,0.0638080250657058
|
||||
2026-03-03 07:05,平仓100%,1998.8595042062318,0.012907448320821777,,0.0012900087875562685,103.25935418481824,回开仓价全平,0.0
|
||||
|
580
bb_backtest_2025_multi_timeframe.py
Normal file
580
bb_backtest_2025_multi_timeframe.py
Normal file
@@ -0,0 +1,580 @@
|
||||
"""
|
||||
布林带延迟反转策略回测 - 2025年多周期测试
|
||||
测试1分钟和15分钟周期的收益对比
|
||||
|
||||
策略规则：
|
||||
1. BB(10, 2.5)
|
||||
2. 空仓触上轨开空，触下轨开多
|
||||
3. 同向加仓最多1次，保证金1%
|
||||
4. 延迟反转：触轨不立刻平仓，记录价格，回调到该价再平仓+反向开仓
|
||||
5. 中轨平半+回开仓价全平
|
||||
|
||||
回测参数：
|
||||
- 本金: 100U
|
||||
- 杠杆: 100x
|
||||
- 逐仓模式
|
||||
- 开仓保证金: 1%
|
||||
- 手续费: 0.05% (万五)
|
||||
- 返佣: 90%，次日早上8点到账
|
||||
"""
|
||||
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
from peewee import *
|
||||
from loguru import logger
|
||||
import numpy as np
|
||||
|
||||
# 数据库配置
|
||||
DB_PATH = Path(__file__).parent / 'models' / 'database.db'
|
||||
db = SqliteDatabase(str(DB_PATH))
|
||||
|
||||
|
||||
class BitMartETH1M(Model):
|
||||
"""1分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_1m'
|
||||
|
||||
|
||||
class BitMartETH3M(Model):
|
||||
"""3分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_3m'
|
||||
|
||||
|
||||
class BitMartETH5M(Model):
|
||||
"""5分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_5m'
|
||||
|
||||
|
||||
class BitMartETH15M(Model):
|
||||
"""15分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_15m'
|
||||
|
||||
|
||||
class BBDelayReversalBacktest:
|
||||
"""布林带延迟反转策略回测"""
|
||||
|
||||
def __init__(self, timeframe='1m'):
|
||||
# 策略参数
|
||||
self.timeframe = timeframe
|
||||
self.bb_period = 10
|
||||
self.bb_std = 2.5
|
||||
self.initial_capital = 100 # 初始本金100U
|
||||
self.leverage = 100 # 100倍杠杆
|
||||
self.fee_rate = 0.0005 # 万五手续费
|
||||
self.rebate_rate = 0.9 # 90%返佣
|
||||
self.margin_ratio = 0.01 # 开仓保证金1%
|
||||
self.rebate_credit_hour = 8 # 次日早上8点返佣到账
|
||||
|
||||
# 账户状态
|
||||
self.capital = self.initial_capital
|
||||
self.position = 0 # 持仓量（正=多，负=空）
|
||||
self.position_count = 0 # 持仓次数（0=空仓，1=首次，2=加仓）
|
||||
self.entry_price = 0 # 开仓均价
|
||||
self.total_margin = 0 # 总保证金
|
||||
|
||||
# 延迟反转状态
|
||||
self.delay_reverse_price = None
|
||||
self.delay_reverse_type = None
|
||||
self.delay_reverse_kline_index = None
|
||||
|
||||
# 中轨平仓记录
|
||||
self.mid_closed_half = False
|
||||
|
||||
# 交易记录
|
||||
self.trades = []
|
||||
self.pending_rebates = []
|
||||
self.total_rebate_credited = 0.0
|
||||
|
||||
def calculate_bollinger_bands(self, df):
|
||||
"""计算布林带（整体右移1根，避免使用当前K收盘价）"""
|
||||
df['sma'] = df['close'].rolling(window=self.bb_period).mean()
|
||||
df['std'] = df['close'].rolling(window=self.bb_period).std()
|
||||
df['upper'] = (df['sma'] + self.bb_std * df['std']).shift(1)
|
||||
df['lower'] = (df['sma'] - self.bb_std * df['std']).shift(1)
|
||||
df['middle'] = df['sma'].shift(1)
|
||||
return df
|
||||
|
||||
def schedule_rebate(self, fee, timestamp):
|
||||
"""登记返佣到账时间（次日08:00，上海时间）"""
|
||||
rebate = fee * self.rebate_rate
|
||||
if rebate <= 0:
|
||||
return
|
||||
|
||||
trade_utc = pd.Timestamp(timestamp, tz='UTC')
|
||||
trade_local = trade_utc.tz_convert('Asia/Shanghai')
|
||||
credit_local = (trade_local + pd.Timedelta(days=1)).normalize() + pd.Timedelta(hours=self.rebate_credit_hour)
|
||||
credit_utc = credit_local.tz_convert('UTC').tz_localize(None)
|
||||
|
||||
self.pending_rebates.append({
|
||||
'credit_time': credit_utc,
|
||||
'amount': rebate,
|
||||
'trade_time': trade_utc.tz_localize(None),
|
||||
})
|
||||
|
||||
def apply_pending_rebates(self, current_time):
|
||||
"""处理当前时刻前应到账的返佣"""
|
||||
if not self.pending_rebates:
|
||||
return
|
||||
|
||||
remaining = []
|
||||
for item in self.pending_rebates:
|
||||
if item['credit_time'] <= current_time:
|
||||
amount = item['amount']
|
||||
self.capital += amount
|
||||
self.total_rebate_credited += amount
|
||||
else:
|
||||
remaining.append(item)
|
||||
|
||||
self.pending_rebates = remaining
|
||||
|
||||
def clear_delay_reversal(self):
|
||||
"""清理延迟反转状态"""
|
||||
self.delay_reverse_price = None
|
||||
self.delay_reverse_type = None
|
||||
self.delay_reverse_kline_index = None
|
||||
|
||||
def mark_delay_reversal(self, reverse_type, trigger_price, kline_index):
|
||||
"""记录延迟反转触发信息"""
|
||||
self.delay_reverse_type = reverse_type
|
||||
self.delay_reverse_price = trigger_price
|
||||
self.delay_reverse_kline_index = kline_index
|
||||
|
||||
def check_delay_reversal_signal(self, i, row, prev_row):
|
||||
"""检查延迟反转是否成立"""
|
||||
if self.position == 0 or self.delay_reverse_price is None or self.delay_reverse_kline_index is None:
|
||||
return None
|
||||
|
||||
offset = i - self.delay_reverse_kline_index
|
||||
if offset <= 0:
|
||||
return None
|
||||
|
||||
high = row['high']
|
||||
low = row['low']
|
||||
|
||||
if self.delay_reverse_type == 'long_to_short':
|
||||
# 多转空：回调确认
|
||||
if offset == 1 and low <= self.delay_reverse_price:
|
||||
return 'short', self.delay_reverse_price, "次K回调确认"
|
||||
|
||||
if offset >= 2 and prev_row is not None:
|
||||
prev_upper = prev_row['upper']
|
||||
prev_touch_upper = pd.notna(prev_upper) and prev_row['high'] >= prev_upper
|
||||
if prev_touch_upper:
|
||||
if low <= prev_upper:
|
||||
return 'short', prev_upper, "上一根触上轨后回调确认"
|
||||
else:
|
||||
prev_body_low = min(prev_row['open'], prev_row['close'])
|
||||
if low <= prev_body_low:
|
||||
return 'short', prev_body_low, "跌破上一根实体确认"
|
||||
|
||||
elif self.delay_reverse_type == 'short_to_long':
|
||||
# 空转多：反弹确认
|
||||
if offset == 1 and high >= self.delay_reverse_price:
|
||||
return 'long', self.delay_reverse_price, "次K反弹确认"
|
||||
|
||||
if offset >= 2 and prev_row is not None:
|
||||
prev_lower = prev_row['lower']
|
||||
prev_touch_lower = pd.notna(prev_lower) and prev_row['low'] <= prev_lower
|
||||
if prev_touch_lower:
|
||||
if high >= prev_lower:
|
||||
return 'long', prev_lower, "上一根触下轨后反弹确认"
|
||||
else:
|
||||
prev_body_high = max(prev_row['open'], prev_row['close'])
|
||||
if high >= prev_body_high:
|
||||
return 'long', prev_body_high, "突破上一根实体确认"
|
||||
|
||||
return None
|
||||
|
||||
def open_position(self, price, direction, timestamp, reason):
|
||||
"""开仓或加仓"""
|
||||
if self.position_count not in (0, 1):
|
||||
return False
|
||||
|
||||
if self.position_count == 1:
|
||||
current_direction = 'long' if self.position > 0 else 'short'
|
||||
if direction != current_direction:
|
||||
return False
|
||||
|
||||
margin = self.capital * self.margin_ratio
|
||||
if margin <= 0:
|
||||
return False
|
||||
|
||||
position_size = margin * self.leverage / price
|
||||
fee = position_size * price * self.fee_rate
|
||||
required = margin + fee
|
||||
if self.capital < required:
|
||||
return False
|
||||
|
||||
self.capital -= required
|
||||
self.schedule_rebate(fee, timestamp)
|
||||
|
||||
if self.position_count == 0:
|
||||
self.position = position_size if direction == 'long' else -position_size
|
||||
self.entry_price = price
|
||||
self.total_margin = margin
|
||||
self.position_count = 1
|
||||
else:
|
||||
old_size = abs(self.position)
|
||||
new_size = old_size + position_size
|
||||
old_value = old_size * self.entry_price
|
||||
new_value = position_size * price
|
||||
self.entry_price = (old_value + new_value) / new_size
|
||||
self.position = new_size if direction == 'long' else -new_size
|
||||
self.total_margin += margin
|
||||
self.position_count = 2
|
||||
|
||||
self.mid_closed_half = False
|
||||
|
||||
self.trades.append({
|
||||
'timestamp': timestamp,
|
||||
'action': f'开{direction}' if self.position_count == 1 else f'加{direction}',
|
||||
'price': price,
|
||||
'size': position_size,
|
||||
'margin': margin,
|
||||
'fee': fee,
|
||||
'capital': self.capital,
|
||||
'reason': reason
|
||||
})
|
||||
|
||||
return True
|
||||
|
||||
def close_position(self, price, ratio, timestamp, reason):
|
||||
"""平仓"""
|
||||
if self.position == 0:
|
||||
return False
|
||||
|
||||
ratio = min(max(ratio, 0.0), 1.0)
|
||||
if ratio == 0:
|
||||
return False
|
||||
|
||||
close_size = abs(self.position) * ratio
|
||||
if self.position > 0:
|
||||
pnl = close_size * (price - self.entry_price)
|
||||
else:
|
||||
pnl = close_size * (self.entry_price - price)
|
||||
|
||||
fee = close_size * price * self.fee_rate
|
||||
|
||||
released_margin = self.total_margin * ratio
|
||||
self.capital += released_margin + pnl - fee
|
||||
self.schedule_rebate(fee, timestamp)
|
||||
|
||||
if ratio >= 0.999:
|
||||
self.position = 0
|
||||
self.position_count = 0
|
||||
self.total_margin = 0
|
||||
self.entry_price = 0
|
||||
self.mid_closed_half = False
|
||||
self.clear_delay_reversal()
|
||||
else:
|
||||
self.position *= (1 - ratio)
|
||||
self.total_margin *= (1 - ratio)
|
||||
|
||||
self.trades.append({
|
||||
'timestamp': timestamp,
|
||||
'action': f'平仓{int(ratio*100)}%',
|
||||
'price': price,
|
||||
'size': close_size,
|
||||
'pnl': pnl,
|
||||
'fee': fee,
|
||||
'capital': self.capital,
|
||||
'reason': reason
|
||||
})
|
||||
|
||||
return True
|
||||
|
||||
def run_backtest(self, start_date, end_date):
|
||||
"""运行回测"""
|
||||
# 重置状态
|
||||
self.capital = self.initial_capital
|
||||
self.position = 0
|
||||
self.position_count = 0
|
||||
self.entry_price = 0
|
||||
self.total_margin = 0
|
||||
self.mid_closed_half = False
|
||||
self.trades = []
|
||||
self.pending_rebates = []
|
||||
self.total_rebate_credited = 0.0
|
||||
self.clear_delay_reversal()
|
||||
|
||||
logger.info(f"{'='*80}")
|
||||
logger.info(f"开始回测: {start_date} ~ {end_date} | 周期: {self.timeframe}")
|
||||
logger.info(f"初始资金: {self.initial_capital}U | 杠杆: {self.leverage}x | BB({self.bb_period}, {self.bb_std})")
|
||||
logger.info(f"{'='*80}")
|
||||
|
||||
# 从数据库加载数据
|
||||
start_dt = pd.Timestamp(start_date)
|
||||
end_dt = pd.Timestamp(end_date)
|
||||
if isinstance(end_date, str) and len(end_date) <= 10:
|
||||
end_dt = end_dt + pd.Timedelta(days=1) - pd.Timedelta(milliseconds=1)
|
||||
|
||||
start_ts = int(start_dt.timestamp() * 1000)
|
||||
end_ts = int(end_dt.timestamp() * 1000)
|
||||
|
||||
# 根据周期选择数据表
|
||||
model_mapping = {
|
||||
'1m': BitMartETH1M,
|
||||
'3m': BitMartETH3M,
|
||||
'5m': BitMartETH5M,
|
||||
'15m': BitMartETH15M,
|
||||
}
|
||||
Model = model_mapping.get(self.timeframe)
|
||||
if Model is None:
|
||||
logger.error(f"不支持的周期: {self.timeframe}")
|
||||
return None
|
||||
|
||||
query = Model.select().where(
|
||||
(Model.id >= start_ts) & (Model.id <= end_ts)
|
||||
).order_by(Model.id)
|
||||
|
||||
data = []
|
||||
for row in query:
|
||||
data.append({
|
||||
'timestamp': row.id,
|
||||
'open': row.open,
|
||||
'high': row.high,
|
||||
'low': row.low,
|
||||
'close': row.close
|
||||
})
|
||||
|
||||
if not data:
|
||||
logger.error("没有找到数据！")
|
||||
return None
|
||||
|
||||
df = pd.DataFrame(data)
|
||||
df['datetime'] = pd.to_datetime(df['timestamp'], unit='ms')
|
||||
|
||||
logger.info(f"加载数据: {len(df)} 根K线")
|
||||
logger.info(f"时间范围: {df['datetime'].min()} ~ {df['datetime'].max()}")
|
||||
|
||||
# 计算布林带
|
||||
df = self.calculate_bollinger_bands(df)
|
||||
|
||||
if len(df) <= self.bb_period + 1:
|
||||
logger.error("数据不足，无法执行回测")
|
||||
return None
|
||||
|
||||
# 逐根K线回测
|
||||
for i in range(self.bb_period, len(df)):
|
||||
row = df.iloc[i]
|
||||
prev_row = df.iloc[i-1] if i > 0 else None
|
||||
|
||||
signal_dt = row['datetime']
|
||||
signal_ts = signal_dt.strftime('%Y-%m-%d %H:%M')
|
||||
|
||||
high = row['high']
|
||||
low = row['low']
|
||||
close = row['close']
|
||||
upper = row['upper']
|
||||
lower = row['lower']
|
||||
middle = row['middle']
|
||||
|
||||
# 处理返佣到账
|
||||
self.apply_pending_rebates(signal_dt)
|
||||
|
||||
if pd.isna(upper) or pd.isna(lower) or pd.isna(middle):
|
||||
continue
|
||||
|
||||
# 检查延迟反转确认
|
||||
if self.delay_reverse_price is not None:
|
||||
reversal_signal = self.check_delay_reversal_signal(i, row, prev_row)
|
||||
if reversal_signal is not None and self.position != 0:
|
||||
new_direction, reversal_price, reason = reversal_signal
|
||||
self.close_position(reversal_price, 1.0, signal_ts, f"{reason}-平仓")
|
||||
self.open_position(reversal_price, new_direction, signal_ts, f"{reason}-开仓")
|
||||
self.mid_closed_half = False
|
||||
self.clear_delay_reversal()
|
||||
continue
|
||||
|
||||
# 中轨平仓逻辑
|
||||
if self.position != 0:
|
||||
if self.position > 0:
|
||||
# 回到开仓价全平+反手
|
||||
if self.mid_closed_half and low <= self.entry_price:
|
||||
self.close_position(close, 1.0, signal_ts, "回开仓价全平")
|
||||
self.open_position(close, 'short', signal_ts, "回开仓价反手开空")
|
||||
self.mid_closed_half = False
|
||||
continue
|
||||
# 触中轨平半
|
||||
if not self.mid_closed_half and low <= middle <= high:
|
||||
self.close_position(close, 0.5, signal_ts, "触中轨平50%")
|
||||
self.mid_closed_half = True
|
||||
continue
|
||||
|
||||
else: # 空仓
|
||||
# 回到开仓价全平+反手
|
||||
if self.mid_closed_half and high >= self.entry_price:
|
||||
self.close_position(close, 1.0, signal_ts, "回开仓价全平")
|
||||
self.open_position(close, 'long', signal_ts, "回开仓价反手开多")
|
||||
self.mid_closed_half = False
|
||||
continue
|
||||
# 触中轨平半
|
||||
if not self.mid_closed_half and low <= middle <= high:
|
||||
self.close_position(close, 0.5, signal_ts, "触中轨平50%")
|
||||
self.mid_closed_half = True
|
||||
continue
|
||||
|
||||
# 开仓与加仓逻辑
|
||||
if self.position == 0:
|
||||
self.clear_delay_reversal()
|
||||
|
||||
# 触上轨开空
|
||||
if high >= upper:
|
||||
self.open_position(upper, 'short', signal_ts, "触上轨开空")
|
||||
|
||||
# 触下轨开多
|
||||
elif low <= lower:
|
||||
self.open_position(lower, 'long', signal_ts, "触下轨开多")
|
||||
continue
|
||||
|
||||
# 延迟反转触发
|
||||
if self.position > 0 and high >= upper:
|
||||
self.mark_delay_reversal('long_to_short', upper, i)
|
||||
continue
|
||||
|
||||
elif self.position < 0 and low <= lower:
|
||||
self.mark_delay_reversal('short_to_long', lower, i)
|
||||
continue
|
||||
|
||||
# 加仓
|
||||
if self.delay_reverse_price is None and self.position_count == 1:
|
||||
if self.position > 0 and low <= lower:
|
||||
self.open_position(lower, 'long', signal_ts, "触下轨加多")
|
||||
elif self.position < 0 and high >= upper:
|
||||
self.open_position(upper, 'short', signal_ts, "触上轨加空")
|
||||
|
||||
# 回测末尾处理返佣
|
||||
self.apply_pending_rebates(df.iloc[-1]['datetime'])
|
||||
|
||||
# 最后平仓
|
||||
if self.position != 0:
|
||||
final_price = df.iloc[-1]['close']
|
||||
final_time = df.iloc[-1]['datetime'].strftime('%Y-%m-%d %H:%M')
|
||||
self.close_position(final_price, 1.0, final_time, "回测结束平仓")
|
||||
|
||||
# 生成报告
|
||||
return self.generate_report(df)
|
||||
|
||||
def generate_report(self, df):
|
||||
"""生成回测报告"""
|
||||
logger.info(f"\n{'='*80}")
|
||||
logger.info(f"回测报告 - {self.timeframe}")
|
||||
logger.info(f"{'='*80}")
|
||||
|
||||
# 基本统计
|
||||
total_trades = len([t for t in self.trades if '开' in t['action']])
|
||||
win_trades = len([t for t in self.trades if '平' in t['action'] and t.get('pnl', 0) > 0])
|
||||
loss_trades = len([t for t in self.trades if '平' in t['action'] and t.get('pnl', 0) < 0])
|
||||
|
||||
total_pnl = sum([t.get('pnl', 0) for t in self.trades])
|
||||
total_fee = sum([t.get('fee', 0) for t in self.trades])
|
||||
pending_rebate = sum([x['amount'] for x in self.pending_rebates])
|
||||
realized_net_fee = total_fee - self.total_rebate_credited
|
||||
|
||||
final_capital = self.capital
|
||||
roi = (final_capital - self.initial_capital) / self.initial_capital * 100
|
||||
|
||||
logger.info(f"初始资金: {self.initial_capital:.2f}U")
|
||||
logger.info(f"最终资金: {final_capital:.2f}U")
|
||||
logger.info(f"总盈亏: {total_pnl:.2f}U")
|
||||
logger.info(f"总手续费: {total_fee:.2f}U")
|
||||
logger.info(f"返佣已到账: {self.total_rebate_credited:.2f}U")
|
||||
logger.info(f"返佣待到账: {pending_rebate:.2f}U")
|
||||
logger.info(f"已实现净手续费: {realized_net_fee:.2f}U")
|
||||
logger.info(f"净收益: {final_capital - self.initial_capital:.2f}U")
|
||||
logger.info(f"收益率: {roi:.2f}%")
|
||||
logger.info(f"总交易次数: {total_trades}")
|
||||
logger.info(f"盈利次数: {win_trades}")
|
||||
logger.info(f"亏损次数: {loss_trades}")
|
||||
if win_trades + loss_trades > 0:
|
||||
logger.info(f"胜率: {win_trades/(win_trades+loss_trades)*100:.2f}%")
|
||||
|
||||
# 保存交易记录
|
||||
trades_df = pd.DataFrame(self.trades)
|
||||
output_dir = Path(__file__).parent / 'backtest_outputs' / 'trades'
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
output_file = output_dir / f'bb_backtest_2025_{self.timeframe}_trades.csv'
|
||||
trades_df.to_csv(output_file, index=False, encoding='utf-8-sig')
|
||||
logger.info(f"\n交易记录已保存到: {output_file}")
|
||||
|
||||
return {
|
||||
'timeframe': self.timeframe,
|
||||
'initial_capital': self.initial_capital,
|
||||
'final_capital': final_capital,
|
||||
'total_pnl': total_pnl,
|
||||
'total_fee': total_fee,
|
||||
'total_rebate_credited': self.total_rebate_credited,
|
||||
'pending_rebate': pending_rebate,
|
||||
'realized_net_fee': realized_net_fee,
|
||||
'roi': roi,
|
||||
'total_trades': total_trades,
|
||||
'win_trades': win_trades,
|
||||
'loss_trades': loss_trades,
|
||||
'win_rate': win_trades/(win_trades+loss_trades)*100 if (win_trades+loss_trades) > 0 else 0,
|
||||
'trades_file': str(output_file)
|
||||
}
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# 连接数据库
|
||||
db.connect(reuse_if_open=True)
|
||||
|
||||
try:
|
||||
results = []
|
||||
|
||||
for tf in ['1m', '3m', '5m', '15m']:
|
||||
logger.info("\n" + "="*80)
|
||||
logger.info(f"测试 {tf} 周期")
|
||||
logger.info("="*80)
|
||||
backtest = BBDelayReversalBacktest(timeframe=tf)
|
||||
result = backtest.run_backtest('2025-01-01', '2025-12-31')
|
||||
if result:
|
||||
results.append(result)
|
||||
|
||||
# 对比总结
|
||||
if len(results) > 0:
|
||||
logger.info("\n" + "="*80)
|
||||
logger.info("回测对比总结")
|
||||
logger.info("="*80)
|
||||
|
||||
for result in results:
|
||||
logger.info(f"\n【{result['timeframe']}周期】")
|
||||
logger.info(f" 收益率: {result['roi']:.2f}%")
|
||||
logger.info(f" 最终资金: {result['final_capital']:.2f}U")
|
||||
logger.info(f" 总交易次数: {result['total_trades']}")
|
||||
logger.info(f" 胜率: {result['win_rate']:.2f}%")
|
||||
logger.info(f" 净手续费: {result['realized_net_fee']:.2f}U")
|
||||
|
||||
finally:
|
||||
db.close()
|
||||
754
bb_backtest_march_2026.py
Normal file
754
bb_backtest_march_2026.py
Normal file
@@ -0,0 +1,754 @@
|
||||
"""
|
||||
布林带延迟反转策略回测 - 2026年3月
|
||||
策略规则：
|
||||
1. 5分钟K线，BB(10, 2.5)
|
||||
2. 空仓触上轨开空，触下轨开多
|
||||
3. 同向加仓最多1次，保证金递增(1%->2%)
|
||||
4. 延迟反转：触轨不立刻平仓，记录价格，回调到该价再平仓+反向开仓
|
||||
5. 中轨平半+回开仓价全平
|
||||
6. 止损：亏损达保证金50%
|
||||
"""
|
||||
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
from peewee import *
|
||||
from loguru import logger
|
||||
|
||||
# 数据库配置
|
||||
DB_PATH = Path(__file__).parent / 'models' / 'database.db'
|
||||
db = SqliteDatabase(str(DB_PATH))
|
||||
|
||||
class BitMartETH5M(Model):
|
||||
"""5分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_5m'
|
||||
|
||||
|
||||
class BitMartETH1M(Model):
|
||||
"""1分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_1m'
|
||||
|
||||
|
||||
class BollingerBandBacktest:
|
||||
"""布林带延迟反转策略回测"""
|
||||
|
||||
def __init__(self):
|
||||
# 策略参数
|
||||
self.bb_period = 10
|
||||
self.bb_std = 2.5
|
||||
self.initial_capital = 100 # 初始本金100U
|
||||
self.leverage = 50 # 50倍杠杆
|
||||
self.fee_rate = 0.0005 # 万五手续费
|
||||
self.rebate_rate = 0.9 # 90%返佣
|
||||
self.margin_ratio_1 = 0.01 # 首次开仓保证金比例1%
|
||||
self.margin_ratio_2 = 0.01 # 加仓保证金比例1%
|
||||
self.stop_loss_ratio = 0.5 # 止损比例50%
|
||||
self.entry_slippage = 0.0002 # 开仓滑点（2bps）
|
||||
self.rebate_credit_hour = 8 # 次日早上8点返佣到账（上海时间）
|
||||
|
||||
# 账户状态
|
||||
self.capital = self.initial_capital
|
||||
self.position = 0 # 持仓量（正=多，负=空）
|
||||
self.position_count = 0 # 持仓次数（0=空仓，1=首次，2=加仓）
|
||||
self.entry_price = 0 # 开仓均价
|
||||
self.total_margin = 0 # 总保证金
|
||||
|
||||
# 延迟反转状态
|
||||
self.delay_reverse_price = None # 记录触碰轨道时的轨道价格
|
||||
self.delay_reverse_type = None # 'long_to_short' 或 'short_to_long'
|
||||
self.delay_reverse_kline_index = None # 触发延迟反转的K线索引
|
||||
|
||||
# 中轨平仓记录
|
||||
self.mid_closed_half = False # 是否已平50%
|
||||
|
||||
# 1分钟K线缓存（key=5分钟起始时间戳, value=该5分钟内的1m列表）
|
||||
self.one_minute_by_5m = {}
|
||||
|
||||
# 交易记录
|
||||
self.trades = []
|
||||
self.daily_pnl = []
|
||||
self.pending_rebates = [] # 待到账返佣队列
|
||||
self.total_rebate_credited = 0.0
|
||||
self.current_run_label = "default"
|
||||
|
||||
def calculate_bollinger_bands(self, df):
|
||||
"""计算布林带（整体右移1根，避免使用当前K收盘价）"""
|
||||
df['sma'] = df['close'].rolling(window=self.bb_period).mean()
|
||||
df['std'] = df['close'].rolling(window=self.bb_period).std()
|
||||
df['upper'] = (df['sma'] + self.bb_std * df['std']).shift(1)
|
||||
df['lower'] = (df['sma'] - self.bb_std * df['std']).shift(1)
|
||||
df['middle'] = df['sma'].shift(1)
|
||||
return df
|
||||
|
||||
def get_rebate_amount(self, fee):
|
||||
"""计算返佣金额"""
|
||||
return fee * self.rebate_rate
|
||||
|
||||
def schedule_rebate(self, fee, timestamp):
|
||||
"""登记返佣到账时间（次日08:00，上海时间）"""
|
||||
rebate = self.get_rebate_amount(fee)
|
||||
if rebate <= 0:
|
||||
return
|
||||
|
||||
trade_utc = pd.Timestamp(timestamp, tz='UTC')
|
||||
trade_local = trade_utc.tz_convert('Asia/Shanghai')
|
||||
credit_local = (trade_local + pd.Timedelta(days=1)).normalize() + pd.Timedelta(hours=self.rebate_credit_hour)
|
||||
credit_utc = credit_local.tz_convert('UTC').tz_localize(None)
|
||||
|
||||
self.pending_rebates.append({
|
||||
'credit_time': credit_utc,
|
||||
'amount': rebate,
|
||||
'trade_time': trade_utc.tz_localize(None),
|
||||
})
|
||||
|
||||
def apply_pending_rebates(self, current_time):
|
||||
"""处理当前时刻前应到账的返佣"""
|
||||
if not self.pending_rebates:
|
||||
return
|
||||
|
||||
remaining = []
|
||||
for item in self.pending_rebates:
|
||||
if item['credit_time'] <= current_time:
|
||||
amount = item['amount']
|
||||
self.capital += amount
|
||||
self.total_rebate_credited += amount
|
||||
self.trades.append({
|
||||
'timestamp': current_time.strftime('%Y-%m-%d %H:%M'),
|
||||
'action': '返佣到账',
|
||||
'price': None,
|
||||
'size': None,
|
||||
'rebate': amount,
|
||||
'capital': self.capital,
|
||||
'reason': f"次日08:00返佣到账({item['trade_time'].strftime('%Y-%m-%d %H:%M')}手续费)"
|
||||
})
|
||||
logger.info(
|
||||
f"[{current_time.strftime('%Y-%m-%d %H:%M')}] 返佣到账: {amount:.4f}U | 可用资金: {self.capital:.4f}U"
|
||||
)
|
||||
else:
|
||||
remaining.append(item)
|
||||
|
||||
self.pending_rebates = remaining
|
||||
|
||||
def apply_entry_slippage(self, price, direction):
|
||||
"""按方向施加不利滑点"""
|
||||
if direction == 'long':
|
||||
return price * (1 + self.entry_slippage)
|
||||
return price * (1 - self.entry_slippage)
|
||||
|
||||
def load_one_minute_cache(self, start_ts, end_ts):
|
||||
"""加载并缓存1分钟K线，用于5分钟内走势确认"""
|
||||
query = BitMartETH1M.select().where(
|
||||
(BitMartETH1M.id >= start_ts) & (BitMartETH1M.id <= end_ts)
|
||||
).order_by(BitMartETH1M.id)
|
||||
|
||||
bucket = {}
|
||||
for row in query:
|
||||
five_min_start = int(row.id - (row.id % 300000))
|
||||
bucket.setdefault(five_min_start, []).append({
|
||||
'timestamp': int(row.id),
|
||||
'open': float(row.open) if row.open is not None else None,
|
||||
'high': float(row.high) if row.high is not None else None,
|
||||
'low': float(row.low) if row.low is not None else None,
|
||||
'close': float(row.close) if row.close is not None else None,
|
||||
})
|
||||
|
||||
self.one_minute_by_5m = bucket
|
||||
total_rows = sum(len(v) for v in bucket.values())
|
||||
logger.info(f"加载1分钟数据: {total_rows} 根 | 5分钟桶: {len(bucket)}")
|
||||
|
||||
def should_close_half_by_1m_trend(self, five_min_ts, middle_price, side):
|
||||
"""
|
||||
1分钟顺序确认中轨平半：
|
||||
- 多仓：先到中轨上方，再回踩中轨
|
||||
- 空仓：先到中轨下方，再反抽中轨
|
||||
"""
|
||||
minute_rows = self.one_minute_by_5m.get(five_min_ts, [])
|
||||
if not minute_rows:
|
||||
return False, None
|
||||
|
||||
seen_above_middle = False
|
||||
seen_below_middle = False
|
||||
|
||||
for minute in minute_rows:
|
||||
m_open = minute['open']
|
||||
m_high = minute['high']
|
||||
m_low = minute['low']
|
||||
m_close = minute['close']
|
||||
|
||||
if None in (m_open, m_high, m_low, m_close):
|
||||
continue
|
||||
|
||||
minute_time = pd.to_datetime(minute['timestamp'], unit='ms').strftime('%H:%M')
|
||||
|
||||
if side == 'long':
|
||||
# 当前1m开在中轨上方且回踩到中轨，视为有效回踩
|
||||
if m_open >= middle_price and m_low <= middle_price:
|
||||
return True, f"1m({minute_time})回踩中轨"
|
||||
|
||||
# 已经到过中轨上方后，再次触及中轨
|
||||
if seen_above_middle and m_low <= middle_price:
|
||||
return True, f"1m({minute_time})回踩中轨"
|
||||
|
||||
if m_high >= middle_price:
|
||||
seen_above_middle = True
|
||||
|
||||
else: # short
|
||||
# 当前1m开在中轨下方且反抽到中轨，视为有效反抽
|
||||
if m_open <= middle_price and m_high >= middle_price:
|
||||
return True, f"1m({minute_time})反抽中轨"
|
||||
|
||||
# 已经到过中轨下方后，再次触及中轨
|
||||
if seen_below_middle and m_high >= middle_price:
|
||||
return True, f"1m({minute_time})反抽中轨"
|
||||
|
||||
if m_low <= middle_price:
|
||||
seen_below_middle = True
|
||||
|
||||
return False, None
|
||||
|
||||
def get_touch_entry_price(self, five_min_ts, direction, touch_price):
|
||||
"""
|
||||
触轨开仓的保守成交价：
|
||||
- 在该5分钟内找到首个触轨1m
|
||||
- 用该1m收盘价作为基准
|
||||
- 为避免“过于理想”，不允许优于触轨价，再叠加不利滑点
|
||||
"""
|
||||
minute_rows = self.one_minute_by_5m.get(five_min_ts, [])
|
||||
if not minute_rows:
|
||||
return self.apply_entry_slippage(touch_price, direction)
|
||||
|
||||
trigger_close = None
|
||||
for minute in minute_rows:
|
||||
m_high = minute['high']
|
||||
m_low = minute['low']
|
||||
m_close = minute['close']
|
||||
if None in (m_high, m_low, m_close):
|
||||
continue
|
||||
|
||||
if direction == 'short' and m_high >= touch_price:
|
||||
trigger_close = m_close
|
||||
break
|
||||
if direction == 'long' and m_low <= touch_price:
|
||||
trigger_close = m_close
|
||||
break
|
||||
|
||||
if trigger_close is None:
|
||||
base_price = touch_price
|
||||
elif direction == 'long':
|
||||
base_price = max(touch_price, trigger_close)
|
||||
else:
|
||||
base_price = min(touch_price, trigger_close)
|
||||
|
||||
return self.apply_entry_slippage(base_price, direction)
|
||||
|
||||
def clear_delay_reversal(self):
|
||||
"""清理延迟反转状态"""
|
||||
self.delay_reverse_price = None
|
||||
self.delay_reverse_type = None
|
||||
self.delay_reverse_kline_index = None
|
||||
|
||||
def mark_delay_reversal(self, reverse_type, trigger_price, kline_index, timestamp):
|
||||
"""记录延迟反转触发信息"""
|
||||
self.delay_reverse_type = reverse_type
|
||||
self.delay_reverse_price = trigger_price
|
||||
self.delay_reverse_kline_index = kline_index
|
||||
|
||||
if reverse_type == 'long_to_short':
|
||||
logger.info(f"[{timestamp}] 多仓触上轨 @ {trigger_price:.2f}，进入延迟反转")
|
||||
else:
|
||||
logger.info(f"[{timestamp}] 空仓触下轨 @ {trigger_price:.2f}，进入延迟反转")
|
||||
|
||||
def reverse_position(self, price, new_direction, timestamp, reason):
|
||||
"""全平后反向开仓"""
|
||||
if self.position == 0:
|
||||
self.clear_delay_reversal()
|
||||
return False
|
||||
|
||||
close_side = "多" if self.position > 0 else "空"
|
||||
open_side = "多" if new_direction == "long" else "空"
|
||||
self.close_position(price, 1.0, timestamp, f"{reason}-平{close_side}")
|
||||
open_price = self.apply_entry_slippage(price, new_direction)
|
||||
self.open_position(open_price, new_direction, timestamp, f"{reason}-开{open_side}")
|
||||
self.mid_closed_half = False
|
||||
self.clear_delay_reversal()
|
||||
return True
|
||||
|
||||
def check_delay_reversal_signal(self, i, row, prev_row):
|
||||
"""检查延迟反转是否在当前收盘K成立（仅返回信号，不直接执行）"""
|
||||
if self.position == 0 or self.delay_reverse_price is None or self.delay_reverse_kline_index is None:
|
||||
return None
|
||||
|
||||
offset = i - self.delay_reverse_kline_index
|
||||
# 禁止同K确认，最早次K确认
|
||||
if offset <= 0:
|
||||
return None
|
||||
|
||||
high = row['high']
|
||||
low = row['low']
|
||||
|
||||
if self.delay_reverse_type == 'long_to_short':
|
||||
# 情况1：触上轨后，次K回调到记录上轨价
|
||||
if offset == 1 and low <= self.delay_reverse_price:
|
||||
return 'short', "延迟反转-次K回调确认", self.delay_reverse_price
|
||||
|
||||
# 情况2：持续等待，动态追踪上一根K线条件
|
||||
if offset >= 2 and prev_row is not None:
|
||||
prev_upper = prev_row['upper']
|
||||
prev_touch_upper = pd.notna(prev_upper) and prev_row['high'] >= prev_upper
|
||||
if prev_touch_upper:
|
||||
if low <= prev_upper:
|
||||
return 'short', "延迟反转-上一根触上轨后回调确认", prev_upper
|
||||
else:
|
||||
prev_body_low = min(prev_row['open'], prev_row['close'])
|
||||
if low <= prev_body_low:
|
||||
return 'short', "延迟反转-跌破上一根实体确认", prev_body_low
|
||||
|
||||
elif self.delay_reverse_type == 'short_to_long':
|
||||
# 情况1：触下轨后，次K反弹到记录下轨价
|
||||
if offset == 1 and high >= self.delay_reverse_price:
|
||||
return 'long', "延迟反转-次K反弹确认", self.delay_reverse_price
|
||||
|
||||
# 情况2：持续等待，动态追踪上一根K线条件
|
||||
if offset >= 2 and prev_row is not None:
|
||||
prev_lower = prev_row['lower']
|
||||
prev_touch_lower = pd.notna(prev_lower) and prev_row['low'] <= prev_lower
|
||||
if prev_touch_lower:
|
||||
if high >= prev_lower:
|
||||
return 'long', "延迟反转-上一根触下轨后反弹确认", prev_lower
|
||||
else:
|
||||
prev_body_high = max(prev_row['open'], prev_row['close'])
|
||||
if high >= prev_body_high:
|
||||
return 'long', "延迟反转-突破上一根实体确认", prev_body_high
|
||||
|
||||
return None
|
||||
|
||||
def open_position(self, price, direction, timestamp, reason):
|
||||
"""开仓或加仓"""
|
||||
if self.position_count not in (0, 1):
|
||||
return False
|
||||
|
||||
if self.position_count == 1:
|
||||
current_direction = 'long' if self.position > 0 else 'short'
|
||||
if direction != current_direction:
|
||||
logger.warning("加仓方向不一致，跳过")
|
||||
return False
|
||||
|
||||
margin_ratio = self.margin_ratio_1 if self.position_count == 0 else self.margin_ratio_2
|
||||
margin = self.capital * margin_ratio
|
||||
if margin <= 0:
|
||||
logger.warning(f"[{timestamp}] 资金不足，无法开仓 | 可用资金: {self.capital:.4f}U")
|
||||
return False
|
||||
|
||||
position_size = margin * self.leverage / price
|
||||
fee = position_size * price * self.fee_rate
|
||||
required = margin + fee
|
||||
if self.capital < required:
|
||||
logger.warning(
|
||||
f"[{timestamp}] 可用资金不足，无法开仓 | 需要: {required:.4f}U | 可用: {self.capital:.4f}U"
|
||||
)
|
||||
return False
|
||||
|
||||
# 冻结保证金并扣除手续费
|
||||
self.capital -= required
|
||||
self.schedule_rebate(fee, timestamp)
|
||||
|
||||
if self.position_count == 0:
|
||||
self.position = position_size if direction == 'long' else -position_size
|
||||
self.entry_price = price
|
||||
self.total_margin = margin
|
||||
self.position_count = 1
|
||||
action = f'开{direction}'
|
||||
else:
|
||||
old_size = abs(self.position)
|
||||
new_size = old_size + position_size
|
||||
old_value = old_size * self.entry_price
|
||||
new_value = position_size * price
|
||||
self.entry_price = (old_value + new_value) / new_size
|
||||
self.position = new_size if direction == 'long' else -new_size
|
||||
self.total_margin += margin
|
||||
self.position_count = 2
|
||||
action = f'加{direction}'
|
||||
|
||||
self.mid_closed_half = False
|
||||
|
||||
self.trades.append({
|
||||
'timestamp': timestamp,
|
||||
'action': action,
|
||||
'price': price,
|
||||
'size': position_size,
|
||||
'margin': margin,
|
||||
'fee': fee,
|
||||
'rebate': self.get_rebate_amount(fee),
|
||||
'capital': self.capital,
|
||||
'reason': reason
|
||||
})
|
||||
|
||||
logger.info(
|
||||
f"[{timestamp}] {action} @ {price:.2f} | 仓位: {position_size:.4f} | "
|
||||
f"保证金: {margin:.4f}U | 手续费: {fee:.4f}U | 返佣待到账: {self.get_rebate_amount(fee):.4f}U | "
|
||||
f"可用资金: {self.capital:.4f}U | {reason}"
|
||||
)
|
||||
return True
|
||||
|
||||
def close_position(self, price, ratio, timestamp, reason):
|
||||
"""平仓"""
|
||||
if self.position == 0:
|
||||
return False
|
||||
|
||||
ratio = min(max(ratio, 0.0), 1.0)
|
||||
if ratio == 0:
|
||||
return False
|
||||
|
||||
close_size = abs(self.position) * ratio
|
||||
if self.position > 0:
|
||||
pnl = close_size * (price - self.entry_price)
|
||||
else:
|
||||
pnl = close_size * (self.entry_price - price)
|
||||
|
||||
fee = close_size * price * self.fee_rate
|
||||
|
||||
released_margin = self.total_margin * ratio
|
||||
self.capital += released_margin + pnl - fee
|
||||
self.schedule_rebate(fee, timestamp)
|
||||
|
||||
if ratio >= 0.999:
|
||||
self.position = 0
|
||||
self.position_count = 0
|
||||
self.total_margin = 0
|
||||
self.entry_price = 0
|
||||
self.mid_closed_half = False
|
||||
self.clear_delay_reversal()
|
||||
else:
|
||||
self.position *= (1 - ratio)
|
||||
self.total_margin *= (1 - ratio)
|
||||
if abs(self.position) < 1e-12:
|
||||
self.position = 0
|
||||
self.position_count = 0
|
||||
self.total_margin = 0
|
||||
self.entry_price = 0
|
||||
self.mid_closed_half = False
|
||||
self.clear_delay_reversal()
|
||||
|
||||
self.trades.append({
|
||||
'timestamp': timestamp,
|
||||
'action': f'平仓{int(ratio*100)}%',
|
||||
'price': price,
|
||||
'size': close_size,
|
||||
'pnl': pnl,
|
||||
'fee': fee,
|
||||
'rebate': self.get_rebate_amount(fee),
|
||||
'capital': self.capital,
|
||||
'reason': reason
|
||||
})
|
||||
|
||||
logger.info(f"[{timestamp}] 平仓{int(ratio*100)}% @ {price:.2f} | "
|
||||
f"盈亏: {pnl:.4f}U | 手续费: {fee:.4f}U | 返佣待到账: {self.get_rebate_amount(fee):.4f}U | "
|
||||
f"可用资金: {self.capital:.4f}U | {reason}")
|
||||
return True
|
||||
|
||||
def check_stop_loss(self, high, low):
|
||||
"""检查当前收盘K是否触发止损信号"""
|
||||
if self.position == 0:
|
||||
return False
|
||||
|
||||
stop_price = low if self.position > 0 else high
|
||||
if self.position > 0:
|
||||
unrealized_pnl = abs(self.position) * (stop_price - self.entry_price)
|
||||
else:
|
||||
unrealized_pnl = abs(self.position) * (self.entry_price - stop_price)
|
||||
|
||||
return unrealized_pnl <= -self.total_margin * self.stop_loss_ratio
|
||||
|
||||
def run_backtest(self, start_date, end_date):
|
||||
"""运行回测（开仓当K触发，平仓/止损仍按下一根K开盘执行）"""
|
||||
# 重置状态，支持同一实例重复回测
|
||||
self.capital = self.initial_capital
|
||||
self.position = 0
|
||||
self.position_count = 0
|
||||
self.entry_price = 0
|
||||
self.total_margin = 0
|
||||
self.mid_closed_half = False
|
||||
self.trades = []
|
||||
self.daily_pnl = []
|
||||
self.pending_rebates = []
|
||||
self.total_rebate_credited = 0.0
|
||||
self.clear_delay_reversal()
|
||||
|
||||
logger.info(f"{'='*80}")
|
||||
logger.info(f"开始回测: {start_date} ~ {end_date}")
|
||||
logger.info(f"初始资金: {self.initial_capital}U | 杠杆: {self.leverage}x | BB({self.bb_period}, {self.bb_std})")
|
||||
logger.info(f"{'='*80}")
|
||||
|
||||
# 从数据库加载数据
|
||||
start_dt = pd.Timestamp(start_date)
|
||||
end_dt = pd.Timestamp(end_date)
|
||||
if isinstance(end_date, str) and len(end_date) <= 10:
|
||||
end_dt = end_dt + pd.Timedelta(days=1) - pd.Timedelta(milliseconds=1)
|
||||
|
||||
self.current_run_label = f"{start_dt.strftime('%Y%m%d')}_{end_dt.strftime('%Y%m%d')}"
|
||||
|
||||
start_ts = int(start_dt.timestamp() * 1000)
|
||||
end_ts = int(end_dt.timestamp() * 1000)
|
||||
|
||||
query = BitMartETH5M.select().where(
|
||||
(BitMartETH5M.id >= start_ts) & (BitMartETH5M.id <= end_ts)
|
||||
).order_by(BitMartETH5M.id)
|
||||
|
||||
data = []
|
||||
for row in query:
|
||||
data.append({
|
||||
'timestamp': row.id,
|
||||
'open': row.open,
|
||||
'high': row.high,
|
||||
'low': row.low,
|
||||
'close': row.close
|
||||
})
|
||||
|
||||
if not data:
|
||||
logger.error("没有找到数据！")
|
||||
return None
|
||||
|
||||
df = pd.DataFrame(data)
|
||||
df['datetime'] = pd.to_datetime(df['timestamp'], unit='ms')
|
||||
|
||||
logger.info(f"加载数据: {len(df)} 根K线")
|
||||
logger.info(f"时间范围: {df['datetime'].min()} ~ {df['datetime'].max()}")
|
||||
|
||||
# 计算布林带
|
||||
df = self.calculate_bollinger_bands(df)
|
||||
|
||||
if len(df) <= self.bb_period + 1:
|
||||
logger.error("数据不足，无法执行回测")
|
||||
return None
|
||||
|
||||
# 逐根K线回测（开仓当K触发，平仓/止损下一K开盘执行）
|
||||
for i in range(self.bb_period, len(df) - 1):
|
||||
row = df.iloc[i]
|
||||
prev_row = df.iloc[i-1] if i > 0 else None
|
||||
next_row = df.iloc[i + 1]
|
||||
|
||||
signal_dt = row['datetime']
|
||||
signal_ts = signal_dt.strftime('%Y-%m-%d %H:%M')
|
||||
five_min_ts = int(row['timestamp'])
|
||||
execute_ts = next_row['datetime'].strftime('%Y-%m-%d %H:%M')
|
||||
next_open = float(next_row['open']) if pd.notna(next_row['open']) else None
|
||||
|
||||
high = row['high']
|
||||
low = row['low']
|
||||
upper = row['upper']
|
||||
lower = row['lower']
|
||||
middle = row['middle']
|
||||
|
||||
# 先处理当前收盘时刻返佣到账
|
||||
self.apply_pending_rebates(signal_dt)
|
||||
|
||||
if pd.isna(upper) or pd.isna(lower) or pd.isna(middle):
|
||||
continue
|
||||
if next_open is None:
|
||||
continue
|
||||
|
||||
# 检查止损（收盘确认，下一K开盘平仓）
|
||||
if self.check_stop_loss(high, low):
|
||||
logger.warning(f"[{signal_ts}] 触发止损信号，下一K开盘执行")
|
||||
self.close_position(next_open, 1.0, execute_ts, f"止损-收盘确认({signal_ts})")
|
||||
continue
|
||||
|
||||
# 已处于延迟反转状态时，先检查确认逻辑
|
||||
if self.delay_reverse_price is not None:
|
||||
reversal_signal = self.check_delay_reversal_signal(i, row, prev_row)
|
||||
if reversal_signal is not None and self.position != 0:
|
||||
new_direction, reason, reversal_price = reversal_signal
|
||||
if reversal_price is None or pd.isna(reversal_price):
|
||||
reversal_price = float(row['close'])
|
||||
close_side = "多" if self.position > 0 else "空"
|
||||
open_side = "多" if new_direction == 'long' else "空"
|
||||
self.close_position(
|
||||
reversal_price,
|
||||
1.0,
|
||||
signal_ts,
|
||||
f"{reason}-当K确认({signal_ts})-平{close_side}"
|
||||
)
|
||||
open_price = self.apply_entry_slippage(reversal_price, new_direction)
|
||||
self.open_position(
|
||||
open_price,
|
||||
new_direction,
|
||||
signal_ts,
|
||||
f"{reason}-当K确认({signal_ts})-开{open_side}"
|
||||
)
|
||||
self.mid_closed_half = False
|
||||
self.clear_delay_reversal()
|
||||
continue
|
||||
|
||||
# === 中轨平仓逻辑 ===
|
||||
if self.position != 0:
|
||||
had_mid_closed_half = self.mid_closed_half
|
||||
if self.position > 0: # 多仓
|
||||
# 回到开仓价全平+反手（仅在此前已平半的前提下触发）
|
||||
if had_mid_closed_half and low <= self.entry_price:
|
||||
self.close_position(next_open, 1.0, execute_ts, f"回开仓价全平-收盘确认({signal_ts})")
|
||||
entry_price = self.apply_entry_slippage(next_open, 'short')
|
||||
self.open_position(entry_price, 'short', execute_ts, f"回开仓价反手开空-收盘确认({signal_ts})")
|
||||
self.mid_closed_half = False
|
||||
continue
|
||||
# 触中轨平半（收盘确认）
|
||||
if not had_mid_closed_half and low <= middle <= high:
|
||||
self.close_position(next_open, 0.5, execute_ts, f"触中轨平50%-收盘确认({signal_ts})")
|
||||
self.mid_closed_half = True
|
||||
continue
|
||||
|
||||
else: # 空仓
|
||||
# 回到开仓价全平+反手（仅在此前已平半的前提下触发）
|
||||
if had_mid_closed_half and high >= self.entry_price:
|
||||
self.close_position(next_open, 1.0, execute_ts, f"回开仓价全平-收盘确认({signal_ts})")
|
||||
entry_price = self.apply_entry_slippage(next_open, 'long')
|
||||
self.open_position(entry_price, 'long', execute_ts, f"回开仓价反手开多-收盘确认({signal_ts})")
|
||||
self.mid_closed_half = False
|
||||
continue
|
||||
# 触中轨平半（收盘确认）
|
||||
if not had_mid_closed_half and low <= middle <= high:
|
||||
self.close_position(next_open, 0.5, execute_ts, f"触中轨平50%-收盘确认({signal_ts})")
|
||||
self.mid_closed_half = True
|
||||
continue
|
||||
|
||||
# === 开仓与加仓逻辑 ===
|
||||
if self.position == 0: # 空仓
|
||||
self.clear_delay_reversal()
|
||||
|
||||
# 触上轨开空
|
||||
if high >= upper:
|
||||
entry_price = self.get_touch_entry_price(five_min_ts, 'short', upper)
|
||||
self.open_position(entry_price, 'short', signal_ts, f"触上轨开空-当K触发({signal_ts})")
|
||||
|
||||
# 触下轨开多
|
||||
elif low <= lower:
|
||||
entry_price = self.get_touch_entry_price(five_min_ts, 'long', lower)
|
||||
self.open_position(entry_price, 'long', signal_ts, f"触下轨开多-当K触发({signal_ts})")
|
||||
continue
|
||||
|
||||
# 有持仓：先检查是否触发延迟反转（核心）
|
||||
if self.position > 0 and high >= upper:
|
||||
self.mark_delay_reversal('long_to_short', upper, i, signal_ts)
|
||||
continue
|
||||
|
||||
elif self.position < 0 and low <= lower:
|
||||
self.mark_delay_reversal('short_to_long', lower, i, signal_ts)
|
||||
continue
|
||||
|
||||
# 进入延迟反转等待后，不再执行加仓
|
||||
if self.delay_reverse_price is not None:
|
||||
continue
|
||||
|
||||
# 同向加仓最多1次
|
||||
if self.position_count == 1:
|
||||
if self.position > 0 and low <= lower:
|
||||
entry_price = self.get_touch_entry_price(five_min_ts, 'long', lower)
|
||||
self.open_position(entry_price, 'long', signal_ts, f"触下轨加多-当K触发({signal_ts})")
|
||||
elif self.position < 0 and high >= upper:
|
||||
entry_price = self.get_touch_entry_price(five_min_ts, 'short', upper)
|
||||
self.open_position(entry_price, 'short', signal_ts, f"触上轨加空-当K触发({signal_ts})")
|
||||
|
||||
# 回测末尾再处理一次返佣到账
|
||||
self.apply_pending_rebates(df.iloc[-1]['datetime'])
|
||||
|
||||
# 最后平仓
|
||||
if self.position != 0:
|
||||
final_price = df.iloc[-1]['close']
|
||||
final_time = df.iloc[-1]['datetime'].strftime('%Y-%m-%d %H:%M')
|
||||
self.close_position(final_price, 1.0, final_time, "回测结束平仓")
|
||||
|
||||
# 生成报告
|
||||
return self.generate_report(df)
|
||||
|
||||
def generate_report(self, df):
|
||||
"""生成回测报告"""
|
||||
logger.info(f"\n{'='*80}")
|
||||
logger.info("回测报告")
|
||||
logger.info(f"{'='*80}")
|
||||
|
||||
# 基本统计
|
||||
total_trades = len([t for t in self.trades if '开' in t['action']])
|
||||
win_trades = len([t for t in self.trades if '平' in t['action'] and t.get('pnl', 0) > 0])
|
||||
loss_trades = len([t for t in self.trades if '平' in t['action'] and t.get('pnl', 0) < 0])
|
||||
|
||||
total_pnl = sum([t.get('pnl', 0) for t in self.trades])
|
||||
total_fee = sum([t.get('fee', 0) for t in self.trades])
|
||||
total_rebate_expected = sum([t.get('rebate', 0) for t in self.trades if t.get('fee', 0) > 0])
|
||||
pending_rebate = sum([x['amount'] for x in self.pending_rebates])
|
||||
realized_net_fee = total_fee - self.total_rebate_credited
|
||||
|
||||
final_capital = self.capital
|
||||
roi = (final_capital - self.initial_capital) / self.initial_capital * 100
|
||||
|
||||
logger.info(f"初始资金: {self.initial_capital:.2f}U")
|
||||
logger.info(f"最终资金: {final_capital:.2f}U")
|
||||
logger.info(f"总盈亏: {total_pnl:.2f}U")
|
||||
logger.info(f"总手续费(开平全额): {total_fee:.2f}U")
|
||||
logger.info(f"返佣应返总额: {total_rebate_expected:.2f}U")
|
||||
logger.info(f"返佣已到账: {self.total_rebate_credited:.2f}U")
|
||||
logger.info(f"返佣待到账: {pending_rebate:.2f}U")
|
||||
logger.info(f"已实现净手续费: {realized_net_fee:.2f}U")
|
||||
logger.info(f"净收益: {final_capital - self.initial_capital:.2f}U")
|
||||
logger.info(f"收益率: {roi:.2f}%")
|
||||
logger.info(f"总交易次数: {total_trades}")
|
||||
logger.info(f"盈利次数: {win_trades}")
|
||||
logger.info(f"亏损次数: {loss_trades}")
|
||||
if win_trades + loss_trades > 0:
|
||||
logger.info(f"胜率: {win_trades/(win_trades+loss_trades)*100:.2f}%")
|
||||
|
||||
# 保存交易记录
|
||||
trades_df = pd.DataFrame(self.trades)
|
||||
output_dir = Path(__file__).parent / 'backtest_outputs' / 'trades'
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
output_file = output_dir / f'bb_backtest_{self.current_run_label}_trades.csv'
|
||||
trades_df.to_csv(output_file, index=False, encoding='utf-8-sig')
|
||||
logger.info(f"\n交易记录已保存到: {output_file}")
|
||||
|
||||
return {
|
||||
'initial_capital': self.initial_capital,
|
||||
'final_capital': final_capital,
|
||||
'total_pnl': total_pnl,
|
||||
'total_fee': total_fee,
|
||||
'total_rebate_expected': total_rebate_expected,
|
||||
'total_rebate_credited': self.total_rebate_credited,
|
||||
'pending_rebate': pending_rebate,
|
||||
'realized_net_fee': realized_net_fee,
|
||||
'roi': roi,
|
||||
'total_trades': total_trades,
|
||||
'win_trades': win_trades,
|
||||
'loss_trades': loss_trades,
|
||||
'trades_file': str(output_file),
|
||||
'trades': self.trades
|
||||
}
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# 连接数据库
|
||||
db.connect(reuse_if_open=True)
|
||||
|
||||
try:
|
||||
# 创建回测实例
|
||||
backtest = BollingerBandBacktest()
|
||||
|
||||
# 运行回测（2026年全年）
|
||||
result = backtest.run_backtest('2026-01-01', '2026-12-31')
|
||||
|
||||
if result:
|
||||
logger.success(f"\n回测完成！最终收益率: {result['roi']:.2f}%")
|
||||
|
||||
finally:
|
||||
db.close()
|
||||
626
bb_delay_reversal_trade.py
Normal file
626
bb_delay_reversal_trade.py
Normal file
@@ -0,0 +1,626 @@
|
||||
"""
|
||||
布林带均值回归策略 — 实盘交易 (D方案: 递增加仓)
|
||||
BB(10, 2.5) | 5分钟K线 | ETH | 50x杠杆 逐仓 | 递增加仓+1%/次 max=3
|
||||
|
||||
逻辑:
|
||||
- 价格触及上布林带 → 平多(如有) + 开空; 已持空则加仓
|
||||
- 价格触及下布林带 → 平空(如有) + 开多; 已持多则加仓
|
||||
- 始终持仓（多空翻转 + 同向加仓）
|
||||
- 加仓比例: 开仓1%, 第1次加仓2%, 第2次3%, 第3次4%, 最多加仓3次
|
||||
|
||||
使用浏览器自动化进行开平仓（有手续费返佣），API仅用于查询数据
|
||||
"""
|
||||
import time
|
||||
import numpy as np
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
|
||||
from loguru import logger
|
||||
from bitmart.api_contract import APIContract
|
||||
from bit_tools import openBrowser
|
||||
from DrissionPage import ChromiumPage, ChromiumOptions
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 配置
|
||||
# ---------------------------------------------------------------------------
|
||||
class BBDelayReversalConfig:
|
||||
# API 凭证
|
||||
API_KEY = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8"
|
||||
SECRET_KEY = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5"
|
||||
MEMO = "合约交易"
|
||||
|
||||
# 合约
|
||||
CONTRACT_SYMBOL = "ETHUSDT"
|
||||
TRADE_URL = "https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT"
|
||||
|
||||
# 浏览器
|
||||
BIT_ID = "f2320f57e24c45529a009e1541e25961"
|
||||
|
||||
# 布林带参数
|
||||
BB_PERIOD = 10 # 10根5分钟K线 = 50分钟回看
|
||||
BB_STD = 2.5 # 标准差倍数
|
||||
|
||||
# 仓位管理
|
||||
LEVERAGE = 50 # 杠杆倍数
|
||||
OPEN_TYPE = "isolated" # 逐仓模式
|
||||
MARGIN_PCT = 0.01 # 首次开仓用权益的1%作为保证金
|
||||
|
||||
# 递增加仓 (D方案)
|
||||
PYRAMID_STEP = 0.01 # 每次加仓增加1%权益比例 (1%→2%→3%→4%)
|
||||
PYRAMID_MAX = 3 # 最多加仓3次 (首次开仓不算)
|
||||
|
||||
# 风控
|
||||
MAX_DAILY_LOSS = 50.0 # 日最大亏损(U)，达到后停止交易
|
||||
COOLDOWN_SECONDS = 30 # 两次交易之间最小间隔(秒)
|
||||
|
||||
# 运行
|
||||
POLL_INTERVAL = 5 # 主循环轮询间隔(秒)
|
||||
KLINE_STEP = 5 # K线周期(分钟)
|
||||
KLINE_HOURS = 2 # 获取最近多少小时K线(需覆盖BB_PERIOD)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 布林带计算
|
||||
# ---------------------------------------------------------------------------
|
||||
def calc_bollinger(closes: list, period: int, n_std: float):
|
||||
"""计算布林带，返回 (mid, upper, lower) 或 None（数据不足时）"""
|
||||
if len(closes) < period:
|
||||
return None
|
||||
arr = np.array(closes[-period:], dtype=float)
|
||||
mid = arr.mean()
|
||||
std = arr.std(ddof=0)
|
||||
upper = mid + n_std * std
|
||||
lower = mid - n_std * std
|
||||
return mid, upper, lower
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 交易主类
|
||||
# ---------------------------------------------------------------------------
|
||||
class BBDelayReversalTrader:
|
||||
def __init__(self, cfg: BBDelayReversalConfig = None, bit_id: str = None):
|
||||
self.cfg = cfg or BBDelayReversalConfig()
|
||||
if bit_id:
|
||||
self.cfg.BIT_ID = bit_id
|
||||
self.api = APIContract(
|
||||
self.cfg.API_KEY, self.cfg.SECRET_KEY, self.cfg.MEMO,
|
||||
timeout=(5, 15)
|
||||
)
|
||||
|
||||
# 浏览器
|
||||
self.page: ChromiumPage | None = None
|
||||
self.page_start = True # 需要(重新)打开浏览器
|
||||
self.last_page_open_time = 0.0 # 上次打开浏览器的时间
|
||||
self.PAGE_REFRESH_INTERVAL = 1800 # 每30分钟关闭重开浏览器
|
||||
|
||||
# 持仓状态: -1=空, 0=无, 1=多
|
||||
self.position = 0
|
||||
self.open_avg_price = None
|
||||
self.current_amount = None
|
||||
|
||||
# 加仓状态
|
||||
self.pyramid_count = 0 # 当前已加仓次数 (0=仅首次开仓)
|
||||
|
||||
# 风控
|
||||
self.daily_pnl = 0.0
|
||||
self.daily_stopped = False
|
||||
self.current_date = None
|
||||
self.last_trade_time = 0.0
|
||||
|
||||
# 日志
|
||||
self.log_dir = Path(__file__).resolve().parent
|
||||
logger.add(
|
||||
self.log_dir / "bb_delay_reversal_trade_{time:YYYY-MM-DD}.log",
|
||||
rotation="1 day", retention="30 days",
|
||||
format="{time:YYYY-MM-DD HH:mm:ss} | {level} | {message}"
|
||||
)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# API 封装
|
||||
# ------------------------------------------------------------------
|
||||
def get_klines(self) -> list | None:
|
||||
"""获取最近N小时的5分钟K线，返回 [{id, open, high, low, close}, ...]"""
|
||||
try:
|
||||
end_time = int(time.time())
|
||||
start_time = end_time - 3600 * self.cfg.KLINE_HOURS
|
||||
resp = self.api.get_kline(
|
||||
contract_symbol=self.cfg.CONTRACT_SYMBOL,
|
||||
step=self.cfg.KLINE_STEP,
|
||||
start_time=start_time,
|
||||
end_time=end_time
|
||||
)[0]
|
||||
if resp.get("code") != 1000:
|
||||
logger.error(f"获取K线失败: {resp}")
|
||||
return None
|
||||
data = resp["data"]
|
||||
klines = []
|
||||
for k in data:
|
||||
klines.append({
|
||||
"id": int(k["timestamp"]),
|
||||
"open": float(k["open_price"]),
|
||||
"high": float(k["high_price"]),
|
||||
"low": float(k["low_price"]),
|
||||
"close": float(k["close_price"]),
|
||||
})
|
||||
klines.sort(key=lambda x: x["id"])
|
||||
return klines
|
||||
except Exception as e:
|
||||
logger.error(f"获取K线异常: {e}")
|
||||
return None
|
||||
|
||||
def get_current_price(self) -> float | None:
|
||||
"""获取当前最新价格（最近1分钟K线收盘价）"""
|
||||
try:
|
||||
end_time = int(time.time())
|
||||
resp = self.api.get_kline(
|
||||
contract_symbol=self.cfg.CONTRACT_SYMBOL,
|
||||
step=1,
|
||||
start_time=end_time - 300,
|
||||
end_time=end_time
|
||||
)[0]
|
||||
if resp.get("code") == 1000 and resp["data"]:
|
||||
return float(resp["data"][-1]["close_price"])
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"获取价格异常: {e}")
|
||||
return None
|
||||
|
||||
def get_balance(self) -> float | None:
|
||||
"""获取合约账户可用余额"""
|
||||
try:
|
||||
resp = self.api.get_assets_detail()[0]
|
||||
if resp.get("code") == 1000:
|
||||
data = resp["data"]
|
||||
if isinstance(data, dict):
|
||||
return float(data.get("available_balance", 0))
|
||||
elif isinstance(data, list):
|
||||
for asset in data:
|
||||
if asset.get("currency") == "USDT":
|
||||
return float(asset.get("available_balance", 0))
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"查询余额异常: {e}")
|
||||
return None
|
||||
|
||||
def get_position_status(self) -> bool:
|
||||
"""查询当前持仓，更新 self.position / open_avg_price / current_amount"""
|
||||
try:
|
||||
resp = self.api.get_position(contract_symbol=self.cfg.CONTRACT_SYMBOL)[0]
|
||||
if resp.get("code") != 1000:
|
||||
logger.error(f"查询持仓失败: {resp}")
|
||||
return False
|
||||
positions = resp["data"]
|
||||
if not positions:
|
||||
self.position = 0
|
||||
self.open_avg_price = None
|
||||
self.current_amount = None
|
||||
return True
|
||||
pos = positions[0]
|
||||
self.position = 1 if pos["position_type"] == 1 else -1
|
||||
self.open_avg_price = float(pos["open_avg_price"])
|
||||
self.current_amount = float(pos["current_amount"])
|
||||
unrealized = float(pos.get("unrealized_value", 0))
|
||||
logger.debug(f"持仓: dir={self.position} price={self.open_avg_price} "
|
||||
f"amt={self.current_amount} upnl={unrealized:.2f}")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"查询持仓异常: {e}")
|
||||
return False
|
||||
|
||||
def set_leverage(self) -> bool:
|
||||
"""设置杠杆和逐仓模式"""
|
||||
try:
|
||||
resp = self.api.post_submit_leverage(
|
||||
contract_symbol=self.cfg.CONTRACT_SYMBOL,
|
||||
leverage=str(self.cfg.LEVERAGE),
|
||||
open_type=self.cfg.OPEN_TYPE
|
||||
)[0]
|
||||
if resp.get("code") == 1000:
|
||||
logger.success(f"杠杆设置成功: {self.cfg.LEVERAGE}x {self.cfg.OPEN_TYPE}")
|
||||
return True
|
||||
else:
|
||||
logger.error(f"杠杆设置失败: {resp}")
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"设置杠杆异常: {e}")
|
||||
return False
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 浏览器自动化
|
||||
# ------------------------------------------------------------------
|
||||
def open_browser(self) -> bool:
|
||||
"""打开浏览器并进入交易页面"""
|
||||
try:
|
||||
bit_port = openBrowser(id=self.cfg.BIT_ID)
|
||||
co = ChromiumOptions()
|
||||
co.set_local_port(port=bit_port)
|
||||
self.page = ChromiumPage(addr_or_opts=co)
|
||||
self.last_page_open_time = time.time()
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"打开浏览器失败: {e}")
|
||||
return False
|
||||
|
||||
def click_safe(self, xpath, sleep=0.5) -> bool:
|
||||
"""安全点击元素"""
|
||||
try:
|
||||
ele = self.page.ele(xpath)
|
||||
if not ele:
|
||||
return False
|
||||
ele.click(by_js=True)
|
||||
time.sleep(sleep)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning(f"点击失败 [{xpath}]: {e}")
|
||||
return False
|
||||
|
||||
def browser_close_position(self) -> bool:
|
||||
"""浏览器点击市价全平"""
|
||||
logger.info("浏览器操作: 市价平仓")
|
||||
return self.click_safe('x://span[normalize-space(text()) ="市价"]')
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 仓位操作
|
||||
# ------------------------------------------------------------------
|
||||
def calc_order_usdt(self, is_add: bool = False) -> float:
|
||||
"""
|
||||
计算开仓/加仓金额(U)
|
||||
首次开仓: 余额 × MARGIN_PCT (1%)
|
||||
加仓: 余额 × (MARGIN_PCT + PYRAMID_STEP × (pyramid_count+1))
|
||||
例: 开仓1%, 第1次加仓2%, 第2次加仓3%, 第3次加仓4%
|
||||
"""
|
||||
balance = self.get_balance()
|
||||
if balance is None or balance <= 0:
|
||||
logger.warning(f"余额不足或查询失败: {balance}")
|
||||
return 0
|
||||
if is_add:
|
||||
pct = self.cfg.MARGIN_PCT + self.cfg.PYRAMID_STEP * (self.pyramid_count + 1)
|
||||
else:
|
||||
pct = self.cfg.MARGIN_PCT
|
||||
order_usdt = round(balance * pct, 2)
|
||||
logger.info(f"仓位计算: 余额={balance:.2f} × {pct:.0%} = {order_usdt} U"
|
||||
f" ({'加仓#' + str(self.pyramid_count+1) if is_add else '首次开仓'})")
|
||||
return order_usdt
|
||||
|
||||
def verify_position(self, expected: int) -> bool:
|
||||
"""验证持仓方向"""
|
||||
if self.get_position_status():
|
||||
if self.position == expected:
|
||||
return True
|
||||
logger.warning(f"持仓方向不符: 期望{expected}, 实际{self.position}")
|
||||
return False
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 风控
|
||||
# ------------------------------------------------------------------
|
||||
def check_daily_reset(self):
|
||||
"""每日重置(UTC+8 00:00 = UTC 16:00)"""
|
||||
now = datetime.now(timezone.utc)
|
||||
# 用UTC日期做简单日切
|
||||
today = now.date()
|
||||
if self.current_date != today:
|
||||
if self.current_date is not None:
|
||||
logger.info(f"日切: {self.current_date} → {today}, 日PnL={self.daily_pnl:.2f}")
|
||||
self.current_date = today
|
||||
self.daily_pnl = 0.0
|
||||
self.daily_stopped = False
|
||||
|
||||
def can_trade(self) -> bool:
|
||||
"""检查是否可交易"""
|
||||
if self.daily_stopped:
|
||||
return False
|
||||
now = time.time()
|
||||
if now - self.last_trade_time < self.cfg.COOLDOWN_SECONDS:
|
||||
remain = self.cfg.COOLDOWN_SECONDS - (now - self.last_trade_time)
|
||||
logger.debug(f"交易冷却中，剩余 {remain:.0f}s")
|
||||
return False
|
||||
return True
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 日志
|
||||
# ------------------------------------------------------------------
|
||||
def write_trade_log(self, action: str, price: float, bb_upper: float,
|
||||
bb_mid: float, bb_lower: float, reason: str):
|
||||
"""写入交易日志文件"""
|
||||
try:
|
||||
date_str = datetime.now().strftime("%Y%m%d")
|
||||
log_file = self.log_dir / f"bb_delay_reversal_trade_log_{date_str}.txt"
|
||||
time_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
block = (
|
||||
f"\n{'='*60}\n"
|
||||
f"时间: {time_str}\n"
|
||||
f"操作: {action}\n"
|
||||
f"价格: {price:.2f}\n"
|
||||
f"BB上轨: {bb_upper:.2f} | 中轨: {bb_mid:.2f} | 下轨: {bb_lower:.2f}\n"
|
||||
f"原因: {reason}\n"
|
||||
f"{'='*60}\n"
|
||||
)
|
||||
with open(log_file, "a", encoding="utf-8") as f:
|
||||
f.write(block)
|
||||
except Exception as e:
|
||||
logger.warning(f"写入日志失败: {e}")
|
||||
|
||||
def login(self):
|
||||
self.page.ele('x://input[@placeholder="邮箱"]').input("ddrwode@gmail.com")
|
||||
self.page.ele('x://input[@placeholder="密码"]').input("040828cjj")
|
||||
self.page.ele('x://*[@id="__layout"]/div/div[2]/div/div[2]/div/div/div[2]/div[1]/div[2]/div/div[1]/div[2]/form/div[3]/div/button').click()
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 主循环（浏览器流程与四分之一代码一致）
|
||||
# ------------------------------------------------------------------
|
||||
def run(self):
|
||||
"""策略主循环"""
|
||||
logger.info("=" * 60)
|
||||
logger.info(f" BB策略启动(D方案): BB({self.cfg.BB_PERIOD},{self.cfg.BB_STD})")
|
||||
logger.info(f" 合约: {self.cfg.CONTRACT_SYMBOL} | {self.cfg.LEVERAGE}x {self.cfg.OPEN_TYPE}")
|
||||
logger.info(f" 首次开仓: 权益×{self.cfg.MARGIN_PCT:.0%} | 递增加仓: +{self.cfg.PYRAMID_STEP:.0%}/次 | 最多{self.cfg.PYRAMID_MAX}次")
|
||||
logger.info("=" * 60)
|
||||
|
||||
# 设置杠杆
|
||||
if not self.set_leverage():
|
||||
logger.error("杠杆设置失败，退出")
|
||||
return
|
||||
|
||||
# 初始持仓同步
|
||||
if not self.get_position_status():
|
||||
logger.error("初始持仓查询失败，退出")
|
||||
return
|
||||
logger.info(f"初始持仓状态: {self.position}")
|
||||
|
||||
last_kline_id = None # 避免同一根K线重复触发
|
||||
page_start = True # 需要打开浏览器
|
||||
|
||||
while True:
|
||||
|
||||
# ===== 浏览器管理 =====
|
||||
# page_start时: 打开浏览器 → 导航 → 点市价 → 输入张数
|
||||
if page_start:
|
||||
for i in range(5):
|
||||
if self.open_browser():
|
||||
logger.info("浏览器打开成功")
|
||||
break
|
||||
else:
|
||||
logger.error("打开浏览器失败！")
|
||||
return
|
||||
|
||||
# self.login()
|
||||
|
||||
self.page.get(self.cfg.TRADE_URL)
|
||||
time.sleep(2)
|
||||
# 点击市价模式
|
||||
self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
time.sleep(0.5)
|
||||
|
||||
# 计算并预输入开仓金额(U)
|
||||
current_price = self.get_current_price()
|
||||
if current_price:
|
||||
order_usdt = self.calc_order_usdt()
|
||||
if order_usdt > 0:
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=order_usdt, clear=True)
|
||||
logger.info(f"预输入开仓金额: {order_usdt} U")
|
||||
|
||||
page_start = False
|
||||
|
||||
try:
|
||||
# 每30分钟关闭浏览器重新打开
|
||||
if time.time() - self.last_page_open_time >= self.PAGE_REFRESH_INTERVAL:
|
||||
logger.info("浏览器已打开超过30分钟，关闭刷新")
|
||||
try:
|
||||
self.page.close()
|
||||
except Exception:
|
||||
pass
|
||||
self.page = None
|
||||
page_start = True
|
||||
time.sleep(3)
|
||||
continue
|
||||
|
||||
self.check_daily_reset()
|
||||
|
||||
if self.daily_stopped:
|
||||
logger.info(f"日亏损已达限制({self.daily_pnl:.2f})，等待日切")
|
||||
time.sleep(60)
|
||||
continue
|
||||
|
||||
# 1. 获取K线
|
||||
klines = self.get_klines()
|
||||
if not klines or len(klines) < self.cfg.BB_PERIOD:
|
||||
logger.warning(f"K线数据不足({len(klines) if klines else 0}根)，等待...")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
closed_klines = klines[:-1]
|
||||
current_kline = klines[-1]
|
||||
|
||||
if len(closed_klines) < self.cfg.BB_PERIOD:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
# 2. 计算布林带
|
||||
closes = [k["close"] for k in closed_klines]
|
||||
bb = calc_bollinger(closes, self.cfg.BB_PERIOD, self.cfg.BB_STD)
|
||||
if bb is None:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
bb_mid, bb_upper, bb_lower = bb
|
||||
|
||||
# 3. 获取当前价格
|
||||
current_price = self.get_current_price()
|
||||
if current_price is None:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
cur_high = current_kline["high"]
|
||||
cur_low = current_kline["low"]
|
||||
# 容错: K线high/low + 当前实时价格，任一触及即算触碰
|
||||
touched_upper = cur_high >= bb_upper or current_price >= bb_upper
|
||||
touched_lower = cur_low <= bb_lower or current_price <= bb_lower
|
||||
|
||||
logger.info(
|
||||
f"价格={current_price:.2f} | "
|
||||
f"BB: {bb_lower:.2f} / {bb_mid:.2f} / {bb_upper:.2f} | "
|
||||
f"H={cur_high:.2f} L={cur_low:.2f} | "
|
||||
f"触上={touched_upper} 触下={touched_lower} | "
|
||||
f"仓位={self.position}"
|
||||
)
|
||||
|
||||
# 4. 同步持仓状态
|
||||
if not self.get_position_status():
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
# 5. 信号判断
|
||||
kline_id = current_kline["id"]
|
||||
if kline_id == last_kline_id:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
if touched_upper and touched_lower:
|
||||
logger.warning("同时触及上下轨，跳过")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
action = None
|
||||
reason = ""
|
||||
success = False
|
||||
|
||||
# ===== 触及上轨 → 开空 / 翻转为空 / 加仓空 =====
|
||||
if touched_upper:
|
||||
if not self.can_trade():
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
reason = (f"价格最高{cur_high:.2f}触及上轨{bb_upper:.2f}，"
|
||||
f"BB({self.cfg.BB_PERIOD},{self.cfg.BB_STD})")
|
||||
|
||||
if self.position == 1:
|
||||
action = "翻转: 平多→开空"
|
||||
# 在当前页面点市价平仓
|
||||
self.browser_close_position()
|
||||
time.sleep(1)
|
||||
# 等待确认平仓
|
||||
for _ in range(10):
|
||||
if self.get_position_status() and self.position == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.position != 0:
|
||||
logger.warning(f"平仓后仍有持仓({self.position})，放弃开空")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
# 翻转时重置加仓计数
|
||||
self.pyramid_count = 0
|
||||
# 平仓后在同一页面直接点卖出/做空
|
||||
logger.info("平仓完成，直接开空")
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(-1):
|
||||
success = True
|
||||
elif self.position == 0:
|
||||
action = "开空"
|
||||
self.pyramid_count = 0
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(-1):
|
||||
success = True
|
||||
elif self.position == -1 and self.pyramid_count < self.cfg.PYRAMID_MAX:
|
||||
# 已持空仓 + 再次触上轨 → 加仓做空
|
||||
action = f"加仓空#{self.pyramid_count+1}"
|
||||
reason += f" (加仓#{self.pyramid_count+1}/{self.cfg.PYRAMID_MAX})"
|
||||
# 重新计算加仓金额并输入
|
||||
add_usdt = self.calc_order_usdt(is_add=True)
|
||||
if add_usdt > 0:
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=add_usdt, clear=True)
|
||||
time.sleep(0.5)
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(-1):
|
||||
self.pyramid_count += 1
|
||||
success = True
|
||||
else:
|
||||
logger.info(f"已持空仓，加仓已达上限({self.pyramid_count}/{self.cfg.PYRAMID_MAX})")
|
||||
|
||||
# ===== 触及下轨 → 开多 / 翻转为多 / 加仓多 =====
|
||||
elif touched_lower:
|
||||
if not self.can_trade():
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
reason = (f"价格最低{cur_low:.2f}触及下轨{bb_lower:.2f}，"
|
||||
f"BB({self.cfg.BB_PERIOD},{self.cfg.BB_STD})")
|
||||
|
||||
if self.position == -1:
|
||||
action = "翻转: 平空→开多"
|
||||
self.browser_close_position()
|
||||
time.sleep(1)
|
||||
for _ in range(10):
|
||||
if self.get_position_status() and self.position == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.position != 0:
|
||||
logger.warning(f"平仓后仍有持仓({self.position})，放弃开多")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
# 翻转时重置加仓计数
|
||||
self.pyramid_count = 0
|
||||
logger.info("平仓完成，直接开多")
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(1):
|
||||
success = True
|
||||
elif self.position == 0:
|
||||
action = "开多"
|
||||
self.pyramid_count = 0
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(1):
|
||||
success = True
|
||||
elif self.position == 1 and self.pyramid_count < self.cfg.PYRAMID_MAX:
|
||||
# 已持多仓 + 再次触下轨 → 加仓做多
|
||||
action = f"加仓多#{self.pyramid_count+1}"
|
||||
reason += f" (加仓#{self.pyramid_count+1}/{self.cfg.PYRAMID_MAX})"
|
||||
# 重新计算加仓金额并输入
|
||||
add_usdt = self.calc_order_usdt(is_add=True)
|
||||
if add_usdt > 0:
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=add_usdt, clear=True)
|
||||
time.sleep(0.5)
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(1):
|
||||
self.pyramid_count += 1
|
||||
success = True
|
||||
else:
|
||||
logger.info(f"已持多仓，加仓已达上限({self.pyramid_count}/{self.cfg.PYRAMID_MAX})")
|
||||
|
||||
# ===== 交易成功后处理 =====
|
||||
if success and action:
|
||||
last_kline_id = kline_id
|
||||
self.last_trade_time = time.time()
|
||||
self.write_trade_log(action, current_price,
|
||||
bb_upper, bb_mid, bb_lower, reason)
|
||||
logger.success(f"{action} 执行成功")
|
||||
# 交易完成后关闭浏览器，下轮重新打开
|
||||
page_start = True
|
||||
try:
|
||||
self.page.close()
|
||||
except Exception:
|
||||
pass
|
||||
self.page = None
|
||||
time.sleep(5)
|
||||
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
logger.info("用户中断，程序退出")
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"主循环异常: {e}")
|
||||
page_start = True
|
||||
time.sleep(10)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 入口
|
||||
# ---------------------------------------------------------------------------
|
||||
if __name__ == "__main__":
|
||||
trader = BBDelayReversalTrader()
|
||||
trader.run()
|
||||
189789
bb_sweep_results.csv
Normal file
189789
bb_sweep_results.csv
Normal file
File diff suppressed because it is too large
Load Diff
388
bb_trade.py
388
bb_trade.py
@@ -1,22 +1,24 @@
|
||||
"""
|
||||
布林带均值回归策略 — 实盘交易
|
||||
BB(10, 2.5) | 5分钟K线 | ETH | 50x杠杆 | 每单权益1%
|
||||
布林带均值回归策略 — 实盘交易 (D方案: 递增加仓)
|
||||
BB(10, 2.5) | 5分钟K线 | ETH | 50x杠杆 逐仓 | 递增加仓+1%/次 max=3
|
||||
|
||||
逻辑:
|
||||
- 价格触及上布林带 → 平多(如有) + 开空
|
||||
- 价格触及下布林带 → 平空(如有) + 开多
|
||||
- 始终持仓（多空翻转）
|
||||
- 价格触及上布林带 → 平多(如有) + 开空; 已持空则加仓
|
||||
- 价格触及下布林带 → 平空(如有) + 开多; 已持多则加仓
|
||||
- 始终持仓（多空翻转 + 同向加仓）
|
||||
- 加仓比例: 开仓1%, 第1次加仓2%, 第2次3%, 第3次4%, 最多加仓3次
|
||||
|
||||
使用 BitMart Futures API 进行开平仓
|
||||
使用浏览器自动化进行开平仓（有手续费返佣），API仅用于查询数据
|
||||
"""
|
||||
import time
|
||||
import uuid
|
||||
import numpy as np
|
||||
from datetime import datetime
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
|
||||
from loguru import logger
|
||||
from bitmart.api_contract import APIContract
|
||||
from bit_tools import openBrowser
|
||||
from DrissionPage import ChromiumPage, ChromiumOptions
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -30,6 +32,10 @@ class BBTradeConfig:
|
||||
|
||||
# 合约
|
||||
CONTRACT_SYMBOL = "ETHUSDT"
|
||||
TRADE_URL = "https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT"
|
||||
|
||||
# 浏览器
|
||||
BIT_ID = "62f9107d0c674925972084e282df55b3"
|
||||
|
||||
# 布林带参数
|
||||
BB_PERIOD = 10 # 10根5分钟K线 = 50分钟回看
|
||||
@@ -37,8 +43,12 @@ class BBTradeConfig:
|
||||
|
||||
# 仓位管理
|
||||
LEVERAGE = 50 # 杠杆倍数
|
||||
OPEN_TYPE = "cross" # 全仓模式
|
||||
MARGIN_PCT = 0.01 # 每单用权益的1%作为保证金
|
||||
OPEN_TYPE = "isolated" # 逐仓模式
|
||||
MARGIN_PCT = 0.01 # 首次开仓用权益的1%作为保证金
|
||||
|
||||
# 递增加仓 (D方案)
|
||||
PYRAMID_STEP = 0.01 # 每次加仓增加1%权益比例 (1%→2%→3%→4%)
|
||||
PYRAMID_MAX = 3 # 最多加仓3次 (首次开仓不算)
|
||||
|
||||
# 风控
|
||||
MAX_DAILY_LOSS = 50.0 # 日最大亏损(U)，达到后停止交易
|
||||
@@ -76,11 +86,20 @@ class BBTrader:
|
||||
timeout=(5, 15)
|
||||
)
|
||||
|
||||
# 浏览器
|
||||
self.page: ChromiumPage | None = None
|
||||
self.page_start = True # 需要(重新)打开浏览器
|
||||
self.last_page_open_time = 0.0 # 上次打开浏览器的时间
|
||||
self.PAGE_REFRESH_INTERVAL = 1800 # 每30分钟关闭重开浏览器
|
||||
|
||||
# 持仓状态: -1=空, 0=无, 1=多
|
||||
self.position = 0
|
||||
self.open_avg_price = None
|
||||
self.current_amount = None
|
||||
|
||||
# 加仓状态
|
||||
self.pyramid_count = 0 # 当前已加仓次数 (0=仅首次开仓)
|
||||
|
||||
# 风控
|
||||
self.daily_pnl = 0.0
|
||||
self.daily_stopped = False
|
||||
@@ -188,7 +207,7 @@ class BBTrader:
|
||||
return False
|
||||
|
||||
def set_leverage(self) -> bool:
|
||||
"""设置杠杆和全仓模式"""
|
||||
"""设置杠杆和逐仓模式"""
|
||||
try:
|
||||
resp = self.api.post_submit_leverage(
|
||||
contract_symbol=self.cfg.CONTRACT_SYMBOL,
|
||||
@@ -205,133 +224,77 @@ class BBTrader:
|
||||
logger.error(f"设置杠杆异常: {e}")
|
||||
return False
|
||||
|
||||
def _gen_client_order_id(self) -> str:
|
||||
return f"BB_{uuid.uuid4().hex[:12]}"
|
||||
|
||||
def submit_order(self, side: int, size: int) -> bool:
|
||||
"""
|
||||
提交市价单
|
||||
side: 1=买入开多, 2=买入平空, 3=卖出平多, 4=卖出开空
|
||||
size: 张数
|
||||
"""
|
||||
side_names = {1: "买入开多", 2: "买入平空", 3: "卖出平多", 4: "卖出开空"}
|
||||
logger.info(f"下单: {side_names.get(side, side)} {size}张")
|
||||
# ------------------------------------------------------------------
|
||||
# 浏览器自动化
|
||||
# ------------------------------------------------------------------
|
||||
def open_browser(self) -> bool:
|
||||
"""打开浏览器并进入交易页面"""
|
||||
try:
|
||||
resp = self.api.post_submit_order(
|
||||
contract_symbol=self.cfg.CONTRACT_SYMBOL,
|
||||
client_order_id=self._gen_client_order_id(),
|
||||
side=side,
|
||||
mode=1, # GTC
|
||||
type="market",
|
||||
leverage=str(self.cfg.LEVERAGE),
|
||||
open_type=self.cfg.OPEN_TYPE,
|
||||
size=size,
|
||||
)[0]
|
||||
if resp.get("code") == 1000:
|
||||
logger.success(f"下单成功: {side_names.get(side)} {size}张 resp={resp}")
|
||||
return True
|
||||
else:
|
||||
logger.error(f"下单失败: {resp}")
|
||||
return False
|
||||
bit_port = openBrowser(id=self.cfg.BIT_ID)
|
||||
co = ChromiumOptions()
|
||||
co.set_local_port(port=bit_port)
|
||||
self.page = ChromiumPage(addr_or_opts=co)
|
||||
self.last_page_open_time = time.time()
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"下单异常: {e}")
|
||||
logger.error(f"打开浏览器失败: {e}")
|
||||
return False
|
||||
|
||||
def click_safe(self, xpath, sleep=0.5) -> bool:
|
||||
"""安全点击元素"""
|
||||
try:
|
||||
ele = self.page.ele(xpath)
|
||||
if not ele:
|
||||
return False
|
||||
ele.click(by_js=True)
|
||||
time.sleep(sleep)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning(f"点击失败 [{xpath}]: {e}")
|
||||
return False
|
||||
|
||||
def browser_close_position(self) -> bool:
|
||||
"""浏览器点击市价全平"""
|
||||
logger.info("浏览器操作: 市价平仓")
|
||||
return self.click_safe('x://span[normalize-space(text()) ="市价"]')
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 仓位操作
|
||||
# ------------------------------------------------------------------
|
||||
def calc_order_size(self, price: float) -> int:
|
||||
def calc_order_usdt(self, is_add: bool = False) -> float:
|
||||
"""
|
||||
根据当前权益的1%计算开仓张数
|
||||
BitMart ETH合约: 1张 = 0.01 ETH
|
||||
保证金 = equity * margin_pct
|
||||
名义价值 = margin * leverage
|
||||
数量(ETH) = 名义价值 / price
|
||||
张数 = 数量 / 0.01
|
||||
计算开仓/加仓金额(U)
|
||||
首次开仓: 余额 × MARGIN_PCT (1%)
|
||||
加仓: 余额 × (MARGIN_PCT + PYRAMID_STEP × (pyramid_count+1))
|
||||
例: 开仓1%, 第1次加仓2%, 第2次加仓3%, 第3次加仓4%
|
||||
"""
|
||||
balance = self.get_balance()
|
||||
if balance is None or balance <= 0:
|
||||
logger.warning(f"余额不足或查询失败: {balance}")
|
||||
return 0
|
||||
margin = balance * self.cfg.MARGIN_PCT
|
||||
notional = margin * self.cfg.LEVERAGE
|
||||
qty_eth = notional / price
|
||||
size = max(1, int(qty_eth / 0.01)) # 1张=0.01ETH
|
||||
logger.info(f"仓位计算: 余额={balance:.2f} 保证金={margin:.2f} "
|
||||
f"名义={notional:.2f} 数量={qty_eth:.4f}ETH = {size}张")
|
||||
return size
|
||||
|
||||
def close_current_position(self) -> bool:
|
||||
"""平掉当前持仓"""
|
||||
if not self.get_position_status():
|
||||
return False
|
||||
if self.position == 0:
|
||||
logger.info("无持仓，无需平仓")
|
||||
return True
|
||||
if self.position == 1:
|
||||
# 平多: side=3
|
||||
size = int(self.current_amount)
|
||||
return self.submit_order(side=3, size=size)
|
||||
if is_add:
|
||||
pct = self.cfg.MARGIN_PCT + self.cfg.PYRAMID_STEP * (self.pyramid_count + 1)
|
||||
else:
|
||||
# 平空: side=2
|
||||
size = int(self.current_amount)
|
||||
return self.submit_order(side=2, size=size)
|
||||
pct = self.cfg.MARGIN_PCT
|
||||
order_usdt = round(balance * pct, 2)
|
||||
logger.info(f"仓位计算: 余额={balance:.2f} × {pct:.0%} = {order_usdt} U"
|
||||
f" ({'加仓#' + str(self.pyramid_count+1) if is_add else '首次开仓'})")
|
||||
return order_usdt
|
||||
|
||||
def open_long(self, price: float) -> bool:
|
||||
"""开多"""
|
||||
size = self.calc_order_size(price)
|
||||
if size <= 0:
|
||||
return False
|
||||
return self.submit_order(side=1, size=size)
|
||||
|
||||
def open_short(self, price: float) -> bool:
|
||||
"""开空"""
|
||||
size = self.calc_order_size(price)
|
||||
if size <= 0:
|
||||
return False
|
||||
return self.submit_order(side=4, size=size)
|
||||
|
||||
def flip_to_long(self, price: float) -> bool:
|
||||
"""平空 → 开多"""
|
||||
logger.info("=== 翻转为多 ===")
|
||||
if self.position == -1:
|
||||
if not self.close_current_position():
|
||||
logger.error("平空失败，放弃开多")
|
||||
return False
|
||||
time.sleep(2)
|
||||
# 确认已无仓
|
||||
for _ in range(5):
|
||||
if self.get_position_status() and self.position == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.position != 0:
|
||||
logger.warning(f"平仓后仍有持仓({self.position})，放弃开多")
|
||||
return False
|
||||
return self.open_long(price)
|
||||
|
||||
def flip_to_short(self, price: float) -> bool:
|
||||
"""平多 → 开空"""
|
||||
logger.info("=== 翻转为空 ===")
|
||||
if self.position == 1:
|
||||
if not self.close_current_position():
|
||||
logger.error("平多失败，放弃开空")
|
||||
return False
|
||||
time.sleep(2)
|
||||
for _ in range(5):
|
||||
if self.get_position_status() and self.position == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.position != 0:
|
||||
logger.warning(f"平仓后仍有持仓({self.position})，放弃开空")
|
||||
return False
|
||||
return self.open_short(price)
|
||||
def verify_position(self, expected: int) -> bool:
|
||||
"""验证持仓方向"""
|
||||
if self.get_position_status():
|
||||
if self.position == expected:
|
||||
return True
|
||||
logger.warning(f"持仓方向不符: 期望{expected}, 实际{self.position}")
|
||||
return False
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 风控
|
||||
# ------------------------------------------------------------------
|
||||
def check_daily_reset(self):
|
||||
"""每日重置(UTC+8 00:00 = UTC 16:00)"""
|
||||
now = datetime.utcnow()
|
||||
now = datetime.now(timezone.utc)
|
||||
# 用UTC日期做简单日切
|
||||
today = now.date()
|
||||
if self.current_date != today:
|
||||
@@ -376,15 +339,20 @@ class BBTrader:
|
||||
except Exception as e:
|
||||
logger.warning(f"写入日志失败: {e}")
|
||||
|
||||
def login(self):
|
||||
self.page.ele('x://input[@placeholder="邮箱"]').input("ddrwode@gmail.com")
|
||||
self.page.ele('x://input[@placeholder="密码"]').input("040828cjj")
|
||||
self.page.ele('x://*[@id="__layout"]/div/div[2]/div/div[2]/div/div/div[2]/div[1]/div[2]/div/div[1]/div[2]/form/div[3]/div/button').click()
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 主循环
|
||||
# 主循环（浏览器流程与四分之一代码一致）
|
||||
# ------------------------------------------------------------------
|
||||
def run(self):
|
||||
"""策略主循环"""
|
||||
logger.info("=" * 60)
|
||||
logger.info(f" BB策略启动: BB({self.cfg.BB_PERIOD},{self.cfg.BB_STD})")
|
||||
logger.info(f" BB策略启动(D方案): BB({self.cfg.BB_PERIOD},{self.cfg.BB_STD})")
|
||||
logger.info(f" 合约: {self.cfg.CONTRACT_SYMBOL} | {self.cfg.LEVERAGE}x {self.cfg.OPEN_TYPE}")
|
||||
logger.info(f" 每单: 权益×{self.cfg.MARGIN_PCT:.0%}")
|
||||
logger.info(f" 首次开仓: 权益×{self.cfg.MARGIN_PCT:.0%} | 递增加仓: +{self.cfg.PYRAMID_STEP:.0%}/次 | 最多{self.cfg.PYRAMID_MAX}次")
|
||||
logger.info("=" * 60)
|
||||
|
||||
# 设置杠杆
|
||||
@@ -399,9 +367,52 @@ class BBTrader:
|
||||
logger.info(f"初始持仓状态: {self.position}")
|
||||
|
||||
last_kline_id = None # 避免同一根K线重复触发
|
||||
page_start = True # 需要打开浏览器
|
||||
|
||||
while True:
|
||||
|
||||
# ===== 浏览器管理 =====
|
||||
# page_start时: 打开浏览器 → 导航 → 点市价 → 输入张数
|
||||
if page_start:
|
||||
for i in range(5):
|
||||
if self.open_browser():
|
||||
logger.info("浏览器打开成功")
|
||||
break
|
||||
else:
|
||||
logger.error("打开浏览器失败！")
|
||||
return
|
||||
|
||||
# self.login()
|
||||
|
||||
self.page.get(self.cfg.TRADE_URL)
|
||||
time.sleep(2)
|
||||
# 点击市价模式
|
||||
self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
time.sleep(0.5)
|
||||
|
||||
# 计算并预输入开仓金额(U)
|
||||
current_price = self.get_current_price()
|
||||
if current_price:
|
||||
order_usdt = self.calc_order_usdt()
|
||||
if order_usdt > 0:
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=order_usdt, clear=True)
|
||||
logger.info(f"预输入开仓金额: {order_usdt} U")
|
||||
|
||||
page_start = False
|
||||
|
||||
try:
|
||||
# 每30分钟关闭浏览器重新打开
|
||||
if time.time() - self.last_page_open_time >= self.PAGE_REFRESH_INTERVAL:
|
||||
logger.info("浏览器已打开超过30分钟，关闭刷新")
|
||||
try:
|
||||
self.page.close()
|
||||
except Exception:
|
||||
pass
|
||||
self.page = None
|
||||
page_start = True
|
||||
time.sleep(3)
|
||||
continue
|
||||
|
||||
self.check_daily_reset()
|
||||
|
||||
if self.daily_stopped:
|
||||
@@ -416,10 +427,8 @@ class BBTrader:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
# 当前K线 = 最后一根（未收盘），信号用已收盘的K线
|
||||
# 使用倒数第二根及之前的收盘价算BB（已收盘的K线）
|
||||
closed_klines = klines[:-1] # 已收盘的K线
|
||||
current_kline = klines[-1] # 当前未收盘K线
|
||||
closed_klines = klines[:-1]
|
||||
current_kline = klines[-1]
|
||||
|
||||
if len(closed_klines) < self.cfg.BB_PERIOD:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
@@ -439,11 +448,11 @@ class BBTrader:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
# 用当前K线的 high/low 判断是否触及布林带
|
||||
cur_high = current_kline["high"]
|
||||
cur_low = current_kline["low"]
|
||||
touched_upper = cur_high >= bb_upper
|
||||
touched_lower = cur_low <= bb_lower
|
||||
# 容错: K线high/low + 当前实时价格，任一触及即算触碰
|
||||
touched_upper = cur_high >= bb_upper or current_price >= bb_upper
|
||||
touched_lower = cur_low <= bb_lower or current_price <= bb_lower
|
||||
|
||||
logger.info(
|
||||
f"价格={current_price:.2f} | "
|
||||
@@ -458,15 +467,12 @@ class BBTrader:
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
# 5. 信号判断 + 执行
|
||||
# 同一根K线只触发一次
|
||||
# 5. 信号判断
|
||||
kline_id = current_kline["id"]
|
||||
if kline_id == last_kline_id:
|
||||
# 已在这根K线触发过，不重复操作
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
# 同时触及上下轨（极端波动）→ 跳过
|
||||
if touched_upper and touched_lower:
|
||||
logger.warning("同时触及上下轨，跳过")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
@@ -474,9 +480,10 @@ class BBTrader:
|
||||
|
||||
action = None
|
||||
reason = ""
|
||||
success = False
|
||||
|
||||
# ===== 触及上轨 → 开空 / 翻转为空 / 加仓空 =====
|
||||
if touched_upper:
|
||||
# 触及上轨 → 开空 / 翻转为空
|
||||
if not self.can_trade():
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
@@ -486,24 +493,52 @@ class BBTrader:
|
||||
|
||||
if self.position == 1:
|
||||
action = "翻转: 平多→开空"
|
||||
success = self.flip_to_short(current_price)
|
||||
# 在当前页面点市价平仓
|
||||
self.browser_close_position()
|
||||
time.sleep(1)
|
||||
# 等待确认平仓
|
||||
for _ in range(10):
|
||||
if self.get_position_status() and self.position == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.position != 0:
|
||||
logger.warning(f"平仓后仍有持仓({self.position})，放弃开空")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
# 翻转时重置加仓计数
|
||||
self.pyramid_count = 0
|
||||
# 平仓后在同一页面直接点卖出/做空
|
||||
logger.info("平仓完成，直接开空")
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(-1):
|
||||
success = True
|
||||
elif self.position == 0:
|
||||
action = "开空"
|
||||
success = self.open_short(current_price)
|
||||
self.pyramid_count = 0
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(-1):
|
||||
success = True
|
||||
elif self.position == -1 and self.pyramid_count < self.cfg.PYRAMID_MAX:
|
||||
# 已持空仓 + 再次触上轨 → 加仓做空
|
||||
action = f"加仓空#{self.pyramid_count+1}"
|
||||
reason += f" (加仓#{self.pyramid_count+1}/{self.cfg.PYRAMID_MAX})"
|
||||
# 重新计算加仓金额并输入
|
||||
add_usdt = self.calc_order_usdt(is_add=True)
|
||||
if add_usdt > 0:
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=add_usdt, clear=True)
|
||||
time.sleep(0.5)
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(-1):
|
||||
self.pyramid_count += 1
|
||||
success = True
|
||||
else:
|
||||
# 已经是空仓，不操作
|
||||
logger.info("已持空仓，触上轨无需操作")
|
||||
success = False
|
||||
|
||||
if success:
|
||||
last_kline_id = kline_id
|
||||
self.last_trade_time = time.time()
|
||||
self.write_trade_log(action, current_price,
|
||||
bb_upper, bb_mid, bb_lower, reason)
|
||||
logger.success(f"{action} 执行成功")
|
||||
logger.info(f"已持空仓，加仓已达上限({self.pyramid_count}/{self.cfg.PYRAMID_MAX})")
|
||||
|
||||
# ===== 触及下轨 → 开多 / 翻转为多 / 加仓多 =====
|
||||
elif touched_lower:
|
||||
# 触及下轨 → 开多 / 翻转为多
|
||||
if not self.can_trade():
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
@@ -513,20 +548,62 @@ class BBTrader:
|
||||
|
||||
if self.position == -1:
|
||||
action = "翻转: 平空→开多"
|
||||
success = self.flip_to_long(current_price)
|
||||
self.browser_close_position()
|
||||
time.sleep(1)
|
||||
for _ in range(10):
|
||||
if self.get_position_status() and self.position == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.position != 0:
|
||||
logger.warning(f"平仓后仍有持仓({self.position})，放弃开多")
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
continue
|
||||
# 翻转时重置加仓计数
|
||||
self.pyramid_count = 0
|
||||
logger.info("平仓完成，直接开多")
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(1):
|
||||
success = True
|
||||
elif self.position == 0:
|
||||
action = "开多"
|
||||
success = self.open_long(current_price)
|
||||
self.pyramid_count = 0
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(1):
|
||||
success = True
|
||||
elif self.position == 1 and self.pyramid_count < self.cfg.PYRAMID_MAX:
|
||||
# 已持多仓 + 再次触下轨 → 加仓做多
|
||||
action = f"加仓多#{self.pyramid_count+1}"
|
||||
reason += f" (加仓#{self.pyramid_count+1}/{self.cfg.PYRAMID_MAX})"
|
||||
# 重新计算加仓金额并输入
|
||||
add_usdt = self.calc_order_usdt(is_add=True)
|
||||
if add_usdt > 0:
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=add_usdt, clear=True)
|
||||
time.sleep(0.5)
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
time.sleep(3)
|
||||
if self.verify_position(1):
|
||||
self.pyramid_count += 1
|
||||
success = True
|
||||
else:
|
||||
logger.info("已持多仓，触下轨无需操作")
|
||||
success = False
|
||||
logger.info(f"已持多仓，加仓已达上限({self.pyramid_count}/{self.cfg.PYRAMID_MAX})")
|
||||
|
||||
if success:
|
||||
last_kline_id = kline_id
|
||||
self.last_trade_time = time.time()
|
||||
self.write_trade_log(action, current_price,
|
||||
bb_upper, bb_mid, bb_lower, reason)
|
||||
logger.success(f"{action} 执行成功")
|
||||
# ===== 交易成功后处理 =====
|
||||
if success and action:
|
||||
last_kline_id = kline_id
|
||||
self.last_trade_time = time.time()
|
||||
self.write_trade_log(action, current_price,
|
||||
bb_upper, bb_mid, bb_lower, reason)
|
||||
logger.success(f"{action} 执行成功")
|
||||
# 交易完成后关闭浏览器，下轮重新打开
|
||||
page_start = True
|
||||
try:
|
||||
self.page.close()
|
||||
except Exception:
|
||||
pass
|
||||
self.page = None
|
||||
time.sleep(5)
|
||||
|
||||
time.sleep(self.cfg.POLL_INTERVAL)
|
||||
|
||||
@@ -535,6 +612,7 @@ class BBTrader:
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"主循环异常: {e}")
|
||||
page_start = True
|
||||
time.sleep(10)
|
||||
|
||||
|
||||
|
||||
262
bit_tools.py
Normal file
262
bit_tools.py
Normal file
@@ -0,0 +1,262 @@
|
||||
import json
|
||||
import random
|
||||
|
||||
import requests
|
||||
from peewee import fn
|
||||
|
||||
from models.ips import Ips
|
||||
from models.xstart import Xstart
|
||||
from models.xtoken import XToken
|
||||
|
||||
url = "http://127.0.0.1:54345"
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
tg_url = "https://web.telegram.org/a/"
|
||||
|
||||
|
||||
def createBrowser(
|
||||
groupId=None,
|
||||
host=None,
|
||||
port=None,
|
||||
proxyUserName=None,
|
||||
proxyPassword=None,
|
||||
name='google',
|
||||
proxyType="socks5"
|
||||
): # 创建或者更新窗口，指纹参数 browserFingerPrint 如没有特定需求，只需要指定下内核即可，如果需要更详细的参数，请参考文档
|
||||
json_data = {
|
||||
"groupId": groupId, # 分组id
|
||||
'name': name, # 窗口名称
|
||||
'remark': '', # 备注
|
||||
'proxyMethod': 1, # 代理方式 2自定义 3 提取IP
|
||||
# 代理类型 ['noproxy', 'http', 'https', 'socks5', 'ssh']
|
||||
'proxyType': proxyType,
|
||||
'host': host, # 代理主机EE
|
||||
'port': port, # 代理端口
|
||||
'proxyUserName': proxyUserName, # 代理账号
|
||||
'proxyPassword': proxyPassword, # 代理账号
|
||||
"browserFingerPrint": { # 指纹对象
|
||||
'coreVersion': '138' # 内核版本，注意，win7/win8/winserver 2012 已经不支持112及以上内核了，无法打开
|
||||
}
|
||||
}
|
||||
|
||||
res = requests.post(f"{url}/browser/update",
|
||||
data=json.dumps(json_data), headers=headers).json()
|
||||
|
||||
print(res)
|
||||
|
||||
browserId = res['data']['id']
|
||||
|
||||
return browserId
|
||||
|
||||
|
||||
def updateBrowser(): # 更新窗口，支持批量更新和按需更新，ids 传入数组，单独更新只传一个id即可，只传入需要修改的字段即可，比如修改备注，具体字段请参考文档，browserFingerPrint指纹对象不修改，则无需传入
|
||||
json_data = {'ids': ['93672cf112a044f08b653cab691216f0'],
|
||||
'remark': '我是一个备注', 'browserFingerPrint': {}}
|
||||
res = requests.post(f"{url}/browser/update/partial",
|
||||
data=json.dumps(json_data), headers=headers).json()
|
||||
print(res)
|
||||
|
||||
|
||||
def openBrowser(id): # 直接指定ID打开窗口，也可以使用 createBrowser 方法返回的ID
|
||||
json_data = {"id": f'{id}', "args": [
|
||||
# "--disable-application-cache",
|
||||
# "--disable-cache",
|
||||
# "--disable-gpu-shader-disk-cache",
|
||||
# "--media-cache-size=1",
|
||||
# "--disk-cache-size=1",
|
||||
# "--incognito"
|
||||
]}
|
||||
res = requests.post(f"{url}/browser/open",
|
||||
data=json.dumps(json_data), headers=headers).json()
|
||||
|
||||
print(res)
|
||||
|
||||
return res["data"]["http"].split(":")[1]
|
||||
|
||||
|
||||
def closeBrowser(id): # 关闭窗口
|
||||
json_data = {'id': f'{id}'}
|
||||
res = requests.post(f"{url}/browser/close",
|
||||
data=json.dumps(json_data), headers=headers)
|
||||
return res.json()
|
||||
|
||||
|
||||
def deleteBrowser(id): # 删除窗口
|
||||
json_data = {'id': f'{id}'}
|
||||
print(requests.post(f"{url}/browser/delete",
|
||||
data=json.dumps(json_data), headers=headers).json())
|
||||
|
||||
|
||||
def query_bit_browser(page, page_size):
|
||||
data = {"page": page, "pageSize": page_size, 'sort': 'asc'}
|
||||
|
||||
res = requests.post(f'{url}/browser/list', data=json.dumps(data), headers=headers)
|
||||
|
||||
return res.json()["data"]["list"]
|
||||
|
||||
|
||||
def update_proxy_Browser(
|
||||
id,
|
||||
host,
|
||||
port,
|
||||
proxyType="socks5",
|
||||
proxyUserName="",
|
||||
proxyPassword=""
|
||||
):
|
||||
json_data = {
|
||||
"ids": [id],
|
||||
# "ipCheckService": "ip123in",
|
||||
"proxyMethod": 2,
|
||||
"proxyType": proxyType,
|
||||
"host": host,
|
||||
"port": port,
|
||||
"proxyUserName": proxyUserName,
|
||||
"proxyPassword": proxyPassword
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/browser/proxy/update', data=json.dumps(json_data), headers=headers)
|
||||
print(res.json())
|
||||
return res.json()
|
||||
|
||||
|
||||
def get_group_lists_Browser():
|
||||
json_data = {
|
||||
"page": 0,
|
||||
"pageSize": 100,
|
||||
"all": True
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/group/list', data=json.dumps(json_data), headers=headers)
|
||||
return res.json()["data"]["list"]
|
||||
|
||||
|
||||
def get_browser_lists_Browser(id, page=0):
|
||||
json_data = {
|
||||
"groupId": id,
|
||||
"page": page,
|
||||
"pageSize": 100
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/browser/list', data=json.dumps(json_data), headers=headers)
|
||||
return res.json()["data"]["list"]
|
||||
|
||||
|
||||
def get_group_lists(): # 获取全部分组的信息
|
||||
# url = "/group/list"
|
||||
|
||||
json_data = {
|
||||
"page": 0,
|
||||
"pageSize": 100,
|
||||
"all": True
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/group/list', data=json.dumps(json_data), headers=headers)
|
||||
|
||||
data = {}
|
||||
|
||||
for i in res.json()["data"]["list"]:
|
||||
data[i["groupName"]] = i["id"]
|
||||
|
||||
return data
|
||||
|
||||
|
||||
def group_add(groupName):
|
||||
json_data = {
|
||||
"groupName": groupName,
|
||||
"sortNum": 0
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/group/add', data=json.dumps(json_data), headers=headers)
|
||||
|
||||
return res.json()
|
||||
|
||||
|
||||
def browser_detail(id):
|
||||
json_data = {
|
||||
"id": id
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/browser/detail', data=json.dumps(json_data), headers=headers)
|
||||
|
||||
return res.json()
|
||||
|
||||
|
||||
def group_update(groupId, browserIds):
|
||||
# json_data = {
|
||||
# "groupId": "41notc1202sr8gu5o6emb9ihaqbzbkic",
|
||||
# "browserIds": ["af25e626167f4870b8f257e697bb4f05", "3baa6e990fee4e839c72722c8dc18019"]
|
||||
# }
|
||||
|
||||
json_data = {
|
||||
"groupId": groupId,
|
||||
"browserIds": browserIds
|
||||
}
|
||||
|
||||
res = requests.post(f'{url}/browser/group/update', data=json.dumps(json_data), headers=headers)
|
||||
|
||||
return res.json()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# for i in Xstart.select().where(
|
||||
# Xstart.x_id.is_null()
|
||||
# ):
|
||||
# ips_info = Ips.select().where(Ips.start == 1, Ips.country == "法国").order_by(fn.Rand()).get()
|
||||
#
|
||||
# update_proxy_Browser(
|
||||
# id=i.bit_id,
|
||||
# host=ips_info.host,
|
||||
# port=ips_info.port,
|
||||
# proxyUserName=ips_info.username,
|
||||
# proxyPassword=ips_info.password
|
||||
# )
|
||||
|
||||
# fz_datas = get_group_lists()
|
||||
# # fz_datas['推特']
|
||||
#
|
||||
# for i in range(10):
|
||||
# for i in get_browser_lists_Browser(id=fz_datas['推特'], page=i):
|
||||
# x_start_info = Xstart.get_or_none(
|
||||
# Xstart.bit_id == i["id"]
|
||||
# )
|
||||
#
|
||||
# if not x_start_info:
|
||||
# deleteBrowser(id=i["id"])
|
||||
#
|
||||
# continue
|
||||
#
|
||||
# if x_start_info.start:
|
||||
# continue
|
||||
#
|
||||
# deleteBrowser(id=i["id"])
|
||||
#
|
||||
# x_start_info.bit_id = None
|
||||
# x_start_info.save()
|
||||
|
||||
# for i in Xstart.select():
|
||||
# res = browser_detail(id=i.bit_id)
|
||||
# print(res)
|
||||
#
|
||||
# if not res["success"]:
|
||||
# i.bit_id = None
|
||||
# i.save()
|
||||
|
||||
# print(browser_detail(id="532651f5330e4caa917e644f9b676b"))
|
||||
|
||||
# 批量修改代理
|
||||
for i in Xstart.select().where(Xstart.start == 1):
|
||||
update_proxy_Browser(id=i.bit_id, proxyType="http", host="127.0.0.1", port=random.randint(42000, 42089), )
|
||||
|
||||
# fz_datas = get_group_lists()
|
||||
# print(fz_datas)
|
||||
# bit_id_list = []
|
||||
# for i in XToken.select().where(XToken.account_start == 2):
|
||||
# sql_info = Xstart.get_or_none(
|
||||
# Xstart.x_id == i.id
|
||||
# )
|
||||
#
|
||||
# bit_id_list.append(sql_info.bit_id)
|
||||
#
|
||||
# print(len(bit_id_list))
|
||||
# print(bit_id_list)
|
||||
#
|
||||
# print(group_update(fz_datas["西班牙语"], bit_id_list))
|
||||
268
bitmart/框架.py
Normal file
268
bitmart/框架.py
Normal file
@@ -0,0 +1,268 @@
|
||||
import time
|
||||
|
||||
from tqdm import tqdm
|
||||
from loguru import logger
|
||||
from bit_tools import openBrowser
|
||||
from DrissionPage import ChromiumPage
|
||||
from DrissionPage import ChromiumOptions
|
||||
|
||||
from bitmart.api_contract import APIContract
|
||||
|
||||
|
||||
class BitmartFuturesTransaction:
|
||||
def __init__(self, bit_id):
|
||||
|
||||
self.page: ChromiumPage | None = None
|
||||
|
||||
self.api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8"
|
||||
self.secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5"
|
||||
self.memo = "合约交易"
|
||||
|
||||
self.contract_symbol = "ETHUSDT"
|
||||
|
||||
self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15))
|
||||
|
||||
self.start = 0 # 持仓状态: -1 空, 0 无, 1 多
|
||||
self.direction = None
|
||||
|
||||
self.pbar = tqdm(total=30, desc="等待K线", ncols=80)
|
||||
|
||||
self.last_kline_time = None
|
||||
|
||||
self.leverage = "100" # 高杠杆（全仓模式下可开更大仓位）
|
||||
self.open_type = "cross" # 全仓模式（你的“成本开仓”需求）
|
||||
self.risk_percent = 0.01 # 每次开仓使用可用余额的 1%
|
||||
|
||||
self.open_avg_price = None # 开仓价格
|
||||
self.current_amount = None # 持仓量
|
||||
|
||||
self.bit_id = bit_id
|
||||
|
||||
def get_klines(self):
|
||||
"""获取最近3根30分钟K线（step=30）"""
|
||||
try:
|
||||
end_time = int(time.time())
|
||||
# 获取足够多的条目确保有最新3根
|
||||
response = self.contractAPI.get_kline(
|
||||
contract_symbol=self.contract_symbol,
|
||||
step=30, # 30分钟
|
||||
start_time=end_time - 3600 * 10, # 取最近10小时
|
||||
end_time=end_time
|
||||
)[0]["data"]
|
||||
|
||||
# 每根: [timestamp, open, high, low, close, volume]
|
||||
formatted = []
|
||||
for k in response:
|
||||
formatted.append({
|
||||
'id': int(k["timestamp"]),
|
||||
'open': float(k["open_price"]),
|
||||
'high': float(k["high_price"]),
|
||||
'low': float(k["low_price"]),
|
||||
'close': float(k["close_price"])
|
||||
})
|
||||
formatted.sort(key=lambda x: x['id'])
|
||||
return formatted # 最近3根: kline_1 (最老), kline_2, kline_3 (最新)
|
||||
except Exception as e:
|
||||
logger.error(f"获取K线异常: {e}")
|
||||
self.ding(error=True, msg="获取K线异常")
|
||||
return None
|
||||
|
||||
def get_current_price(self):
|
||||
"""获取当前最新价格，用于计算张数"""
|
||||
try:
|
||||
end_time = int(time.time())
|
||||
response = self.contractAPI.get_kline(
|
||||
contract_symbol=self.contract_symbol,
|
||||
step=1, # 1分钟
|
||||
start_time=end_time - 3600 * 3, # 取最近10小时
|
||||
end_time=end_time
|
||||
)[0]
|
||||
if response['code'] == 1000:
|
||||
return float(response['data'][-1]["close_price"])
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"获取价格异常: {e}")
|
||||
return None
|
||||
|
||||
def get_available_balance(self):
|
||||
"""获取合约账户可用USDT余额"""
|
||||
try:
|
||||
response = self.contractAPI.get_assets_detail()[0]
|
||||
if response['code'] == 1000:
|
||||
data = response['data']
|
||||
if isinstance(data, dict):
|
||||
return float(data.get('available_balance', 0))
|
||||
elif isinstance(data, list):
|
||||
for asset in data:
|
||||
if asset.get('currency') == 'USDT':
|
||||
return float(asset.get('available_balance', 0))
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"余额查询异常: {e}")
|
||||
return None
|
||||
|
||||
# 获取当前持仓方向
|
||||
def get_position_status(self):
|
||||
"""获取当前持仓方向"""
|
||||
try:
|
||||
response = self.contractAPI.get_position(contract_symbol=self.contract_symbol)[0]
|
||||
if response['code'] == 1000:
|
||||
positions = response['data']
|
||||
if not positions:
|
||||
self.start = 0
|
||||
return True
|
||||
self.start = 1 if positions[0]['position_type'] == 1 else -1
|
||||
self.open_avg_price = positions[0]['open_avg_price']
|
||||
self.current_amount = positions[0]['current_amount']
|
||||
self.position_cross = positions[0]["position_cross"]
|
||||
return True
|
||||
|
||||
else:
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"持仓查询异常: {e}")
|
||||
return False
|
||||
|
||||
# 设置杠杆和全仓
|
||||
def set_leverage(self):
|
||||
"""程序启动时设置全仓 + 高杠杆"""
|
||||
try:
|
||||
response = self.contractAPI.post_submit_leverage(
|
||||
contract_symbol=self.contract_symbol,
|
||||
leverage=self.leverage,
|
||||
open_type=self.open_type
|
||||
)[0]
|
||||
if response['code'] == 1000:
|
||||
logger.success(f"全仓模式 + {self.leverage}x 杠杆设置成功")
|
||||
return True
|
||||
else:
|
||||
logger.error(f"杠杆设置失败: {response}")
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"设置杠杆异常: {e}")
|
||||
return False
|
||||
|
||||
def openBrowser(self):
|
||||
"""打开 TGE 对应浏览器实例"""
|
||||
try:
|
||||
bit_port = openBrowser(id=self.bit_id)
|
||||
co = ChromiumOptions()
|
||||
co.set_local_port(port=bit_port)
|
||||
self.page = ChromiumPage(addr_or_opts=co)
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
def take_over_browser(self):
|
||||
"""接管浏览器"""
|
||||
try:
|
||||
co = ChromiumOptions()
|
||||
co.set_local_port(self.tge_port)
|
||||
self.page = ChromiumPage(addr_or_opts=co)
|
||||
self.page.set.window.max()
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
def close_extra_tabs(self):
|
||||
"""关闭多余 tab"""
|
||||
try:
|
||||
for idx, tab in enumerate(self.page.get_tabs()):
|
||||
if idx > 0:
|
||||
tab.close()
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
def click_safe(self, xpath, sleep=0.5):
|
||||
"""安全点击"""
|
||||
try:
|
||||
ele = self.page.ele(xpath)
|
||||
if not ele:
|
||||
return False
|
||||
ele.scroll.to_see(center=True)
|
||||
time.sleep(sleep)
|
||||
ele.click()
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
def 全平仓(self):
|
||||
self.click_safe('x://span[normalize-space(text()) ="市价"]')
|
||||
|
||||
def 平一半多仓(self):
|
||||
self.click_safe('x://button[normalize-space(text()) ="平仓"]')
|
||||
self.click_safe('x://*[@id="futureTradeForm"]/div[5]/div[3]/div[3]/span[3]')
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/平多"]')
|
||||
|
||||
def 平一半空仓(self):
|
||||
self.click_safe('x://button[normalize-space(text()) ="平仓"]')
|
||||
self.click_safe('x://*[@id="futureTradeForm"]/div[5]/div[3]/div[3]/span[3]')
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/平空"]')
|
||||
|
||||
def 开单(self, marketPriceLongOrder=0, limitPriceShortOrder=0, size=None, price=None):
|
||||
"""
|
||||
marketPriceLongOrder 市价最多或者做空，1是做多，-1是做空
|
||||
limitPriceShortOrder 限价最多或者做空
|
||||
"""
|
||||
|
||||
if marketPriceLongOrder == -1:
|
||||
self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
self.page.ele('x://*[@id="size_0"]').input(size)
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
elif marketPriceLongOrder == 1:
|
||||
self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
self.page.ele('x://*[@id="size_0"]').input(size)
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
|
||||
if limitPriceShortOrder == -1:
|
||||
self.click_safe('x://button[normalize-space(text()) ="限价"]')
|
||||
self.page.ele('x://*[@id="price_0"]').input(vals=price, clear=True)
|
||||
time.sleep(1)
|
||||
self.page.ele('x://*[@id="size_0"]').input(1)
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
elif limitPriceShortOrder == 1:
|
||||
self.click_safe('x://button[normalize-space(text()) ="限价"]')
|
||||
self.page.ele('x://*[@id="price_0"]').input(vals=price, clear=True)
|
||||
time.sleep(1)
|
||||
self.page.ele('x://*[@id="size_0"]').input(1)
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
|
||||
def ding(self, text, error=False):
|
||||
logger.info(text)
|
||||
|
||||
def action(self):
|
||||
# 启动时设置全仓高杠杆
|
||||
if not self.set_leverage():
|
||||
logger.error("杠杆设置失败，程序继续运行但可能下单失败")
|
||||
return
|
||||
|
||||
# 1. 打开浏览器
|
||||
if not self.openBrowser():
|
||||
self.ding("打开 TGE 失败！", error=True)
|
||||
return
|
||||
logger.info("TGE 端口获取成功")
|
||||
|
||||
self.get_klines()
|
||||
|
||||
# self.close_extra_tabs()
|
||||
# self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT")
|
||||
#
|
||||
self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
# self.click_safe('x://button[normalize-space(text()) ="限价"]')
|
||||
#
|
||||
# self.page.ele('x://*[@id="price_0"]').input(vals=3000, clear=True)
|
||||
# self.page.ele('x://*[@id="size_0"]').input(1)
|
||||
# self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
# self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
|
||||
self.click_safe('x://button[normalize-space(text()) ="开仓"]')
|
||||
self.click_safe('x://button[normalize-space(text()) ="平仓"]')
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/平空"]')
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/平多"]')
|
||||
self.click_safe('x://*[@id="futureTradeForm"]/div[5]/div[3]/div[3]/span[3]')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
BitmartFuturesTransaction(bit_id="f2320f57e24c45529a009e1541e25961").action()
|
||||
527
generate_backtest_chart.py
Normal file
527
generate_backtest_chart.py
Normal file
@@ -0,0 +1,527 @@
|
||||
"""
|
||||
生成回测可视化图表
|
||||
显示K线、布林带、开仓/平仓位置
|
||||
"""
|
||||
|
||||
import pandas as pd
|
||||
import json
|
||||
from pathlib import Path
|
||||
from peewee import *
|
||||
import time
|
||||
from loguru import logger
|
||||
|
||||
# 数据库配置
|
||||
DB_PATH = Path(__file__).parent / 'models' / 'database.db'
|
||||
db = SqliteDatabase(str(DB_PATH))
|
||||
|
||||
class BitMartETH5M(Model):
|
||||
"""5分钟K线模型"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'bitmart_eth_5m'
|
||||
|
||||
|
||||
def calculate_bollinger_bands(df, period=10, std_dev=2.5):
|
||||
"""计算布林带（右移1根，与回测口径一致）"""
|
||||
df['sma'] = df['close'].rolling(window=period).mean()
|
||||
df['std'] = df['close'].rolling(window=period).std()
|
||||
df['bb_upper'] = (df['sma'] + std_dev * df['std']).shift(1)
|
||||
df['bb_mid'] = df['sma'].shift(1)
|
||||
df['bb_lower'] = (df['sma'] - std_dev * df['std']).shift(1)
|
||||
return df
|
||||
|
||||
|
||||
def generate_chart_data(start_date, end_date, trades_file):
|
||||
"""生成图表数据"""
|
||||
|
||||
# 1. 加载K线数据
|
||||
start_ts = int(pd.Timestamp(start_date).timestamp() * 1000)
|
||||
end_ts = int(pd.Timestamp(end_date).timestamp() * 1000) + 86400000 # 加一天确保包含end_date当天的数据
|
||||
|
||||
query = BitMartETH5M.select().where(
|
||||
(BitMartETH5M.id >= start_ts) & (BitMartETH5M.id <= end_ts)
|
||||
).order_by(BitMartETH5M.id)
|
||||
|
||||
data = []
|
||||
for row in query:
|
||||
data.append({
|
||||
'timestamp': row.id,
|
||||
'open': row.open,
|
||||
'high': row.high,
|
||||
'low': row.low,
|
||||
'close': row.close
|
||||
})
|
||||
|
||||
df = pd.DataFrame(data)
|
||||
df['datetime'] = pd.to_datetime(df['timestamp'], unit='ms')
|
||||
|
||||
# 2. 计算布林带
|
||||
df = calculate_bollinger_bands(df)
|
||||
|
||||
# 3. 加载交易记录
|
||||
trades_df = pd.read_csv(trades_file)
|
||||
trades_df['datetime'] = pd.to_datetime(trades_df['timestamp'])
|
||||
|
||||
# 4. 准备图表数据
|
||||
chart_data = []
|
||||
for idx, row in df.iterrows():
|
||||
chart_data.append({
|
||||
'timestamp': int(row['timestamp']),
|
||||
'datetime': row['datetime'].strftime('%Y-%m-%d %H:%M'),
|
||||
'open': float(row['open']) if pd.notna(row['open']) else None,
|
||||
'high': float(row['high']) if pd.notna(row['high']) else None,
|
||||
'low': float(row['low']) if pd.notna(row['low']) else None,
|
||||
'close': float(row['close']) if pd.notna(row['close']) else None,
|
||||
'bb_upper': float(row['bb_upper']) if pd.notna(row['bb_upper']) else None,
|
||||
'bb_mid': float(row['bb_mid']) if pd.notna(row['bb_mid']) else None,
|
||||
'bb_lower': float(row['bb_lower']) if pd.notna(row['bb_lower']) else None,
|
||||
})
|
||||
|
||||
# 5. 准备交易标记数据
|
||||
trades_markers = []
|
||||
for idx, trade in trades_df.iterrows():
|
||||
action = trade['action']
|
||||
price = trade['price']
|
||||
timestamp = trade['datetime']
|
||||
reason = trade['reason']
|
||||
|
||||
# 找到对应的K线索引（使用最近的K线）
|
||||
kline_idx = df[df['datetime'] == timestamp].index
|
||||
if len(kline_idx) == 0:
|
||||
# 如果找不到完全匹配的，找最近的K线
|
||||
time_diff = abs(df['datetime'] - timestamp)
|
||||
min_diff = time_diff.min()
|
||||
# 如果时间差超过10分钟，跳过这个标记
|
||||
if min_diff > pd.Timedelta(minutes=10):
|
||||
print(f"跳过标记 {timestamp}，找不到匹配的K线（最小时间差: {min_diff}）")
|
||||
continue
|
||||
kline_idx = time_diff.idxmin()
|
||||
else:
|
||||
kline_idx = kline_idx[0]
|
||||
|
||||
# 图上显示真实成交价，避免“总在最高/最低点成交”的错觉
|
||||
kline = df.loc[kline_idx]
|
||||
if pd.notna(price):
|
||||
display_price = float(price)
|
||||
else:
|
||||
display_price = float(kline['close'])
|
||||
|
||||
marker = {
|
||||
'timestamp': timestamp.strftime('%Y-%m-%d %H:%M'),
|
||||
'price': display_price, # 使用K线实际价格
|
||||
'action': action,
|
||||
'reason': reason,
|
||||
'index': int(kline_idx)
|
||||
}
|
||||
|
||||
# 关键操作直接显示在图上，便于快速理解“为什么做这笔交易”
|
||||
# 新增：开仓/加仓也展示标签
|
||||
marker['show_reason_label'] = (
|
||||
('延迟反转' in reason)
|
||||
or ('止损' in reason)
|
||||
or ('开long' in action)
|
||||
or ('开short' in action)
|
||||
or ('加long' in action)
|
||||
or ('加short' in action)
|
||||
)
|
||||
if '止损' in reason:
|
||||
marker['short_reason'] = '止损'
|
||||
elif '延迟反转' in reason:
|
||||
marker['short_reason'] = '延迟反转'
|
||||
elif '触中轨平50%' in reason:
|
||||
marker['short_reason'] = '中轨平半'
|
||||
elif '回开仓价全平' in reason:
|
||||
marker['short_reason'] = '回本全平'
|
||||
elif '触上轨开空' in reason:
|
||||
marker['short_reason'] = '上轨开空'
|
||||
elif '触下轨开多' in reason:
|
||||
marker['short_reason'] = '下轨开多'
|
||||
elif '触上轨加空' in reason:
|
||||
marker['short_reason'] = '上轨加空'
|
||||
elif '触下轨加多' in reason:
|
||||
marker['short_reason'] = '下轨加多'
|
||||
else:
|
||||
marker['short_reason'] = reason
|
||||
|
||||
# 分类标记
|
||||
if '开long' in action or '加long' in action:
|
||||
marker['type'] = 'open_long'
|
||||
marker['color'] = '#00ff00'
|
||||
marker['symbol'] = 'triangle'
|
||||
elif '开short' in action or '加short' in action:
|
||||
marker['type'] = 'open_short'
|
||||
marker['color'] = '#ff0000'
|
||||
marker['symbol'] = 'triangle'
|
||||
elif '平仓' in action:
|
||||
if '50%' in action:
|
||||
marker['type'] = 'close_half'
|
||||
marker['color'] = '#ffff00'
|
||||
marker['symbol'] = 'diamond'
|
||||
else:
|
||||
marker['type'] = 'close_all'
|
||||
marker['color'] = '#ff00ff'
|
||||
marker['symbol'] = 'circle'
|
||||
else:
|
||||
marker['type'] = 'other'
|
||||
marker['color'] = '#ffffff'
|
||||
marker['symbol'] = 'circle'
|
||||
|
||||
trades_markers.append(marker)
|
||||
|
||||
return chart_data, trades_markers
|
||||
|
||||
|
||||
def generate_html(chart_data, trades_markers, output_file):
|
||||
"""生成HTML文件"""
|
||||
|
||||
html_content = f"""<!DOCTYPE html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<title>布林带策略回测可视化 - 2026年3月</title>
|
||||
<style>
|
||||
html,
|
||||
body {{
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: #0a0e27;
|
||||
color: #e0e6ed;
|
||||
font-family: 'SF Mono', Monaco, 'Cascadia Code', 'Roboto Mono', Consolas, 'Courier New', monospace;
|
||||
}}
|
||||
#chart {{
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
}}
|
||||
.legend {{
|
||||
position: fixed;
|
||||
top: 20px;
|
||||
right: 20px;
|
||||
background: rgba(15, 23, 42, 0.95);
|
||||
padding: 20px;
|
||||
border-radius: 12px;
|
||||
border: 1px solid #334155;
|
||||
font-size: 13px;
|
||||
line-height: 1.8;
|
||||
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.4);
|
||||
backdrop-filter: blur(10px);
|
||||
z-index: 1000;
|
||||
}}
|
||||
.legend-title {{
|
||||
font-weight: 600;
|
||||
margin-bottom: 12px;
|
||||
color: #f1f5f9;
|
||||
font-size: 14px;
|
||||
letter-spacing: 0.5px;
|
||||
}}
|
||||
.legend-item {{
|
||||
display: flex;
|
||||
align-items: center;
|
||||
margin: 8px 0;
|
||||
}}
|
||||
.legend-marker {{
|
||||
width: 14px;
|
||||
height: 14px;
|
||||
margin-right: 10px;
|
||||
border-radius: 2px;
|
||||
}}
|
||||
</style>
|
||||
<script src="https://cdn.jsdelivr.net/npm/echarts@5/dist/echarts.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div id="chart"></div>
|
||||
<div class="legend">
|
||||
<div class="legend-title">📊 交易标记说明</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-marker" style="background: #00ff00;">▲</div>
|
||||
<span>开多/加多</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-marker" style="background: #ff0000;">▼</div>
|
||||
<span>开空/加空</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-marker" style="background: #ffff00;">◆</div>
|
||||
<span>平仓50%</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-marker" style="background: #ff00ff;">●</div>
|
||||
<span>平仓100%</span>
|
||||
</div>
|
||||
</div>
|
||||
<script>
|
||||
const chartData = {json.dumps(chart_data, ensure_ascii=False)};
|
||||
const tradesMarkers = {json.dumps(trades_markers, ensure_ascii=False)};
|
||||
|
||||
function main() {{
|
||||
const categoryData = [];
|
||||
const klineData = [];
|
||||
const upper = [];
|
||||
const mid = [];
|
||||
const lower = [];
|
||||
|
||||
for (const k of chartData) {{
|
||||
const d = new Date(k.timestamp);
|
||||
const label = `${{d.getMonth()+1}}/${{d.getDate()}} ${{d.getHours().toString().padStart(2, "0")}}:${{d
|
||||
.getMinutes()
|
||||
.toString()
|
||||
.padStart(2, "0")}}`;
|
||||
categoryData.push(label);
|
||||
klineData.push([k.open, k.close, k.low, k.high]);
|
||||
upper.push(k.bb_upper);
|
||||
mid.push(k.bb_mid);
|
||||
lower.push(k.bb_lower);
|
||||
}}
|
||||
|
||||
// 准备交易标记数据
|
||||
const openLongData = [];
|
||||
const openShortData = [];
|
||||
const closeHalfData = [];
|
||||
const closeAllData = [];
|
||||
|
||||
for (const marker of tradesMarkers) {{
|
||||
const point = {{
|
||||
value: [marker.index, marker.price],
|
||||
reason: marker.reason,
|
||||
action: marker.action,
|
||||
shortReason: marker.short_reason,
|
||||
label: marker.show_reason_label
|
||||
? {{
|
||||
show: true,
|
||||
formatter: marker.short_reason,
|
||||
color: "#f8fafc",
|
||||
backgroundColor: "rgba(15,23,42,0.85)",
|
||||
borderColor: "#475569",
|
||||
borderWidth: 1,
|
||||
borderRadius: 4,
|
||||
padding: [2, 4],
|
||||
fontSize: 10,
|
||||
}}
|
||||
: {{ show: false }},
|
||||
itemStyle: {{ color: marker.color }},
|
||||
}};
|
||||
|
||||
if (marker.type === 'open_long') {{
|
||||
openLongData.push(point);
|
||||
}} else if (marker.type === 'open_short') {{
|
||||
openShortData.push(point);
|
||||
}} else if (marker.type === 'close_half') {{
|
||||
closeHalfData.push(point);
|
||||
}} else if (marker.type === 'close_all') {{
|
||||
closeAllData.push(point);
|
||||
}}
|
||||
}}
|
||||
|
||||
const chartDom = document.getElementById("chart");
|
||||
const chart = echarts.init(chartDom, null, {{ renderer: "canvas" }});
|
||||
|
||||
const option = {{
|
||||
backgroundColor: "#0a0e27",
|
||||
tooltip: {{
|
||||
trigger: "axis",
|
||||
axisPointer: {{ type: "cross" }},
|
||||
backgroundColor: "rgba(15, 23, 42, 0.95)",
|
||||
borderColor: "#334155",
|
||||
textStyle: {{ color: "#e0e6ed" }},
|
||||
}},
|
||||
axisPointer: {{
|
||||
link: [{{ xAxisIndex: "all" }}],
|
||||
}},
|
||||
grid: {{
|
||||
left: "3%",
|
||||
right: "200px",
|
||||
top: "6%",
|
||||
bottom: "8%",
|
||||
containLabel: true,
|
||||
}},
|
||||
xAxis: {{
|
||||
type: "category",
|
||||
data: categoryData,
|
||||
scale: true,
|
||||
boundaryGap: true,
|
||||
axisLine: {{ lineStyle: {{ color: "#475569" }} }},
|
||||
axisLabel: {{
|
||||
color: "#94a3b8",
|
||||
rotate: 45,
|
||||
fontSize: 11
|
||||
}},
|
||||
}},
|
||||
yAxis: {{
|
||||
scale: true,
|
||||
axisLine: {{ lineStyle: {{ color: "#475569" }} }},
|
||||
splitLine: {{ lineStyle: {{ color: "#1e293b" }} }},
|
||||
axisLabel: {{ color: "#94a3b8" }},
|
||||
}},
|
||||
dataZoom: [
|
||||
{{
|
||||
type: "inside",
|
||||
start: 0,
|
||||
end: 100,
|
||||
}},
|
||||
{{
|
||||
type: "slider",
|
||||
start: 0,
|
||||
end: 100,
|
||||
height: 30,
|
||||
backgroundColor: "#1e293b",
|
||||
fillerColor: "rgba(100, 116, 139, 0.3)",
|
||||
borderColor: "#334155",
|
||||
handleStyle: {{
|
||||
color: "#64748b",
|
||||
borderColor: "#94a3b8"
|
||||
}},
|
||||
textStyle: {{ color: "#94a3b8" }},
|
||||
}},
|
||||
],
|
||||
series: [
|
||||
{{
|
||||
name: "K线",
|
||||
type: "candlestick",
|
||||
data: klineData,
|
||||
itemStyle: {{
|
||||
color: "#10b981",
|
||||
color0: "#ef4444",
|
||||
borderColor: "#10b981",
|
||||
borderColor0: "#ef4444",
|
||||
}},
|
||||
}},
|
||||
{{
|
||||
name: "BB上轨",
|
||||
type: "line",
|
||||
data: upper,
|
||||
symbol: "none",
|
||||
lineStyle: {{ color: "#f59e0b", width: 2 }},
|
||||
z: 1,
|
||||
}},
|
||||
{{
|
||||
name: "BB中轨",
|
||||
type: "line",
|
||||
data: mid,
|
||||
symbol: "none",
|
||||
lineStyle: {{ color: "#8b5cf6", width: 2, type: "dashed" }},
|
||||
z: 1,
|
||||
}},
|
||||
{{
|
||||
name: "BB下轨",
|
||||
type: "line",
|
||||
data: lower,
|
||||
symbol: "none",
|
||||
lineStyle: {{ color: "#f59e0b", width: 2 }},
|
||||
z: 1,
|
||||
}},
|
||||
{{
|
||||
name: "开多/加多",
|
||||
type: "scatter",
|
||||
symbol: "triangle",
|
||||
symbolSize: 12,
|
||||
symbolOffset: [0, 8], // 向下偏移，使三角形底部对齐价格
|
||||
data: openLongData,
|
||||
itemStyle: {{ color: "#00ff00" }},
|
||||
z: 10,
|
||||
tooltip: {{
|
||||
formatter: (params) => {{
|
||||
const marker = params.data;
|
||||
return `开多/加多<br/>价格: ${{marker.value[1].toFixed(2)}}<br/>原因: ${{marker.reason}}`;
|
||||
}}
|
||||
}}
|
||||
}},
|
||||
{{
|
||||
name: "开空/加空",
|
||||
type: "scatter",
|
||||
symbol: "triangle",
|
||||
symbolSize: 12,
|
||||
symbolRotate: 180,
|
||||
symbolOffset: [0, -8], // 向上偏移，使三角形底部对齐价格
|
||||
data: openShortData,
|
||||
itemStyle: {{ color: "#ff0000" }},
|
||||
z: 10,
|
||||
tooltip: {{
|
||||
formatter: (params) => {{
|
||||
const marker = params.data;
|
||||
return `开空/加空<br/>价格: ${{marker.value[1].toFixed(2)}}<br/>原因: ${{marker.reason}}`;
|
||||
}}
|
||||
}}
|
||||
}},
|
||||
{{
|
||||
name: "平仓50%",
|
||||
type: "scatter",
|
||||
symbol: "diamond",
|
||||
symbolSize: 10,
|
||||
data: closeHalfData,
|
||||
itemStyle: {{ color: "#ffff00" }},
|
||||
z: 10,
|
||||
tooltip: {{
|
||||
formatter: (params) => {{
|
||||
const marker = params.data;
|
||||
return `平仓50%<br/>价格: ${{marker.value[1].toFixed(2)}}<br/>原因: ${{marker.reason}}`;
|
||||
}}
|
||||
}}
|
||||
}},
|
||||
{{
|
||||
name: "平仓100%",
|
||||
type: "scatter",
|
||||
symbol: "circle",
|
||||
symbolSize: 10,
|
||||
data: closeAllData,
|
||||
itemStyle: {{ color: "#ff00ff" }},
|
||||
z: 10,
|
||||
tooltip: {{
|
||||
formatter: (params) => {{
|
||||
const marker = params.data;
|
||||
return `平仓100%<br/>价格: ${{marker.value[1].toFixed(2)}}<br/>原因: ${{marker.reason}}`;
|
||||
}}
|
||||
}}
|
||||
}},
|
||||
],
|
||||
}};
|
||||
|
||||
chart.setOption(option);
|
||||
window.addEventListener("resize", () => chart.resize());
|
||||
}}
|
||||
|
||||
main();
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
with open(output_file, 'w', encoding='utf-8') as f:
|
||||
f.write(html_content)
|
||||
|
||||
print(f"✅ 图表已生成: {output_file}")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
db.connect(reuse_if_open=True)
|
||||
|
||||
try:
|
||||
print("正在生成回测可视化图表...")
|
||||
|
||||
output_dir = Path(__file__).parent / 'backtest_outputs' / 'charts'
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# 生成图表数据
|
||||
chart_data, trades_markers = generate_chart_data(
|
||||
start_date='2026-03-01',
|
||||
end_date='2026-03-03',
|
||||
trades_file=str(Path(__file__).parent / 'backtest_outputs' / 'trades' / 'bb_backtest_march_2026_trades.csv')
|
||||
)
|
||||
|
||||
print(f"📊 K线数据: {len(chart_data)} 根")
|
||||
print(f"📍 交易标记: {len(trades_markers)} 个")
|
||||
|
||||
# 生成HTML
|
||||
output_file = output_dir / 'bb_backtest_visualization.html'
|
||||
generate_html(chart_data, trades_markers, str(output_file))
|
||||
|
||||
print(f"\n🎉 完成！请在浏览器中打开 {output_file} 查看图表")
|
||||
|
||||
finally:
|
||||
db.close()
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
@@ -1,11 +0,0 @@
|
||||
bitmart-python-sdk-api
|
||||
loguru
|
||||
peewee
|
||||
pymysql
|
||||
numpy
|
||||
pandas
|
||||
scikit-learn
|
||||
joblib
|
||||
lightgbm>=3.0.0
|
||||
optuna>=3.0.0
|
||||
matplotlib
|
||||
@@ -1 +0,0 @@
|
||||
from .bb_backtest import BBConfig, BBResult, BBTrade, run_bb_backtest
|
||||
@@ -1,156 +0,0 @@
|
||||
"""
|
||||
2023 年回测入口 - 用训练出的最优参数在 2023 全年数据上回测
|
||||
"""
|
||||
import json
|
||||
import sys
|
||||
import os
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
|
||||
from strategy.data_loader import load_klines
|
||||
from strategy.indicators import compute_all_indicators
|
||||
from strategy.strategy_signal import (
|
||||
generate_indicator_signals, compute_composite_score,
|
||||
apply_htf_filter,
|
||||
)
|
||||
from strategy.backtest_engine import BacktestEngine
|
||||
|
||||
|
||||
def main():
|
||||
# 加载最佳参数
|
||||
params_path = os.path.join(os.path.dirname(__file__), 'best_params_2020_2022.json')
|
||||
if not os.path.exists(params_path):
|
||||
print(f"错误: 找不到参数文件 {params_path}")
|
||||
print("请先运行 train.py 进行训练")
|
||||
return
|
||||
|
||||
with open(params_path, 'r') as f:
|
||||
params = json.load(f)
|
||||
|
||||
print("=" * 70)
|
||||
print("2023 年真实回测 (样本外)")
|
||||
print("=" * 70)
|
||||
|
||||
# 加载数据 (多加载一些前置数据用于指标预热)
|
||||
print("\n加载数据...")
|
||||
df_5m = load_klines('5m', '2022-11-01', '2024-01-01')
|
||||
df_1h = load_klines('1h', '2022-11-01', '2024-01-01')
|
||||
print(f" 5m: {len(df_5m)} 条, 1h: {len(df_1h)} 条")
|
||||
|
||||
# 计算指标
|
||||
print("计算指标...")
|
||||
df_5m = compute_all_indicators(df_5m, params)
|
||||
df_1h = compute_all_indicators(df_1h, params)
|
||||
|
||||
# 生成信号
|
||||
print("生成信号...")
|
||||
df_5m = generate_indicator_signals(df_5m, params)
|
||||
df_1h = generate_indicator_signals(df_1h, params)
|
||||
|
||||
# 综合得分
|
||||
score = compute_composite_score(df_5m, params)
|
||||
score = apply_htf_filter(score, df_1h, params)
|
||||
|
||||
# 截取 2023 年数据
|
||||
mask = (df_5m.index >= '2023-01-01') & (df_5m.index < '2024-01-01')
|
||||
df_2023 = df_5m.loc[mask]
|
||||
score_2023 = score.loc[mask]
|
||||
print(f" 2023年数据: {len(df_2023)} 条")
|
||||
|
||||
# 回测
|
||||
print("\n开始回测...")
|
||||
engine = BacktestEngine(
|
||||
initial_capital=1000.0,
|
||||
margin_per_trade=25.0,
|
||||
leverage=50,
|
||||
fee_rate=0.0005,
|
||||
rebate_ratio=0.70,
|
||||
max_daily_drawdown=50.0,
|
||||
min_hold_bars=1,
|
||||
stop_loss_pct=params['stop_loss_pct'],
|
||||
take_profit_pct=params['take_profit_pct'],
|
||||
max_positions=int(params.get('max_positions', 3)),
|
||||
)
|
||||
|
||||
result = engine.run(df_2023, score_2023, open_threshold=params['open_threshold'])
|
||||
|
||||
# ============================================================
|
||||
# 输出结果
|
||||
# ============================================================
|
||||
print("\n" + "=" * 70)
|
||||
print("2023 年回测结果")
|
||||
print("=" * 70)
|
||||
print(f" 初始资金: 1000.00 U")
|
||||
print(f" 最终资金: {result['final_capital']:.2f} U")
|
||||
print(f" 总收益: {result['total_pnl']:.2f} U")
|
||||
print(f" 总手续费: {result['total_fee']:.2f} U")
|
||||
print(f" 总返佣: {result['total_rebate']:.2f} U")
|
||||
print(f" 交易次数: {result['num_trades']}")
|
||||
print(f" 胜率: {result['win_rate']:.2%}")
|
||||
print(f" 盈亏比: {result['profit_factor']:.2f}")
|
||||
print(f" 日均收益: {result['avg_daily_pnl']:.2f} U")
|
||||
print(f" 最大日回撤: {result['max_daily_dd']:.2f} U")
|
||||
|
||||
# 月度统计
|
||||
daily_pnl = result['daily_pnl']
|
||||
if daily_pnl:
|
||||
df_daily = pd.DataFrame(list(daily_pnl.items()), columns=['date', 'pnl'])
|
||||
df_daily['date'] = pd.to_datetime(df_daily['date'])
|
||||
df_daily['month'] = df_daily['date'].dt.to_period('M')
|
||||
monthly = df_daily.groupby('month')['pnl'].agg(['sum', 'count', 'mean', 'min'])
|
||||
monthly.columns = ['月收益', '交易天数', '日均收益', '最大日亏损']
|
||||
|
||||
print("\n" + "-" * 70)
|
||||
print("月度统计:")
|
||||
print("-" * 70)
|
||||
for idx, row in monthly.iterrows():
|
||||
status = "✅" if row['月收益'] > 0 else "❌"
|
||||
dd_status = "✅" if row['最大日亏损'] > -50 else "⚠️"
|
||||
print(f" {idx} | 收益: {row['月收益']:>8.2f}U | "
|
||||
f"日均: {row['日均收益']:>7.2f}U | "
|
||||
f"最大日亏: {row['最大日亏损']:>7.2f}U {dd_status} | {status}")
|
||||
|
||||
# 日均收益是否达标
|
||||
avg_daily = df_daily['pnl'].mean()
|
||||
days_above_50 = (df_daily['pnl'] >= 50).sum()
|
||||
days_below_neg50 = (df_daily['pnl'] < -50).sum()
|
||||
print(f"\n 日均收益: {avg_daily:.2f}U {'✅ 达标' if avg_daily >= 50 else '❌ 未达标'}")
|
||||
print(f" 日收益>=50U的天数: {days_above_50} / {len(df_daily)}")
|
||||
print(f" 日回撤>50U的天数: {days_below_neg50} / {len(df_daily)}")
|
||||
|
||||
# 保存逐日 PnL
|
||||
output_dir = os.path.dirname(__file__)
|
||||
if daily_pnl:
|
||||
df_daily_out = pd.DataFrame(list(daily_pnl.items()), columns=['date', 'pnl'])
|
||||
df_daily_out['cumulative_pnl'] = df_daily_out['pnl'].cumsum()
|
||||
daily_csv = os.path.join(output_dir, 'backtest_2023_daily_pnl.csv')
|
||||
df_daily_out.to_csv(daily_csv, index=False)
|
||||
print(f"\n逐日PnL已保存: {daily_csv}")
|
||||
|
||||
# 保存交易记录
|
||||
if result['trades']:
|
||||
trades_data = []
|
||||
for t in result['trades']:
|
||||
trades_data.append({
|
||||
'entry_time': t.entry_time,
|
||||
'exit_time': t.exit_time,
|
||||
'direction': '多' if t.direction == 1 else '空',
|
||||
'entry_price': t.entry_price,
|
||||
'exit_price': t.exit_price,
|
||||
'pnl': round(t.pnl, 4),
|
||||
'fee': round(t.fee, 4),
|
||||
'rebate': round(t.rebate, 4),
|
||||
'holding_bars': t.holding_bars,
|
||||
})
|
||||
df_trades = pd.DataFrame(trades_data)
|
||||
trades_csv = os.path.join(output_dir, 'backtest_2023_trades.csv')
|
||||
df_trades.to_csv(trades_csv, index=False)
|
||||
print(f"交易记录已保存: {trades_csv}")
|
||||
|
||||
print("\n" + "=" * 70)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -1,366 +0,0 @@
|
||||
date,pnl,cumulative_pnl
|
||||
2023-01-01,-13.24030780391167,-13.24030780391167
|
||||
2023-01-02,-6.446144625588336,-19.686452429500005
|
||||
2023-01-03,1.604645378778668,-18.081807050721338
|
||||
2023-01-04,56.24999999999943,38.168192949278094
|
||||
2023-01-05,0.33406192478092844,38.50225487405902
|
||||
2023-01-06,-4.28936549280675,34.21288938125227
|
||||
2023-01-07,14.786004985419915,48.99889436667218
|
||||
2023-01-08,74.57347500987392,123.5723693765461
|
||||
2023-01-09,100.43932814185042,224.01169751839655
|
||||
2023-01-10,-11.400950315324355,212.61074720307218
|
||||
2023-01-11,119.73808656927638,332.34883377234854
|
||||
2023-01-12,-46.87500000000008,285.4738337723485
|
||||
2023-01-13,24.95301706493165,310.42685083728014
|
||||
2023-01-14,36.87499999999923,347.3018508372794
|
||||
2023-01-15,-42.164085212923396,305.137765624356
|
||||
2023-01-16,-42.37550401931327,262.76226160504274
|
||||
2023-01-17,-39.23788027501831,223.52438133002443
|
||||
2023-01-18,10.968990345277774,234.4933716753022
|
||||
2023-01-19,-17.519099732290336,216.97427194301187
|
||||
2023-01-20,258.1249999999992,475.0992719430111
|
||||
2023-01-21,-26.63800028548694,448.46127165752415
|
||||
2023-01-22,-27.862031912052718,420.59923974547144
|
||||
2023-01-23,-40.570948096946864,380.0282916485246
|
||||
2023-01-24,153.52954075490175,533.5578324034263
|
||||
2023-01-25,76.9770888682049,610.5349212716312
|
||||
2023-01-26,-43.12500000000006,567.4099212716312
|
||||
2023-01-27,4.574004296634158,571.9839255682654
|
||||
2023-01-28,110.89323045990369,682.8771560281691
|
||||
2023-01-29,65.39337129909306,748.2705273272621
|
||||
2023-01-30,89.15573047359129,837.4262578008534
|
||||
2023-01-31,-33.65661196432259,803.7696458365308
|
||||
2023-02-01,-42.346269783529834,761.423376053001
|
||||
2023-02-02,5.6249999999996945,767.0483760530007
|
||||
2023-02-03,-38.015635992701625,729.032740060299
|
||||
2023-02-04,-6.061609860875804,722.9711301994232
|
||||
2023-02-05,91.32767729532108,814.2988074947443
|
||||
2023-02-06,12.340770370556534,826.6395778653009
|
||||
2023-02-07,-38.31565728321921,788.3239205820817
|
||||
2023-02-08,-10.754771409427375,777.5691491726543
|
||||
2023-02-09,180.00000000000034,957.5691491726546
|
||||
2023-02-10,90.62500000000017,1048.1941491726548
|
||||
2023-02-11,-40.23338038017373,1007.9607687924811
|
||||
2023-02-12,50.843005130216255,1058.8037739226972
|
||||
2023-02-13,-43.12499999999999,1015.6787739226972
|
||||
2023-02-14,-45.000000000000014,970.6787739226972
|
||||
2023-02-15,211.8749999999989,1182.553773922696
|
||||
2023-02-16,123.74999999999923,1306.3037739226954
|
||||
2023-02-17,-43.1250000000002,1263.1787739226952
|
||||
2023-02-18,-30.38874055427764,1232.7900333684177
|
||||
2023-02-19,2.5357914472640948,1235.3258248156817
|
||||
2023-02-20,10.13433097511785,1245.4601557907995
|
||||
2023-02-21,41.5960974135976,1287.056253204397
|
||||
2023-02-22,39.9999999999999,1327.056253204397
|
||||
2023-02-23,-13.478092269295054,1313.578160935102
|
||||
2023-02-24,-33.61127571949922,1279.9668852156028
|
||||
2023-02-25,56.87500000000026,1336.841885215603
|
||||
2023-02-26,52.96295237320025,1389.8048375888034
|
||||
2023-02-27,-21.012957685691507,1368.7918799031117
|
||||
2023-02-28,-17.510525954953838,1351.2813539481579
|
||||
2023-03-01,48.43861521106629,1399.719969159224
|
||||
2023-03-02,5.370115987703678,1405.0900851469278
|
||||
2023-03-03,114.81346298981391,1519.9035481367416
|
||||
2023-03-04,-9.975555145718014,1509.9279929910235
|
||||
2023-03-05,-40.070176144315376,1469.8578168467081
|
||||
2023-03-06,-11.368260314393366,1458.4895565323147
|
||||
2023-03-07,29.800169999101556,1488.2897265314164
|
||||
2023-03-08,-41.066516251938125,1447.2232102794783
|
||||
2023-03-09,178.12499999999966,1625.3482102794778
|
||||
2023-03-10,69.54272408495805,1694.890934364436
|
||||
2023-03-11,218.8441938252083,1913.7351281896442
|
||||
2023-03-12,-43.124999999999986,1870.6101281896442
|
||||
2023-03-13,31.874999999999282,1902.4851281896435
|
||||
2023-03-14,71.24999999999882,1973.7351281896424
|
||||
2023-03-15,-46.87499999999994,1926.8601281896424
|
||||
2023-03-16,-47.19007322239124,1879.6700549672512
|
||||
2023-03-17,249.37499999999858,2129.0450549672496
|
||||
2023-03-18,-39.375000000000455,2089.670054967249
|
||||
2023-03-19,-37.72054430463878,2051.9495106626105
|
||||
2023-03-20,-48.125000000000256,2003.8245106626102
|
||||
2023-03-21,-48.955919791756116,1954.8685908708542
|
||||
2023-03-22,-41.34851470243514,1913.520076168419
|
||||
2023-03-23,-40.53293708055611,1872.987139087863
|
||||
2023-03-24,-40.62177198705648,1832.3653671008065
|
||||
2023-03-25,-12.808008186129763,1819.5573589146768
|
||||
2023-03-26,44.60456842447671,1864.1619273391534
|
||||
2023-03-27,33.10077209532424,1897.2626994344776
|
||||
2023-03-28,-40.54590870106257,1856.7167907334149
|
||||
2023-03-29,32.68290319879213,1889.399693932207
|
||||
2023-03-30,-42.18093929678437,1847.2187546354226
|
||||
2023-03-31,-30.18435407486843,1817.034400560554
|
||||
2023-04-01,-18.629080327821725,1798.4053202327323
|
||||
2023-04-02,78.36987927566116,1876.7751995083934
|
||||
2023-04-03,-14.310148754581672,1862.4650507538117
|
||||
2023-04-04,67.49999999999953,1929.9650507538113
|
||||
2023-04-05,40.981623971671745,1970.946674725483
|
||||
2023-04-06,27.071471993660218,1998.0181467191433
|
||||
2023-04-07,69.95707277743023,2067.9752194965736
|
||||
2023-04-08,16.74780048539444,2084.723019981968
|
||||
2023-04-09,47.28635900754121,2132.009378989509
|
||||
2023-04-10,92.25687955666356,2224.2662585461726
|
||||
2023-04-11,13.118453933996253,2237.3847124801687
|
||||
2023-04-12,56.24999999999995,2293.6347124801687
|
||||
2023-04-13,179.99999999999943,2473.634712480168
|
||||
2023-04-14,-21.87500000000091,2451.7597124801673
|
||||
2023-04-15,0.6060490696602718,2452.3657615498278
|
||||
2023-04-16,69.62762541934998,2521.9933869691777
|
||||
2023-04-17,65.86212708679903,2587.8555140559765
|
||||
2023-04-18,11.498179506746062,2599.3536935627226
|
||||
2023-04-19,223.1815368848387,2822.5352304475614
|
||||
2023-04-20,-43.12499999999999,2779.4102304475614
|
||||
2023-04-21,31.875000000000142,2811.2852304475614
|
||||
2023-04-22,-29.84738767205142,2781.43784277551
|
||||
2023-04-23,13.154733757123939,2794.5925765326338
|
||||
2023-04-24,6.396324986843672,2800.9889015194776
|
||||
2023-04-25,123.74011330692568,2924.7290148264033
|
||||
2023-04-26,261.41402100210826,3186.1430358285115
|
||||
2023-04-27,24.10664119340748,3210.249677021919
|
||||
2023-04-28,-10.62612672957838,3199.6235502923405
|
||||
2023-04-29,23.597281085864836,3223.2208313782053
|
||||
2023-04-30,-44.289545693205795,3178.9312856849997
|
||||
2023-05-01,54.37500000000002,3233.3062856849997
|
||||
2023-05-02,-2.017144354733148,3231.2891413302664
|
||||
2023-05-03,81.77174013147513,3313.0608814617417
|
||||
2023-05-04,-25.04485318862535,3288.0160282731163
|
||||
2023-05-05,171.61321250444536,3459.629240777562
|
||||
2023-05-06,52.49999999999993,3512.129240777562
|
||||
2023-05-07,-33.168505868798924,3478.960734908763
|
||||
2023-05-08,8.124999999999917,3487.085734908763
|
||||
2023-05-09,-12.584917211039063,3474.5008176977235
|
||||
2023-05-10,52.019173246963206,3526.519990944687
|
||||
2023-05-11,90.00000000000003,3616.519990944687
|
||||
2023-05-12,126.17158084605737,3742.691571790744
|
||||
2023-05-13,8.545669463922014,3751.237241254666
|
||||
2023-05-14,1.8924095106008352,3753.129650765267
|
||||
2023-05-15,10.943496294234567,3764.0731470595015
|
||||
2023-05-16,-30.264218933238727,3733.808928126263
|
||||
2023-05-17,30.026157944387133,3763.83508607065
|
||||
2023-05-18,23.13394310654973,3786.9690291772
|
||||
2023-05-19,15.149354042131993,3802.118383219332
|
||||
2023-05-20,-16.41923661401725,3785.6991466053146
|
||||
2023-05-21,7.846127328452241,3793.545273933767
|
||||
2023-05-22,21.279945465818493,3814.8252193995854
|
||||
2023-05-23,70.02437426214179,3884.8495936617273
|
||||
2023-05-24,72.70217181804935,3957.551765479777
|
||||
2023-05-25,-16.75708025521019,3940.794685224567
|
||||
2023-05-26,18.74999999999976,3959.5446852245664
|
||||
2023-05-27,39.20117578898695,3998.745861013553
|
||||
2023-05-28,110.91041187532412,4109.6562728888775
|
||||
2023-05-29,-32.49999999999996,4077.1562728888775
|
||||
2023-05-30,10.449185839751497,4087.605458728629
|
||||
2023-05-31,-10.136360635569764,4077.469098093059
|
||||
2023-06-01,14.358833920817762,4091.8279320138768
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||||
2023-06-02,65.90793376617691,4157.735865780053
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||||
2023-06-03,2.796329514545665,4160.532195294599
|
||||
2023-06-04,-6.651917557240656,4153.8802777373585
|
||||
2023-06-05,168.7500000000002,4322.6302777373585
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||||
2023-06-06,-43.12500000000005,4279.5052777373585
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||||
2023-06-07,34.36109954050025,4313.866377277859
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||||
2023-06-08,-25.452505493132982,4288.413871784726
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||||
2023-06-09,7.08099194612123,4295.494863730848
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||||
2023-06-10,121.25000000000003,4416.744863730848
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||||
2023-06-11,-20.937848671894088,4395.807015058954
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||||
2023-06-12,-21.37821245611659,4374.428802602837
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||||
2023-06-13,-13.703676058378367,4360.725126544458
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||||
2023-06-14,166.27160175206745,4526.996728296526
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||||
2023-06-15,15.069476387286578,4542.066204683812
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||||
2023-06-16,106.96240346155682,4649.02860814537
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||||
2023-06-17,-11.250000000000341,4637.77860814537
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||||
2023-06-18,-10.120078428463955,4627.658529716906
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||||
2023-06-19,-38.97345934789618,4588.68507036901
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||||
2023-06-20,42.86461601305588,4631.549686382065
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||||
2023-06-21,187.49999999999937,4819.0496863820645
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||||
2023-06-22,31.80896255236462,4850.858648934429
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||||
2023-06-23,23.85220828852076,4874.71085722295
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||||
2023-06-24,-30.371879505034936,4844.338977717915
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||||
2023-06-25,12.45391150222293,4856.792889220138
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||||
2023-06-26,78.4973773289051,4935.290266549043
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||||
2023-06-27,-39.87042272482522,4895.419843824217
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||||
2023-06-28,88.12499999999999,4983.544843824217
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||||
2023-06-29,-40.51516243372697,4943.029681390491
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||||
2023-06-30,105.46931766571112,5048.498999056202
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||||
2023-07-01,-13.796315557439133,5034.702683498763
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||||
2023-07-02,-41.59344453195906,4993.109238966804
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||||
2023-07-03,28.89550853439942,5022.004747501203
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||||
2023-07-04,-5.3332824068334626,5016.6714650943695
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||||
2023-07-05,90.00000000000007,5106.6714650943695
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||||
2023-07-06,65.47404542743519,5172.145510521805
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||||
2023-07-07,-8.375646476725684,5163.769864045079
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||||
2023-07-08,2.0825098762478143,5165.852373921327
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||||
2023-07-09,-12.284261589217671,5153.568112332109
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||||
2023-07-10,4.7069840687455775,5158.275096400855
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||||
2023-07-11,29.744227743509978,5188.019324144365
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||||
2023-07-12,13.786259374056783,5201.805583518421
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||||
2023-07-13,179.07533869993108,5380.880922218353
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||||
2023-07-14,74.05844966531129,5454.939371883664
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||||
2023-07-15,-24.570748403829185,5430.368623479834
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||||
2023-07-16,6.803094664210427,5437.1717181440445
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||||
2023-07-17,27.410515235666534,5464.582233379711
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||||
2023-07-18,4.897911857902959,5469.480145237614
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||||
2023-07-19,6.308694855454021,5475.788840093068
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||||
2023-07-20,41.93544480774592,5517.7242849008135
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||||
2023-07-21,16.096325607887692,5533.820610508701
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||||
2023-07-22,-2.7025252562022395,5531.1180852524985
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||||
2023-07-23,-36.865989707872636,5494.252095544626
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||||
2023-07-24,86.80264475362813,5581.054740298255
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||||
2023-07-25,-24.16611590079934,5556.888624397456
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||||
2023-07-26,-12.803087110558725,5544.085537286897
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||||
2023-07-27,29.206711819629362,5573.2922491065265
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||||
2023-07-28,13.812242058805946,5587.104491165333
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||||
2023-07-29,11.977355224058611,5599.081846389391
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||||
2023-07-30,-5.150633707859324,5593.931212681532
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||||
2023-07-31,-31.586985170360826,5562.344227511171
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||||
2023-08-01,34.57747987841326,5596.921707389584
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||||
2023-08-02,19.53988833101348,5616.461595720598
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||||
2023-08-03,26.963711901014904,5643.425307621613
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||||
2023-08-04,0.4840259877677071,5643.90933360938
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||||
2023-08-05,8.851832296486007,5652.761165905866
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||||
2023-08-06,-4.2929518635524,5648.468214042313
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||||
2023-08-07,4.423504364914294,5652.891718407227
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||||
2023-08-08,79.37499999999964,5732.266718407227
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||||
2023-08-09,-1.0555745361586295,5731.211143871068
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||||
2023-08-10,-15.802261213704188,5715.408882657364
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||||
2023-08-11,-19.434997227631737,5695.973885429733
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||||
2023-08-12,-14.180480342977727,5681.793405086755
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||||
2023-08-13,-25.33078616920967,5656.462618917545
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||||
2023-08-14,-29.365151992789308,5627.097466924756
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||||
2023-08-15,-1.25,5625.847466924756
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||||
2023-08-16,90.00000000000014,5715.847466924756
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||||
2023-08-17,181.8750000000003,5897.722466924756
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||||
2023-08-18,20.625000000000128,5918.347466924756
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||||
2023-08-19,-27.59032679226934,5890.757140132487
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||||
2023-08-20,-23.87577257083145,5866.881367561656
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||||
2023-08-21,-22.59314579170043,5844.288221769955
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||||
2023-08-22,113.75000000000014,5958.038221769955
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||||
2023-08-23,8.70637062854804,5966.744592398503
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||||
2023-08-24,22.993336529216194,5989.73792892772
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||||
2023-08-25,-41.837123197460336,5947.900805730259
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||||
2023-08-26,-20.238929404490822,5927.661876325768
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||||
2023-08-27,-2.006488273327664,5925.655388052441
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||||
2023-08-28,14.024404963407886,5939.679793015848
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||||
2023-08-29,143.13137132947674,6082.811164345325
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||||
2023-08-30,-43.125000000000064,6039.686164345325
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||||
2023-08-31,31.6249079218707,6071.311072267195
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||||
2023-09-01,56.25000000000017,6127.561072267195
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||||
2023-09-02,-27.62863635821808,6099.932435908977
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||||
2023-09-03,-18.380622263138324,6081.551813645839
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||||
2023-09-04,-4.629639415293694,6076.922174230545
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||||
2023-09-05,24.14433818655366,6101.066512417099
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||||
2023-09-06,-46.72867445132057,6054.337837965779
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||||
2023-09-07,-3.6562754869909058,6050.681562478788
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||||
2023-09-08,42.254582050520796,6092.936144529309
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||||
2023-09-09,-30.94267544057865,6061.99346908873
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||||
2023-09-10,53.2912479279699,6115.284717016701
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||||
2023-09-11,146.25000000000028,6261.534717016701
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||||
2023-09-12,-18.31728723379048,6243.21742978291
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||||
2023-09-13,-2.141383984249483,6241.07604579866
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||||
2023-09-14,56.24999999999978,6297.32604579866
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||||
2023-09-15,-37.98094850138423,6259.345097297276
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||||
2023-09-16,-33.38082020481237,6225.964277092464
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||||
2023-09-17,-2.737757522168219,6223.226519570296
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||||
2023-09-18,28.781772740126208,6252.008292310422
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||||
2023-09-19,4.273043833846757,6256.281336144269
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||||
2023-09-20,24.242189180030334,6280.523525324299
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||||
2023-09-21,90.00000000000011,6370.523525324299
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||||
2023-09-22,-30.115416338642312,6340.408108985656
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||||
2023-09-23,-24.28225302122884,6316.1258559644275
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||||
2023-09-24,-42.98193078708244,6273.143925177345
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||||
2023-09-25,-5.561737200674414,6267.582187976671
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||||
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||||
2023-09-27,56.24999999999976,6343.314229309671
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||||
2023-09-28,109.05931606292351,6452.373545372594
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||||
2023-09-29,-3.7500000000000906,6448.623545372594
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||||
2023-09-30,34.11899846667325,6482.7425438392675
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||||
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||||
2023-10-02,-43.125,6534.3987381612515
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2023-10-03,-1.875,6532.5237381612515
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||||
2023-10-04,60.137202072927415,6592.660940234179
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2023-10-05,-47.15508896159986,6545.505851272579
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2023-10-06,-41.50509357550347,6504.000757697076
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||||
2023-10-07,-21.848785430736374,6482.151972266339
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||||
2023-10-08,-2.133334555954726,6480.018637710384
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||||
2023-10-09,120.94752554130996,6600.966163251694
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||||
2023-10-10,-30.55517668632468,6570.410986565369
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||||
2023-10-11,12.918899632245676,6583.3298861976145
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||||
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||||
2023-10-13,-38.92743296812289,6630.82190792463
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||||
2023-10-14,-9.664398308242207,6621.157509616388
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||||
2023-10-15,0.32442084565507256,6621.481930462043
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||||
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||||
2023-10-17,71.96782243080129,6711.11661345908
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||||
2023-10-18,-26.10871664471985,6685.007896814361
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||||
2023-10-19,27.131717309356045,6712.1396141237165
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||||
2023-10-20,104.9999999999995,6817.139614123716
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||||
2023-10-21,95.53563465609497,6912.67524877981
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||||
2023-10-22,-39.07986275419109,6873.5953860256195
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||||
2023-10-23,159.37499999999892,7032.970386025619
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||||
2023-10-24,125.89084826115247,7158.861234286771
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||||
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||||
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||||
2023-10-27,-40.93958561285608,7155.02190137028
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||||
2023-10-28,-0.12582720298443117,7154.896074167295
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||||
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||||
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||||
2023-10-31,-0.7859893532677678,7170.676551029209
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||||
2023-11-01,45.63294697011628,7216.309497999325
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||||
2023-11-02,66.38708795013648,7282.696585949461
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||||
2023-11-03,7.818102574679843,7290.514688524141
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||||
2023-11-04,78.74999999999962,7369.264688524141
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||||
2023-11-05,93.530612820923,7462.795301345064
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||||
2023-11-06,-8.841261133494985,7453.954040211569
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||||
2023-11-07,13.587699262662081,7467.541739474231
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||||
2023-11-08,-27.39298530178767,7440.148754172443
|
||||
2023-11-09,233.65340882150477,7673.802162993948
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||||
2023-11-10,-43.1250000000002,7630.677162993948
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||||
2023-11-11,65.04467136509504,7695.721834359043
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||||
2023-11-12,-24.51389709666313,7671.20793726238
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||||
2023-11-13,6.381878610566607,7677.589815872947
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||||
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||||
2023-11-15,-15.4428344502457,7786.877203153671
|
||||
2023-11-16,22.788163027994152,7809.665366181665
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||||
2023-11-17,-40.58878257444296,7769.076583607222
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||||
2023-11-18,10.05941544996627,7779.135999057188
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||||
2023-11-19,77.18072310694912,7856.316722164137
|
||||
2023-11-20,-33.719119790508586,7822.597602373628
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||||
2023-11-21,-39.39362250328517,7783.203979870344
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||||
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||||
2023-11-23,-43.750000000000135,7801.953979870343
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||||
2023-11-24,43.12499999999979,7845.078979870343
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||||
2023-11-25,2.7372815485791326,7847.816261418921
|
||||
2023-11-26,-19.434424922416646,7828.381836496505
|
||||
2023-11-27,74.22705085378658,7902.608887350291
|
||||
2023-11-28,-21.10900157778203,7881.4998857725095
|
||||
2023-11-29,1.584413397259107,7883.084299169768
|
||||
2023-11-30,-5.586662127245132,7877.497637042523
|
||||
2023-12-01,68.65652016602549,7946.154157208548
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||||
2023-12-02,116.24999999999937,8062.404157208547
|
||||
2023-12-03,48.229742583832405,8110.633899792379
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||||
2023-12-04,13.529045410407036,8124.162945202786
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||||
2023-12-05,93.37552564770242,8217.538470850488
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||||
2023-12-06,-39.37279199427863,8178.1656788562095
|
||||
2023-12-07,160.37637314576938,8338.54205200198
|
||||
2023-12-08,-32.94183697847613,8305.600215023504
|
||||
2023-12-09,-22.342388616671474,8283.257826406832
|
||||
2023-12-10,-29.00075720912898,8254.257069197703
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||||
2023-12-11,112.22981231135489,8366.486881509058
|
||||
2023-12-12,-46.76135746492969,8319.725524044128
|
||||
2023-12-13,102.21323939340017,8421.938763437529
|
||||
2023-12-14,33.74999999999983,8455.688763437529
|
||||
2023-12-15,63.75916511664332,8519.447928554173
|
||||
2023-12-16,-32.300370998108704,8487.147557556063
|
||||
2023-12-17,17.066032222984127,8504.213589779047
|
||||
2023-12-18,168.68048765961714,8672.894077438665
|
||||
2023-12-19,25.118359089859197,8698.012436528525
|
||||
2023-12-20,-43.080721035673186,8654.931715492852
|
||||
2023-12-21,-31.737797271451193,8623.193918221401
|
||||
2023-12-22,47.49999999999983,8670.693918221401
|
||||
2023-12-23,20.47855147595199,8691.172469697352
|
||||
2023-12-24,108.453203178383,8799.625672875736
|
||||
2023-12-25,-34.74504529363933,8764.880627582097
|
||||
2023-12-26,104.99999999999984,8869.880627582097
|
||||
2023-12-27,204.66554953165667,9074.546177113754
|
||||
2023-12-28,-5.606769621811815,9068.939407491942
|
||||
2023-12-29,220.95172689013637,9289.891134382078
|
||||
2023-12-30,-15.105228436109885,9274.785905945968
|
||||
2023-12-31,-0.005881281931285898,9274.780024664036
|
||||
|
File diff suppressed because it is too large
Load Diff
@@ -1,298 +0,0 @@
|
||||
"""
|
||||
回测引擎 - 完整模拟手续费、返佣延迟到账、每日回撤限制、持仓时间约束
|
||||
支持同时持有多单并发，严格控制每日最大回撤
|
||||
"""
|
||||
import datetime
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from dataclasses import dataclass
|
||||
from typing import List, Optional
|
||||
|
||||
|
||||
@dataclass
|
||||
class Trade:
|
||||
entry_time: pd.Timestamp
|
||||
exit_time: Optional[pd.Timestamp] = None
|
||||
direction: int = 0
|
||||
entry_price: float = 0.0
|
||||
exit_price: float = 0.0
|
||||
pnl: float = 0.0
|
||||
fee: float = 0.0
|
||||
rebate: float = 0.0
|
||||
holding_bars: int = 0
|
||||
|
||||
|
||||
@dataclass
|
||||
class OpenPosition:
|
||||
direction: int = 0
|
||||
entry_price: float = 0.0
|
||||
entry_time: pd.Timestamp = None
|
||||
hold_bars: int = 0
|
||||
|
||||
|
||||
class BacktestEngine:
|
||||
def __init__(
|
||||
self,
|
||||
initial_capital: float = 1000.0,
|
||||
margin_per_trade: float = 25.0,
|
||||
leverage: int = 50,
|
||||
fee_rate: float = 0.0005,
|
||||
rebate_ratio: float = 0.70,
|
||||
max_daily_drawdown: float = 50.0,
|
||||
min_hold_bars: int = 1,
|
||||
stop_loss_pct: float = 0.005,
|
||||
take_profit_pct: float = 0.01,
|
||||
max_positions: int = 3,
|
||||
):
|
||||
self.initial_capital = initial_capital
|
||||
self.margin = margin_per_trade
|
||||
self.leverage = leverage
|
||||
self.notional = margin_per_trade * leverage
|
||||
self.fee_rate = fee_rate
|
||||
self.rebate_ratio = rebate_ratio
|
||||
self.max_daily_dd = max_daily_drawdown
|
||||
self.min_hold_bars = min_hold_bars
|
||||
self.sl_pct = stop_loss_pct
|
||||
self.tp_pct = take_profit_pct
|
||||
self.max_positions = max_positions
|
||||
|
||||
def _close_position(self, pos, exit_price, t, today, trades, pending_rebates):
|
||||
"""平仓一个持仓，返回 net_pnl"""
|
||||
qty = self.notional / pos.entry_price
|
||||
if pos.direction == 1:
|
||||
raw_pnl = qty * (exit_price - pos.entry_price)
|
||||
else:
|
||||
raw_pnl = qty * (pos.entry_price - exit_price)
|
||||
|
||||
close_fee = self.notional * self.fee_rate
|
||||
net_pnl = raw_pnl - close_fee
|
||||
total_fee = self.notional * self.fee_rate * 2
|
||||
rebate = total_fee * self.rebate_ratio
|
||||
|
||||
rebate_date = today + datetime.timedelta(days=1)
|
||||
pending_rebates.append((rebate_date, rebate))
|
||||
|
||||
trades.append(Trade(
|
||||
entry_time=pos.entry_time, exit_time=t,
|
||||
direction=pos.direction, entry_price=pos.entry_price,
|
||||
exit_price=exit_price, pnl=net_pnl, fee=total_fee,
|
||||
rebate=rebate, holding_bars=pos.hold_bars,
|
||||
))
|
||||
return net_pnl
|
||||
|
||||
def _worst_unrealized(self, positions, h, lo):
|
||||
"""计算所有持仓在本K线内的最坏浮动亏损（用 high/low）"""
|
||||
worst = 0.0
|
||||
for pos in positions:
|
||||
qty = self.notional / pos.entry_price
|
||||
if pos.direction == 1:
|
||||
# 多单最坏情况: 价格跌到 low
|
||||
worst += qty * (lo - pos.entry_price)
|
||||
else:
|
||||
# 空单最坏情况: 价格涨到 high
|
||||
worst += qty * (pos.entry_price - h)
|
||||
return worst
|
||||
|
||||
def run(self, df: pd.DataFrame, score: pd.Series, open_threshold: float = 0.3) -> dict:
|
||||
capital = self.initial_capital
|
||||
trades: List[Trade] = []
|
||||
daily_pnl = {}
|
||||
pending_rebates = []
|
||||
positions: List[OpenPosition] = []
|
||||
used_margin = 0.0
|
||||
|
||||
current_date = None
|
||||
day_pnl = 0.0
|
||||
day_stopped = False
|
||||
|
||||
close_arr = df['close'].values
|
||||
high_arr = df['high'].values
|
||||
low_arr = df['low'].values
|
||||
times = df.index
|
||||
scores = score.values
|
||||
|
||||
for i in range(len(df)):
|
||||
t = times[i]
|
||||
c = close_arr[i]
|
||||
h = high_arr[i]
|
||||
lo = low_arr[i]
|
||||
s = scores[i]
|
||||
today = t.date()
|
||||
|
||||
# --- 日切换 ---
|
||||
if today != current_date:
|
||||
if current_date is not None:
|
||||
daily_pnl[current_date] = day_pnl
|
||||
current_date = today
|
||||
day_pnl = 0.0
|
||||
day_stopped = False
|
||||
|
||||
arrived = []
|
||||
remaining = []
|
||||
for rd, ra in pending_rebates:
|
||||
if today >= rd:
|
||||
arrived.append(ra)
|
||||
else:
|
||||
remaining.append((rd, ra))
|
||||
if arrived:
|
||||
capital += sum(arrived)
|
||||
pending_rebates = remaining
|
||||
|
||||
if day_stopped:
|
||||
for pos in positions:
|
||||
pos.hold_bars += 1
|
||||
continue
|
||||
|
||||
# --- 正常止损止盈逻辑 ---
|
||||
closed_indices = []
|
||||
for pi, pos in enumerate(positions):
|
||||
pos.hold_bars += 1
|
||||
qty = self.notional / pos.entry_price
|
||||
|
||||
if pos.direction == 1:
|
||||
sl_price = pos.entry_price * (1 - self.sl_pct)
|
||||
tp_price = pos.entry_price * (1 + self.tp_pct)
|
||||
hit_sl = lo <= sl_price
|
||||
hit_tp = h >= tp_price
|
||||
else:
|
||||
sl_price = pos.entry_price * (1 + self.sl_pct)
|
||||
tp_price = pos.entry_price * (1 - self.tp_pct)
|
||||
hit_sl = h >= sl_price
|
||||
hit_tp = lo <= tp_price
|
||||
|
||||
should_close = False
|
||||
exit_price = c
|
||||
|
||||
# 止损始终生效（不受持仓时间限制）
|
||||
if hit_sl:
|
||||
should_close = True
|
||||
exit_price = sl_price
|
||||
elif pos.hold_bars >= self.min_hold_bars:
|
||||
# 止盈和信号反转需要满足最小持仓时间
|
||||
if hit_tp:
|
||||
should_close = True
|
||||
exit_price = tp_price
|
||||
elif (pos.direction == 1 and s < -open_threshold) or \
|
||||
(pos.direction == -1 and s > open_threshold):
|
||||
should_close = True
|
||||
exit_price = c
|
||||
|
||||
if should_close:
|
||||
net = self._close_position(pos, exit_price, t, today, trades, pending_rebates)
|
||||
capital += net
|
||||
used_margin -= self.margin
|
||||
day_pnl += net
|
||||
closed_indices.append(pi)
|
||||
|
||||
# 每笔平仓后立即检查日回撤
|
||||
if day_pnl < -self.max_daily_dd:
|
||||
# 熔断剩余持仓
|
||||
for pj, pos2 in enumerate(positions):
|
||||
if pj not in closed_indices:
|
||||
pos2.hold_bars += 1
|
||||
net2 = self._close_position(pos2, c, t, today, trades, pending_rebates)
|
||||
capital += net2
|
||||
used_margin -= self.margin
|
||||
day_pnl += net2
|
||||
closed_indices.append(pj)
|
||||
day_stopped = True
|
||||
break
|
||||
|
||||
for pi in sorted(set(closed_indices), reverse=True):
|
||||
positions.pop(pi)
|
||||
|
||||
if day_stopped:
|
||||
continue
|
||||
|
||||
# --- 开仓 ---
|
||||
if len(positions) < self.max_positions:
|
||||
if np.isnan(s):
|
||||
continue
|
||||
|
||||
# 开仓前检查: 当前所有持仓 + 新仓同时止损的最大亏损
|
||||
n_after = len(positions) + 1
|
||||
worst_total_sl = n_after * (self.notional * self.sl_pct + self.notional * self.fee_rate * 2)
|
||||
if day_pnl - worst_total_sl < -self.max_daily_dd:
|
||||
continue # 风险敞口太大
|
||||
|
||||
open_fee = self.notional * self.fee_rate
|
||||
if capital - used_margin < self.margin + open_fee:
|
||||
continue
|
||||
|
||||
new_dir = 0
|
||||
if s > open_threshold:
|
||||
new_dir = 1
|
||||
elif s < -open_threshold:
|
||||
new_dir = -1
|
||||
|
||||
if new_dir != 0:
|
||||
positions.append(OpenPosition(
|
||||
direction=new_dir, entry_price=c,
|
||||
entry_time=t, hold_bars=0,
|
||||
))
|
||||
capital -= open_fee
|
||||
used_margin += self.margin
|
||||
day_pnl -= open_fee
|
||||
|
||||
# 最后一天
|
||||
if current_date is not None:
|
||||
daily_pnl[current_date] = day_pnl
|
||||
|
||||
# 强制平仓
|
||||
if positions and len(df) > 0:
|
||||
last_close = close_arr[-1]
|
||||
for pos in positions:
|
||||
qty = self.notional / pos.entry_price
|
||||
if pos.direction == 1:
|
||||
raw_pnl = qty * (last_close - pos.entry_price)
|
||||
else:
|
||||
raw_pnl = qty * (pos.entry_price - last_close)
|
||||
fee = self.notional * self.fee_rate
|
||||
net_pnl = raw_pnl - fee
|
||||
capital += net_pnl
|
||||
trades.append(Trade(
|
||||
entry_time=pos.entry_time, exit_time=times[-1],
|
||||
direction=pos.direction, entry_price=pos.entry_price,
|
||||
exit_price=last_close, pnl=net_pnl,
|
||||
fee=self.notional * self.fee_rate * 2,
|
||||
rebate=0, holding_bars=pos.hold_bars,
|
||||
))
|
||||
|
||||
remaining_rebate = sum(amt for _, amt in pending_rebates)
|
||||
capital += remaining_rebate
|
||||
|
||||
return self._build_result(trades, daily_pnl, capital)
|
||||
|
||||
def _build_result(self, trades, daily_pnl, final_capital):
|
||||
if not trades:
|
||||
return {
|
||||
'total_pnl': 0, 'final_capital': final_capital,
|
||||
'num_trades': 0, 'win_rate': 0, 'avg_pnl': 0,
|
||||
'max_daily_dd': 0, 'avg_daily_pnl': 0,
|
||||
'profit_factor': 0, 'trades': [], 'daily_pnl': daily_pnl,
|
||||
'total_fee': 0, 'total_rebate': 0,
|
||||
}
|
||||
|
||||
pnls = [t.pnl for t in trades]
|
||||
wins = [p for p in pnls if p > 0]
|
||||
losses = [p for p in pnls if p <= 0]
|
||||
daily_vals = list(daily_pnl.values())
|
||||
total_fee = sum(t.fee for t in trades)
|
||||
total_rebate = sum(t.rebate for t in trades)
|
||||
gross_profit = sum(wins) if wins else 0
|
||||
gross_loss = abs(sum(losses)) if losses else 1e-10
|
||||
|
||||
return {
|
||||
'total_pnl': sum(pnls) + total_rebate,
|
||||
'final_capital': final_capital,
|
||||
'num_trades': len(trades),
|
||||
'win_rate': len(wins) / len(trades) if trades else 0,
|
||||
'avg_pnl': np.mean(pnls),
|
||||
'max_daily_dd': min(daily_vals) if daily_vals else 0,
|
||||
'avg_daily_pnl': np.mean(daily_vals) if daily_vals else 0,
|
||||
'profit_factor': gross_profit / gross_loss,
|
||||
'total_fee': total_fee,
|
||||
'total_rebate': total_rebate,
|
||||
'trades': trades,
|
||||
'daily_pnl': daily_pnl,
|
||||
}
|
||||
@@ -1,315 +0,0 @@
|
||||
"""Bollinger Band mean-reversion strategy backtest.
|
||||
|
||||
Logic:
|
||||
- Price touches upper BB → close any long, open short
|
||||
- Price touches lower BB → close any short, open long
|
||||
- Always in position (flip between long and short)
|
||||
|
||||
Uses 5-minute OHLC data from the database.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime, timezone
|
||||
from typing import List, Optional
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
from .data_loader import KlineSource, load_klines
|
||||
from .indicators import bollinger
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Config & result types
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@dataclass
|
||||
class BBConfig:
|
||||
# Bollinger Band parameters
|
||||
bb_period: int = 20 # SMA window
|
||||
bb_std: float = 2.0 # standard deviation multiplier
|
||||
|
||||
# Position sizing
|
||||
margin_per_trade: float = 80.0
|
||||
leverage: float = 100.0
|
||||
initial_capital: float = 1000.0
|
||||
|
||||
# Risk management
|
||||
max_daily_loss: float = 150.0 # stop trading after this daily loss
|
||||
stop_loss_pct: float = 0.0 # 0 = disabled; e.g. 0.02 = 2% SL from entry
|
||||
|
||||
# Dynamic sizing: if > 0, margin = equity * margin_pct (overrides margin_per_trade)
|
||||
margin_pct: float = 0.0 # e.g. 0.01 = 1% of equity per trade
|
||||
|
||||
# Fee structure (taker)
|
||||
fee_rate: float = 0.0006 # 0.06%
|
||||
rebate_rate: float = 0.0 # instant maker rebate (if any)
|
||||
|
||||
# Delayed rebate: rebate_pct of daily fees returned next day at rebate_hour UTC
|
||||
rebate_pct: float = 0.0 # e.g. 0.70 = 70% rebate
|
||||
rebate_hour_utc: int = 0 # hour in UTC when rebate arrives (0 = 8am UTC+8)
|
||||
|
||||
|
||||
@dataclass
|
||||
class BBTrade:
|
||||
side: str # "long" or "short"
|
||||
entry_price: float
|
||||
exit_price: float
|
||||
entry_time: object # pd.Timestamp
|
||||
exit_time: object
|
||||
margin: float
|
||||
leverage: float
|
||||
qty: float
|
||||
gross_pnl: float
|
||||
fee: float
|
||||
net_pnl: float
|
||||
|
||||
|
||||
@dataclass
|
||||
class BBResult:
|
||||
equity_curve: pd.DataFrame # columns: equity, balance, price, position
|
||||
trades: List[BBTrade]
|
||||
daily_stats: pd.DataFrame # daily equity + pnl
|
||||
total_fee: float
|
||||
total_rebate: float
|
||||
config: BBConfig
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Backtest engine
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
|
||||
"""Run Bollinger Band mean-reversion backtest on 5m OHLC data."""
|
||||
|
||||
close = df["close"].astype(float)
|
||||
high = df["high"].astype(float)
|
||||
low = df["low"].astype(float)
|
||||
n = len(df)
|
||||
|
||||
# Compute Bollinger Bands
|
||||
bb_mid, bb_upper, bb_lower, bb_width = bollinger(close, cfg.bb_period, cfg.bb_std)
|
||||
|
||||
# Convert to numpy for speed
|
||||
arr_close = close.values
|
||||
arr_high = high.values
|
||||
arr_low = low.values
|
||||
arr_upper = bb_upper.values
|
||||
arr_lower = bb_lower.values
|
||||
ts_index = df.index
|
||||
|
||||
# State
|
||||
balance = cfg.initial_capital
|
||||
position = 0 # +1 = long, -1 = short, 0 = flat
|
||||
entry_price = 0.0
|
||||
entry_time = None
|
||||
entry_margin = 0.0
|
||||
entry_qty = 0.0
|
||||
|
||||
trades: List[BBTrade] = []
|
||||
total_fee = 0.0
|
||||
total_rebate = 0.0
|
||||
|
||||
# Daily tracking
|
||||
day_pnl = 0.0
|
||||
day_stopped = False
|
||||
current_day = None
|
||||
|
||||
# Delayed rebate tracking
|
||||
pending_rebate = 0.0 # fees from previous day to be rebated
|
||||
today_fees = 0.0 # fees accumulated today
|
||||
rebate_applied_today = False
|
||||
|
||||
# Output arrays
|
||||
out_equity = np.full(n, np.nan)
|
||||
out_balance = np.full(n, np.nan)
|
||||
out_position = np.zeros(n)
|
||||
|
||||
def unrealised(price):
|
||||
if position == 0:
|
||||
return 0.0
|
||||
if position == 1:
|
||||
return entry_qty * (price - entry_price)
|
||||
else:
|
||||
return entry_qty * (entry_price - price)
|
||||
|
||||
def close_position(exit_price, exit_idx):
|
||||
nonlocal balance, position, entry_price, entry_time, entry_margin, entry_qty
|
||||
nonlocal total_fee, total_rebate, day_pnl, today_fees
|
||||
|
||||
if position == 0:
|
||||
return
|
||||
|
||||
if position == 1:
|
||||
gross = entry_qty * (exit_price - entry_price)
|
||||
else:
|
||||
gross = entry_qty * (entry_price - exit_price)
|
||||
|
||||
exit_notional = entry_qty * exit_price
|
||||
fee = exit_notional * cfg.fee_rate
|
||||
rebate = exit_notional * cfg.rebate_rate # instant rebate only
|
||||
net = gross - fee + rebate
|
||||
|
||||
trades.append(BBTrade(
|
||||
side="long" if position == 1 else "short",
|
||||
entry_price=entry_price,
|
||||
exit_price=exit_price,
|
||||
entry_time=entry_time,
|
||||
exit_time=ts_index[exit_idx],
|
||||
margin=entry_margin,
|
||||
leverage=cfg.leverage,
|
||||
qty=entry_qty,
|
||||
gross_pnl=gross,
|
||||
fee=fee,
|
||||
net_pnl=net,
|
||||
))
|
||||
|
||||
balance += net
|
||||
total_fee += fee
|
||||
total_rebate += rebate
|
||||
today_fees += fee
|
||||
day_pnl += net
|
||||
position = 0
|
||||
entry_price = 0.0
|
||||
entry_time = None
|
||||
entry_margin = 0.0
|
||||
entry_qty = 0.0
|
||||
|
||||
def open_position(side, price, idx):
|
||||
nonlocal position, entry_price, entry_time, entry_margin, entry_qty
|
||||
nonlocal balance, total_fee, day_pnl, today_fees
|
||||
|
||||
if cfg.margin_pct > 0:
|
||||
equity = balance + unrealised(price) if position != 0 else balance
|
||||
margin = equity * cfg.margin_pct
|
||||
else:
|
||||
margin = cfg.margin_per_trade
|
||||
margin = min(margin, balance * 0.95)
|
||||
if margin <= 0:
|
||||
return
|
||||
notional = margin * cfg.leverage
|
||||
qty = notional / price
|
||||
fee = notional * cfg.fee_rate
|
||||
|
||||
balance -= fee
|
||||
total_fee += fee
|
||||
today_fees += fee
|
||||
day_pnl -= fee
|
||||
|
||||
position = 1 if side == "long" else -1
|
||||
entry_price = price
|
||||
entry_time = ts_index[idx]
|
||||
entry_margin = margin
|
||||
entry_qty = qty
|
||||
|
||||
# Main loop
|
||||
for i in range(n):
|
||||
# Daily reset + delayed rebate
|
||||
bar_day = ts_index[i].date() if hasattr(ts_index[i], 'date') else None
|
||||
bar_hour = ts_index[i].hour if hasattr(ts_index[i], 'hour') else 0
|
||||
if bar_day is not None and bar_day != current_day:
|
||||
# New day: move today's fees to pending, reset
|
||||
if cfg.rebate_pct > 0:
|
||||
pending_rebate = today_fees * cfg.rebate_pct
|
||||
today_fees = 0.0
|
||||
rebate_applied_today = False
|
||||
day_pnl = 0.0
|
||||
day_stopped = False
|
||||
current_day = bar_day
|
||||
|
||||
# Apply delayed rebate at specified hour
|
||||
if cfg.rebate_pct > 0 and not rebate_applied_today and bar_hour >= cfg.rebate_hour_utc and pending_rebate > 0:
|
||||
balance += pending_rebate
|
||||
total_rebate += pending_rebate
|
||||
pending_rebate = 0.0
|
||||
rebate_applied_today = True
|
||||
|
||||
# Skip if BB not ready
|
||||
if np.isnan(arr_upper[i]) or np.isnan(arr_lower[i]):
|
||||
out_equity[i] = balance + unrealised(arr_close[i])
|
||||
out_balance[i] = balance
|
||||
out_position[i] = position
|
||||
continue
|
||||
|
||||
# Daily loss check
|
||||
if day_stopped:
|
||||
out_equity[i] = balance + unrealised(arr_close[i])
|
||||
out_balance[i] = balance
|
||||
out_position[i] = position
|
||||
continue
|
||||
|
||||
cur_equity = balance + unrealised(arr_close[i])
|
||||
if day_pnl + unrealised(arr_close[i]) <= -cfg.max_daily_loss:
|
||||
close_position(arr_close[i], i)
|
||||
day_stopped = True
|
||||
out_equity[i] = balance
|
||||
out_balance[i] = balance
|
||||
out_position[i] = 0
|
||||
continue
|
||||
|
||||
# Stop loss check
|
||||
if position != 0 and cfg.stop_loss_pct > 0:
|
||||
if position == 1 and arr_low[i] <= entry_price * (1 - cfg.stop_loss_pct):
|
||||
sl_price = entry_price * (1 - cfg.stop_loss_pct)
|
||||
close_position(sl_price, i)
|
||||
elif position == -1 and arr_high[i] >= entry_price * (1 + cfg.stop_loss_pct):
|
||||
sl_price = entry_price * (1 + cfg.stop_loss_pct)
|
||||
close_position(sl_price, i)
|
||||
|
||||
# Signal detection: use high/low to check if price touched BB
|
||||
touched_upper = arr_high[i] >= arr_upper[i]
|
||||
touched_lower = arr_low[i] <= arr_lower[i]
|
||||
|
||||
if touched_upper and touched_lower:
|
||||
# Both touched in same bar (wide bar) — skip, too volatile
|
||||
pass
|
||||
elif touched_upper:
|
||||
# Price touched upper BB → go short
|
||||
if position == 1:
|
||||
# Close long at upper BB price
|
||||
close_position(arr_upper[i], i)
|
||||
if position != -1:
|
||||
# Open short
|
||||
open_position("short", arr_upper[i], i)
|
||||
elif touched_lower:
|
||||
# Price touched lower BB → go long
|
||||
if position == -1:
|
||||
# Close short at lower BB price
|
||||
close_position(arr_lower[i], i)
|
||||
if position != 1:
|
||||
# Open long
|
||||
open_position("long", arr_lower[i], i)
|
||||
|
||||
# Record equity
|
||||
out_equity[i] = balance + unrealised(arr_close[i])
|
||||
out_balance[i] = balance
|
||||
out_position[i] = position
|
||||
|
||||
# Force close at end
|
||||
if position != 0:
|
||||
close_position(arr_close[n - 1], n - 1)
|
||||
out_equity[n - 1] = balance
|
||||
out_balance[n - 1] = balance
|
||||
out_position[n - 1] = 0
|
||||
|
||||
# Build equity DataFrame
|
||||
eq_df = pd.DataFrame({
|
||||
"equity": out_equity,
|
||||
"balance": out_balance,
|
||||
"price": arr_close,
|
||||
"position": out_position,
|
||||
}, index=ts_index)
|
||||
|
||||
# Daily stats
|
||||
daily_eq = eq_df["equity"].resample("1D").last().dropna().to_frame("equity")
|
||||
daily_eq["pnl"] = daily_eq["equity"].diff().fillna(0.0)
|
||||
|
||||
return BBResult(
|
||||
equity_curve=eq_df,
|
||||
trades=trades,
|
||||
daily_stats=daily_eq,
|
||||
total_fee=total_fee,
|
||||
total_rebate=total_rebate,
|
||||
config=cfg,
|
||||
)
|
||||
@@ -1,53 +0,0 @@
|
||||
{
|
||||
"bb_period": 36,
|
||||
"bb_std": 3.3000000000000003,
|
||||
"kc_period": 24,
|
||||
"kc_mult": 1.3,
|
||||
"dc_period": 41,
|
||||
"ema_fast": 3,
|
||||
"ema_slow": 15,
|
||||
"macd_fast": 9,
|
||||
"macd_slow": 34,
|
||||
"macd_signal": 15,
|
||||
"adx_period": 16,
|
||||
"st_period": 5,
|
||||
"st_mult": 1.4,
|
||||
"rsi_period": 7,
|
||||
"stoch_k": 18,
|
||||
"stoch_d": 6,
|
||||
"stoch_smooth": 3,
|
||||
"cci_period": 12,
|
||||
"wr_period": 9,
|
||||
"wma_period": 47,
|
||||
"bb_oversold": -0.19999999999999998,
|
||||
"bb_overbought": 1.3,
|
||||
"kc_oversold": 0.2,
|
||||
"kc_overbought": 0.75,
|
||||
"dc_oversold": 0.05,
|
||||
"dc_overbought": 0.75,
|
||||
"adx_threshold": 15.0,
|
||||
"rsi_overbought": 70.0,
|
||||
"rsi_oversold": 18.0,
|
||||
"stoch_overbought": 89.0,
|
||||
"stoch_oversold": 10.0,
|
||||
"cci_overbought": 80.0,
|
||||
"cci_oversold": -140.0,
|
||||
"wr_overbought": -28.0,
|
||||
"wr_oversold": -90.0,
|
||||
"w_bb": 0.15000000000000002,
|
||||
"w_kc": 0.4,
|
||||
"w_dc": 0.0,
|
||||
"w_ema": 0.8500000000000001,
|
||||
"w_macd": 0.35000000000000003,
|
||||
"w_adx": 0.0,
|
||||
"w_st": 0.15000000000000002,
|
||||
"w_rsi": 0.4,
|
||||
"w_stoch": 0.15000000000000002,
|
||||
"w_cci": 0.1,
|
||||
"w_wr": 0.0,
|
||||
"w_wma": 0.4,
|
||||
"open_threshold": 0.22,
|
||||
"max_positions": 3,
|
||||
"take_profit_pct": 0.024999999999999998,
|
||||
"stop_loss_pct": 0.008
|
||||
}
|
||||
@@ -1,69 +0,0 @@
|
||||
"""
|
||||
数据加载模块 - 从 SQLite 加载多周期K线数据为 DataFrame
|
||||
"""
|
||||
import pandas as pd
|
||||
from peewee import SqliteDatabase
|
||||
from pathlib import Path
|
||||
|
||||
DB_PATH = Path(__file__).parent.parent / 'models' / 'database.db'
|
||||
|
||||
# 周期 -> 表名
|
||||
PERIOD_MAP = {
|
||||
'1m': 'bitmart_eth_1m',
|
||||
'3m': 'bitmart_eth_3m',
|
||||
'5m': 'bitmart_eth_5m',
|
||||
'15m': 'bitmart_eth_15m',
|
||||
'30m': 'bitmart_eth_30m',
|
||||
'1h': 'bitmart_eth_1h',
|
||||
}
|
||||
|
||||
|
||||
def load_klines(period: str, start_date: str, end_date: str) -> pd.DataFrame:
|
||||
"""
|
||||
加载指定周期、指定日期范围的K线数据
|
||||
:param period: '1m','3m','5m','15m','30m','1h'
|
||||
:param start_date: 'YYYY-MM-DD'
|
||||
:param end_date: 'YYYY-MM-DD' (不包含该日)
|
||||
:return: DataFrame with columns: datetime, open, high, low, close
|
||||
"""
|
||||
table = PERIOD_MAP.get(period)
|
||||
if not table:
|
||||
raise ValueError(f"不支持的周期: {period}, 可选: {list(PERIOD_MAP.keys())}")
|
||||
|
||||
start_ts = int(pd.Timestamp(start_date).timestamp() * 1000)
|
||||
end_ts = int(pd.Timestamp(end_date).timestamp() * 1000)
|
||||
|
||||
db = SqliteDatabase(str(DB_PATH))
|
||||
db.connect()
|
||||
cursor = db.execute_sql(
|
||||
f'SELECT id, open, high, low, close FROM [{table}] '
|
||||
f'WHERE id >= ? AND id < ? ORDER BY id',
|
||||
(start_ts, end_ts)
|
||||
)
|
||||
rows = cursor.fetchall()
|
||||
db.close()
|
||||
|
||||
df = pd.DataFrame(rows, columns=['timestamp_ms', 'open', 'high', 'low', 'close'])
|
||||
df['datetime'] = pd.to_datetime(df['timestamp_ms'], unit='ms')
|
||||
df.set_index('datetime', inplace=True)
|
||||
df.drop(columns=['timestamp_ms'], inplace=True)
|
||||
df = df.astype(float)
|
||||
return df
|
||||
|
||||
|
||||
def load_multi_period(periods: list, start_date: str, end_date: str) -> dict:
|
||||
"""
|
||||
加载多个周期的数据
|
||||
:return: {period: DataFrame}
|
||||
"""
|
||||
result = {}
|
||||
for p in periods:
|
||||
result[p] = load_klines(p, start_date, end_date)
|
||||
print(f" 加载 {p}: {len(result[p])} 条 ({start_date} ~ {end_date})")
|
||||
return result
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
data = load_multi_period(['5m', '15m', '1h'], '2020-01-01', '2024-01-01')
|
||||
for k, v in data.items():
|
||||
print(f"{k}: {v.shape}, {v.index[0]} ~ {v.index[-1]}")
|
||||
@@ -1,104 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def ema(s: pd.Series, span: int) -> pd.Series:
|
||||
return s.ewm(span=span, adjust=False).mean()
|
||||
|
||||
|
||||
def rsi(close: pd.Series, period: int) -> pd.Series:
|
||||
delta = close.diff()
|
||||
up = delta.clip(lower=0.0)
|
||||
down = (-delta).clip(lower=0.0)
|
||||
|
||||
roll_up = up.ewm(alpha=1 / period, adjust=False).mean()
|
||||
roll_down = down.ewm(alpha=1 / period, adjust=False).mean()
|
||||
|
||||
rs = roll_up / roll_down.replace(0.0, np.nan)
|
||||
return 100.0 - (100.0 / (1.0 + rs))
|
||||
|
||||
|
||||
def atr(high: pd.Series, low: pd.Series, close: pd.Series, period: int) -> pd.Series:
|
||||
prev_close = close.shift(1)
|
||||
tr = pd.concat(
|
||||
[
|
||||
(high - low).abs(),
|
||||
(high - prev_close).abs(),
|
||||
(low - prev_close).abs(),
|
||||
],
|
||||
axis=1,
|
||||
).max(axis=1)
|
||||
return tr.ewm(alpha=1 / period, adjust=False).mean()
|
||||
|
||||
|
||||
def bollinger(close: pd.Series, window: int, n_std: float):
|
||||
mid = close.rolling(window=window, min_periods=window).mean()
|
||||
std = close.rolling(window=window, min_periods=window).std(ddof=0)
|
||||
upper = mid + n_std * std
|
||||
lower = mid - n_std * std
|
||||
width = (upper - lower) / mid
|
||||
return mid, upper, lower, width
|
||||
|
||||
|
||||
def macd(close: pd.Series, fast: int, slow: int, signal: int):
|
||||
fast_ema = ema(close, fast)
|
||||
slow_ema = ema(close, slow)
|
||||
line = fast_ema - slow_ema
|
||||
sig = ema(line, signal)
|
||||
hist = line - sig
|
||||
return line, sig, hist
|
||||
|
||||
|
||||
def stochastic(high: pd.Series, low: pd.Series, close: pd.Series,
|
||||
k_period: int = 14, d_period: int = 3):
|
||||
"""Stochastic Oscillator (%K and %D)."""
|
||||
lowest = low.rolling(window=k_period, min_periods=k_period).min()
|
||||
highest = high.rolling(window=k_period, min_periods=k_period).max()
|
||||
denom = highest - lowest
|
||||
k = 100.0 * (close - lowest) / denom.replace(0.0, np.nan)
|
||||
d = k.rolling(window=d_period, min_periods=d_period).mean()
|
||||
return k, d
|
||||
|
||||
|
||||
def cci(high: pd.Series, low: pd.Series, close: pd.Series,
|
||||
period: int = 20) -> pd.Series:
|
||||
"""Commodity Channel Index."""
|
||||
tp = (high + low + close) / 3.0
|
||||
sma = tp.rolling(window=period, min_periods=period).mean()
|
||||
mad = tp.rolling(window=period, min_periods=period).apply(
|
||||
lambda x: np.mean(np.abs(x - np.mean(x))), raw=True
|
||||
)
|
||||
return (tp - sma) / (0.015 * mad.replace(0.0, np.nan))
|
||||
|
||||
|
||||
def adx(high: pd.Series, low: pd.Series, close: pd.Series,
|
||||
period: int = 14) -> pd.Series:
|
||||
"""Average Directional Index (returns ADX line only)."""
|
||||
up_move = high.diff()
|
||||
down_move = -low.diff()
|
||||
|
||||
plus_dm = pd.Series(np.where((up_move > down_move) & (up_move > 0), up_move, 0.0),
|
||||
index=high.index)
|
||||
minus_dm = pd.Series(np.where((down_move > up_move) & (down_move > 0), down_move, 0.0),
|
||||
index=high.index)
|
||||
|
||||
atr_val = atr(high, low, close, period)
|
||||
|
||||
plus_di = 100.0 * plus_dm.ewm(alpha=1 / period, adjust=False).mean() / atr_val.replace(0.0, np.nan)
|
||||
minus_di = 100.0 * minus_dm.ewm(alpha=1 / period, adjust=False).mean() / atr_val.replace(0.0, np.nan)
|
||||
|
||||
dx = 100.0 * (plus_di - minus_di).abs() / (plus_di + minus_di).replace(0.0, np.nan)
|
||||
adx_line = dx.ewm(alpha=1 / period, adjust=False).mean()
|
||||
return adx_line
|
||||
|
||||
|
||||
def keltner_channel(high: pd.Series, low: pd.Series, close: pd.Series,
|
||||
ema_period: int = 20, atr_period: int = 14, atr_mult: float = 1.5):
|
||||
"""Keltner Channel (mid, upper, lower)."""
|
||||
mid = ema(close, ema_period)
|
||||
atr_val = atr(high, low, close, atr_period)
|
||||
upper = mid + atr_mult * atr_val
|
||||
lower = mid - atr_mult * atr_val
|
||||
return mid, upper, lower
|
||||
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|
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|
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|
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|
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|
Before Width: | Height: | Size: 115 KiB |
@@ -1,199 +0,0 @@
|
||||
"""Run Bollinger Band mean-reversion backtest on ETH 2023+2024.
|
||||
|
||||
Preloads data once, then sweeps parameters in-memory for speed.
|
||||
"""
|
||||
import sys, time
|
||||
sys.stdout.reconfigure(line_buffering=True)
|
||||
sys.path.insert(0, str(__import__("pathlib").Path(__file__).resolve().parents[1]))
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import matplotlib
|
||||
matplotlib.use("Agg")
|
||||
import matplotlib.pyplot as plt
|
||||
from pathlib import Path
|
||||
from collections import defaultdict
|
||||
|
||||
from strategy.bb_backtest import BBConfig, run_bb_backtest
|
||||
from strategy.data_loader import KlineSource, load_klines
|
||||
from datetime import datetime, timezone
|
||||
|
||||
root = Path(__file__).resolve().parents[1]
|
||||
src = KlineSource(db_path=root / "models" / "database.db", table_name="bitmart_eth_5m")
|
||||
out_dir = root / "strategy" / "results"
|
||||
out_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
t0 = time.time()
|
||||
|
||||
# Preload data once
|
||||
print("Loading data...")
|
||||
df_23 = load_klines(src, datetime(2023,1,1,tzinfo=timezone.utc),
|
||||
datetime(2023,12,31,23,59,tzinfo=timezone.utc))
|
||||
df_24 = load_klines(src, datetime(2024,1,1,tzinfo=timezone.utc),
|
||||
datetime(2024,12,31,23,59,tzinfo=timezone.utc))
|
||||
data = {2023: df_23, 2024: df_24}
|
||||
print(f"Loaded: 2023={len(df_23)} bars, 2024={len(df_24)} bars ({time.time()-t0:.1f}s)")
|
||||
|
||||
# ================================================================
|
||||
# Sweep
|
||||
# ================================================================
|
||||
print("\n" + "=" * 120)
|
||||
print(" Bollinger Band Mean-Reversion — ETH 5min | 1000U capital")
|
||||
print(" touch upper BB -> short, touch lower BB -> long (flip)")
|
||||
print("=" * 120)
|
||||
|
||||
results = []
|
||||
|
||||
def test(label, cfg):
|
||||
"""Run on both years, print summary, store results."""
|
||||
row = {"label": label, "cfg": cfg}
|
||||
for year in [2023, 2024]:
|
||||
r = run_bb_backtest(data[year], cfg)
|
||||
d = r.daily_stats
|
||||
pnl = d["pnl"].astype(float)
|
||||
eq = d["equity"].astype(float)
|
||||
dd = float((eq - eq.cummax()).min())
|
||||
final = float(eq.iloc[-1])
|
||||
nt = len(r.trades)
|
||||
wr = sum(1 for t in r.trades if t.net_pnl > 0) / max(nt, 1) * 100
|
||||
nf = r.total_fee - r.total_rebate
|
||||
row[f"a{year}"] = float(pnl.mean())
|
||||
row[f"d{year}"] = dd
|
||||
row[f"r{year}"] = r
|
||||
row[f"n{year}"] = nt
|
||||
row[f"w{year}"] = wr
|
||||
row[f"f{year}"] = nf
|
||||
row[f"eq{year}"] = final
|
||||
mn = min(row["a2023"], row["a2024"])
|
||||
avg = (row["a2023"] + row["a2024"]) / 2
|
||||
mark = " <<<" if mn >= 20 else (" **" if mn >= 10 else "")
|
||||
print(f" {label:52s} 23:{row['a2023']:+6.1f} 24:{row['a2024']:+6.1f} "
|
||||
f"avg:{avg:+5.1f} n23:{row['n2023']:3d} n24:{row['n2024']:3d} "
|
||||
f"dd:{min(row['d2023'],row['d2024']):+7.0f}{mark}")
|
||||
row["mn"] = mn; row["avg"] = avg
|
||||
results.append(row)
|
||||
|
||||
# [1] BB period
|
||||
print("\n[1] Period sweep")
|
||||
for p in [10, 15, 20, 30, 40]:
|
||||
test(f"BB({p},2.0) 80u 100x", BBConfig(bb_period=p, bb_std=2.0, margin_per_trade=80, leverage=100))
|
||||
|
||||
# [2] BB std
|
||||
print("\n[2] Std sweep")
|
||||
for s in [1.5, 1.8, 2.0, 2.5, 3.0]:
|
||||
test(f"BB(20,{s}) 80u 100x", BBConfig(bb_period=20, bb_std=s, margin_per_trade=80, leverage=100))
|
||||
|
||||
# [3] Margin
|
||||
print("\n[3] Margin sweep")
|
||||
for m in [40, 60, 80, 100, 120]:
|
||||
test(f"BB(20,2.0) {m}u 100x", BBConfig(bb_period=20, bb_std=2.0, margin_per_trade=m, leverage=100))
|
||||
|
||||
# [4] SL
|
||||
print("\n[4] Stop-loss sweep")
|
||||
for sl in [0.0, 0.01, 0.02, 0.03, 0.05]:
|
||||
test(f"BB(20,2.0) 80u SL={sl:.0%}", BBConfig(bb_period=20, bb_std=2.0, margin_per_trade=80, leverage=100, stop_loss_pct=sl))
|
||||
|
||||
# [5] MDL
|
||||
print("\n[5] Max daily loss")
|
||||
for mdl in [50, 100, 150, 200]:
|
||||
test(f"BB(20,2.0) 80u mdl={mdl}", BBConfig(bb_period=20, bb_std=2.0, margin_per_trade=80, leverage=100, max_daily_loss=mdl))
|
||||
|
||||
# [6] Combined fine-tune
|
||||
print("\n[6] Fine-tune")
|
||||
for p in [15, 20, 30]:
|
||||
for s in [1.5, 2.0, 2.5]:
|
||||
for m in [80, 100]:
|
||||
test(f"BB({p},{s}) {m}u mdl=150",
|
||||
BBConfig(bb_period=p, bb_std=s, margin_per_trade=m, leverage=100, max_daily_loss=150))
|
||||
|
||||
# ================================================================
|
||||
# Ranking
|
||||
# ================================================================
|
||||
results.sort(key=lambda x: x["mn"], reverse=True)
|
||||
print(f"\n{'='*120}")
|
||||
print(f" TOP 10 — ranked by min(daily_avg_2023, daily_avg_2024)")
|
||||
print(f"{'='*120}")
|
||||
for i, r in enumerate(results[:10]):
|
||||
print(f" {i+1:2d}. {r['label']:50s} 23:{r['a2023']:+6.1f} 24:{r['a2024']:+6.1f} "
|
||||
f"min:{r['mn']:+6.1f} dd:{min(r['d2023'],r['d2024']):+7.0f} "
|
||||
f"wr23:{r['w2023']:.0f}% wr24:{r['w2024']:.0f}%")
|
||||
|
||||
# ================================================================
|
||||
# Detailed report for best
|
||||
# ================================================================
|
||||
best = results[0]
|
||||
print(f"\n{'#'*70}")
|
||||
print(f" BEST: {best['label']}")
|
||||
print(f"{'#'*70}")
|
||||
|
||||
for year in [2023, 2024]:
|
||||
r = best[f"r{year}"]
|
||||
cfg = best["cfg"]
|
||||
d = r.daily_stats
|
||||
pnl = d["pnl"].astype(float)
|
||||
eq = d["equity"].astype(float)
|
||||
dd = (eq - eq.cummax()).min()
|
||||
final = float(eq.iloc[-1])
|
||||
nt = len(r.trades)
|
||||
wr = sum(1 for t in r.trades if t.net_pnl > 0) / max(nt, 1)
|
||||
nf = r.total_fee - r.total_rebate
|
||||
|
||||
loss_streak = max_ls = 0
|
||||
for v in pnl.values:
|
||||
if v < 0: loss_streak += 1; max_ls = max(max_ls, loss_streak)
|
||||
else: loss_streak = 0
|
||||
|
||||
print(f"\n --- {year} ---")
|
||||
print(f" Final equity : {final:,.2f} U ({final-cfg.initial_capital:+,.2f}, "
|
||||
f"{(final-cfg.initial_capital)/cfg.initial_capital*100:+.1f}%)")
|
||||
print(f" Max drawdown : {dd:,.2f} U")
|
||||
print(f" Avg daily PnL : {pnl.mean():+,.2f} U")
|
||||
print(f" Median daily PnL : {pnl.median():+,.2f} U")
|
||||
print(f" Best/worst day : {pnl.max():+,.2f} / {pnl.min():+,.2f}")
|
||||
print(f" Profitable days : {(pnl>0).sum()}/{len(pnl)} ({(pnl>0).mean():.1%})")
|
||||
print(f" Days >= 20U : {(pnl>=20).sum()}")
|
||||
print(f" Max loss streak : {max_ls} days")
|
||||
print(f" Trades : {nt} (win rate {wr:.1%})")
|
||||
print(f" Net fees : {nf:,.0f} U")
|
||||
sharpe = pnl.mean() / max(pnl.std(), 1e-10) * np.sqrt(365)
|
||||
print(f" Sharpe (annual) : {sharpe:.2f}")
|
||||
|
||||
# ================================================================
|
||||
# Chart
|
||||
# ================================================================
|
||||
fig, axes = plt.subplots(3, 2, figsize=(18, 12),
|
||||
gridspec_kw={"height_ratios": [3, 1.5, 1]})
|
||||
|
||||
for col, year in enumerate([2023, 2024]):
|
||||
r = best[f"r{year}"]
|
||||
cfg = best["cfg"]
|
||||
d = r.daily_stats
|
||||
eq = d["equity"].astype(float)
|
||||
pnl = d["pnl"].astype(float)
|
||||
dd = eq - eq.cummax()
|
||||
|
||||
axes[0, col].plot(eq.index, eq.values, linewidth=1.2, color="#1f77b4")
|
||||
axes[0, col].axhline(cfg.initial_capital, color="gray", ls="--", lw=0.5)
|
||||
axes[0, col].set_title(f"BB Strategy Equity — {year}\n"
|
||||
f"BB({cfg.bb_period},{cfg.bb_std}) {cfg.margin_per_trade}u {cfg.leverage:.0f}x",
|
||||
fontsize=11)
|
||||
axes[0, col].set_ylabel("Equity (U)")
|
||||
axes[0, col].grid(True, alpha=0.3)
|
||||
|
||||
colors = ["#2ca02c" if v >= 0 else "#d62728" for v in pnl.values]
|
||||
axes[1, col].bar(pnl.index, pnl.values, color=colors, width=0.8)
|
||||
axes[1, col].axhline(20, color="orange", ls="--", lw=1, label="20U target")
|
||||
axes[1, col].axhline(0, color="gray", lw=0.5)
|
||||
axes[1, col].set_ylabel("Daily PnL (U)")
|
||||
axes[1, col].legend(fontsize=8)
|
||||
axes[1, col].grid(True, alpha=0.3)
|
||||
|
||||
axes[2, col].fill_between(dd.index, dd.values, 0, color="#d62728", alpha=0.4)
|
||||
axes[2, col].set_ylabel("Drawdown (U)")
|
||||
axes[2, col].grid(True, alpha=0.3)
|
||||
|
||||
fig.tight_layout()
|
||||
fig.savefig(out_dir / "bb_strategy_report.png", dpi=150)
|
||||
plt.close(fig)
|
||||
print(f"\nChart: {out_dir / 'bb_strategy_report.png'}")
|
||||
print(f"Total time: {time.time()-t0:.0f}s")
|
||||
@@ -1,125 +0,0 @@
|
||||
"""
|
||||
信号生成模块 - 多指标加权投票 + 多时间框架过滤
|
||||
"""
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def generate_indicator_signals(df: pd.DataFrame, params: dict) -> pd.DataFrame:
|
||||
"""
|
||||
根据指标值生成每个指标的独立信号 (+1 做多 / -1 做空 / 0 中性)
|
||||
df 必须已经包含 compute_all_indicators 计算出的列
|
||||
"""
|
||||
out = df.copy()
|
||||
|
||||
# --- 布林带 %B ---
|
||||
out['sig_bb'] = 0
|
||||
out.loc[out['bb_pct'] < params.get('bb_oversold', 0.0), 'sig_bb'] = 1
|
||||
out.loc[out['bb_pct'] > params.get('bb_overbought', 1.0), 'sig_bb'] = -1
|
||||
|
||||
# --- 肯特纳通道 ---
|
||||
out['sig_kc'] = 0
|
||||
out.loc[out['kc_pct'] < params.get('kc_oversold', 0.0), 'sig_kc'] = 1
|
||||
out.loc[out['kc_pct'] > params.get('kc_overbought', 1.0), 'sig_kc'] = -1
|
||||
|
||||
# --- 唐奇安通道 ---
|
||||
out['sig_dc'] = 0
|
||||
out.loc[out['dc_pct'] < params.get('dc_oversold', 0.2), 'sig_dc'] = 1
|
||||
out.loc[out['dc_pct'] > params.get('dc_overbought', 0.8), 'sig_dc'] = -1
|
||||
|
||||
# --- EMA 交叉 ---
|
||||
out['sig_ema'] = 0
|
||||
out.loc[out['ema_diff'] > 0, 'sig_ema'] = 1
|
||||
out.loc[out['ema_diff'] < 0, 'sig_ema'] = -1
|
||||
|
||||
# --- MACD ---
|
||||
out['sig_macd'] = 0
|
||||
out.loc[out['macd_hist'] > 0, 'sig_macd'] = 1
|
||||
out.loc[out['macd_hist'] < 0, 'sig_macd'] = -1
|
||||
|
||||
# --- ADX + DI ---
|
||||
adx_thresh = params.get('adx_threshold', 25)
|
||||
out['sig_adx'] = 0
|
||||
out.loc[(out['adx'] > adx_thresh) & (out['di_diff'] > 0), 'sig_adx'] = 1
|
||||
out.loc[(out['adx'] > adx_thresh) & (out['di_diff'] < 0), 'sig_adx'] = -1
|
||||
|
||||
# --- Supertrend ---
|
||||
out['sig_st'] = out['st_dir']
|
||||
|
||||
# --- RSI ---
|
||||
rsi_ob = params.get('rsi_overbought', 70)
|
||||
rsi_os = params.get('rsi_oversold', 30)
|
||||
out['sig_rsi'] = 0
|
||||
out.loc[out['rsi'] < rsi_os, 'sig_rsi'] = 1
|
||||
out.loc[out['rsi'] > rsi_ob, 'sig_rsi'] = -1
|
||||
|
||||
# --- Stochastic ---
|
||||
stoch_ob = params.get('stoch_overbought', 80)
|
||||
stoch_os = params.get('stoch_oversold', 20)
|
||||
out['sig_stoch'] = 0
|
||||
out.loc[(out['stoch_k'] < stoch_os) & (out['stoch_k'] > out['stoch_d']), 'sig_stoch'] = 1
|
||||
out.loc[(out['stoch_k'] > stoch_ob) & (out['stoch_k'] < out['stoch_d']), 'sig_stoch'] = -1
|
||||
|
||||
# --- CCI ---
|
||||
cci_ob = params.get('cci_overbought', 100)
|
||||
cci_os = params.get('cci_oversold', -100)
|
||||
out['sig_cci'] = 0
|
||||
out.loc[out['cci'] < cci_os, 'sig_cci'] = 1
|
||||
out.loc[out['cci'] > cci_ob, 'sig_cci'] = -1
|
||||
|
||||
# --- Williams %R ---
|
||||
wr_ob = params.get('wr_overbought', -20)
|
||||
wr_os = params.get('wr_oversold', -80)
|
||||
out['sig_wr'] = 0
|
||||
out.loc[out['wr'] < wr_os, 'sig_wr'] = 1
|
||||
out.loc[out['wr'] > wr_ob, 'sig_wr'] = -1
|
||||
|
||||
# --- WMA ---
|
||||
out['sig_wma'] = 0
|
||||
out.loc[out['wma_diff'] > 0, 'sig_wma'] = 1
|
||||
out.loc[out['wma_diff'] < 0, 'sig_wma'] = -1
|
||||
|
||||
return out
|
||||
|
||||
|
||||
SIGNAL_COLS = [
|
||||
'sig_bb', 'sig_kc', 'sig_dc', 'sig_ema', 'sig_macd',
|
||||
'sig_adx', 'sig_st', 'sig_rsi', 'sig_stoch', 'sig_cci',
|
||||
'sig_wr', 'sig_wma',
|
||||
]
|
||||
|
||||
WEIGHT_KEYS = [
|
||||
'w_bb', 'w_kc', 'w_dc', 'w_ema', 'w_macd',
|
||||
'w_adx', 'w_st', 'w_rsi', 'w_stoch', 'w_cci',
|
||||
'w_wr', 'w_wma',
|
||||
]
|
||||
|
||||
|
||||
def compute_composite_score(df: pd.DataFrame, params: dict) -> pd.Series:
|
||||
"""
|
||||
加权投票计算综合得分 (-1 ~ +1)
|
||||
"""
|
||||
weights = np.array([params.get(k, 1.0) for k in WEIGHT_KEYS])
|
||||
total_w = weights.sum()
|
||||
if total_w == 0:
|
||||
total_w = 1.0
|
||||
|
||||
signals = df[SIGNAL_COLS].values # (N, 12)
|
||||
score = (signals * weights).sum(axis=1) / total_w
|
||||
return pd.Series(score, index=df.index, name='score')
|
||||
|
||||
|
||||
def apply_htf_filter(score: pd.Series, htf_df: pd.DataFrame, params: dict) -> pd.Series:
|
||||
"""
|
||||
用高时间框架（如1h）的趋势方向过滤信号
|
||||
htf_df 需要包含 'ema_diff' 列
|
||||
只允许与大趋势同向的信号通过
|
||||
"""
|
||||
# 将 htf 的 ema_diff reindex 到主时间框架
|
||||
htf_trend = htf_df['ema_diff'].reindex(score.index, method='ffill')
|
||||
filtered = score.copy()
|
||||
# 大趋势向上时，屏蔽做空信号
|
||||
filtered.loc[(htf_trend > 0) & (filtered < 0)] = 0
|
||||
# 大趋势向下时，屏蔽做多信号
|
||||
filtered.loc[(htf_trend < 0) & (filtered > 0)] = 0
|
||||
return filtered
|
||||
@@ -1,226 +0,0 @@
|
||||
"""
|
||||
Optuna 训练入口 - 在 2020-2022 数据上搜索最优参数
|
||||
"""
|
||||
import json
|
||||
import sys
|
||||
import os
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
import optuna
|
||||
from optuna.samplers import TPESampler
|
||||
import numpy as np
|
||||
|
||||
from strategy.data_loader import load_klines
|
||||
from strategy.indicators import compute_all_indicators
|
||||
from strategy.strategy_signal import (
|
||||
generate_indicator_signals, compute_composite_score,
|
||||
apply_htf_filter, WEIGHT_KEYS,
|
||||
)
|
||||
from strategy.backtest_engine import BacktestEngine
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 全局加载数据 (只加载一次)
|
||||
# ============================================================
|
||||
print("正在加载 2020-2022 训练数据...")
|
||||
DF_5M = load_klines('5m', '2020-01-01', '2023-01-01')
|
||||
DF_1H = load_klines('1h', '2020-01-01', '2023-01-01')
|
||||
print(f" 5m: {len(DF_5M)} 条, 1h: {len(DF_1H)} 条")
|
||||
print("数据加载完成。\n")
|
||||
|
||||
|
||||
def build_params(trial: optuna.Trial) -> dict:
|
||||
"""从 Optuna trial 构建完整参数字典"""
|
||||
p = {}
|
||||
|
||||
# --- 指标参数 ---
|
||||
p['bb_period'] = trial.suggest_int('bb_period', 10, 50)
|
||||
p['bb_std'] = trial.suggest_float('bb_std', 1.0, 3.5, step=0.1)
|
||||
|
||||
p['kc_period'] = trial.suggest_int('kc_period', 10, 50)
|
||||
p['kc_mult'] = trial.suggest_float('kc_mult', 0.5, 3.0, step=0.1)
|
||||
|
||||
p['dc_period'] = trial.suggest_int('dc_period', 10, 50)
|
||||
|
||||
p['ema_fast'] = trial.suggest_int('ema_fast', 3, 20)
|
||||
p['ema_slow'] = trial.suggest_int('ema_slow', 15, 60)
|
||||
|
||||
p['macd_fast'] = trial.suggest_int('macd_fast', 6, 20)
|
||||
p['macd_slow'] = trial.suggest_int('macd_slow', 18, 40)
|
||||
p['macd_signal'] = trial.suggest_int('macd_signal', 5, 15)
|
||||
|
||||
p['adx_period'] = trial.suggest_int('adx_period', 7, 30)
|
||||
|
||||
p['st_period'] = trial.suggest_int('st_period', 5, 20)
|
||||
p['st_mult'] = trial.suggest_float('st_mult', 1.0, 5.0, step=0.1)
|
||||
|
||||
p['rsi_period'] = trial.suggest_int('rsi_period', 7, 28)
|
||||
|
||||
p['stoch_k'] = trial.suggest_int('stoch_k', 5, 21)
|
||||
p['stoch_d'] = trial.suggest_int('stoch_d', 2, 7)
|
||||
p['stoch_smooth'] = trial.suggest_int('stoch_smooth', 2, 7)
|
||||
|
||||
p['cci_period'] = trial.suggest_int('cci_period', 10, 40)
|
||||
|
||||
p['wr_period'] = trial.suggest_int('wr_period', 7, 28)
|
||||
|
||||
p['wma_period'] = trial.suggest_int('wma_period', 10, 50)
|
||||
|
||||
# --- 信号阈值参数 ---
|
||||
p['bb_oversold'] = trial.suggest_float('bb_oversold', -0.3, 0.3, step=0.05)
|
||||
p['bb_overbought'] = trial.suggest_float('bb_overbought', 0.7, 1.3, step=0.05)
|
||||
p['kc_oversold'] = trial.suggest_float('kc_oversold', -0.3, 0.3, step=0.05)
|
||||
p['kc_overbought'] = trial.suggest_float('kc_overbought', 0.7, 1.3, step=0.05)
|
||||
p['dc_oversold'] = trial.suggest_float('dc_oversold', 0.0, 0.3, step=0.05)
|
||||
p['dc_overbought'] = trial.suggest_float('dc_overbought', 0.7, 1.0, step=0.05)
|
||||
p['adx_threshold'] = trial.suggest_float('adx_threshold', 15, 35, step=1)
|
||||
p['rsi_overbought'] = trial.suggest_float('rsi_overbought', 60, 85, step=1)
|
||||
p['rsi_oversold'] = trial.suggest_float('rsi_oversold', 15, 40, step=1)
|
||||
p['stoch_overbought'] = trial.suggest_float('stoch_overbought', 70, 90, step=1)
|
||||
p['stoch_oversold'] = trial.suggest_float('stoch_oversold', 10, 30, step=1)
|
||||
p['cci_overbought'] = trial.suggest_float('cci_overbought', 80, 200, step=5)
|
||||
p['cci_oversold'] = trial.suggest_float('cci_oversold', -200, -80, step=5)
|
||||
p['wr_overbought'] = trial.suggest_float('wr_overbought', -30, -10, step=1)
|
||||
p['wr_oversold'] = trial.suggest_float('wr_oversold', -90, -70, step=1)
|
||||
|
||||
# --- 权重 ---
|
||||
for wk in WEIGHT_KEYS:
|
||||
p[wk] = trial.suggest_float(wk, 0.0, 1.0, step=0.05)
|
||||
|
||||
# --- 回测参数 ---
|
||||
p['open_threshold'] = trial.suggest_float('open_threshold', 0.1, 0.6, step=0.02)
|
||||
p['max_positions'] = trial.suggest_int('max_positions', 1, 3)
|
||||
p['take_profit_pct'] = trial.suggest_float('take_profit_pct', 0.003, 0.025, step=0.001)
|
||||
|
||||
# 止损约束: N单同时止损 + 手续费 <= 50U
|
||||
# N * 1250 * sl_pct + N * 1.25 <= 50
|
||||
# sl_pct <= (50 - N*1.25) / (N*1250)
|
||||
n = p['max_positions']
|
||||
max_sl = (50.0 - n * 1.25) / (n * 1250.0)
|
||||
max_sl = round(max(max_sl, 0.002), 3) # 至少 0.2%
|
||||
p['stop_loss_pct'] = trial.suggest_float('stop_loss_pct', 0.002, max_sl, step=0.001)
|
||||
|
||||
return p
|
||||
|
||||
|
||||
def objective(trial: optuna.Trial) -> float:
|
||||
params = build_params(trial)
|
||||
|
||||
# 确保 ema_slow > ema_fast, macd_slow > macd_fast
|
||||
if params['ema_slow'] <= params['ema_fast']:
|
||||
return -1e6
|
||||
if params['macd_slow'] <= params['macd_fast']:
|
||||
return -1e6
|
||||
|
||||
try:
|
||||
# 计算指标
|
||||
df_5m = compute_all_indicators(DF_5M, params)
|
||||
df_1h = compute_all_indicators(DF_1H, params)
|
||||
|
||||
# 生成信号
|
||||
df_5m = generate_indicator_signals(df_5m, params)
|
||||
df_1h = generate_indicator_signals(df_1h, params)
|
||||
|
||||
# 综合得分
|
||||
score = compute_composite_score(df_5m, params)
|
||||
|
||||
# 高时间框架过滤
|
||||
score = apply_htf_filter(score, df_1h, params)
|
||||
|
||||
# 回测
|
||||
engine = BacktestEngine(
|
||||
initial_capital=1000.0,
|
||||
margin_per_trade=25.0,
|
||||
leverage=50,
|
||||
fee_rate=0.0005,
|
||||
rebate_ratio=0.70,
|
||||
max_daily_drawdown=50.0,
|
||||
min_hold_bars=1,
|
||||
stop_loss_pct=params['stop_loss_pct'],
|
||||
take_profit_pct=params['take_profit_pct'],
|
||||
max_positions=params['max_positions'],
|
||||
)
|
||||
|
||||
result = engine.run(df_5m, score, open_threshold=params['open_threshold'])
|
||||
|
||||
num_trades = result['num_trades']
|
||||
if num_trades < 50:
|
||||
return -1e6 # 交易次数太少，不可靠
|
||||
|
||||
total_pnl = result['total_pnl']
|
||||
max_dd = result['max_daily_dd'] # 负数 (引擎已保证 >= -50)
|
||||
avg_daily = result['avg_daily_pnl']
|
||||
|
||||
# 引擎内部已经有每日 50U 回撤熔断，这里不再硬约束
|
||||
# 目标: 最大化总收益
|
||||
score_val = total_pnl
|
||||
|
||||
# 奖励日均收益高的方案
|
||||
if avg_daily >= 50:
|
||||
score_val *= 1.3
|
||||
elif avg_daily >= 30:
|
||||
score_val *= 1.15
|
||||
|
||||
trial.set_user_attr('total_pnl', total_pnl)
|
||||
trial.set_user_attr('num_trades', num_trades)
|
||||
trial.set_user_attr('win_rate', result['win_rate'])
|
||||
trial.set_user_attr('max_daily_dd', max_dd)
|
||||
trial.set_user_attr('avg_daily_pnl', avg_daily)
|
||||
trial.set_user_attr('profit_factor', result['profit_factor'])
|
||||
|
||||
return score_val
|
||||
|
||||
except Exception as e:
|
||||
print(f"Trial {trial.number} 异常: {e}")
|
||||
return -1e6
|
||||
|
||||
|
||||
def main():
|
||||
study = optuna.create_study(
|
||||
direction='maximize',
|
||||
sampler=TPESampler(seed=42, n_startup_trials=30),
|
||||
study_name='eth_strategy_v1',
|
||||
)
|
||||
|
||||
# 设置日志级别
|
||||
optuna.logging.set_verbosity(optuna.logging.WARNING)
|
||||
|
||||
n_trials = 1000
|
||||
print(f"开始 Optuna 优化, 共 {n_trials} 次试验 (多单并发版)...")
|
||||
print("=" * 60)
|
||||
|
||||
def callback(study, trial):
|
||||
if trial.number % 10 == 0:
|
||||
best = study.best_trial
|
||||
print(f"[Trial {trial.number:>4d}] "
|
||||
f"当前值={trial.value:.2f} | "
|
||||
f"最佳值={best.value:.2f} | "
|
||||
f"PnL={best.user_attrs.get('total_pnl', 0):.1f}U | "
|
||||
f"胜率={best.user_attrs.get('win_rate', 0):.1%} | "
|
||||
f"日均={best.user_attrs.get('avg_daily_pnl', 0):.1f}U | "
|
||||
f"最大日回撤={best.user_attrs.get('max_daily_dd', 0):.1f}U")
|
||||
|
||||
study.optimize(objective, n_trials=n_trials, callbacks=[callback], show_progress_bar=True)
|
||||
|
||||
# 输出最佳结果
|
||||
best = study.best_trial
|
||||
print("\n" + "=" * 60)
|
||||
print("训练完成！最佳参数:")
|
||||
print("=" * 60)
|
||||
print(f" 目标值: {best.value:.4f}")
|
||||
print(f" 总收益: {best.user_attrs.get('total_pnl', 0):.2f}U")
|
||||
print(f" 交易次数: {best.user_attrs.get('num_trades', 0)}")
|
||||
print(f" 胜率: {best.user_attrs.get('win_rate', 0):.2%}")
|
||||
print(f" 日均收益: {best.user_attrs.get('avg_daily_pnl', 0):.2f}U")
|
||||
print(f" 最大日回撤: {best.user_attrs.get('max_daily_dd', 0):.2f}U")
|
||||
print(f" 盈亏比: {best.user_attrs.get('profit_factor', 0):.2f}")
|
||||
|
||||
# 保存最佳参数
|
||||
output_path = os.path.join(os.path.dirname(__file__), 'best_params_2020_2022.json')
|
||||
with open(output_path, 'w') as f:
|
||||
json.dump(best.params, f, indent=2, ensure_ascii=False)
|
||||
print(f"\n最佳参数已保存到: {output_path}")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
38
test.py
Normal file
38
test.py
Normal file
@@ -0,0 +1,38 @@
|
||||
import subprocess
|
||||
import time
|
||||
from wxautox4 import WeChat
|
||||
|
||||
def make_wechat_call(contact_name, retry_times=3):
|
||||
"""
|
||||
可靠的微信拨电话方法
|
||||
|
||||
Args:
|
||||
contact_name: 联系人名称
|
||||
retry_times: 重试次数
|
||||
"""
|
||||
for attempt in range(retry_times):
|
||||
try:
|
||||
# 打开微信应用
|
||||
subprocess.Popen(['/Applications/WeChat.app/Contents/MacOS/WeChat'])
|
||||
time.sleep(2) # 等待微信启动
|
||||
|
||||
# 初始化
|
||||
wx = WeChat()
|
||||
time.sleep(1)
|
||||
|
||||
# 切换聊天
|
||||
wx.ChatWith(contact_name)
|
||||
time.sleep(1)
|
||||
|
||||
print(f"✓ 已切换到 {contact_name} 聊天")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠ 第 {attempt+1} 次尝试失败: {e}")
|
||||
if attempt < retry_times - 1:
|
||||
time.sleep(1)
|
||||
|
||||
return False
|
||||
|
||||
# 使用
|
||||
make_wechat_call('Rainbow')
|
||||
1
token.json
Normal file
1
token.json
Normal file
@@ -0,0 +1 @@
|
||||
{"token": "ya29.a0ATkoCc7EYaXMumpShCwmfiq5pqSbgMB_XkUuWWUFnYRs8fvfPt6xYaU3r8rrdiFWHpQ_07R2FN_ML4X-4Q9eoHp5Dj6R0xgL1A9xFONvaJhlEP_ndce3Uht6LpeIUhfoGw2fHU9ZlvKcVNyCfcGsTqsR8YXWoe49MmU3k-DiHQgIDrxZ0c7Kyfb0FltZ9bUwXJg8ILIaCgYKAYUSARMSFQHGX2MiD7gOuz1kuvvNQABqx39YNw0206", "refresh_token": "1//0gVVN8c-x-T1MCgYIARAAGBASNwF-L9IrNPuDnHu-3vZoJvPChjsyjrUwtlSX7qmY_xnwFUr0FPf-t7Tm53f3vSo4OZOaJWSqA0s", "token_uri": "https://oauth2.googleapis.com/token", "client_id": "823839778551-mgovppr13aoil1r69upj7uiv84ej0sih.apps.googleusercontent.com", "client_secret": "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", "scopes": ["https://www.googleapis.com/auth/gmail.readonly"], "universe_domain": "googleapis.com", "account": "", "expiry": "2026-02-28T19:35:00Z"}
|
||||
686
四分之一，五分钟，反手条件充足.py
Normal file
686
四分之一，五分钟，反手条件充足.py
Normal file
@@ -0,0 +1,686 @@
|
||||
import time
|
||||
|
||||
from tqdm import tqdm
|
||||
from loguru import logger
|
||||
from bit_tools import openBrowser
|
||||
from DrissionPage import ChromiumPage
|
||||
from DrissionPage import ChromiumOptions
|
||||
|
||||
from bitmart.api_contract import APIContract
|
||||
|
||||
|
||||
class BitmartFuturesTransaction:
|
||||
def __init__(self, bit_id):
|
||||
|
||||
self.page: ChromiumPage | None = None
|
||||
|
||||
self.api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8"
|
||||
self.secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5"
|
||||
self.memo = "合约交易"
|
||||
|
||||
self.contract_symbol = "ETHUSDT"
|
||||
|
||||
self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15))
|
||||
|
||||
self.start = 0 # 持仓状态: -1 空, 0 无, 1 多
|
||||
|
||||
self.pbar = tqdm(total=30, desc="等待K线", ncols=80) # 可选：用于长时间等待时展示进度
|
||||
|
||||
self.last_kline_time = None # 上一次处理的K线时间戳，用于判断是否是新K线
|
||||
|
||||
# 反手频率控制
|
||||
self.reverse_cooldown_seconds = 1.5 * 60 # 反手冷却时间（秒）
|
||||
self.reverse_min_move_pct = 0.05 # 反手最小价差过滤（百分比）
|
||||
self.last_reverse_time = None # 上次反手时间
|
||||
|
||||
# 开仓频率控制
|
||||
self.open_cooldown_seconds = 60 # 开仓冷却时间（秒），两次开仓至少间隔此时长
|
||||
self.last_open_time = None # 上次开仓时间
|
||||
self.last_open_kline_id = None # 上次开仓所在 K 线 id，同一根 K 线只允许开仓一次
|
||||
|
||||
self.leverage = "100" # 高杠杆（全仓模式下可开更大仓位）
|
||||
self.open_type = "cross" # 全仓模式
|
||||
self.risk_percent = 0 # 未使用；若启用则可为每次开仓占可用余额的百分比
|
||||
self.take_profit_usd = 5 # 仓位盈利达到此金额（美元）时平仓止盈
|
||||
self.stop_loss_usd = -3 # 固定止损：亏损达到 3 美元平仓
|
||||
self.trailing_activation_usd = 2 # 盈利达到此金额后启动移动止损
|
||||
self.trailing_distance_usd = 1.5 # 从最高盈利回撤此金额则平仓
|
||||
self.max_unrealized_pnl_seen = None # 持仓期间见过的最大盈利（用于移动止损）
|
||||
|
||||
self.open_avg_price = None # 开仓价格
|
||||
self.current_amount = None # 持仓量
|
||||
|
||||
self.bit_id = bit_id
|
||||
self.default_order_size = 25 # 开仓/反手张数，统一在此修改
|
||||
|
||||
# 策略相关变量
|
||||
self.prev_kline = None # 上一根K线
|
||||
self.current_kline = None # 当前K线
|
||||
self.prev_entity = None # 上一根K线实体大小
|
||||
self.current_open = None # 当前K线开盘价
|
||||
|
||||
def get_klines(self):
|
||||
"""获取最近2根K线（当前K线和上一根K线）"""
|
||||
try:
|
||||
end_time = int(time.time())
|
||||
# 获取足够多的条目确保有最新的K线
|
||||
response = self.contractAPI.get_kline(
|
||||
contract_symbol=self.contract_symbol,
|
||||
step=5, # 5分钟
|
||||
start_time=end_time - 3600 * 3, # 取最近3小时
|
||||
end_time=end_time
|
||||
)[0]["data"]
|
||||
|
||||
# 每根: [timestamp, open, high, low, close, volume]
|
||||
formatted = []
|
||||
for k in response:
|
||||
formatted.append({
|
||||
'id': int(k["timestamp"]),
|
||||
'open': float(k["open_price"]),
|
||||
'high': float(k["high_price"]),
|
||||
'low': float(k["low_price"]),
|
||||
'close': float(k["close_price"])
|
||||
})
|
||||
formatted.sort(key=lambda x: x['id'])
|
||||
|
||||
# 返回最近2根K线：倒数第二根（上一根）和最后一根（当前）
|
||||
if len(formatted) >= 2:
|
||||
return formatted[-2], formatted[-1]
|
||||
return None, None
|
||||
except Exception as e:
|
||||
logger.error(f"获取K线异常: {e}")
|
||||
self.ding(text="获取K线异常", error=True)
|
||||
return None, None
|
||||
|
||||
def get_current_price(self):
|
||||
"""获取当前最新价格"""
|
||||
try:
|
||||
end_time = int(time.time())
|
||||
response = self.contractAPI.get_kline(
|
||||
contract_symbol=self.contract_symbol,
|
||||
step=1, # 1分钟
|
||||
start_time=end_time - 3600 * 1, # 取最近1小时
|
||||
end_time=end_time
|
||||
)[0]
|
||||
if response['code'] == 1000:
|
||||
return float(response['data'][-1]["close_price"])
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"获取价格异常: {e}")
|
||||
return None
|
||||
|
||||
def get_available_balance(self):
|
||||
"""获取合约账户可用USDT余额"""
|
||||
try:
|
||||
response = self.contractAPI.get_assets_detail()[0]
|
||||
if response['code'] == 1000:
|
||||
data = response['data']
|
||||
if isinstance(data, dict):
|
||||
return float(data.get('available_balance', 0))
|
||||
elif isinstance(data, list):
|
||||
for asset in data:
|
||||
if asset.get('currency') == 'USDT':
|
||||
return float(asset.get('available_balance', 0))
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"余额查询异常: {e}")
|
||||
return None
|
||||
|
||||
def get_position_status(self):
|
||||
"""获取当前持仓方向"""
|
||||
try:
|
||||
response = self.contractAPI.get_position(contract_symbol=self.contract_symbol)[0]
|
||||
if response['code'] == 1000:
|
||||
positions = response['data']
|
||||
if not positions:
|
||||
self.start = 0
|
||||
self.open_avg_price = None
|
||||
self.current_amount = None
|
||||
self.unrealized_pnl = None
|
||||
return True
|
||||
pos = positions[0]
|
||||
self.start = 1 if pos['position_type'] == 1 else -1
|
||||
self.open_avg_price = float(pos['open_avg_price'])
|
||||
self.current_amount = float(pos['current_amount'])
|
||||
self.position_cross = pos["position_cross"]
|
||||
# 直接从API获取未实现盈亏（Bitmart返回的是 unrealized_value 字段）
|
||||
self.unrealized_pnl = float(pos.get('unrealized_value', 0))
|
||||
logger.debug(f"持仓详情: 方向={self.start}, 开仓均价={self.open_avg_price}, "
|
||||
f"持仓量={self.current_amount}, 未实现盈亏={self.unrealized_pnl:.2f}")
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"持仓查询异常: {e}")
|
||||
return False
|
||||
|
||||
def get_unrealized_pnl_usd(self):
|
||||
"""
|
||||
获取当前持仓未实现盈亏（美元），直接使用API返回值
|
||||
"""
|
||||
if self.start == 0 or self.unrealized_pnl is None:
|
||||
return None
|
||||
return self.unrealized_pnl
|
||||
|
||||
def set_leverage(self):
|
||||
"""程序启动时设置全仓 + 高杠杆"""
|
||||
try:
|
||||
response = self.contractAPI.post_submit_leverage(
|
||||
contract_symbol=self.contract_symbol,
|
||||
leverage=self.leverage,
|
||||
open_type=self.open_type
|
||||
)[0]
|
||||
if response['code'] == 1000:
|
||||
logger.success(f"全仓模式 + {self.leverage}x 杠杆设置成功")
|
||||
return True
|
||||
else:
|
||||
logger.error(f"杠杆设置失败: {response}")
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"设置杠杆异常: {e}")
|
||||
return False
|
||||
|
||||
def openBrowser(self):
|
||||
"""打开 TGE 对应浏览器实例"""
|
||||
try:
|
||||
bit_port = openBrowser(id=self.bit_id)
|
||||
co = ChromiumOptions()
|
||||
co.set_local_port(port=bit_port)
|
||||
self.page = ChromiumPage(addr_or_opts=co)
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
def click_safe(self, xpath, sleep=0.5):
|
||||
"""安全点击"""
|
||||
try:
|
||||
ele = self.page.ele(xpath)
|
||||
if not ele:
|
||||
return False
|
||||
# ele.scroll.to_see(center=True)
|
||||
# time.sleep(sleep)
|
||||
ele.click(by_js=True)
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
def 平仓(self):
|
||||
"""平仓操作"""
|
||||
self.click_safe('x://span[normalize-space(text()) ="市价"]')
|
||||
|
||||
def 开单(self, marketPriceLongOrder=0, limitPriceShortOrder=0, size=None, price=None):
|
||||
"""
|
||||
marketPriceLongOrder 市价做多或者做空，1是做多，-1是做空
|
||||
limitPriceShortOrder 限价做多或者做空
|
||||
"""
|
||||
if marketPriceLongOrder == -1:
|
||||
# self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
# self.page.ele('x://*[@id="size_0"]').input(vals=size, clear=True)
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
elif marketPriceLongOrder == 1:
|
||||
# self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
# self.page.ele('x://*[@id="size_0"]').input(vals=size, clear=True)
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
|
||||
if limitPriceShortOrder == -1:
|
||||
self.click_safe('x://button[normalize-space(text()) ="限价"]')
|
||||
self.page.ele('x://*[@id="price_0"]').input(vals=price, clear=True)
|
||||
time.sleep(1)
|
||||
self.page.ele('x://*[@id="size_0"]').input(1)
|
||||
self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
|
||||
elif limitPriceShortOrder == 1:
|
||||
self.click_safe('x://button[normalize-space(text()) ="限价"]')
|
||||
self.page.ele('x://*[@id="price_0"]').input(vals=price, clear=True)
|
||||
time.sleep(1)
|
||||
self.page.ele('x://*[@id="size_0"]').input(1)
|
||||
self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
|
||||
|
||||
def ding(self, text, error=False):
|
||||
"""日志通知"""
|
||||
if error:
|
||||
logger.error(text)
|
||||
else:
|
||||
logger.info(text)
|
||||
|
||||
def calculate_entity(self, kline):
|
||||
"""计算K线实体大小（绝对值）"""
|
||||
return abs(kline['close'] - kline['open'])
|
||||
|
||||
def calculate_upper_shadow(self, kline):
|
||||
"""计算上阴线（上影线）涨幅百分比"""
|
||||
# 上阴线 = (最高价 - max(开盘价, 收盘价)) / max(开盘价, 收盘价)
|
||||
body_top = max(kline['open'], kline['close'])
|
||||
if body_top == 0:
|
||||
return 0
|
||||
return (kline['high'] - body_top) / body_top * 100
|
||||
|
||||
def calculate_lower_shadow(self, kline):
|
||||
"""计算下阴线（下影线）跌幅百分比"""
|
||||
# 下阴线 = (min(开盘价, 收盘价) - 最低价) / min(开盘价, 收盘价)
|
||||
body_bottom = min(kline['open'], kline['close'])
|
||||
if body_bottom == 0:
|
||||
return 0
|
||||
return (body_bottom - kline['low']) / body_bottom * 100
|
||||
|
||||
def get_entity_edge(self, kline):
|
||||
"""获取K线实体边（收盘价或开盘价，取决于是阳线还是阴线）"""
|
||||
# 阳线（收盘>开盘）：实体上边=收盘价，实体下边=开盘价
|
||||
# 阴线（收盘<开盘）：实体上边=开盘价，实体下边=收盘价
|
||||
return {
|
||||
'upper': max(kline['open'], kline['close']), # 实体上边
|
||||
'lower': min(kline['open'], kline['close']) # 实体下边
|
||||
}
|
||||
|
||||
def check_signal(self, current_price, prev_kline, current_kline):
|
||||
"""
|
||||
检查交易信号
|
||||
返回: ('long', trigger_price) / ('short', trigger_price) / None
|
||||
"""
|
||||
# 计算上一根K线实体
|
||||
prev_entity = self.calculate_entity(prev_kline)
|
||||
|
||||
# 实体过小不交易（实体 < 0.1）
|
||||
if prev_entity < 0.1:
|
||||
logger.info(f"上一根K线实体过小: {prev_entity:.4f}，跳过信号检测")
|
||||
return None
|
||||
|
||||
# 获取上一根K线的实体上下边
|
||||
prev_entity_edge = self.get_entity_edge(prev_kline)
|
||||
prev_entity_upper = prev_entity_edge['upper'] # 实体上边
|
||||
prev_entity_lower = prev_entity_edge['lower'] # 实体下边
|
||||
|
||||
# 优化：以下两种情况以当前这根的开盘价作为计算基准
|
||||
# 1) 上一根阳线 且 当前开盘价 > 上一根收盘价（跳空高开）
|
||||
# 2) 上一根阴线 且 当前开盘价 < 上一根收盘价（跳空低开）
|
||||
prev_is_bullish_for_calc = prev_kline['close'] > prev_kline['open']
|
||||
prev_is_bearish_for_calc = prev_kline['close'] < prev_kline['open']
|
||||
current_open_above_prev_close = current_kline['open'] > prev_kline['close']
|
||||
current_open_below_prev_close = current_kline['open'] < prev_kline['close']
|
||||
use_current_open_as_base = (prev_is_bullish_for_calc and current_open_above_prev_close) or (prev_is_bearish_for_calc and current_open_below_prev_close)
|
||||
|
||||
if use_current_open_as_base:
|
||||
# 以当前K线开盘价为基准计算（跳空时用当前开盘价参与计算）
|
||||
calc_lower = current_kline['open']
|
||||
calc_upper = current_kline['open'] # 同一基准，上下四分之一对称
|
||||
long_trigger = calc_lower + prev_entity / 4
|
||||
short_trigger = calc_upper - prev_entity / 4
|
||||
long_breakout = calc_upper + prev_entity / 4
|
||||
short_breakout = calc_lower - prev_entity / 4
|
||||
else:
|
||||
# 原有计算方式
|
||||
long_trigger = prev_entity_lower + prev_entity / 4 # 做多触发价 = 实体下边 + 实体/4（下四分之一处）
|
||||
short_trigger = prev_entity_upper - prev_entity / 4 # 做空触发价 = 实体上边 - 实体/4（上四分之一处）
|
||||
long_breakout = prev_entity_upper + prev_entity / 4 # 做多突破价 = 实体上边 + 实体/4
|
||||
short_breakout = prev_entity_lower - prev_entity / 4 # 做空突破价 = 实体下边 - 实体/4
|
||||
|
||||
# 上一根阴线 + 当前阳线：做多形态，不按上一根K线上三分之一做空
|
||||
prev_is_bearish = prev_kline['close'] < prev_kline['open']
|
||||
current_is_bullish = current_kline['close'] > current_kline['open']
|
||||
skip_short_by_upper_third = prev_is_bearish and current_is_bullish
|
||||
# 上一根阳线 + 当前阴线：做空形态，不按上一根K线下三分之一做多
|
||||
prev_is_bullish = prev_kline['close'] > prev_kline['open']
|
||||
current_is_bearish = current_kline['close'] < current_kline['open']
|
||||
skip_long_by_lower_third = prev_is_bullish and current_is_bearish
|
||||
|
||||
if use_current_open_as_base:
|
||||
if prev_is_bullish_for_calc and current_open_above_prev_close:
|
||||
logger.info(f"上一根阳线且当前开盘价({current_kline['open']:.2f})>上一根收盘价({prev_kline['close']:.2f})，以当前开盘价为基准计算")
|
||||
else:
|
||||
logger.info(f"上一根阴线且当前开盘价({current_kline['open']:.2f})<上一根收盘价({prev_kline['close']:.2f})，以当前开盘价为基准计算")
|
||||
logger.info(f"当前价格: {current_price:.2f}, 上一根实体: {prev_entity:.4f}")
|
||||
logger.info(f"上一根实体上边: {prev_entity_upper:.2f}, 下边: {prev_entity_lower:.2f}")
|
||||
logger.info(f"做多触发价(下1/4): {long_trigger:.2f}, 做空触发价(上1/4): {short_trigger:.2f}")
|
||||
logger.info(f"突破做多价(上1/4外): {long_breakout:.2f}, 突破做空价(下1/4外): {short_breakout:.2f}")
|
||||
if skip_short_by_upper_third:
|
||||
logger.info("上一根阴线+当前阳线(做多形态)，不按上四分之一做空")
|
||||
if skip_long_by_lower_third:
|
||||
logger.info("上一根阳线+当前阴线(做空形态)，不按下四分之一做多")
|
||||
|
||||
# 无持仓时检查开仓信号
|
||||
if self.start == 0:
|
||||
if current_price >= long_breakout and not skip_long_by_lower_third:
|
||||
logger.info(f"触发做多信号！价格 {current_price:.2f} >= 突破价(上1/4外) {long_breakout:.2f}")
|
||||
return ('long', long_breakout)
|
||||
elif current_price <= short_breakout and not skip_short_by_upper_third:
|
||||
logger.info(f"触发做空信号！价格 {current_price:.2f} <= 突破价(下1/4外) {short_breakout:.2f}")
|
||||
return ('short', short_breakout)
|
||||
|
||||
# 持仓时检查反手信号
|
||||
elif self.start == 1: # 持多仓
|
||||
# 反手条件1: 价格跌到上一根K线的上三分之一处（做空触发价）；上一根阴线+当前阳线做多时跳过
|
||||
if current_price <= short_trigger and not skip_short_by_upper_third:
|
||||
logger.info(f"持多反手做空！价格 {current_price:.2f} <= 触发价(上1/4) {short_trigger:.2f}")
|
||||
return ('reverse_short', short_trigger)
|
||||
|
||||
# 反手条件2: 上一根K线上阴线涨幅>0.01%，当前跌到上一根实体下边
|
||||
upper_shadow_pct = self.calculate_upper_shadow(prev_kline)
|
||||
if upper_shadow_pct > 0.01 and current_price <= prev_entity_lower:
|
||||
logger.info(f"持多反手做空！上阴线涨幅 {upper_shadow_pct:.4f}% > 0.01%，"
|
||||
f"价格 {current_price:.2f} <= 实体下边 {prev_entity_lower:.2f}")
|
||||
return ('reverse_short', prev_entity_lower)
|
||||
|
||||
elif self.start == -1: # 持空仓
|
||||
# 反手条件1: 价格涨到上一根K线的下三分之一处（做多触发价）；上一根阳线+当前阴线做空时跳过
|
||||
if current_price >= long_trigger and not skip_long_by_lower_third:
|
||||
logger.info(f"持空反手做多！价格 {current_price:.2f} >= 触发价(下1/4) {long_trigger:.2f}")
|
||||
return ('reverse_long', long_trigger)
|
||||
|
||||
# 反手条件2: 上一根K线下阴线跌幅>0.01%，当前涨到上一根实体上边
|
||||
lower_shadow_pct = self.calculate_lower_shadow(prev_kline)
|
||||
if lower_shadow_pct > 0.01 and current_price >= prev_entity_upper:
|
||||
logger.info(f"持空反手做多！下阴线跌幅 {lower_shadow_pct:.4f}% > 0.01%，"
|
||||
f"价格 {current_price:.2f} >= 实体上边 {prev_entity_upper:.2f}")
|
||||
return ('reverse_long', prev_entity_upper)
|
||||
|
||||
return None
|
||||
|
||||
def can_open(self, current_kline_id):
|
||||
"""开仓前过滤：同一根 K 线只开一次 + 开仓冷却时间。仅用于 long/short 新开仓。"""
|
||||
now = time.time()
|
||||
if self.last_open_kline_id is not None and self.last_open_kline_id == current_kline_id:
|
||||
logger.info(f"开仓频率控制：本 K 线({current_kline_id})已开过仓，跳过")
|
||||
return False
|
||||
if self.last_open_time is not None and now - self.last_open_time < self.open_cooldown_seconds:
|
||||
remain = self.open_cooldown_seconds - (now - self.last_open_time)
|
||||
logger.info(f"开仓冷却中，剩余 {remain:.0f} 秒")
|
||||
return False
|
||||
return True
|
||||
|
||||
def can_reverse(self, current_price, trigger_price):
|
||||
"""反手前过滤：冷却时间 + 最小价差"""
|
||||
now = time.time()
|
||||
if self.last_reverse_time and now - self.last_reverse_time < self.reverse_cooldown_seconds:
|
||||
remain = self.reverse_cooldown_seconds - (now - self.last_reverse_time)
|
||||
logger.info(f"反手冷却中，剩余 {remain:.0f} 秒")
|
||||
return False
|
||||
|
||||
if trigger_price and trigger_price > 0:
|
||||
move_pct = abs(current_price - trigger_price) / trigger_price * 100
|
||||
if move_pct < self.reverse_min_move_pct:
|
||||
logger.info(f"反手价差不足: {move_pct:.4f}% < {self.reverse_min_move_pct}%")
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
def verify_no_position(self, max_retries=5, retry_interval=3):
|
||||
"""
|
||||
验证当前无持仓
|
||||
返回: True 表示无持仓可以开仓，False 表示有持仓不能开仓
|
||||
"""
|
||||
for i in range(max_retries):
|
||||
if self.get_position_status():
|
||||
if self.start == 0:
|
||||
logger.info(f"确认无持仓，可以开仓")
|
||||
return True
|
||||
else:
|
||||
logger.warning(
|
||||
f"仍有持仓 (方向: {self.start})，等待 {retry_interval} 秒后重试 ({i + 1}/{max_retries})")
|
||||
time.sleep(retry_interval)
|
||||
else:
|
||||
logger.warning(f"查询持仓状态失败，等待 {retry_interval} 秒后重试 ({i + 1}/{max_retries})")
|
||||
time.sleep(retry_interval)
|
||||
|
||||
logger.error(f"经过 {max_retries} 次重试仍有持仓或查询失败，放弃开仓")
|
||||
return False
|
||||
|
||||
def verify_position_direction(self, expected_direction):
|
||||
"""
|
||||
验证当前持仓方向是否与预期一致
|
||||
expected_direction: 1 多仓, -1 空仓
|
||||
返回: True 表示持仓方向正确，False 表示不正确
|
||||
"""
|
||||
if self.get_position_status():
|
||||
if self.start == expected_direction:
|
||||
logger.info(f"持仓方向验证成功: {self.start}")
|
||||
return True
|
||||
else:
|
||||
logger.warning(f"持仓方向不符: 期望 {expected_direction}, 实际 {self.start}")
|
||||
return False
|
||||
else:
|
||||
logger.error("查询持仓状态失败")
|
||||
return False
|
||||
|
||||
def execute_trade(self, signal, size=None):
|
||||
"""执行交易。size 不传或为 None 时使用 default_order_size。"""
|
||||
signal_type, trigger_price = signal
|
||||
size = self.default_order_size if size is None else size
|
||||
|
||||
if signal_type == 'long':
|
||||
# 开多前先确认无持仓
|
||||
logger.info(f"准备开多，触发价: {trigger_price:.2f}")
|
||||
if not self.get_position_status():
|
||||
logger.error("开仓前查询持仓状态失败，放弃开仓")
|
||||
return False
|
||||
if self.start != 0:
|
||||
logger.warning(f"开多前发现已有持仓 (方向: {self.start})，放弃开仓避免双向持仓")
|
||||
return False
|
||||
|
||||
logger.info(f"确认无持仓，执行开多")
|
||||
self.开单(marketPriceLongOrder=1, size=size)
|
||||
time.sleep(3) # 等待订单执行
|
||||
|
||||
# 验证开仓是否成功
|
||||
if self.verify_position_direction(1):
|
||||
self.max_unrealized_pnl_seen = None # 新仓位重置移动止损记录
|
||||
self.last_open_time = time.time()
|
||||
self.last_open_kline_id = getattr(self, "_current_kline_id_for_open", None)
|
||||
logger.success("开多成功")
|
||||
return True
|
||||
else:
|
||||
logger.error("开多后持仓验证失败")
|
||||
return False
|
||||
|
||||
elif signal_type == 'short':
|
||||
# 开空前先确认无持仓
|
||||
logger.info(f"准备开空，触发价: {trigger_price:.2f}")
|
||||
if not self.get_position_status():
|
||||
logger.error("开仓前查询持仓状态失败，放弃开仓")
|
||||
return False
|
||||
if self.start != 0:
|
||||
logger.warning(f"开空前发现已有持仓 (方向: {self.start})，放弃开仓避免双向持仓")
|
||||
return False
|
||||
|
||||
logger.info(f"确认无持仓，执行开空")
|
||||
self.开单(marketPriceLongOrder=-1, size=size)
|
||||
time.sleep(3) # 等待订单执行
|
||||
|
||||
# 验证开仓是否成功
|
||||
if self.verify_position_direction(-1):
|
||||
self.max_unrealized_pnl_seen = None # 新仓位重置移动止损记录
|
||||
self.last_open_time = time.time()
|
||||
self.last_open_kline_id = getattr(self, "_current_kline_id_for_open", None)
|
||||
logger.success("开空成功")
|
||||
return True
|
||||
else:
|
||||
logger.error("开空后持仓验证失败")
|
||||
return False
|
||||
|
||||
elif signal_type == 'reverse_long':
|
||||
# 平空 + 开多（反手做多）：先平仓，确认无仓后再开多，避免双向持仓
|
||||
logger.info(f"执行反手做多，触发价: {trigger_price:.2f}")
|
||||
self.平仓()
|
||||
time.sleep(1) # 给交易所处理平仓的时间
|
||||
# 轮询确认已无持仓再开多（最多等约 10 秒）
|
||||
for _ in range(10):
|
||||
if self.get_position_status() and self.start == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.start != 0:
|
||||
logger.warning("反手做多：平仓后仍有持仓，放弃本次开多")
|
||||
return False
|
||||
logger.info("已确认无持仓，执行开多")
|
||||
self.开单(marketPriceLongOrder=1, size=size)
|
||||
time.sleep(3)
|
||||
|
||||
if self.verify_position_direction(1):
|
||||
self.max_unrealized_pnl_seen = None
|
||||
logger.success("反手做多成功")
|
||||
self.last_reverse_time = time.time()
|
||||
time.sleep(20)
|
||||
return True
|
||||
else:
|
||||
logger.error("反手做多后持仓验证失败")
|
||||
return False
|
||||
|
||||
elif signal_type == 'reverse_short':
|
||||
# 平多 + 开空（反手做空）：先平仓，确认无仓后再开空
|
||||
logger.info(f"执行反手做空，触发价: {trigger_price:.2f}")
|
||||
self.平仓()
|
||||
time.sleep(1)
|
||||
for _ in range(10):
|
||||
if self.get_position_status() and self.start == 0:
|
||||
break
|
||||
time.sleep(1)
|
||||
if self.start != 0:
|
||||
logger.warning("反手做空：平仓后仍有持仓，放弃本次开空")
|
||||
return False
|
||||
logger.info("已确认无持仓，执行开空")
|
||||
self.开单(marketPriceLongOrder=-1, size=size)
|
||||
time.sleep(3)
|
||||
|
||||
if self.verify_position_direction(-1):
|
||||
self.max_unrealized_pnl_seen = None
|
||||
logger.success("反手做空成功")
|
||||
self.last_reverse_time = time.time()
|
||||
time.sleep(20)
|
||||
return True
|
||||
else:
|
||||
logger.error("反手做空后持仓验证失败")
|
||||
return False
|
||||
|
||||
return False
|
||||
|
||||
def action(self):
|
||||
"""主循环"""
|
||||
|
||||
logger.info("开始运行四分之一策略交易...")
|
||||
|
||||
# 启动时设置全仓高杠杆
|
||||
if not self.set_leverage():
|
||||
logger.error("杠杆设置失败，程序继续运行但可能下单失败")
|
||||
return
|
||||
|
||||
page_start = True
|
||||
|
||||
while True:
|
||||
|
||||
if page_start:
|
||||
# 打开浏览器
|
||||
for i in range(5):
|
||||
if self.openBrowser():
|
||||
logger.info("浏览器打开成功")
|
||||
break
|
||||
else:
|
||||
self.ding("打开浏览器失败！", error=True)
|
||||
return
|
||||
|
||||
# 进入交易页面
|
||||
self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT")
|
||||
self.click_safe('x://button[normalize-space(text()) ="市价"]')
|
||||
|
||||
self.page.ele('x://*[@id="size_0"]').input(vals=25, clear=True)
|
||||
|
||||
page_start = False
|
||||
|
||||
try:
|
||||
# 1. 获取K线数据（当前K线和上一根K线）
|
||||
prev_kline, current_kline = self.get_klines()
|
||||
if not prev_kline or not current_kline:
|
||||
logger.warning("获取K线失败，等待重试...")
|
||||
time.sleep(5)
|
||||
continue
|
||||
|
||||
# 记录进入新的K线
|
||||
current_kline_time = current_kline['id']
|
||||
if self.last_kline_time != current_kline_time:
|
||||
self.last_kline_time = current_kline_time
|
||||
logger.info(f"进入新K线: {current_kline_time}")
|
||||
|
||||
# 2. 获取当前价格
|
||||
current_price = self.get_current_price()
|
||||
if not current_price:
|
||||
logger.warning("获取价格失败，等待重试...")
|
||||
time.sleep(2)
|
||||
continue
|
||||
|
||||
# 3. 每次循环都通过SDK获取真实持仓状态（避免状态不同步导致双向持仓）
|
||||
if not self.get_position_status():
|
||||
logger.warning("获取持仓状态失败，等待重试...")
|
||||
time.sleep(2)
|
||||
continue
|
||||
|
||||
logger.debug(f"当前持仓状态: {self.start} (0=无, 1=多, -1=空)")
|
||||
|
||||
# 3.5 止损/止盈/移动止损
|
||||
if self.start != 0:
|
||||
pnl_usd = self.get_unrealized_pnl_usd()
|
||||
if pnl_usd is not None:
|
||||
# 固定止损：亏损达到 3 美元平仓
|
||||
if pnl_usd <= self.stop_loss_usd:
|
||||
logger.info(f"仓位亏损 {pnl_usd:.2f} 美元 <= 止损 {self.stop_loss_usd} 美元，执行止损平仓")
|
||||
self.平仓()
|
||||
self.max_unrealized_pnl_seen = None
|
||||
time.sleep(3)
|
||||
continue
|
||||
# 更新持仓期间最大盈利（用于移动止损）
|
||||
if self.max_unrealized_pnl_seen is None:
|
||||
self.max_unrealized_pnl_seen = pnl_usd
|
||||
else:
|
||||
self.max_unrealized_pnl_seen = max(self.max_unrealized_pnl_seen, pnl_usd)
|
||||
# 移动止损：盈利曾达到 activation 后，从最高盈利回撤 trailing_distance 则平仓
|
||||
if self.max_unrealized_pnl_seen >= self.trailing_activation_usd:
|
||||
if pnl_usd < self.max_unrealized_pnl_seen - self.trailing_distance_usd:
|
||||
logger.info(f"移动止损：当前盈利 {pnl_usd:.2f} 从最高 {self.max_unrealized_pnl_seen:.2f} 回撤 >= {self.trailing_distance_usd} 美元，平仓")
|
||||
self.平仓()
|
||||
self.max_unrealized_pnl_seen = None
|
||||
time.sleep(3)
|
||||
continue
|
||||
# 止盈：盈利达到 take_profit_usd 平仓
|
||||
if pnl_usd >= self.take_profit_usd:
|
||||
logger.info(f"仓位盈利 {pnl_usd:.2f} 美元 >= {self.take_profit_usd} 美元，执行止盈平仓")
|
||||
self.平仓()
|
||||
self.max_unrealized_pnl_seen = None
|
||||
time.sleep(3)
|
||||
continue
|
||||
|
||||
# 4. 检查信号
|
||||
signal = self.check_signal(current_price, prev_kline, current_kline)
|
||||
|
||||
# 5. 反手过滤：冷却时间 + 最小价差
|
||||
if signal and signal[0].startswith('reverse_'):
|
||||
if not self.can_reverse(current_price, signal[1]):
|
||||
signal = None
|
||||
|
||||
# 5.5 开仓频率过滤：同一根 K 线只开一次 + 开仓冷却
|
||||
if signal and signal[0] in ('long', 'short'):
|
||||
if not self.can_open(current_kline_time):
|
||||
signal = None
|
||||
else:
|
||||
self._current_kline_id_for_open = current_kline_time # 供 execute_trade 成功后记录
|
||||
|
||||
# 6. 有信号则执行交易
|
||||
if signal:
|
||||
trade_success = self.execute_trade(signal)
|
||||
if trade_success:
|
||||
logger.success(f"交易执行完成: {signal[0]}, 当前持仓状态: {self.start}")
|
||||
page_start = True
|
||||
else:
|
||||
logger.warning(f"交易执行失败或被阻止: {signal[0]}")
|
||||
|
||||
# 短暂等待后继续循环（同一根K线遇到信号就操作）
|
||||
time.sleep(0.1)
|
||||
|
||||
if page_start:
|
||||
self.page.close()
|
||||
time.sleep(5)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
logger.info("用户中断，程序退出")
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"主循环异常: {e}")
|
||||
time.sleep(5)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
BitmartFuturesTransaction(bit_id="f2320f57e24c45529a009e1541e25961").action()
|
||||
540
抓取币安K线.py
Normal file
540
抓取币安K线.py
Normal file
@@ -0,0 +1,540 @@
|
||||
"""
|
||||
币安 永续合约 ETHUSDT 多周期K线 + 秒级数据抓取
|
||||
- K线: 1m、3m、5m、15m、30m、1h
|
||||
- 秒级: 通过 aggTrades 逐笔成交聚合，每秒一条 (时间, 价格 OHLC)
|
||||
支持断点续传
|
||||
"""
|
||||
|
||||
import time
|
||||
import datetime
|
||||
from pathlib import Path
|
||||
from loguru import logger
|
||||
from peewee import *
|
||||
|
||||
try:
|
||||
import requests
|
||||
except ImportError:
|
||||
requests = None
|
||||
|
||||
DB_PATH = Path(__file__).parent / 'models' / 'database.db'
|
||||
db = SqliteDatabase(str(DB_PATH))
|
||||
|
||||
KLINE_CONFIGS = {
|
||||
1: '1m',
|
||||
3: '3m',
|
||||
5: '5m',
|
||||
15: '15m',
|
||||
30: '30m',
|
||||
60: '1h',
|
||||
}
|
||||
|
||||
BINANCE_INTERVALS = {
|
||||
1: '1m',
|
||||
3: '3m',
|
||||
5: '5m',
|
||||
15: '15m',
|
||||
30: '30m',
|
||||
60: '1h',
|
||||
}
|
||||
|
||||
BINANCE_BASE = 'https://fapi.binance.com'
|
||||
|
||||
|
||||
class BinanceETHTrades(Model):
|
||||
"""逐笔成交（aggTrades 原始数据）"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
timestamp = BigIntegerField(index=True)
|
||||
price = FloatField()
|
||||
volume = FloatField()
|
||||
side = IntegerField() # 1=买, 0=卖
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'binance_eth_trades'
|
||||
|
||||
|
||||
class BinanceETHSecond(Model):
|
||||
"""秒级数据：每秒一条，id=时间戳(毫秒取整到秒), close=该秒收盘价"""
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
volume = FloatField(null=True)
|
||||
trade_count = IntegerField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'binance_eth_1s'
|
||||
|
||||
|
||||
def create_binance_kline_model(step: int):
|
||||
"""动态创建币安K线模型"""
|
||||
suffix = KLINE_CONFIGS.get(step, f'{step}m')
|
||||
tbl_name = f'binance_eth_{suffix}'
|
||||
attrs = {
|
||||
'id': BigIntegerField(primary_key=True),
|
||||
'open': FloatField(null=True),
|
||||
'high': FloatField(null=True),
|
||||
'low': FloatField(null=True),
|
||||
'close': FloatField(null=True),
|
||||
}
|
||||
meta_attrs = {'database': db, 'table_name': tbl_name}
|
||||
Meta = type('Meta', (), meta_attrs)
|
||||
attrs['Meta'] = Meta
|
||||
name = f'BinanceETH{suffix.replace("m", "m").replace("h", "h")}'
|
||||
return type(name, (Model,), attrs)
|
||||
|
||||
|
||||
class BinanceKlineCollector:
|
||||
"""币安永续合约 K线抓取器"""
|
||||
|
||||
def __init__(self, symbol: str = "ETHUSDT", proxy: str = None, verify_ssl: bool = True):
|
||||
"""
|
||||
:param symbol: 合约代码
|
||||
:param proxy: 代理地址，如 'http://127.0.0.1:7890'，也可通过环境变量 BINANCE_PROXY 设置
|
||||
:param verify_ssl: 是否校验 SSL 证书，网络异常时可设为 False
|
||||
"""
|
||||
self.symbol = symbol
|
||||
self.proxy = proxy or __import__('os').environ.get('BINANCE_PROXY', '').strip() or None
|
||||
self.verify_ssl = verify_ssl
|
||||
self._session = requests.Session() if requests else None
|
||||
self.models = {}
|
||||
self._init_database()
|
||||
|
||||
def _init_database(self):
|
||||
DB_PATH.parent.mkdir(parents=True, exist_ok=True)
|
||||
db.connect(reuse_if_open=True)
|
||||
for step in KLINE_CONFIGS.keys():
|
||||
model = create_binance_kline_model(step)
|
||||
self.models[step] = model
|
||||
db.create_tables([model], safe=True)
|
||||
logger.info(f"初始化表: {model._meta.table_name}")
|
||||
db.create_tables([BinanceETHTrades, BinanceETHSecond], safe=True)
|
||||
logger.info("初始化表: binance_eth_trades, binance_eth_1s")
|
||||
|
||||
def get_db_time_range(self, step: int):
|
||||
model = self.models.get(step)
|
||||
if not model:
|
||||
return None, None
|
||||
try:
|
||||
earliest = model.select(fn.MIN(model.id)).scalar()
|
||||
latest = model.select(fn.MAX(model.id)).scalar()
|
||||
return earliest, latest
|
||||
except Exception as e:
|
||||
logger.error(f"查询数据库异常: {e}")
|
||||
return None, None
|
||||
|
||||
def get_klines(self, step: int, start_time: int, end_time: int, max_retries: int = 3):
|
||||
"""
|
||||
从币安 API 获取K线
|
||||
:param step: 周期(分钟)
|
||||
:param start_time: 开始时间戳(秒)
|
||||
:param end_time: 结束时间戳(秒)
|
||||
:return: [{'id', 'open', 'high', 'low', 'close'}, ...]
|
||||
"""
|
||||
if not requests:
|
||||
logger.error("需要安装 requests: pip install requests")
|
||||
return []
|
||||
|
||||
interval = BINANCE_INTERVALS.get(step, f'{step}m')
|
||||
start_ms = int(start_time) * 1000
|
||||
end_ms = int(end_time) * 1000
|
||||
url = f"{BINANCE_BASE}/fapi/v1/klines"
|
||||
|
||||
kwargs = {'timeout': 30, 'verify': self.verify_ssl}
|
||||
if self.proxy:
|
||||
kwargs['proxies'] = {'http': self.proxy, 'https': self.proxy}
|
||||
sess = self._session
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
params = {
|
||||
'symbol': self.symbol,
|
||||
'interval': interval,
|
||||
'startTime': start_ms,
|
||||
'endTime': end_ms,
|
||||
'limit': 1500,
|
||||
}
|
||||
r = (sess or requests).get(url, params=params, **kwargs)
|
||||
r.raise_for_status()
|
||||
data = r.json()
|
||||
|
||||
formatted = []
|
||||
for k in data:
|
||||
# [open_time, open, high, low, close, volume, ...]
|
||||
formatted.append({
|
||||
'id': k[0],
|
||||
'open': float(k[1]),
|
||||
'high': float(k[2]),
|
||||
'low': float(k[3]),
|
||||
'close': float(k[4]),
|
||||
})
|
||||
formatted.sort(key=lambda x: x['id'])
|
||||
return formatted
|
||||
|
||||
except Exception as e:
|
||||
delay = 3 + attempt * 2
|
||||
logger.warning(f"获取K线异常 (尝试 {attempt+1}/{max_retries}): {e}，{delay}s 后重试")
|
||||
if attempt < max_retries - 1:
|
||||
time.sleep(delay)
|
||||
return []
|
||||
|
||||
def save_klines(self, step: int, klines: list):
|
||||
model = self.models.get(step)
|
||||
if not model:
|
||||
return 0
|
||||
new_count = 0
|
||||
for kline in klines:
|
||||
try:
|
||||
_, created = model.get_or_create(
|
||||
id=kline['id'],
|
||||
defaults={
|
||||
'open': kline['open'],
|
||||
'high': kline['high'],
|
||||
'low': kline['low'],
|
||||
'close': kline['close'],
|
||||
}
|
||||
)
|
||||
if created:
|
||||
new_count += 1
|
||||
except Exception as e:
|
||||
logger.error(f"保存失败 {kline['id']}: {e}")
|
||||
return new_count
|
||||
|
||||
def get_batch_seconds(self, step: int):
|
||||
if step == 1:
|
||||
return 3600 * 4
|
||||
elif step == 3:
|
||||
return 3600 * 8
|
||||
elif step == 5:
|
||||
return 3600 * 12
|
||||
elif step == 15:
|
||||
return 3600 * 24
|
||||
elif step == 30:
|
||||
return 3600 * 48
|
||||
else:
|
||||
return 3600 * 72
|
||||
|
||||
def collect_period_range(self, step: int, target_start: int, target_end: int):
|
||||
suffix = KLINE_CONFIGS.get(step, f'{step}m')
|
||||
batch_seconds = self.get_batch_seconds(step)
|
||||
db_earliest, db_latest = self.get_db_time_range(step)
|
||||
|
||||
if db_earliest and db_latest:
|
||||
db_earliest_sec = db_earliest // 1000
|
||||
db_latest_sec = db_latest // 1000
|
||||
logger.info(f"[{suffix}] 数据库已有: "
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(db_earliest_sec))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(db_latest_sec))}")
|
||||
else:
|
||||
db_earliest_sec = db_latest_sec = None
|
||||
|
||||
total_saved = 0
|
||||
|
||||
# 向前抓取历史
|
||||
backward_end = db_earliest_sec if db_earliest_sec else target_end
|
||||
if backward_end > target_start:
|
||||
logger.info(f"[{suffix}] === 向前抓取历史 ===")
|
||||
total_backward = backward_end - target_start
|
||||
current_end = backward_end
|
||||
fail_count = 0
|
||||
while current_end > target_start and fail_count < 5:
|
||||
current_start = max(current_end - batch_seconds, target_start)
|
||||
klines = self.get_klines(step, current_start, current_end)
|
||||
if klines:
|
||||
saved = self.save_klines(step, klines)
|
||||
total_saved += saved
|
||||
progress = (backward_end - current_end) / total_backward * 100 if total_backward > 0 else 0
|
||||
logger.info(f"[{suffix}] ← {time.strftime('%Y-%m-%d %H:%M', time.localtime(current_start))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(current_end))} | "
|
||||
f"获取 {len(klines)} 新增 {saved} | 进度 {progress:.1f}%")
|
||||
fail_count = 0
|
||||
else:
|
||||
fail_count += 1
|
||||
current_end = current_start
|
||||
time.sleep(0.2)
|
||||
|
||||
# 向后抓取最新
|
||||
forward_start = db_latest_sec if db_latest_sec else target_start
|
||||
if forward_start < target_end:
|
||||
logger.info(f"[{suffix}] === 向后抓取最新 ===")
|
||||
current_start = forward_start
|
||||
fail_count = 0
|
||||
while current_start < target_end and fail_count < 3:
|
||||
current_end = min(current_start + batch_seconds, target_end)
|
||||
klines = self.get_klines(step, current_start, current_end)
|
||||
if klines:
|
||||
saved = self.save_klines(step, klines)
|
||||
total_saved += saved
|
||||
logger.info(f"[{suffix}] → {time.strftime('%Y-%m-%d %H:%M', time.localtime(current_start))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(current_end))} | "
|
||||
f"获取 {len(klines)} 新增 {saved}")
|
||||
fail_count = 0
|
||||
else:
|
||||
fail_count += 1
|
||||
current_start = current_end
|
||||
time.sleep(0.2)
|
||||
|
||||
final_earliest, final_latest = self.get_db_time_range(step)
|
||||
if final_earliest and final_latest:
|
||||
logger.success(f"[{suffix}] 完成！本次新增 {total_saved} | "
|
||||
f"{time.strftime('%Y-%m-%d', time.localtime(final_earliest//1000))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d', time.localtime(final_latest//1000))}")
|
||||
return total_saved
|
||||
|
||||
def collect_from_date(self, start_date: str, periods: list = None):
|
||||
if periods is None:
|
||||
periods = list(KLINE_CONFIGS.keys())
|
||||
start_dt = datetime.datetime.strptime(start_date, '%Y-%m-%d')
|
||||
target_start = int(start_dt.timestamp())
|
||||
target_end = int(time.time())
|
||||
|
||||
logger.info(f"币安 ETHUSDT 永续 | {start_date} ~ 当前 | 周期: {[KLINE_CONFIGS[p] for p in periods]}")
|
||||
results = {}
|
||||
for step in periods:
|
||||
saved = self.collect_period_range(step, target_start, target_end)
|
||||
results[KLINE_CONFIGS[step]] = saved
|
||||
time.sleep(0.5)
|
||||
logger.info("抓取完成: " + ", ".join(f"{k}: {v}" for k, v in results.items()))
|
||||
return results
|
||||
|
||||
# ==================== 秒级数据 ====================
|
||||
|
||||
def get_agg_trades(self, start_ms: int, end_ms: int, max_retries: int = 3):
|
||||
"""
|
||||
获取逐笔成交 (aggTrades)，时间范围需 <= 1 小时
|
||||
:return: [{'id', 'timestamp', 'price', 'volume', 'side'}, ...]
|
||||
"""
|
||||
if not requests:
|
||||
return []
|
||||
url = f"{BINANCE_BASE}/fapi/v1/aggTrades"
|
||||
kwargs = {'timeout': 30, 'verify': self.verify_ssl}
|
||||
if self.proxy:
|
||||
kwargs['proxies'] = {'http': self.proxy, 'https': self.proxy}
|
||||
sess = self._session
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
params = {
|
||||
'symbol': self.symbol,
|
||||
'startTime': start_ms,
|
||||
'endTime': end_ms,
|
||||
'limit': 1000,
|
||||
}
|
||||
r = (sess or requests).get(url, params=params, **kwargs)
|
||||
r.raise_for_status()
|
||||
data = r.json()
|
||||
out = []
|
||||
for t in data:
|
||||
out.append({
|
||||
'id': t['a'],
|
||||
'timestamp': t['T'],
|
||||
'price': float(t['p']),
|
||||
'volume': float(t['q']),
|
||||
'side': 0 if t.get('m', False) else 1,
|
||||
})
|
||||
return out
|
||||
except Exception as e:
|
||||
delay = 3 + attempt * 2
|
||||
logger.warning(f"获取 aggTrades 异常 ({attempt+1}/{max_retries}): {e}，{delay}s 后重试")
|
||||
if attempt < max_retries - 1:
|
||||
time.sleep(delay)
|
||||
return []
|
||||
|
||||
def save_trades(self, trades: list):
|
||||
n = 0
|
||||
for t in trades:
|
||||
try:
|
||||
_, created = BinanceETHTrades.get_or_create(
|
||||
id=t['id'],
|
||||
defaults={'timestamp': t['timestamp'], 'price': t['price'],
|
||||
'volume': t['volume'], 'side': t['side']}
|
||||
)
|
||||
if created:
|
||||
n += 1
|
||||
except Exception:
|
||||
pass
|
||||
return n
|
||||
|
||||
def get_second_db_range(self):
|
||||
try:
|
||||
lo = BinanceETHSecond.select(fn.MIN(BinanceETHSecond.id)).scalar()
|
||||
hi = BinanceETHSecond.select(fn.MAX(BinanceETHSecond.id)).scalar()
|
||||
return lo, hi
|
||||
except Exception:
|
||||
return None, None
|
||||
|
||||
def aggregate_trades_to_seconds(self, start_ms: int = None, end_ms: int = None):
|
||||
"""将 binance_eth_trades 聚合为秒级 K 线，写入 binance_eth_1s"""
|
||||
q = BinanceETHTrades.select().order_by(BinanceETHTrades.timestamp)
|
||||
if start_ms:
|
||||
q = q.where(BinanceETHTrades.timestamp >= start_ms)
|
||||
if end_ms:
|
||||
q = q.where(BinanceETHTrades.timestamp <= end_ms)
|
||||
|
||||
sec_data = {}
|
||||
for t in q:
|
||||
sec_ts = (t.timestamp // 1000) * 1000
|
||||
if sec_ts not in sec_data:
|
||||
sec_data[sec_ts] = {
|
||||
'open': t.price, 'high': t.price, 'low': t.price, 'close': t.price,
|
||||
'volume': t.volume, 'trade_count': 1
|
||||
}
|
||||
else:
|
||||
sec_data[sec_ts]['high'] = max(sec_data[sec_ts]['high'], t.price)
|
||||
sec_data[sec_ts]['low'] = min(sec_data[sec_ts]['low'], t.price)
|
||||
sec_data[sec_ts]['close'] = t.price
|
||||
sec_data[sec_ts]['volume'] += t.volume
|
||||
sec_data[sec_ts]['trade_count'] += 1
|
||||
|
||||
n = 0
|
||||
for ts, d in sec_data.items():
|
||||
try:
|
||||
BinanceETHSecond.insert(
|
||||
id=ts, open=d['open'], high=d['high'], low=d['low'], close=d['close'],
|
||||
volume=d['volume'], trade_count=d['trade_count']
|
||||
).on_conflict(
|
||||
conflict_target=[BinanceETHSecond.id],
|
||||
update={BinanceETHSecond.open: d['open'], BinanceETHSecond.high: d['high'],
|
||||
BinanceETHSecond.low: d['low'], BinanceETHSecond.close: d['close'],
|
||||
BinanceETHSecond.volume: d['volume'],
|
||||
BinanceETHSecond.trade_count: d['trade_count']}
|
||||
).execute()
|
||||
n += 1
|
||||
except Exception as e:
|
||||
logger.error(f"保存秒级失败 {ts}: {e}")
|
||||
logger.info(f"聚合: {len(sec_data)} 条秒级数据")
|
||||
return n
|
||||
|
||||
def collect_second_data(self, start_date: str, end_date: str = None):
|
||||
"""
|
||||
抓取秒级数据：逐小时拉 aggTrades，聚合为秒级后入库
|
||||
:param start_date: 'YYYY-MM-DD'
|
||||
:param end_date: 'YYYY-MM-DD' 或 None(当前)
|
||||
"""
|
||||
start_dt = datetime.datetime.strptime(start_date, '%Y-%m-%d')
|
||||
start_ts = int(start_dt.timestamp())
|
||||
end_ts = int(time.time()) if end_date is None else int(
|
||||
datetime.datetime.strptime(end_date, '%Y-%m-%d').timestamp())
|
||||
start_ms = start_ts * 1000
|
||||
end_ms = end_ts * 1000
|
||||
|
||||
# 每次最多 1 小时
|
||||
chunk_ms = 3600 * 1000
|
||||
lo, hi = self.get_second_db_range()
|
||||
if lo and hi:
|
||||
# 向后补
|
||||
fetch_start = hi + 1000
|
||||
else:
|
||||
fetch_start = start_ms
|
||||
|
||||
total_trades = 0
|
||||
total_saved = 0
|
||||
current = fetch_start
|
||||
while current < end_ms:
|
||||
chunk_end = min(current + chunk_ms, end_ms)
|
||||
trades = self.get_agg_trades(current, chunk_end)
|
||||
if trades:
|
||||
saved = self.save_trades(trades)
|
||||
total_trades += len(trades)
|
||||
total_saved += saved
|
||||
ts_str = datetime.datetime.fromtimestamp(current/1000).strftime('%Y-%m-%d %H:%M')
|
||||
logger.info(f"[1s] {ts_str} | 成交 {len(trades)} 条, 新增 {saved}")
|
||||
current = chunk_end
|
||||
time.sleep(0.15)
|
||||
|
||||
if total_trades > 0:
|
||||
self.aggregate_trades_to_seconds(start_ms=fetch_start, end_ms=end_ms)
|
||||
logger.success(f"秒级抓取完成: 成交 {total_trades}, 新增 {total_saved}")
|
||||
return total_saved
|
||||
|
||||
def collect_trades_realtime(self, duration_seconds: int = 3600, interval: float = 0.5):
|
||||
"""实时采集逐笔成交（秒级数据源）"""
|
||||
url = f"{BINANCE_BASE}/fapi/v1/aggTrades"
|
||||
kwargs = {'timeout': 10, 'verify': self.verify_ssl}
|
||||
if self.proxy:
|
||||
kwargs['proxies'] = {'http': self.proxy, 'https': self.proxy}
|
||||
sess = self._session
|
||||
start = time.time()
|
||||
end = start + duration_seconds
|
||||
total = 0
|
||||
last_id = None
|
||||
while time.time() < end:
|
||||
try:
|
||||
params = {'symbol': self.symbol, 'limit': 1000}
|
||||
if last_id:
|
||||
params['fromId'] = last_id + 1
|
||||
r = (sess or requests).get(url, params=params, **kwargs)
|
||||
data = r.json()
|
||||
if data:
|
||||
trades = [{'id': t['a'], 'timestamp': t['T'], 'price': float(t['p']),
|
||||
'volume': float(t['q']), 'side': 0 if t.get('m') else 1} for t in data]
|
||||
saved = self.save_trades(trades)
|
||||
total += saved
|
||||
last_id = data[-1]['a']
|
||||
if saved > 0 and total % 500 == 0:
|
||||
logger.info(f"[实时] 累计新增 {total} | 价格 {trades[-1]['price']:.2f}")
|
||||
except Exception as e:
|
||||
logger.warning(f"实时采集异常: {e}")
|
||||
time.sleep(interval)
|
||||
self.aggregate_trades_to_seconds()
|
||||
logger.success(f"实时采集完成: 新增 {total} 条")
|
||||
return total
|
||||
|
||||
def get_stats(self):
|
||||
logger.info("币安 K线 数据库统计:")
|
||||
for step, model in self.models.items():
|
||||
try:
|
||||
count = model.select().count()
|
||||
earliest, latest = self.get_db_time_range(step)
|
||||
if earliest and latest:
|
||||
s = f" {KLINE_CONFIGS[step]:>4}: {count:>8} 条 | " \
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(earliest//1000))} ~ " \
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(latest//1000))}"
|
||||
else:
|
||||
s = f" {KLINE_CONFIGS[step]:>4}: {count:>8} 条"
|
||||
logger.info(s)
|
||||
except Exception as e:
|
||||
logger.error(f" {KLINE_CONFIGS[step]}: {e}")
|
||||
try:
|
||||
tc = BinanceETHTrades.select().count()
|
||||
sc = BinanceETHSecond.select().count()
|
||||
if sc > 0:
|
||||
lo = BinanceETHSecond.select(fn.MIN(BinanceETHSecond.id)).scalar()
|
||||
hi = BinanceETHSecond.select(fn.MAX(BinanceETHSecond.id)).scalar()
|
||||
logger.info(f" trades: {tc:>8} | 1s: {sc:>8} | "
|
||||
f"{datetime.datetime.fromtimestamp(lo/1000).strftime('%Y-%m-%d %H:%M:%S')} ~ "
|
||||
f"{datetime.datetime.fromtimestamp(hi/1000).strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
else:
|
||||
logger.info(f" trades: {tc:>8} | 1s: {sc:>8}")
|
||||
except Exception as e:
|
||||
logger.error(f" trades/1s: {e}")
|
||||
|
||||
def close(self):
|
||||
if not db.is_closed():
|
||||
db.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import os
|
||||
# 代理示例: export BINANCE_PROXY='http://127.0.0.1:7890'
|
||||
# 或: collector = BinanceKlineCollector(proxy='http://127.0.0.1:7890', verify_ssl=False)
|
||||
collector = BinanceKlineCollector(
|
||||
symbol="ETHUSDT",
|
||||
proxy=os.environ.get('BINANCE_PROXY') or None,
|
||||
verify_ssl=os.environ.get('BINANCE_VERIFY_SSL', '1') != '0',
|
||||
)
|
||||
try:
|
||||
collector.get_stats()
|
||||
|
||||
# 可选: K线
|
||||
# collector.collect_from_date(start_date='2020-01-01', periods=[1, 3, 5, 15, 30, 60])
|
||||
|
||||
# 秒级数据：历史按天抓取（从数据库最新继续）
|
||||
collector.collect_second_data(start_date='2025-01-01')
|
||||
|
||||
# 或实时采集一段时间
|
||||
# collector.collect_trades_realtime(duration_seconds=3600, interval=0.5)
|
||||
|
||||
collector.get_stats()
|
||||
finally:
|
||||
collector.close()
|
||||
408
抓取币安K线_ccxt.py
Normal file
408
抓取币安K线_ccxt.py
Normal file
@@ -0,0 +1,408 @@
|
||||
"""
|
||||
基于 ccxt 的币安永续 ETHUSDT K线 + 秒级数据抓取
|
||||
- K线: 1m、3m、5m、15m、30m、1h
|
||||
- 秒级: fetch_trades 逐笔成交聚合
|
||||
支持代理，与 抓取币安K线.py 共用同一数据库表
|
||||
"""
|
||||
|
||||
import time
|
||||
import datetime
|
||||
import os
|
||||
from pathlib import Path
|
||||
from loguru import logger
|
||||
from peewee import *
|
||||
|
||||
try:
|
||||
import ccxt
|
||||
except ImportError:
|
||||
ccxt = None
|
||||
|
||||
DB_PATH = Path(__file__).parent / 'models' / 'database.db'
|
||||
db = SqliteDatabase(str(DB_PATH))
|
||||
|
||||
KLINE_CONFIGS = {1: '1m', 3: '3m', 5: '5m', 15: '15m', 30: '30m', 60: '1h'}
|
||||
CCXT_INTERVALS = {1: '1m', 3: '3m', 5: '5m', 15: '15m', 30: '30m', 60: '1h'}
|
||||
|
||||
|
||||
class BinanceETHTrades(Model):
|
||||
id = BigIntegerField(primary_key=True)
|
||||
timestamp = BigIntegerField(index=True)
|
||||
price = FloatField()
|
||||
volume = FloatField()
|
||||
side = IntegerField()
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'binance_eth_trades'
|
||||
|
||||
|
||||
class BinanceETHSecond(Model):
|
||||
id = BigIntegerField(primary_key=True)
|
||||
open = FloatField(null=True)
|
||||
high = FloatField(null=True)
|
||||
low = FloatField(null=True)
|
||||
close = FloatField(null=True)
|
||||
volume = FloatField(null=True)
|
||||
trade_count = IntegerField(null=True)
|
||||
|
||||
class Meta:
|
||||
database = db
|
||||
table_name = 'binance_eth_1s'
|
||||
|
||||
|
||||
def create_kline_model(step: int):
|
||||
suffix = KLINE_CONFIGS.get(step, f'{step}m')
|
||||
tbl_name = f'binance_eth_{suffix}'
|
||||
attrs = {
|
||||
'id': BigIntegerField(primary_key=True),
|
||||
'open': FloatField(null=True),
|
||||
'high': FloatField(null=True),
|
||||
'low': FloatField(null=True),
|
||||
'close': FloatField(null=True),
|
||||
}
|
||||
meta = type('Meta', (), {'database': db, 'table_name': tbl_name})
|
||||
attrs['Meta'] = meta
|
||||
return type(f'BinanceETH{suffix}', (Model,), attrs)
|
||||
|
||||
|
||||
class BinanceCCXTCollector:
|
||||
"""基于 ccxt 的币安永续 K 线抓取"""
|
||||
|
||||
def __init__(self, symbol: str = "ETHUSDT", proxy: str = None):
|
||||
self.symbol = symbol
|
||||
self.ccxt_symbol = "ETH/USDT:USDT"
|
||||
self.proxy = proxy or os.environ.get('BINANCE_PROXY', '').strip() or None
|
||||
self.models = {}
|
||||
self.exchange = None
|
||||
self._init_exchange()
|
||||
self._init_database()
|
||||
|
||||
def _init_exchange(self):
|
||||
if not ccxt:
|
||||
raise ImportError("请安装 ccxt: pip install ccxt")
|
||||
options = {'defaultType': 'future', 'adjustForTimeDifference': True}
|
||||
config = {'timeout': 30000, 'enableRateLimit': True}
|
||||
if self.proxy:
|
||||
config['proxy'] = self.proxy
|
||||
self.exchange = ccxt.binanceusdm(config=config)
|
||||
self.exchange.options.update(options)
|
||||
logger.info(f"ccxt 交易所: binanceusdm" + (f" 代理: {self.proxy}" if self.proxy else ""))
|
||||
|
||||
def _init_database(self):
|
||||
DB_PATH.parent.mkdir(parents=True, exist_ok=True)
|
||||
db.connect(reuse_if_open=True)
|
||||
for step in KLINE_CONFIGS.keys():
|
||||
model = create_kline_model(step)
|
||||
self.models[step] = model
|
||||
db.create_tables([model], safe=True)
|
||||
db.create_tables([BinanceETHTrades, BinanceETHSecond], safe=True)
|
||||
logger.info("数据库表已就绪")
|
||||
|
||||
def get_db_time_range(self, step: int):
|
||||
model = self.models.get(step)
|
||||
if not model:
|
||||
return None, None
|
||||
try:
|
||||
lo = model.select(fn.MIN(model.id)).scalar()
|
||||
hi = model.select(fn.MAX(model.id)).scalar()
|
||||
return lo, hi
|
||||
except Exception:
|
||||
return None, None
|
||||
|
||||
def fetch_klines(self, step: int, start_sec: int, end_sec: int, max_retries: int = 5):
|
||||
"""ccxt fetch_ohlcv，按批次拉取"""
|
||||
interval = CCXT_INTERVALS.get(step, f'{step}m')
|
||||
since_ms = int(start_sec) * 1000
|
||||
end_ms = int(end_sec) * 1000
|
||||
out = []
|
||||
while since_ms < end_ms:
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
ohlcv = self.exchange.fetch_ohlcv(
|
||||
self.ccxt_symbol,
|
||||
interval,
|
||||
since=since_ms,
|
||||
limit=1500,
|
||||
)
|
||||
if not ohlcv:
|
||||
break
|
||||
for row in ohlcv:
|
||||
ts, o, h, l, c = int(row[0]), row[1], row[2], row[3], row[4]
|
||||
if ts >= end_ms:
|
||||
break
|
||||
out.append({'id': ts, 'open': float(o), 'high': float(h),
|
||||
'low': float(l), 'close': float(c)})
|
||||
since_ms = int(ohlcv[-1][0]) + 1
|
||||
time.sleep(0.15)
|
||||
break
|
||||
except Exception as e:
|
||||
delay = 2 + attempt * 2
|
||||
logger.warning(f"fetch_ohlcv 异常 ({attempt+1}/{max_retries}): {e}，{delay}s 后重试")
|
||||
if attempt < max_retries - 1:
|
||||
time.sleep(delay)
|
||||
else:
|
||||
return []
|
||||
return out
|
||||
|
||||
def save_klines(self, step: int, klines: list):
|
||||
model = self.models.get(step)
|
||||
if not model:
|
||||
return 0
|
||||
n = 0
|
||||
for k in klines:
|
||||
try:
|
||||
_, created = model.get_or_create(
|
||||
id=k['id'],
|
||||
defaults={'open': k['open'], 'high': k['high'], 'low': k['low'], 'close': k['close']}
|
||||
)
|
||||
if created:
|
||||
n += 1
|
||||
except Exception as e:
|
||||
logger.error(f"保存失败 {k['id']}: {e}")
|
||||
return n
|
||||
|
||||
def get_batch_seconds(self, step: int):
|
||||
return {1: 3600*4, 3: 3600*8, 5: 3600*12, 15: 3600*24, 30: 3600*48}.get(step, 3600*72)
|
||||
|
||||
def collect_period_range(self, step: int, target_start: int, target_end: int):
|
||||
suffix = KLINE_CONFIGS.get(step, f'{step}m')
|
||||
batch = self.get_batch_seconds(step)
|
||||
db_lo, db_hi = self.get_db_time_range(step)
|
||||
db_lo_sec = db_lo // 1000 if db_lo else None
|
||||
db_hi_sec = db_hi // 1000 if db_hi else None
|
||||
|
||||
total = 0
|
||||
|
||||
backward_end = db_lo_sec if db_lo_sec else target_end
|
||||
if backward_end > target_start:
|
||||
logger.info(f"[{suffix}] 向前抓取历史")
|
||||
current = backward_end
|
||||
fail = 0
|
||||
while current > target_start and fail < 5:
|
||||
start = max(current - batch, target_start)
|
||||
klines = self.fetch_klines(step, start, current)
|
||||
if klines:
|
||||
saved = self.save_klines(step, klines)
|
||||
total += saved
|
||||
logger.info(f"[{suffix}] ← {time.strftime('%Y-%m-%d %H:%M', time.localtime(start))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(current))} | "
|
||||
f"获取 {len(klines)} 新增 {saved}")
|
||||
fail = 0
|
||||
else:
|
||||
fail += 1
|
||||
current = start
|
||||
time.sleep(0.3)
|
||||
|
||||
forward_start = db_hi_sec if db_hi_sec else target_start
|
||||
if forward_start < target_end:
|
||||
logger.info(f"[{suffix}] 向后抓取最新")
|
||||
current = forward_start
|
||||
fail = 0
|
||||
while current < target_end and fail < 3:
|
||||
end = min(current + batch, target_end)
|
||||
klines = self.fetch_klines(step, current, end)
|
||||
if klines:
|
||||
saved = self.save_klines(step, klines)
|
||||
total += saved
|
||||
logger.info(f"[{suffix}] → {time.strftime('%Y-%m-%d %H:%M', time.localtime(current))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(end))} | "
|
||||
f"获取 {len(klines)} 新增 {saved}")
|
||||
fail = 0
|
||||
else:
|
||||
fail += 1
|
||||
current = end
|
||||
time.sleep(0.3)
|
||||
|
||||
lo, hi = self.get_db_time_range(step)
|
||||
if lo and hi:
|
||||
logger.success(f"[{suffix}] 完成 新增 {total} | "
|
||||
f"{time.strftime('%Y-%m-%d', time.localtime(lo//1000))} ~ "
|
||||
f"{time.strftime('%Y-%m-%d', time.localtime(hi//1000))}")
|
||||
return total
|
||||
|
||||
def collect_from_date(self, start_date: str, periods: list = None):
|
||||
if periods is None:
|
||||
periods = list(KLINE_CONFIGS.keys())
|
||||
start_ts = int(datetime.datetime.strptime(start_date, '%Y-%m-%d').timestamp())
|
||||
end_ts = int(time.time())
|
||||
logger.info(f"币安 ETHUSDT 永续(ccxt) | {start_date} ~ 当前 | 周期: {[KLINE_CONFIGS[p] for p in periods]}")
|
||||
results = {}
|
||||
for step in periods:
|
||||
results[KLINE_CONFIGS[step]] = self.collect_period_range(step, start_ts, end_ts)
|
||||
time.sleep(0.5)
|
||||
return results
|
||||
|
||||
# ==================== 秒级 ====================
|
||||
|
||||
def fetch_trades(self, since_ms: int = None, limit: int = 1000, max_retries: int = 5):
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
trades = self.exchange.fetch_trades(
|
||||
self.ccxt_symbol,
|
||||
since=since_ms,
|
||||
limit=limit,
|
||||
)
|
||||
out = []
|
||||
for t in trades:
|
||||
out.append({
|
||||
'id': t['id'],
|
||||
'timestamp': t['timestamp'],
|
||||
'price': float(t['price']),
|
||||
'volume': float(t['amount']),
|
||||
'side': 1 if t.get('side') == 'buy' else 0,
|
||||
})
|
||||
return out
|
||||
except Exception as e:
|
||||
delay = 2 + attempt * 2
|
||||
logger.warning(f"fetch_trades 异常 ({attempt+1}/{max_retries}): {e}，{delay}s 后重试")
|
||||
if attempt < max_retries - 1:
|
||||
time.sleep(delay)
|
||||
return []
|
||||
|
||||
def save_trades(self, trades: list):
|
||||
n = 0
|
||||
for t in trades:
|
||||
try:
|
||||
_, created = BinanceETHTrades.get_or_create(
|
||||
id=t['id'],
|
||||
defaults={'timestamp': t['timestamp'], 'price': t['price'],
|
||||
'volume': t['volume'], 'side': t['side']}
|
||||
)
|
||||
if created:
|
||||
n += 1
|
||||
except Exception:
|
||||
pass
|
||||
return n
|
||||
|
||||
def aggregate_to_seconds(self, start_ms: int = None, end_ms: int = None):
|
||||
q = BinanceETHTrades.select().order_by(BinanceETHTrades.timestamp)
|
||||
if start_ms:
|
||||
q = q.where(BinanceETHTrades.timestamp >= start_ms)
|
||||
if end_ms:
|
||||
q = q.where(BinanceETHTrades.timestamp <= end_ms)
|
||||
sec_data = {}
|
||||
for t in q:
|
||||
ts = (t.timestamp // 1000) * 1000
|
||||
if ts not in sec_data:
|
||||
sec_data[ts] = {
|
||||
'open': t.price, 'high': t.price, 'low': t.price, 'close': t.price,
|
||||
'volume': t.volume, 'trade_count': 1,
|
||||
}
|
||||
else:
|
||||
sec_data[ts]['high'] = max(sec_data[ts]['high'], t.price)
|
||||
sec_data[ts]['low'] = min(sec_data[ts]['low'], t.price)
|
||||
sec_data[ts]['close'] = t.price
|
||||
sec_data[ts]['volume'] += t.volume
|
||||
sec_data[ts]['trade_count'] += 1
|
||||
|
||||
for ts, d in sec_data.items():
|
||||
try:
|
||||
BinanceETHSecond.insert(
|
||||
id=ts, open=d['open'], high=d['high'], low=d['low'], close=d['close'],
|
||||
volume=d['volume'], trade_count=d['trade_count']
|
||||
).on_conflict(
|
||||
conflict_target=[BinanceETHSecond.id],
|
||||
update={
|
||||
BinanceETHSecond.open: d['open'], BinanceETHSecond.high: d['high'],
|
||||
BinanceETHSecond.low: d['low'], BinanceETHSecond.close: d['close'],
|
||||
BinanceETHSecond.volume: d['volume'],
|
||||
BinanceETHSecond.trade_count: d['trade_count'],
|
||||
}
|
||||
).execute()
|
||||
except Exception as e:
|
||||
logger.error(f"保存秒级失败 {ts}: {e}")
|
||||
logger.info(f"聚合 {len(sec_data)} 条秒级数据")
|
||||
|
||||
def collect_second_data(self, start_date: str, end_date: str = None):
|
||||
start_ts = int(datetime.datetime.strptime(start_date, '%Y-%m-%d').timestamp())
|
||||
end_ts = int(time.time()) if end_date is None else int(
|
||||
datetime.datetime.strptime(end_date, '%Y-%m-%d').timestamp())
|
||||
try:
|
||||
hi = BinanceETHSecond.select(fn.MAX(BinanceETHSecond.id)).scalar()
|
||||
fetch_start = (hi + 1000) if hi else start_ts * 1000
|
||||
except Exception:
|
||||
fetch_start = start_ts * 1000
|
||||
|
||||
total_saved = 0
|
||||
since = fetch_start
|
||||
while since < end_ts * 1000:
|
||||
trades = self.fetch_trades(since_ms=since, limit=1000)
|
||||
if trades:
|
||||
saved = self.save_trades(trades)
|
||||
total_saved += saved
|
||||
since = trades[-1]['timestamp'] + 1
|
||||
logger.info(f"[1s] {datetime.datetime.fromtimestamp(since/1000).strftime('%Y-%m-%d %H:%M:%S')} | "
|
||||
f"成交 {len(trades)} 新增 {saved}")
|
||||
else:
|
||||
since += 3600 * 1000
|
||||
time.sleep(0.2)
|
||||
|
||||
if total_saved > 0:
|
||||
self.aggregate_to_seconds(start_ms=fetch_start, end_ms=end_ts*1000)
|
||||
logger.success(f"秒级抓取完成 新增 {total_saved}")
|
||||
return total_saved
|
||||
|
||||
def collect_trades_realtime(self, duration_seconds: int = 3600, interval: float = 0.5):
|
||||
end = time.time() + duration_seconds
|
||||
total = 0
|
||||
since = None
|
||||
while time.time() < end:
|
||||
try:
|
||||
trades = self.fetch_trades(since_ms=since, limit=1000)
|
||||
if trades:
|
||||
total += self.save_trades(trades)
|
||||
since = trades[-1]['timestamp'] + 1
|
||||
except Exception as e:
|
||||
logger.warning(f"实时采集异常: {e}")
|
||||
time.sleep(interval)
|
||||
self.aggregate_to_seconds()
|
||||
logger.success(f"实时采集完成 新增 {total}")
|
||||
return total
|
||||
|
||||
def get_stats(self):
|
||||
logger.info("币安(ccxt) 数据库统计:")
|
||||
for step, model in self.models.items():
|
||||
try:
|
||||
c = model.select().count()
|
||||
lo, hi = self.get_db_time_range(step)
|
||||
s = f" {KLINE_CONFIGS[step]:>4}: {c:>8} 条"
|
||||
if lo and hi:
|
||||
s += f" | {time.strftime('%Y-%m-%d %H:%M', time.localtime(lo//1000))} ~ " \
|
||||
f"{time.strftime('%Y-%m-%d %H:%M', time.localtime(hi//1000))}"
|
||||
logger.info(s)
|
||||
except Exception as e:
|
||||
logger.error(f" {KLINE_CONFIGS[step]}: {e}")
|
||||
try:
|
||||
tc = BinanceETHTrades.select().count()
|
||||
sc = BinanceETHSecond.select().count()
|
||||
if sc > 0:
|
||||
lo = BinanceETHSecond.select(fn.MIN(BinanceETHSecond.id)).scalar()
|
||||
hi = BinanceETHSecond.select(fn.MAX(BinanceETHSecond.id)).scalar()
|
||||
logger.info(f" trades: {tc:>8} | 1s: {sc:>8} | "
|
||||
f"{datetime.datetime.fromtimestamp(lo/1000).strftime('%Y-%m-%d %H:%M:%S')} ~ "
|
||||
f"{datetime.datetime.fromtimestamp(hi/1000).strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
else:
|
||||
logger.info(f" trades: {tc:>8} | 1s: {sc:>8}")
|
||||
except Exception as e:
|
||||
logger.error(f" trades/1s: {e}")
|
||||
|
||||
def close(self):
|
||||
if not db.is_closed():
|
||||
db.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
proxy = os.environ.get('BINANCE_PROXY') or None
|
||||
collector = BinanceCCXTCollector(symbol="ETHUSDT", proxy=proxy)
|
||||
try:
|
||||
collector.get_stats()
|
||||
|
||||
# K线（不指定 periods 则抓取全部：1m、3m、5m、15m、30m、1h）
|
||||
collector.collect_from_date(start_date='2025-01-01')
|
||||
|
||||
# 秒级
|
||||
collector.collect_second_data(start_date='2025-01-01')
|
||||
|
||||
collector.get_stats()
|
||||
finally:
|
||||
collector.close()
|
||||
Reference in New Issue
Block a user