175 lines
6.5 KiB
Python
175 lines
6.5 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""regime_perf.py — 策略-温区表现常态化记录（2026-08-13）
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记录策略在不同温区（trend_up/choppy/trend_down）的表现，供"适用温度"动态评估。
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- 数据来源：strategy_research 回测 trades（按入场日归入温区）+ 实盘 strategy_tracking
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- 表：strategy_regime_perf（strategy, regime, trades, win_rate, avg_pnl, updated_at）
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- 原则：策略全温区发信号（去门控后），记录各温区真实表现；适用温区是动态的，随数据更新
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用法：
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python3 regime_perf.py # 全量更新（从回测+实盘重算）
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from regime_perf import get_regime_perf
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"""
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import sys
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import json
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import sqlite3
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from pathlib import Path
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from datetime import datetime
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from collections import defaultdict
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_SCRIPT_DIR = Path(__file__).resolve().parent
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sys.path.insert(0, str(_SCRIPT_DIR))
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sys.path.insert(0, "/home/hmo/MoFin")
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DB = "/home/hmo/MoFin/data/mofin.db"
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def load_all_strategies():
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"""从 strategy_research 读取所有策略版本（含历史/表现不佳的——可能在特定温区能打）"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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rows = conn.execute("SELECT DISTINCT version FROM strategy_research ORDER BY version").fetchall()
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conn.close()
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return [r[0] for r in rows if r[0]]
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# 关注的策略（动态：全部版本）
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STRATEGIES = load_all_strategies()
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def load_regime_map():
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"""date -> regime（用平滑 regime_tracker 的周期反查更合理，这里用 market_regime 原始 + 手动按 K=5 平滑）
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简化：直接用 market_regime 的 regime（与平滑 K=5 差异主要在边界几天，评估可接受）"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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rows = conn.execute("SELECT date, regime FROM market_regime").fetchall()
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conn.close()
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return dict(rows)
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def get_trades_from_research(version):
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"""从 strategy_research 取最新回测 trades"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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rows = conn.execute(
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"SELECT results_json FROM strategy_research WHERE version=? ORDER BY period_tag DESC, created_at DESC LIMIT 1",
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(version,)
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).fetchall()
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conn.close()
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if not rows:
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return []
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try:
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return json.loads(rows[0][0]).get("trades", [])
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except Exception:
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return []
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def get_trades_from_tracking():
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"""从实盘 strategy_tracking 取已平仓交易"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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rows = conn.execute(
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"SELECT version_seq, tracked_at, theoretical_pnl FROM strategy_tracking WHERE status='closed'"
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).fetchall()
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conn.close()
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result = []
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for version_seq, tracked_at, pnl in rows:
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if version_seq and tracked_at:
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result.append({"version": version_seq, "entry_date": tracked_at[:10], "profit_pct": pnl})
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return result
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def compute(use_tracking=True):
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"""计算所有策略各温区表现"""
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regime_map = load_regime_map()
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stats = defaultdict(lambda: defaultdict(lambda: {"n": 0, "win": 0, "pnl": 0}))
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for v in STRATEGIES:
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trades = get_trades_from_research(v)
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for t in trades:
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ed = t.get("entry_date", "")
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if ed not in regime_map:
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continue
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reg = regime_map[ed]
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pnl = t.get("profit_pct", 0) or 0
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stats[v][reg]["n"] += 1
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stats[v][reg]["pnl"] += pnl
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if pnl > 0:
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stats[v][reg]["win"] += 1
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if use_tracking:
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for t in get_trades_from_tracking():
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v = t["version"]
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if v not in stats:
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stats[v] = defaultdict(lambda: {"n": 0, "win": 0, "pnl": 0})
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ed = t["entry_date"]
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if ed in regime_map:
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reg = regime_map[ed]
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pnl = t["profit_pct"] or 0
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stats[v][reg]["n"] += 1
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stats[v][reg]["pnl"] += pnl
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if pnl > 0:
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stats[v][reg]["win"] += 1
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return stats
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def save(stats):
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"""写入 strategy_regime_perf 表（清空重建，保持与最新数据同步）"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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conn.execute("""
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CREATE TABLE IF NOT EXISTS strategy_regime_perf (
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strategy TEXT,
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regime TEXT,
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trades INTEGER,
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win_rate REAL,
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avg_pnl REAL,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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PRIMARY KEY (strategy, regime)
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)
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""")
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conn.execute("DELETE FROM strategy_regime_perf")
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now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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for v, regs in stats.items():
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for reg, s in regs.items():
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if s["n"] < 2:
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continue # 样本太少不记录（>=2 给观察机会）
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wr = s["win"] / s["n"] * 100
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avg = s["pnl"] / s["n"]
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conn.execute(
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"INSERT OR REPLACE INTO strategy_regime_perf (strategy, regime, trades, win_rate, avg_pnl, updated_at) VALUES (?,?,?,?,?,?)",
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(v, reg, s["n"], round(wr, 1), round(avg, 2), now)
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)
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conn.commit()
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conn.close()
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def main():
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stats = compute(use_tracking=True)
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save(stats)
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# 打印
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print("=== 策略-温区表现（strategy_regime_perf）===")
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conn = sqlite3.connect(DB, timeout=30)
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rows = conn.execute("SELECT strategy, regime, trades, win_rate, avg_pnl FROM strategy_regime_perf ORDER BY strategy, regime").fetchall()
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conn.close()
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for r in rows:
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print(f" {r[0]:<12} {r[1]:<12} {r[2]:>4}笔 胜率{r[3]:.0f}% 均盈{r[4]:+.2f}%")
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def get_regime_perf(strategy=None):
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"""读取策略-温区表现（供 router 动态适用温区）"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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if strategy:
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rows = conn.execute(
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"SELECT regime, trades, win_rate, avg_pnl FROM strategy_regime_perf WHERE strategy=?",
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(strategy,)
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).fetchall()
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else:
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rows = conn.execute(
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"SELECT strategy, regime, trades, win_rate, avg_pnl FROM strategy_regime_perf"
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).fetchall()
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conn.close()
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if strategy:
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return {r[0]: {"trades": r[1], "win_rate": r[2], "avg_pnl": r[3]} for r in rows}
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result = defaultdict(dict)
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for r in rows:
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result[r[0]][r[1]] = {"trades": r[2], "win_rate": r[3], "avg_pnl": r[4]}
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return dict(result)
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if __name__ == "__main__":
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main()
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