288 lines
12 KiB
Python
288 lines
12 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""strategy_router.py v5 — MoFin 策略动态路由（动态策略库，2026-08-13）
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核心（老莫原则）：
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- 策略全温区发信号（不留温区门控在策略内）
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- 策略-温区表现常态化记录（regime_perf.py / strategy_regime_perf），适用温区动态化
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- 组合按当前温区自动激活/休眠策略：当前温区实测胜率高的策略优先
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- 不漏历史策略（v_mr_sel trend_down 93%、v7.3 trend_up 94% 等被埋没的强者）
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数据流：
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market_regime(三态) + regime_tracker(平滑K=5) → 当前温区
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temp_band(rsi) → 温度/仓位乘数
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regime_perf(实测) → 各策略温区表现
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→ strategy_weights.json（各策略权重/激活状态）
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"""
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import json
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import sys
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from pathlib import Path
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from datetime import datetime
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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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OUT = Path("/home/hmo/MoFin/data/strategy_weights.json")
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# 2026-08-17 老莫：择优激活——每温区最多激活的策略数
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MAX_ACTIVE = 3
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# 家族映射（同家族只保留质量最优的一个，避免重复策略占位）
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FAMILY_MAP_ACT = {
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"s2_panic": "s2", "s2_panic_v2": "s2",
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"v_lurk_v1": "vlurk", "v_lurk_v2": "vlurk", "v_lurk_v3": "vlurk",
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"v_mr": "vmr", "v_mr2": "vmr", "v_mr3": "vmr", "v_mr4": "vmr",
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"v_oversold": "vover", "v_weak": "vweak",
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"b_td1": "b_td", "b_td1_v2": "b_td", "b_td1_v3": "b_td",
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"v1.0": "v1", "v2.0": "v2", "v3.0": "v3", "v_next": "vnext",
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}
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DEFAULT_FAMILY = "mr"
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FAMILY_MAP = {
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"v_weak": "mr", "v_oversold": "mr", "v_mr": "mr", "v_mr2": "mr", "v_mr3": "mr",
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"v_mr4": "mr", "v_mr_sel": "mr", "v_lurk_v1": "mr", "v_lurk_v2": "mr", "v_lurk_v3": "mr",
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"s2_panic": "mr", "v_osc": "mr",
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"v_next": "trend", "v_next3": "trend", "v_next4": "trend", "v_next5": "trend",
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"v8.0": "trend", "v8.1": "trend", "v8.2": "trend", "v8.3": "trend",
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"v7.0": "trend", "v7.1": "trend", "v7.1b": "trend", "v7.2": "trend", "v7.3": "trend",
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"v6.0": "trend", "v6.1": "trend", "v6.2": "trend",
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"v9.0": "trend", "v9.1": "trend", "v9.2": "trend",
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"v_combo": "trend", "v1.0": "trend", "v2.0": "trend", "v3.0": "trend",
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"v4.0": "trend", "v4.0a": "trend", "v4.0b": "trend", "v4.0c": "trend",
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"v4.0d": "trend", "v4.0e": "trend", "v4.0f": "trend", "v4.0g": "trend",
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"v4.0h": "trend", "v4.1": "trend", "v5.0": "trend",
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"v11.0": "trend", "v11.1": "trend",
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"hk_mr1": "mr", # 港股深度超卖反弹（2026-08-14 港股归因研发，trend_down 主战场）
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}
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def load_regime(market='a'):
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"""读取当前温区。market='a'(默认,A股 smoothed 顶层,行为不变) / 'hk'(港股 markets.hk)"""
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if market == 'hk':
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try:
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p = Path("/home/hmo/MoFin/data/market_regime_smoothed.json")
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if p.exists():
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d = json.loads(p.read_text(encoding="utf-8"))
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mk = (d.get("markets") or {}).get("hk") or {}
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if mk.get("current_regime"):
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return {"regime": mk["current_regime"], "date": mk.get("current_date", "")}
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except Exception:
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pass
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try:
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from market_regime import load_market_regime
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return load_market_regime(market='hk')
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except Exception:
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return {"regime": "unknown"}
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try:
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p = Path("/home/hmo/MoFin/data/market_regime_smoothed.json")
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if p.exists():
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d = json.loads(p.read_text(encoding="utf-8"))
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return {"regime": d.get("current_regime", "unknown"),
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"date": d.get("current_date", "")}
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except Exception:
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pass
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try:
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from market_regime import load_market_regime
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return load_market_regime()
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except Exception:
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return {"regime": "unknown"}
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def load_temp(market='a'):
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"""读取当前温度。market='a'(默认,A股) / 'hk'(港股)"""
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try:
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from temp_band import get_market_temp
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return get_market_temp(market=market)
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except Exception:
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return {"band": "unknown", "rsi": None}
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def load_regime_perf(market='a'):
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"""读取策略-温区表现（2026-08-17 改用 by_period 2y——含 b_td1_v3/s2_panic_v2 等新策略）。
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旧表 strategy_regime_perf 不含新策略，导致择优激活漏选；by_period 全量覆盖。"""
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conn = None
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try:
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import sqlite3
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conn = sqlite3.connect("/home/hmo/MoFin/data/mofin.db", timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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# 新表 by_period(2y) 优先，旧表补齐
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rows = conn.execute(
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"SELECT strategy, regime, trades, win_rate, avg_pnl FROM strategy_regime_perf_by_period "
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"WHERE COALESCE(market,'a')=? AND period_tag='2y'", (market,)
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).fetchall()
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result = {}
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for strat, reg, n, wr, pnl in rows:
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result.setdefault(strat, {})[reg] = {"trades": n, "win_rate": wr, "avg_pnl": pnl}
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# 旧表补缺（by_period 没覆盖的策略）
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rows2 = conn.execute(
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"SELECT strategy, regime, trades, win_rate, avg_pnl FROM strategy_regime_perf "
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"WHERE COALESCE(market,'a')=?", (market,)
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).fetchall()
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for strat, reg, n, wr, pnl in rows2:
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result.setdefault(strat, {}).setdefault(reg, {"trades": n, "win_rate": wr, "avg_pnl": pnl})
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return result
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except Exception:
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return {}
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finally:
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if conn:
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conn.close()
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def route(regime, temp, perf):
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current_regime = regime.get("regime", "unknown")
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band = temp.get("band", "unknown")
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weights = {}
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# 已证伪策略（从 strategy_research.deprecated 读，数据驱动——证伪绝不激活）
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dep = set()
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try:
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import sqlite3 as _sq
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_c = _sq.connect("/home/hmo/MoFin/data/mofin.db", timeout=5)
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dep = {r[0] for r in _c.execute(
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"SELECT DISTINCT version FROM strategy_research WHERE deprecated IS NOT NULL AND deprecated != ''")}
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_c.close()
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except Exception:
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pass
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for name, regs in perf.items():
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if not regs:
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continue
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if name in dep: # 已证伪策略绝不激活（数据驱动，2026-08-15）
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continue
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cur = regs.get(current_regime)
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best = max(regs.items(), key=lambda x: x[1].get("win_rate", 0))
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best_wr = best[1].get("win_rate", 0)
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cur_wr = cur.get("win_rate") if cur else None
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# 2026-08-16 资格标准A（老莫）：长期10y/近期2y/当下1y 适应温区年化>大盘 三项达标 + 手动可用
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# （替代只看胜率≥50%的旧判定——旧标准会让年化-41%但胜率51%的策略激活）
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try:
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from strategy_qualify import evaluate_all_regimes, is_available, get_benchmarks
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_qbench = get_benchmarks('a')
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# 2026-08-17 择优激活：按当前温区评估资格（同 server.py 修复——best_regime 会让
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# v_lurk_v3 在 trend_down 达标却被 choppy 评估误判不合格）
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_qev_all = evaluate_all_regimes(name, 'a', bench=_qbench)
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_qev_cur = (_qev_all or {}).get(current_regime) or {}
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_qual_ok = bool(_qev_cur.get("long_ok") and _qev_cur.get("mid_ok") and _qev_cur.get("short_ok"))
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_manual_ok = is_available(name)
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matched = _qual_ok and _manual_ok
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except Exception:
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matched = (best_wr >= 50) and (cur_wr is not None and cur_wr >= 50) # 兜底旧标准
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family = FAMILY_MAP.get(name, DEFAULT_FAMILY)
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base = 1.0 if matched else 0.3
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try:
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from temp_band import temp_multiplier
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mult = temp_multiplier(band, family)
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except Exception:
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mult = 0.8
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weights[name] = {
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"weight": round(base * mult, 2),
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"regime": current_regime,
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"temp_band": band,
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"family": family,
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"matched": matched,
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"best_regime": best[0],
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"best_win_rate": best[1].get("win_rate", 0),
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"cur_win_rate": cur.get("win_rate") if cur else None,
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"cur_avg_pnl": cur.get("avg_pnl") if cur else None,
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"trades": cur.get("trades") if cur else 0,
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}
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return dict(sorted(weights.items(), key=lambda x: -x[1]["weight"]))
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def _quality_score(name, market, regime):
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"""质量分 = 综合分(含效率惩罚) × 普适有效年占比（与 strategy_activation_selector 一致）"""
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try:
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import sqlite3 as _sq
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_c = _sq.connect("/home/hmo/MoFin/data/mofin.db", timeout=5)
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r = _c.execute(
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"SELECT trades, positions_taken, win_rate, sharpe_ratio, profit_factor, total_return_pct, "
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"portfolio_max_dd_pct, universality_score, universality_years, universality_valid_years "
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"FROM strategy_regime_perf_by_period WHERE strategy=? AND market=? AND regime=? AND period_tag='2y'",
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(name, market, regime)).fetchone()
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_c.close()
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if not r:
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return 0
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sig, pos, wr, sh, pf, ret, dd, univ, uy, uv = r
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pos = pos or 0
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ret_c = min(ret or 0, 100) / 100 * 30
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wr_c = (wr or 0) / 100 * 20
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sh_c = min(max(sh or 0, 0), 20) / 20 * 20
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pf_c = min(pf or 0, 5) / 5 * 15
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dd_c = (1 - min(dd or 0, 50) / 50) * 15
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conf = min(1, (sig or 0) / 40)
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# 效率惩罚（信号/成交比）
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ratio = sig / pos if pos else 99
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eff = 1.0 if ratio <= 2 else 0.9 if ratio <= 5 else 0.75 if ratio <= 10 else 0.5
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comp = (ret_c + wr_c + sh_c + pf_c + dd_c) * conf * eff
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univ_ratio = (uv / uy) if uy else 0
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return comp * (0.5 + 0.5 * univ_ratio)
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except Exception:
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return 0
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def _select_active(weights, regime, market):
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"""择优激活：matched 策略按质量分排序，家族去重，取前 MAX_ACTIVE"""
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matched = [(k, v) for k, v in weights.items() if v.get("matched")]
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scored = []
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for name, v in matched:
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q = _quality_score(name, market, regime)
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fam = FAMILY_MAP_ACT.get(name, name)
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scored.append({"name": name, "quality": q, "family": fam})
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scored.sort(key=lambda x: -x["quality"])
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used_fam = set()
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sel = []
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for s in scored:
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if s["family"] in used_fam:
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continue
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if len(sel) >= MAX_ACTIVE:
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break
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used_fam.add(s["family"])
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sel.append(s["name"])
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return sel
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def main():
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# A股路由（完全不变）
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regime = load_regime() # A股温区
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temp = load_temp() # A股温度
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perf = load_regime_perf('a') # A股策略表现
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weights = route(regime, temp, perf)
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out = {
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"state": regime.get("regime", "unknown"),
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"state_date": regime.get("date", ""),
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"temp_band": temp.get("band", "unknown"),
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"temp_rsi": temp.get("rsi"),
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"weights": weights,
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"active": _select_active(weights, regime.get("regime", "unknown"), 'a'),
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"updated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"note": "择优激活(2026-08-17): 每温区按质量分(综合分×普适有效年占比)排序+家族去重取前%d个; 温区(平滑K=5)选类型+温度乘数" % MAX_ACTIVE,
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}
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# 港股路由（2026-08-14 新增，不影响A股）——港股组合按温区调度（hk_strategies 定义）
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try:
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hk_regime = load_regime('hk')
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hk_temp = load_temp('hk')
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from hk_strategies import strategies_for_regime
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hk_active = strategies_for_regime(hk_regime.get("regime", "unknown"))
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out["markets"] = {"hk": {
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"state": hk_regime.get("regime", "unknown"),
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"state_date": hk_regime.get("date", ""),
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"temp_band": hk_temp.get("band", "unknown"),
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"active": hk_active,
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}}
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except Exception as e:
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print(f"港股路由失败（不影响A股）: {e}", flush=True)
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OUT.write_text(json.dumps(out, ensure_ascii=False, indent=1), encoding="utf-8")
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print(f"strategy_weights.json: 状态={out['state']} 温度={out['temp_band']}(rsi={out['temp_rsi']})")
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print(f"激活策略(A股): {out['active']}")
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if "markets" in out:
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hk = out["markets"]["hk"]
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print(f"港股温区={hk['state']} 激活策略(港股): {hk['active']}")
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print("权重排名（前15）:")
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for name, w in list(weights.items())[:15]:
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mark = "✓" if w["matched"] else "观察"
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print(f" {name:<12} w={w['weight']:<5} {w['best_regime']:<11} 最佳{w['best_win_rate']:>3.0f}% {mark}")
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if __name__ == "__main__":
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main()
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