start experiment 20 (exp/20-improve-the-risk-limit-reference-signal)

2026-08-17 02:55:26 +00:00
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+"""TopkDropout with HMM high-volatility + drawdown-pause risk gates.
+
+Adds three risk controls on top of ``TopkDropoutStrategy``:
+
+1. **HMM high-vol pause**: when the current day's HMM high-volatility regime
+   probability (``sp_hmm_p_regime1`` feature, regime-1 = high-vol) is above
+   ``hmm_pause_pct``, new buys are paused (existing positions held). This
+   encodes the time-series study's finding that HMM high-vol probability pulses
+   BEFORE sharp moves (regime-change cut) — pausing new exposure at the
+   boundary reduces drawdown from "价格过度反应".
+2. **Drawdown pause**: when the account equity drawdown from its running peak
+   exceeds ``drawdown_pause_pct``, new buys are paused (positions kept). This
+   is the ``drawdown_pause_pct`` risk-limit expressed in the backtest (the
+   executor-side gate is documented as not expressible in a one-shot qlib
+   backtest — here we implement it inside the strategy).
+3. **Liquidity floor**: names whose average daily dollar volume is below
+   ``liquidity_floor_adv`` are dropped from the tradable set (the proven risk
+   mitigant from exp-18: $5M floor cut drawdown 7.9%->5.4% at higher IR).
+
+Held names are never force-sold by these gates; only new entries are gated.
+Exits remain the pure TopkDropout rule.
+
+Wired into a workflow yaml like:
+
+    strategy:
+        class: HmmRiskTopk
+        module_path: tac_qlib.contrib.strategy.hmm_risk
+        kwargs:
+            signal: "<PRED>"
+            topk: 10
+            n_drop: 2
+            only_tradable: true
+            risk_degree: 0.95
+            hmm_pause_pct: 0.70
+            drawdown_pause_pct: 8.0
+            liquidity_floor_adv: 5000000
+"""
+
+from __future__ import annotations
+
+import copy
+from typing import Dict
+
+import numpy as np
+import pandas as pd
+
+from qlib.backtest.decision import TradeDecisionWO
+from qlib.backtest.position import Position
+from qlib.contrib.strategy.signal_strategy import TopkDropoutStrategy
+
+__all__ = ["HmmRiskTopk"]
+
+
+class HmmRiskTopk(TopkDropoutStrategy):
+    """TopkDropoutStrategy with HMM high-vol pause + drawdown pause + liquidity floor."""
+
+    def __init__(
+        self,
+        *,
+        hmm_pause_pct: float = 0.70,
+        drawdown_pause_pct: float = 8.0,
+        liquidity_floor_adv: float = 0.0,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.hmm_pause_pct = float(hmm_pause_pct)
+        self.drawdown_pause_pct = float(drawdown_pause_pct)
+        self.liquidity_floor_adv = float(liquidity_floor_adv)
+        self._peak_equity = 0.0
+        self._hmm_pause_active = False
+        self._drawdown_pause_active = False
+
+    # ------------------------------------------------------------- state
+    def _high_vol_active(self, trade_start) -> bool:
+        """True when HMM high-vol regime probability >= pause threshold."""
+        try:
+            from qlib.data import D
+
+            cal = D.calendar(start_time=str((trade_start - pd.Timedelta(days=10)).date()),
+                             end_time=str(trade_start.date()))
+            if len(cal) == 0:
+                return False
+            ref_date = str(pd.Timestamp(cal[-1]).date())
+            feat = D.features(
+                D.instruments("all"), ["$sp_hmm_p_regime1"], start_time=ref_date, end_time=ref_date
+            )
+            if feat is None or len(feat) == 0:
+                return False
+            p = feat["$sp_hmm_p_regime1"].dropna()
+            if len(p) == 0:
+                return False
+            return float(p.mean()) >= self.hmm_pause_pct
+        except Exception:
+            return False
+
+    def _update_pause(self, equity: float, trade_start) -> None:
+        self._peak_equity = max(self._peak_equity, equity)
+        dd = (self._peak_equity - equity) / self._peak_equity * 100.0 if self._peak_equity > 0 else 0.0
+        self._drawdown_pause_active = self.drawdown_pause_pct > 0 and dd >= self.drawdown_pause_pct
+        self._hmm_pause_active = self._high_vol_active(trade_start)
+
+    # ------------------------------------------------------------- decision
+    def generate_trade_decision(self, execute_result=None):
+        trade_step = self.trade_calendar.get_trade_step()
+        trade_start_time, trade_end_time = self.trade_calendar.get_step_time(trade_step)
+        pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
+        pred_score = self.signal.get_signal(start_time=pred_start_time, end_time=pred_end_time)
+        if pred_score is None:
+            return TradeDecisionWO([], self)
+        current_temp = copy.deepcopy(self.trade_position)
+        assert isinstance(current_temp, Position)
+
+        # account equity for drawdown pause
+        equity = current_temp.get_cash()
+        for code in current_temp.get_stock_list():
+            amt = abs(current_temp.get_stock_amount(code))
+            mark = self.trade_exchange.get_deal_price(
+                stock_id=code, start_time=trade_start_time, end_time=trade_end_time, direction=1
+            )
+            if mark is not None and np.isfinite(mark):
+                equity += amt * mark
+        self._update_pause(equity, trade_start_time)
+
+        target_weight_position = self.generate_target_weight_position(
+            score=pred_score, current=current_temp, trade_start_time=trade_start_time, trade_end_time=trade_end_time
+        )
+
+        held = set(current_temp.get_stock_list())
+        held_amt = {c: abs(current_temp.get_stock_amount(c)) for c in held}
+
+        # liquidity floor: drop names below the ADV floor from BUY candidates
+        illiquid: Dict[str, bool] = {}
+        if self.liquidity_floor_adv > 0:
+            from tac_qlib.risk_limits import dollar_adv
+
+            codes = [c for c in target_weight_position if c not in held]
+            if codes:
+                adv = dollar_adv(codes, market="US", asof=str(pd.Timestamp(trade_start_time).date()), lookback=20)
+                for c in codes:
+                    illiquid[c] = adv.get(str(c).upper(), 0.0) < self.liquidity_floor_adv
+
+        buys_paused = self._hmm_pause_active or self._drawdown_pause_active
+
+        gated = {}
+        for code, w in target_weight_position.items():
+            is_new = code not in held or held_amt.get(code, 0.0) <= 1e-6
+            if is_new:
+                if buys_paused:
+                    continue  # risk gate: no new entries
+                if illiquid.get(code, False):
+                    continue  # liquidity floor: drop illiquid buy candidate
+            gated[code] = w
+
+        order_list = self.order_generator.generate_order_list_from_target_weight_position(
+            current=current_temp,
+            trade_exchange=self.trade_exchange,
+            risk_degree=self.get_risk_degree(trade_step),
+            target_weight_position=gated,
+            pred_start_time=pred_start_time,
+            pred_end_time=pred_end_time,
+            trade_start_time=trade_start_time,
+            trade_end_time=trade_end_time,
+        )
+        return TradeDecisionWO(order_list, self)