exp_1187

FORMULA_NAME = "Regime Momentum Contrarian 52W Recovery Quality Hybrid (Arbitrated, v1187)"
LOGIC_VARIANT_COUNT = 3
NOTES = """mode=explore; family=regime-momentum-contrarian-52w-recovery-quality-hybrid
New hybrid family that fuses the shallow-drawdown recovery sweet spot from contrarian-52w, the regime sleeve discipline from regime-momentum-quality-value, and the conflict arbitration concept from recovery-quality-regime-momentum-hybrid. The design is intentionally not a weighted average: bull regimes prefer repaired leaders that already re-accelerated, transition regimes explicitly arbitrate between momentum leadership and recovery depth using stock-level gates, and risk-off regimes keep only resilient recoveries with quality, valuation, and trading continuity support.
Deliberate metric coverage this run: momentum uses 12_1, 6m, and 3m selectively; trend/recovery uses both 200d distance and 52-week-high distance in all branches; volatility is active in every branch; liquidity is active via trading_days_3m and avg_daily_dollar_volume_3m in transition/risk-off while avg_daily_volume_3m is zeroed; income keeps dividend_yield_ttm_pct only in risk-off and zeros dividend_ttm; valuation uses forward_pe and peg outside the bull sleeve while pe is zeroed; growth rotates to forward_eps plus free_cash_flow_growth_pct and operating_income_growth_pct while eps_growth_pct and revenue_growth_pct are zeroed; quality uses free_cash_flow_margin_pct and operating_margin_pct; size uses market_cap only in bull as a mild anti-megacap tilt; remaining raw-level fields are deliberately zeroed."""

BULL = {
    "from_52w_high_pct": (0.24, -1),
    "from_200d_ma_pct": (0.18, +1),
    "momentum_12_1_pct": (0.17, +1),
    "return_6m_pct": (0.13, +1),
    "return_3m_pct": (0.09, +1),
    "realized_vol_3m": (0.07, -1),
    "free_cash_flow_margin_pct": (0.07, +1),
    "forward_eps": (0.05, +1),
    "market_cap": (0.05, -1),
}

TRANSITION = {
    "from_52w_high_pct": (0.16, -1),
    "from_200d_ma_pct": (0.16, +1),
    "momentum_12_1_pct": (0.12, +1),
    "return_6m_pct": (0.10, +1),
    "return_3m_pct": (0.08, +1),
    "realized_vol_3m": (0.10, -1),
    "trading_days_3m": (0.06, +1),
    "avg_daily_dollar_volume_3m": (0.05, +1),
    "operating_margin_pct": (0.07, +1),
    "free_cash_flow_growth_pct": (0.05, +1),
    "forward_pe": (0.05, -1),
}

RISK_OFF = {
    "from_52w_high_pct": (0.10, -1),
    "from_200d_ma_pct": (0.18, +1),
    "realized_vol_3m": (0.16, -1),
    "operating_margin_pct": (0.13, +1),
    "free_cash_flow_margin_pct": (0.09, +1),
    "operating_income_growth_pct": (0.07, +1),
    "trading_days_3m": (0.07, +1),
    "avg_daily_dollar_volume_3m": (0.05, +1),
    "peg": (0.07, -1),
    "forward_pe": (0.04, -1),
    "dividend_yield_ttm_pct": (0.04, +1),
}

def score_universe(stocks, regime, ctx):
    def _get(obj, key, default=None):
        if isinstance(obj, dict):
            return obj.get(key, default)
        return getattr(obj, key, default)

    def _num(x):
        try:
            if x is None:
                return None
            v = float(x)
            if v != v:
                return None
            return v
        except Exception:
            return None

    def _clamp(x, lo, hi):
        if x < lo:
            return lo
        if x > hi:
            return hi
        return x

    def _regime_name(r):
        for key in (
            "regime", "name", "label", "state", "market_regime", "trend_regime",
            "primary", "phase"
        ):
            val = _get(r, key, None)
            if val is not None:
                s = str(val).strip().lower()
                if s:
                    return s
        return ""

    def _is_true(r, key):
        val = _get(r, key, None)
        if isinstance(val, bool):
            return val
        if isinstance(val, (int, float)):
            return val > 0
        if isinstance(val, str):
            return val.strip().lower() in ("1", "true", "yes", "on", "bull", "risk_on")
        return False

    def _pick_branch(r):
        name = _regime_name(r)
        if (
            "risk" in name or "bear" in name or "defensive" in name or
            "off" in name or "down" in name or _is_true(r, "risk_off") or
            _is_true(r, "is_risk_off") or _is_true(r, "bear")
        ):
            return "risk_off"
        if (
            "bull" in name or "up" in name or "on" in name or "strong" in name or
            _is_true(r, "bull") or _is_true(r, "is_bull") or _is_true(r, "risk_on")
        ):
            return "bull"
        return "transition"

    def _rank_scores(spec):
        scores = {}
        for symbol in symbols:
            scores[symbol] = 0.0

        for metric, (weight, direction) in spec.items():
            vals = []
            for symbol, stock in items:
                v = _num(_get(stock, metric, None))
                if v is not None:
                    vals.append((symbol, v))
            n = len(vals)
            if n == 0:
                continue
            vals.sort(key=lambda x: x[1])
            if n == 1:
                symbol = vals[0][0]
                scores[symbol] += weight * 0.5
                continue
            for idx, (symbol, _) in enumerate(vals):
                pct = idx / (n - 1)
                if direction < 0:
                    pct = 1.0 - pct
                scores[symbol] += weight * pct
        return scores

    def _recovery_profile(stock):
        d52 = _num(_get(stock, "from_52w_high_pct", None))
        d200 = _num(_get(stock, "from_200d_ma_pct", None))
        vol = _num(_get(stock, "realized_vol_3m", None))
        qual = _num(_get(stock, "free_cash_flow_margin_pct", None))
        if d52 is None or d200 is None:
            return 0.0

        score = 0.0

        # Prefer stocks meaningfully off highs, but not total breakdowns.
        if d52 <= -8.0 and d52 >= -32.0:
            score += 1.0
        elif d52 <= -5.0 and d52 > -8.0:
            score += 0.65
        elif d52 < -32.0 and d52 >= -45.0:
            score += 0.45
        elif d52 > -5.0:
            score -= 0.35
        else:
            score -= 0.15

        # Recovery must already be repaired above/near long trend.
        if d200 >= 12.0:
            score += 0.95
        elif d200 >= 4.0:
            score += 0.65
        elif d200 >= -2.0:
            score += 0.25
        else:
            score -= 0.75

        if vol is not None:
            if vol <= 28.0:
                score += 0.25
            elif vol >= 45.0:
                score -= 0.30

        if qual is not None:
            if qual >= 8.0:
                score += 0.20
            elif qual < 0.0:
                score -= 0.20

        return score

    def _momentum_profile(stock):
        m12 = _num(_get(stock, "momentum_12_1_pct", None))
        r6 = _num(_get(stock, "return_6m_pct", None))
        r3 = _num(_get(stock, "return_3m_pct", None))
        d200 = _num(_get(stock, "from_200d_ma_pct", None))
        vol = _num(_get(stock, "realized_vol_3m", None))

        score = 0.0
        seen = 0.0

        if m12 is not None:
            seen += 1.0
            if m12 >= 12.0:
                score += 1.0
            elif m12 >= 4.0:
                score += 0.6
            elif m12 < -8.0:
                score -= 0.8

        if r6 is not None:
            seen += 1.0
            if r6 >= 10.0:
                score += 0.85
            elif r6 >= 3.0:
                score += 0.45
            elif r6 < -10.0:
                score -= 0.75

        if r3 is not None:
            seen += 1.0
            if r3 >= 4.0:
                score += 0.55
            elif r3 < -6.0:
                score -= 0.55

        if d200 is not None:
            seen += 1.0
            if d200 >= 8.0:
                score += 0.55
            elif d200 < -4.0:
                score -= 0.55

        if vol is not None:
            seen += 1.0
            if vol >= 42.0:
                score -= 0.35
            elif vol <= 24.0:
                score += 0.10

        if seen == 0.0:
            return 0.0
        return score / seen

    def _defensive_profile(stock):
        vol = _num(_get(stock, "realized_vol_3m", None))
        opm = _num(_get(stock, "operating_margin_pct", None))
        fcfm = _num(_get(stock, "free_cash_flow_margin_pct", None))
        peg = _num(_get(stock, "peg", None))
        fpe = _num(_get(stock, "forward_pe", None))
        liq = _num(_get(stock, "trading_days_3m", None))
        ddv = _num(_get(stock, "avg_daily_dollar_volume_3m", None))
        dy = _num(_get(stock, "dividend_yield_ttm_pct", None))
        d200 = _num(_get(stock, "from_200d_ma_pct", None))

        score = 0.0
        seen = 0.0

        if vol is not None:
            seen += 1.0
            if vol <= 24.0:
                score += 1.0
            elif vol <= 32.0:
                score += 0.55
            elif vol >= 42.0:
                score -= 0.85

        if opm is not None:
            seen += 1.0
            if opm >= 12.0:
                score += 0.8
            elif opm < 0.0:
                score -= 0.7

        if fcfm is not None:
            seen += 1.0
            if fcfm >= 6.0:
                score += 0.7
            elif fcfm < 0.0:
                score -= 0.6

        if peg is not None:
            seen += 1.0
            if peg <= 1.8:
                score += 0.45
            elif peg >= 3.5:
                score -= 0.45
        elif fpe is not None:
            seen += 1.0
            if fpe <= 22.0:
                score += 0.30
            elif fpe >= 38.0:
                score -= 0.30

        if liq is not None:
            seen += 1.0
            if liq >= 58.0:
                score += 0.25
            elif liq < 45.0:
                score -= 0.25

        if ddv is not None:
            seen += 1.0
            if ddv > 0.0:
                score += 0.15

        if dy is not None:
            seen += 1.0
            if dy >= 0.8:
                score += 0.15

        if d200 is not None:
            seen += 1.0
            if d200 >= 0.0:
                score += 0.25
            elif d200 < -6.0:
                score -= 0.35

        if seen == 0.0:
            return 0.0
        return score / seen

    branch = _pick_branch(regime)
    if branch == "bull":
        spec = BULL
    elif branch == "risk_off":
        spec = RISK_OFF
    else:
        spec = TRANSITION

    if isinstance(stocks, dict):
        items = list(stocks.items())
    else:
        items = []
        for stock in stocks:
            symbol = _get(stock, "symbol", None)
            if symbol is not None:
                items.append((symbol, stock))

    symbols = [symbol for symbol, _ in items]
    base_scores = _rank_scores(spec)
    final_scores = {}

    for symbol, stock in items:
        base = base_scores.get(symbol, 0.0)
        recovery = _recovery_profile(stock)
        momentum = _momentum_profile(stock)
        defensive = _defensive_profile(stock)
        d52 = _num(_get(stock, "from_52w_high_pct", None))
        d200 = _num(_get(stock, "from_200d_ma_pct", None))

        score = base

        if branch == "bull":
            # In bull tapes, prefer repaired recoveries that have already graduated into momentum.
            if recovery > 0.45 and momentum > 0.18:
                score += 0.22 * _clamp(recovery, -1.5, 1.5)
                score += 0.18 * _clamp(momentum, -1.5, 1.5)
            elif recovery > 0.55 and momentum <= 0.0:
                score += 0.08 * _clamp(recovery, -1.5, 1.5)
                score -= 0.10
            elif momentum > 0.35 and recovery <= 0.0:
                score += 0.12 * _clamp(momentum, -1.5, 1.5)
                score -= 0.06

            if d52 is not None and d52 > -4.0:
                score -= 0.08
            if d52 is not None and d52 < -38.0:
                score -= 0.10

        elif branch == "transition":
            # Explicit conflict arbitration: choose the sleeve based on whether recovery is repaired.
            if recovery >= 0.55 and momentum >= 0.05:
                score += 0.18 * _clamp(recovery, -1.5, 1.5)
                score += 0.10 * _clamp(momentum, -1.5, 1.5)
            elif momentum >= 0.35 and recovery < 0.25:
                score += 0.16 * _clamp(momentum, -1.5, 1.5)
                score -= 0.05
            elif recovery >= 0.35 and momentum < -0.05:
                score += 0.12 * _clamp(recovery, -1.5, 1.5)
                score -= 0.08
            else:
                score += 0.08 * _clamp(recovery, -1.5, 1.5)
                score += 0.08 * _clamp(momentum, -1.5, 1.5)

            score += 0.10 * _clamp(defensive, -1.5, 1.5)

            if d200 is not None and d200 < -5.0:
                score -= 0.10

        else:
            # In risk-off, only keep recoveries that are already durable and fundamentally supported.
            if recovery > 0.25 and defensive > 0.20:
                score += 0.10 * _clamp(recovery, -1.5, 1.5)
                score += 0.22 * _clamp(defensive, -1.5, 1.5)
            else:
                score += 0.28 * _clamp(defensive, -1.5, 1.5)
                if recovery < -0.10:
                    score -= 0.06

            if momentum < -0.20:
                score -= 0.06
            if d200 is not None and d200 < -8.0:
                score -= 0.10

        final_scores[symbol] = score

    return final_scores