exp_1125

FORMULA_NAME = "Contrarian 52-Week Recovery with Quality-Regime Momentum Arbitration (v1125)"
LOGIC_VARIANT_COUNT = 4
NOTES = """mode=explore; family=contrarian-52w-recovery-quality-regime-momentum-hybrid
New hybrid family that combines deep 52-week-high contrarian recovery, quality-gated rebound repair, and regime-aware momentum confirmation through explicit arbitration instead of flat blending. The design separates washed-out rebound tapes from healthy bull tapes and stressed/risk-off tapes: when the market is damaged it rewards discounted names only if repair and business durability confirm; when the tape is healthy it lets momentum lead but still demands reasonable quality and tradability; when signals conflict, the script resolves them with branch-specific gates and penalties rather than averaging them away.
Deliberate metric coverage: actively use one recovery cluster (from_52w_high_pct plus from_200d_ma_pct), one momentum cluster (return_3m_pct, return_6m_pct, momentum_12_1_pct, with return_12m_pct only as a conflict penalty), one volatility check, all three liquidity checks, one income check, one valuation cluster (peg plus forward_pe, with pe left zero), one growth cluster (revenue_growth_pct, operating_income_growth_pct, free_cash_flow_growth_pct, with eps_growth_pct and forward_eps left zero), one quality cluster (operating_margin_pct plus free_cash_flow_margin_pct), and one size tilt (market_cap only). Deliberately weight return_1m_pct, pe, eps_growth_pct, forward_eps, shares_outstanding, close, adj_close, high_52w, ma_200d, eps_ttm, revenue_ttm, operating_income_ttm, and free_cash_flow_ttm at zero this run to avoid collapsing into the parent stacks while still considering the full menu consciously. Sparse fundamentals are normalized by present weight before sleeve arbitration."""

WASHED_OUT_RECOVERY = {
    "from_52w_high_pct": (0.26, -1),
    "from_200d_ma_pct": (0.18, +1),
    "return_3m_pct": (0.08, +1),
    "return_6m_pct": (0.04, +1),
    "realized_vol_3m": (0.08, -1),
    "avg_daily_dollar_volume_3m": (0.06, +1),
    "trading_days_3m": (0.04, +1),
    "dividend_yield_ttm_pct": (0.03, +1),
    "peg": (0.05, -1),
    "revenue_growth_pct": (0.05, +1),
    "operating_income_growth_pct": (0.04, +1),
    "operating_margin_pct": (0.05, +1),
    "free_cash_flow_margin_pct": (0.04, +1),
    "market_cap": (0.04, -1),
}

CALM_BULL = {
    "from_200d_ma_pct": (0.15, +1),
    "momentum_12_1_pct": (0.16, +1),
    "return_6m_pct": (0.10, +1),
    "from_52w_high_pct": (0.08, -1),
    "realized_vol_3m": (0.05, -1),
    "avg_daily_volume_3m": (0.05, +1),
    "avg_daily_dollar_volume_3m": (0.04, +1),
    "forward_pe": (0.05, -1),
    "revenue_growth_pct": (0.05, +1),
    "free_cash_flow_growth_pct": (0.05, +1),
    "operating_margin_pct": (0.06, +1),
    "free_cash_flow_margin_pct": (0.06, +1),
    "market_cap": (0.03, -1),
}

STRESSED_BULL = {
    "from_200d_ma_pct": (0.16, +1),
    "from_52w_high_pct": (0.13, -1),
    "return_3m_pct": (0.08, +1),
    "momentum_12_1_pct": (0.07, +1),
    "realized_vol_3m": (0.12, -1),
    "avg_daily_dollar_volume_3m": (0.07, +1),
    "trading_days_3m": (0.05, +1),
    "dividend_ttm": (0.03, +1),
    "peg": (0.05, -1),
    "operating_income_growth_pct": (0.05, +1),
    "free_cash_flow_growth_pct": (0.04, +1),
    "operating_margin_pct": (0.08, +1),
    "free_cash_flow_margin_pct": (0.07, +1),
}

RISK_OFF = {
    "realized_vol_3m": (0.18, -1),
    "from_200d_ma_pct": (0.14, +1),
    "from_52w_high_pct": (0.12, -1),
    "avg_daily_dollar_volume_3m": (0.08, +1),
    "trading_days_3m": (0.08, +1),
    "forward_pe": (0.06, -1),
    "peg": (0.05, -1),
    "revenue_growth_pct": (0.04, +1),
    "operating_income_growth_pct": (0.06, +1),
    "operating_margin_pct": (0.10, +1),
    "free_cash_flow_margin_pct": (0.09, +1),
}

def score_universe(stocks, regime, ctx):
    def pick_branch():
        bull = regime.get("bull", False)
        breadth = regime.get("breadth")
        vol = regime.get("avg_realized_vol_3m")
        median_200d = regime.get("median_from_200d_ma_pct")
        median_momo = regime.get("median_momentum_12_1_pct")

        if bull and breadth is not None and breadth >= 0.60 and vol is not None and vol <= 0.32:
            return "calm_bull"
        if bull and (
            (vol is not None and vol > 0.32) or
            (breadth is not None and breadth < 0.60)
        ):
            return "stressed_bull"
        if (not bull) and (
            (median_200d is not None and median_200d > -2.0) or
            (median_momo is not None and median_momo > 2.0)
        ):
            return "washed_out_recovery"
        return "risk_off"

    branch = pick_branch()

    if branch == "calm_bull":
        weights = CALM_BULL
    elif branch == "stressed_bull":
        weights = STRESSED_BULL
    elif branch == "washed_out_recovery":
        weights = WASHED_OUT_RECOVERY
    else:
        weights = RISK_OFF

    z_cache = {}
    for metric in weights:
        z_cache[metric] = ctx.z(metric)

    def weighted_score(symbol, spec):
        total = 0.0
        used = 0.0
        for metric, pair in spec.items():
            weight, direction = pair
            zmap = z_cache.get(metric)
            if not zmap:
                continue
            val = zmap.get(symbol)
            if val is None:
                continue
            total += weight * direction * val
            used += weight
        if used <= 0.0:
            return None
        return total / used

    out = {}
    for stock in stocks:
        symbol = stock["symbol"]

        price_repair_spec = {
            "from_52w_high_pct": weights.get("from_52w_high_pct", (0.0, -1)),
            "from_200d_ma_pct": weights.get("from_200d_ma_pct", (0.0, +1)),
            "return_3m_pct": weights.get("return_3m_pct", (0.0, +1)),
            "return_6m_pct": weights.get("return_6m_pct", (0.0, +1)),
            "momentum_12_1_pct": weights.get("momentum_12_1_pct", (0.0, +1)),
            "realized_vol_3m": weights.get("realized_vol_3m", (0.0, -1)),
            "market_cap": weights.get("market_cap", (0.0, -1)),
        }
        durability_spec = {
            "avg_daily_volume_3m": weights.get("avg_daily_volume_3m", (0.0, +1)),
            "avg_daily_dollar_volume_3m": weights.get("avg_daily_dollar_volume_3m", (0.0, +1)),
            "trading_days_3m": weights.get("trading_days_3m", (0.0, +1)),
            "dividend_yield_ttm_pct": weights.get("dividend_yield_ttm_pct", (0.0, +1)),
            "dividend_ttm": weights.get("dividend_ttm", (0.0, +1)),
            "forward_pe": weights.get("forward_pe", (0.0, -1)),
            "peg": weights.get("peg", (0.0, -1)),
            "revenue_growth_pct": weights.get("revenue_growth_pct", (0.0, +1)),
            "operating_income_growth_pct": weights.get("operating_income_growth_pct", (0.0, +1)),
            "free_cash_flow_growth_pct": weights.get("free_cash_flow_growth_pct", (0.0, +1)),
            "operating_margin_pct": weights.get("operating_margin_pct", (0.0, +1)),
            "free_cash_flow_margin_pct": weights.get("free_cash_flow_margin_pct", (0.0, +1)),
        }

        repair = weighted_score(symbol, price_repair_spec)
        durability = weighted_score(symbol, durability_spec)

        if repair is None and durability is None:
            continue
        if repair is None:
            repair = durability * 0.70
        if durability is None:
            durability = repair * 0.55

        price_gap = stock.get("from_52w_high_pct")
        dist_200d = stock.get("from_200d_ma_pct")
        ret_12m = stock.get("return_12m_pct")
        vol = stock.get("realized_vol_3m")
        breadth = regime.get("breadth")
        bull = regime.get("bull", False)

        score = 0.0

        if branch == "washed_out_recovery":
            if price_gap is not None and price_gap > -0.18:
                score -= 0.35
            if dist_200d is not None and dist_200d < -0.18:
                score -= 0.55
            if repair >= 0.20 and durability >= -0.10:
                score += 0.72 * repair + 0.28 * durability
            elif durability >= 0.35 and repair >= -0.05:
                score += 0.55 * repair + 0.45 * durability
            else:
                score += 0.42 * repair + 0.58 * durability
            if vol is not None and vol > 0.60:
                score -= 0.18
            if ret_12m is not None and ret_12m > 55.0 and durability < 0.10:
                score -= 0.20
        elif branch == "calm_bull":
            score += 0.60 * repair + 0.40 * durability
            if durability >= 0.15:
                score += 0.10 * repair
            if price_gap is not None and price_gap < -0.45 and durability < 0.0:
                score -= 0.22
            if ret_12m is not None and ret_12m < -15.0:
                score -= 0.10
        elif branch == "stressed_bull":
            score += 0.48 * repair + 0.52 * durability
            if repair > 0.35 and durability < -0.15:
                score -= 0.20
            if durability > 0.30 and repair > -0.10:
                score += 0.12
            if vol is not None and vol > 0.55:
                score -= 0.10
        else:
            score += 0.32 * repair + 0.68 * durability
            if repair < -0.25:
                score -= 0.15
            if durability > 0.20 and repair > -0.10:
                score += 0.10
            if price_gap is not None and price_gap > -0.10:
                score -= 0.08

        if bull and breadth is not None and breadth > 0.72 and durability is not None and durability < -0.20:
            score -= 0.10
        if (not bull) and dist_200d is not None and dist_200d > 0.12 and repair is not None and repair < 0.0:
            score -= 0.08

        out[symbol] = score

    return out