replace EV activation gate with cross-sectional 12-1 momentum ranking

The 5-year backtest confirmed the EV gate adds negative value (high threshold =
worst expectancy) and that 12-1 month momentum is the one price signal with a
plausible, right-signed cross-sectional IC (~0.05). So "qualified" now means:
clears the R:R + confidence floors AND the ticker ranks in the top
`min_momentum_percentile` of the universe by 12-1 momentum that week.

- qualification.py: drop expected_value_r / the EV gate; add a momentum-percentile
  gate (duck-typed `momentum_percentile`, only enforced when attached + threshold
  set, else defers to floors). Mirrored in frontend qualification.ts.
- activation config/schema: min_expected_value -> min_momentum_percentile
  (default 80 = top quintile). ActivationSettings, DashboardPage (ranks/【shows】
  momentum instead of EV), and the BacktestPanel sweep follow.
- backtest: rank each ISO week's universe by 12-1 momentum, assign a percentile,
  and qualify the top slice; the sweep now sweeps the percentile cutoff.

Also offload the backtest's per-ticker compute to a worker thread so the heavy
~5y run no longer blocks the API event loop (the "backend offline" flicker).

Production setups don't carry momentum_percentile yet — wiring the scanner to
attach it (a universe momentum-rank step) is the next step; until then the live
gate defers to floors while the backtest measures the momentum selection. 330
backend tests pass; frontend build clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

frontend/src/components/admin/ActivationSettings.tsx

@@ -4,7 +4,7 @@ import { useActivationSettings, useUpdateActivationSettings } from '../../hooks/
 import { SkeletonTable } from '../ui/Skeleton';
 
 const DEFAULTS: ActivationConfig = {
-  min_expected_value: 0.15,
+  min_momentum_percentile: 80,
   min_rr: 1.2,
   min_confidence: 55,
   min_target_probability: 0,
@@ -40,26 +40,27 @@ export function ActivationSettings() {
         <h3 className="text-sm font-semibold text-gray-200">Activation Gate</h3>
         <p className="mt-1 text-xs text-gray-500">
           What counts as a signal worth acting on. Drives the Dashboard's "Qualified" metric, the
-          Signals "Qualified only" view, and the Track Record's qualified stats. The core test is
-          <span className="text-gray-300"> expected value</span> — probability-weighted asymmetry —
-          so R:R and target probability no longer fight each other. All setups are still evaluated
-          regardless; tune the EV floor against the Track Record's EV sweep to see what actually wins.
+          Signals "Qualified only" view, and the Track Record's qualified stats. The core selection is
+          <span className="text-gray-300"> cross-sectional momentum</span> — the ticker must rank in the
+          top slice of the universe by 12-1 month momentum, the one signal the backtest showed predicts
+          forward returns. R:R and confidence stay as floors. Tune the cutoff against the Track Record's
+          momentum sweep to see what actually wins.
         </p>
       </div>
 
       <div className="grid gap-4 md:grid-cols-3">
         <label className="block space-y-1">
-          <span className="text-xs text-gray-400">Min Expected Value (R)</span>
+          <span className="text-xs text-gray-400">Min Momentum Percentile</span>
           <input
             type="number"
-            min={-1}
-            max={10}
-            step={0.05}
-            value={form.min_expected_value}
-            onChange={(e) => setForm((prev) => ({ ...prev, min_expected_value: Number(e.target.value) }))}
+            min={0}
+            max={100}
+            step={5}
+            value={form.min_momentum_percentile}
+            onChange={(e) => setForm((prev) => ({ ...prev, min_momentum_percentile: Number(e.target.value) }))}
             className="w-full input-glass px-3 py-2 text-sm"
           />
-          <span className="text-[11px] text-gray-600">p·R:R − (1−p), in R. 0.15 ≈ +0.15× risk/trade. The core gate.</span>
+          <span className="text-[11px] text-gray-600">Ticker's 12-1 momentum rank. 80 = top 20% of the universe. 0 disables. The core gate.</span>
         </label>
         <label className="block space-y-1">
           <span className="text-xs text-gray-400">Min Risk:Reward (1 : x)</span>
@@ -89,7 +90,7 @@ export function ActivationSettings() {
 
       <div className="border-t border-white/[0.06] pt-4">
         <p className="text-xs font-medium uppercase tracking-widest text-gray-500">Optional tighteners</p>
-        <p className="mt-1 text-[11px] text-gray-600">Off by default — turn on to be more selective on top of the EV gate.</p>
+        <p className="mt-1 text-[11px] text-gray-600">Off by default — turn on to be more selective on top of the momentum gate.</p>
         <div className="mt-3 grid gap-3 md:grid-cols-3">
           <label className="block space-y-1">
             <span className="text-xs text-gray-400">Min Target Probability (%)</span>

frontend/src/components/signals/BacktestPanel.tsx

@@ -184,19 +184,19 @@ export function BacktestPanel() {
             {report.sweep && report.sweep.length > 0 && (
               <div>
                 <p className="mb-2 text-xs font-medium uppercase tracking-widest text-gray-500">
-                  Min expected-value sweep
+                  Momentum-percentile sweep
                 </p>
                 <p className="mb-2 text-[11px] text-gray-500">
-                  How many setups qualify — and how they perform — at each expected-value gate (other
-                  gate conditions held fixed). EV is in R: 0.15 means +0.15× your risk per trade on
-                  average. Lower = more trades, watch that expectancy holds. Your current setting is
+                  How many setups qualify — and how they perform — at each momentum-rank cutoff (floors
+                  held fixed). 80 = only the top 20% of the universe by 12-1 momentum each week; 0 =
+                  floors only. Lower = more trades, watch that expectancy holds. Your current setting is
                   highlighted; set it in Admin → Settings → Activation.
                 </p>
                 <div className="glass overflow-x-auto">
                   <table className="w-full text-sm">
                     <thead>
                       <tr className="border-b border-white/[0.06] text-left text-xs uppercase tracking-wider text-gray-500">
-                        <th className="px-4 py-2.5">Min EV (R)</th>
+                        <th className="px-4 py-2.5">Min momentum %ile</th>
                         <th className="px-4 py-2.5 text-right">Qualified</th>
                         <th className="px-4 py-2.5 text-right">Wins</th>
                         <th className="px-4 py-2.5 text-right">Losses</th>
@@ -207,12 +207,12 @@ export function BacktestPanel() {
                     </thead>
                     <tbody>
                       {report.sweep.map((row) => {
-                        const current = Math.abs(row.min_expected_value - report.min_expected_value) < 0.001;
+                        const current = Math.abs(row.min_momentum_percentile - report.min_momentum_percentile) < 0.001;
                         return (
-                          <tr key={row.min_expected_value} className={`border-b border-white/[0.04] ${current ? 'bg-blue-400/10' : ''}`}>
+                          <tr key={row.min_momentum_percentile} className={`border-b border-white/[0.04] ${current ? 'bg-blue-400/10' : ''}`}>
                             <td className="num px-4 py-2.5 text-gray-200">
                               {current && <span className="mr-1 text-blue-300">★</span>}
-                              {row.min_expected_value.toFixed(2)}
+                              {row.min_momentum_percentile.toFixed(0)}
                             </td>
                             <td className="num px-4 py-2.5 text-right text-gray-200">{row.total}</td>
                             <td className="num px-4 py-2.5 text-right text-emerald-400">{row.wins}</td>

frontend/src/lib/qualification.ts

@@ -13,21 +13,6 @@ export function primaryTargetProbability(setup: TradeSetup): number | null {
   return setup.targets?.length ? bestTargetProbability(setup) : null;
 }
 
-/**
- * Expected value per unit of risk, in R. Probability-weighted payoff:
- *   EV = p·(R:R) − (1 − p)
- * where p is the primary target's hit probability. This is the single "is this
- * worth taking" number — it rewards both a good payoff ratio and a likely
- * target, so a fat-but-improbable target can't outrank a solid, probable one.
- * Returns null when no target probability is known.
- */
-export function expectedValueR(setup: TradeSetup): number | null {
-  const prob = primaryTargetProbability(setup);
-  if (prob == null) return null;
-  const p = prob / 100;
-  return p * setup.rr_ratio - (1 - p);
-}
-
 /** R:R recomputed from the current price (0 if no reward/risk left). */
 export function liveRiskReward(setup: TradeSetup, currentPrice: number): number {
   const reward = setup.direction === 'long' ? setup.target - currentPrice : currentPrice - setup.target;
@@ -48,10 +33,12 @@ export function qualifiesSetup(setup: TradeSetup, config: ActivationConfig): boo
     return false;
   }
   if ((setup.confidence_score ?? 0) < config.min_confidence) return false;
-  // Expected value (R) is the core gate. Only enforced when computable — setups
-  // without target probabilities defer to the R:R + confidence floors above.
-  const ev = expectedValueR(setup);
-  if (ev != null && ev < config.min_expected_value) return false;
+  // Cross-sectional momentum is the core selection — only enforced when a
+  // percentile is attached and a threshold is set; otherwise defer to the floors.
+  if (config.min_momentum_percentile > 0 && setup.momentum_percentile != null
+      && setup.momentum_percentile < config.min_momentum_percentile) {
+    return false;
+  }
   if (config.require_high_conviction && !HIGH_CONVICTION_ACTIONS.has(setup.recommended_action ?? '')) {
     return false;
   }
@@ -64,7 +51,9 @@ export function qualifiesSetup(setup: TradeSetup, config: ActivationConfig): boo
 
 /** Short human summary of the active gate, e.g. for tooltips/labels. */
 export function activationSummary(config: ActivationConfig): string {
-  const parts = [`EV ≥ ${config.min_expected_value.toFixed(2)}R`, `R:R ≥ ${config.min_rr.toFixed(1)}`, `conf ≥ ${config.min_confidence.toFixed(0)}%`];
+  const parts = [];
+  if (config.min_momentum_percentile > 0) parts.push(`top ${(100 - config.min_momentum_percentile).toFixed(0)}% momentum`);
+  parts.push(`R:R ≥ ${config.min_rr.toFixed(1)}`, `conf ≥ ${config.min_confidence.toFixed(0)}%`);
   if (config.require_high_conviction) parts.push('high-conviction');
   if (config.exclude_conflicts) parts.push('clean');
   if (config.min_target_probability > 0) parts.push(`target ≥ ${config.min_target_probability.toFixed(0)}%`);

frontend/src/lib/types.ts

@@ -134,6 +134,7 @@ export interface TradeSetup {
   outcome_date: string | null;
   evaluated_at: string | null;
   current_price: number | null;
+  momentum_percentile?: number | null;
   recommendation_summary?: RecommendationSummary;
 }
 
@@ -158,7 +159,7 @@ export interface PerformanceStats {
 
 // Activation gate: what counts as an actionable signal
 export interface ActivationConfig {
-  min_expected_value: number;
+  min_momentum_percentile: number;
   min_rr: number;
   min_confidence: number;
   min_target_probability: number;
@@ -221,7 +222,7 @@ export interface BacktestCalibrationRow {
 }
 
 export interface BacktestSweepRow extends BacktestBucket {
-  min_expected_value: number;
+  min_momentum_percentile: number;
 }
 
 export interface BacktestSignalEvalRow {
@@ -244,7 +245,7 @@ export interface BacktestReport {
   overall_qualified: BacktestBucket;
   overall_all: BacktestBucket;
   by_direction: Record<string, BacktestBucket>;
-  min_expected_value: number;
+  min_momentum_percentile: number;
   sweep: BacktestSweepRow[];
   calibration: BacktestCalibrationRow[];
   signal_eval?: BacktestSignalEvalRow[];

frontend/src/pages/DashboardPage.tsx

@@ -12,7 +12,7 @@ import { OpenTradesPanel } from '../components/dashboard/OpenTradesPanel';
 import { SkeletonCard, SkeletonTable } from '../components/ui/Skeleton';
 import { formatPrice } from '../lib/format';
 import { recommendationActionLabel } from '../lib/recommendation';
-import { qualifiesSetup, activationSummary, primaryTargetProbability, expectedValueR } from '../lib/qualification';
+import { qualifiesSetup, activationSummary, primaryTargetProbability } from '../lib/qualification';
 import type { TradeSetup } from '../lib/types';
 
 function fmtR(value: number | null): string {
@@ -69,12 +69,12 @@ export default function DashboardPage() {
   );
 
   // Show qualified setups first; fall back to the full list when none qualify.
-  // Rank by expected value (R) so the best opportunity sits at the top.
+  // Rank by 12-1 momentum percentile so the strongest names sit at the top.
   const showingQualified = qualifiedSetups.length > 0;
   const topSetups: TradeSetup[] = useMemo(() => {
     const pool = showingQualified ? qualifiedSetups : trades.data ?? [];
     return [...pool]
-      .sort((a, b) => (expectedValueR(b) ?? -Infinity) - (expectedValueR(a) ?? -Infinity))
+      .sort((a, b) => (b.momentum_percentile ?? -Infinity) - (a.momentum_percentile ?? -Infinity))
       .slice(0, 5);
   }, [showingQualified, qualifiedSetups, trades.data]);
 
@@ -176,13 +176,12 @@ export default function DashboardPage() {
                       <th className="px-4 py-3 text-right">Entry</th>
                       <th className="px-4 py-3 text-right">R:R</th>
                       <th className="px-4 py-3 text-right">Target&nbsp;Prob</th>
-                      <th className="px-4 py-3 text-right">Exp.&nbsp;Value</th>
+                      <th className="px-4 py-3 text-right">Momentum</th>
                       <th className="hidden px-4 py-3 md:table-cell">Action</th>
                     </tr>
                   </thead>
                   <tbody>
                     {topSetups.map((setup, i) => {
-                      const ev = expectedValueR(setup);
                       const isTopPick = i === 0;
                       return (
                         <tr
@@ -212,8 +211,8 @@ export default function DashboardPage() {
                               return p != null ? `${Math.round(p)}%` : '—';
                             })()}
                           </td>
-                          <td className={`num px-4 py-3 text-right font-semibold ${rColor(ev)}`}>
-                            {fmtR(ev)}
+                          <td className="num px-4 py-3 text-right font-semibold text-gray-200">
+                            {setup.momentum_percentile != null ? `${Math.round(setup.momentum_percentile)}%ile` : '—'}
                           </td>
                           <td className="hidden px-4 py-3 text-xs text-gray-400 md:table-cell">
                             {recommendationActionLabel(setup.recommended_action)}
@@ -225,7 +224,7 @@ export default function DashboardPage() {
                 </table>
                 <div className="flex items-center justify-between border-t border-white/[0.04] px-4 py-2.5">
                   <span className="text-[11px] text-gray-500">
-                    Exp. Value = probability-weighted payoff per unit of risk
+                    Momentum = ticker's 12-1 month rank across the universe (higher = stronger)
                   </span>
                   <Link to="/signals" className="text-xs font-medium text-blue-300 hover:text-blue-200 transition-colors">
                     All setups →