add cross-sectional signal evaluation (factor rank-IC) to the backtest

The per-setup hit-rate report can't tell whether a signal predicts returns —
only how a target/stop structure built on one performs. This adds a
cross-sectional factor-IC pass: each week the universe is ranked by a price-only
signal and graded by its rank correlation (Spearman IC) and top-minus-bottom-
quintile spread against the forward 30-day return.

Candidate signals (point-in-time from price; sentiment/fundamentals have no
history in the replay): 12-1/6-1/3-1 month momentum, 1-month reversal,
price-vs-200d SMA, proximity to the 52-week high (George/Hwang), and 126-day
realized volatility (low-vol anomaly).

Reuses the existing per-ticker replay loop (no new data, no second DB pass);
results land in the cached backtest_report as `signal_eval` and render as a
"Signal edge" table in BacktestPanel beside the calibration curve.

330 backend tests pass (10 new in test_signal_eval); frontend build clean.

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

frontend/src/components/signals/BacktestPanel.tsx

@@ -22,6 +22,29 @@ function rColor(v: number | null): string {
   return 'text-gray-300';
 }
 
+const SIGNAL_LABELS: Record<string, string> = {
+  mom_12_1: '12–1 month momentum',
+  mom_6_1: '6–1 month momentum',
+  mom_3_1: '3–1 month momentum',
+  reversal_1m: '1-month reversal',
+  trend_200: 'Price vs 200-day SMA',
+  high_52w: 'Proximity to 52-week high',
+  vol_6m: '6-month realized volatility',
+};
+
+// An |IC| this large, with a consistent sign, is a real (if small) edge worth
+// building on; below it, ranking on the signal sorts essentially nothing.
+const IC_EDGE_THRESHOLD = 0.03;
+
+function icColor(v: number): string {
+  if (Math.abs(v) < 0.02) return 'text-gray-400';
+  return v > 0 ? 'text-emerald-400' : 'text-red-400';
+}
+function fmtSpread(v: number | null): string {
+  if (v === null) return '—';
+  return `${v > 0 ? '+' : ''}${(v * 100).toFixed(2)}%`;
+}
+
 function timeAgo(iso: string): string {
   const mins = Math.floor((Date.now() - new Date(iso).getTime()) / 60_000);
   if (mins < 1) return 'just now';
@@ -247,6 +270,65 @@ export function BacktestPanel() {
               )}
             </div>
 
+            {report.signal_eval && report.signal_eval.length > 0 && (
+              <div>
+                <p className="mb-2 text-xs font-medium uppercase tracking-widest text-gray-500">
+                  Signal edge (cross-sectional)
+                </p>
+                <p className="mb-2 text-[11px] text-gray-500">
+                  Does ranking the universe by a signal predict the forward {report.params.horizon_days}-day
+                  return? Mean IC is the rank correlation between signal and return, averaged over weekly
+                  rebalances. <span className="text-emerald-400">|IC| ≳ {IC_EDGE_THRESHOLD}</span> with a
+                  consistent sign (high IC&gt;0 %) is a real, if small, edge; near 0 means it sorts nothing.
+                  Momentum skips the last month; <em>reversal_1m is expected negative</em> if the universe
+                  mean-reverts. Q5−Q1 is the top-minus-bottom-quintile forward return.
+                </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">Signal</th>
+                        <th className="px-4 py-2.5 text-right">Weeks</th>
+                        <th className="px-4 py-2.5 text-right">Avg N</th>
+                        <th className="px-4 py-2.5 text-right">Mean IC</th>
+                        <th className="px-4 py-2.5 text-right">t-stat</th>
+                        <th className="px-4 py-2.5 text-right">IC&gt;0 %</th>
+                        <th className="px-4 py-2.5 text-right">Q5−Q1 fwd</th>
+                      </tr>
+                    </thead>
+                    <tbody>
+                      {report.signal_eval.map((row) => {
+                        const edge = Math.abs(row.mean_ic) >= IC_EDGE_THRESHOLD;
+                        return (
+                          <tr key={row.signal} className={`border-b border-white/[0.04] ${edge ? 'bg-emerald-400/[0.06]' : ''}`}>
+                            <td className="px-4 py-2.5 font-medium text-gray-200">
+                              {edge && <span className="mr-1 text-emerald-300">★</span>}
+                              {SIGNAL_LABELS[row.signal] ?? row.signal}
+                            </td>
+                            <td className="num px-4 py-2.5 text-right text-gray-400">{row.weeks}</td>
+                            <td className="num px-4 py-2.5 text-right text-gray-400">{row.avg_cross_section ?? '—'}</td>
+                            <td className={`num px-4 py-2.5 text-right font-semibold ${icColor(row.mean_ic)}`}>
+                              {row.mean_ic.toFixed(3)}
+                            </td>
+                            <td className="num px-4 py-2.5 text-right text-gray-300">
+                              {row.ic_t_stat === null ? '—' : row.ic_t_stat.toFixed(2)}
+                            </td>
+                            <td className="num px-4 py-2.5 text-right text-gray-300">{fmtPct(row.ic_positive_pct)}</td>
+                            <td className={`num px-4 py-2.5 text-right ${rColor(row.mean_quintile_spread)}`}>
+                              {fmtSpread(row.mean_quintile_spread)}
+                            </td>
+                          </tr>
+                        );
+                      })}
+                    </tbody>
+                  </table>
+                </div>
+                {report.signal_eval_note && (
+                  <p className="mt-2 text-[11px] text-gray-600">{report.signal_eval_note}</p>
+                )}
+              </div>
+            )}
+
             <p className="text-[11px] text-gray-600">{report.note}</p>
           </>
         )}