deepen OHLCV history + make the factor-IC pass honest about overlap/regime

Two changes so the cross-sectional signal results can actually be trusted.

(a) History depth — the binding constraint. Ingestion defaulted to 365 days, so
long-lookback factors (12-month momentum, 52-week high) were only computable on a
handful of weeks at the tail, and every IC reflected a single market regime.
- New `settings.ohlcv_history_days` (default 1825 ≈ 5y); new tickers backfill this
  far instead of 1 year.
- New manual "data_backfill" job (Admin → Jobs) re-fetches the full window for
  every ticker, ignoring incremental resume — run once to deepen existing
  1-year histories. Idempotent (upsert); resumes after rate limits.

(b) Factor-IC honesty. The IC was averaged over weekly rebalances whose 30-day
forward windows overlap, inflating the t-stat ~sqrt(6)x.
- IC now measured on NON-OVERLAPPING windows (weeks thinned to ~HORIZON apart).
- Each signal carries a `reliable` flag (>= 12 independent windows); BacktestPanel
  greys out and de-stars thin signals so a lucky 9-week IC of 0.3 can't masquerade
  as an edge.

332 backend tests pass; frontend build clean. No migration (config + job + an
added JSON field on the cached backtest report).

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

app/services/admin_service.py

@@ -538,6 +538,7 @@ async def get_pipeline_readiness(db: AsyncSession) -> list[dict]:
 
 VALID_JOB_NAMES = {
     "data_collector",
+    "data_backfill",
     "sentiment_collector",
     "fundamental_collector",
     "rr_scanner",
@@ -552,6 +553,7 @@ VALID_JOB_NAMES = {
 
 JOB_LABELS = {
     "data_collector": "Data Collector (OHLCV)",
+    "data_backfill": "Data Backfill (deep history)",
     "sentiment_collector": "Sentiment Collector",
     "fundamental_collector": "Fundamental Collector",
     "rr_scanner": "R:R Scanner",