feat(tickers): record delisting instead of deleting the symbol

Retiring a symbol meant delete_ticker or bootstrap_universe(prune_missing),
both of which cascade through OHLCV, setups and scores. That destroys exactly
the history four research documents already apologise for: today's tracked
universe projected backward is survivorship-biased, and hard-deleting every
delisted name is what causes it. Keeping the rows preserves the option to fix
that — it does not fix it, which needs the replay to model a delisting as an
exit event.

tickers gains delisted_on / delisted_reason (migration 032). NULL means
actively traded.

The filter is opt-in via ticker_service.active_only rather than folded into a
shared getter: the registry and admin views deliberately keep delisted rows so
the delisting is visible, and a silent default would undo that. Applied to the
live path only — scanner, momentum ranking, scoring, breadth, fundamentals
candidates, SEC universe, earnings import, ingestion loops. run_backtest keeps
them on purpose.

Detection runs off OHLCV staleness, not off the SEC fundamentals import: that
importer stalls for days on unrelated Company-Facts gaps and would take
detection down with it. On a stale symbol the scheduler asks SEC for a Form
25/25-NSE/15 and retires it only on a hit, so a halt or a rename (SATS->ECHO)
keeps the existing warning. The probe waits 3 stale days so a market-data
outage cannot turn into one SEC request per symbol per run.

Safe to automate because it is reversible: clear_delisted un-retires a false
positive, where a delete had already taken the history.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

app/services/scoring_service.py

@@ -20,7 +20,7 @@ from app.database import insert_for_session
 from app.exceptions import NotFoundError, ValidationError
 from app.models.score import CompositeScore, DimensionScore
 from app.models.ticker import Ticker
-from app.services import settings_store
+from app.services import settings_store, ticker_service
 
 logger = logging.getLogger(__name__)
 
@@ -883,7 +883,11 @@ async def get_rankings(db: AsyncSession) -> dict:
     Returns dict suitable for RankingResponse.
     """
     weights = await _get_weights(db)
-    tickers = (await db.execute(select(Ticker).order_by(Ticker.symbol))).scalars().all()
+    tickers = (
+        await db.execute(
+            ticker_service.active_only(select(Ticker).order_by(Ticker.symbol))
+        )
+    ).scalars().all()
 
     async def _load_scores() -> tuple[dict[int, CompositeScore], dict[int, dict[str, DimensionScore]]]:
         comps = {
@@ -947,7 +951,7 @@ async def update_weights(
     await _save_weights(db, full_weights)
 
     # Recompute all composite scores
-    result = await db.execute(select(Ticker))
+    result = await db.execute(ticker_service.active_only(select(Ticker)))
     tickers = list(result.scalars().all())
 
     for ticker in tickers: