Fix O(n^2) blowup and look-ahead leak in SMC/divergence backtest scoring

market_structure() (SMC) and detect_divergence() were each precomputed
once over the ENTIRE multi-year backtest range and reused unchanged for
every candle, so every candle's score could see results derived from
years of future price data — a look-ahead bug that inflated both
single-run backtest and walk-forward results, undermining the very
overfitting check walk-forward exists to provide. A prior fix bounded
this to a per-candle trailing window, which closed most of the leak but
still rescanned pivots from scratch on every candle (O(window) per
candle), too slow to enable 15m/30m walk-forward runs.

The real fix: pivot detection is itself a bounded rolling-window scan
(each position only depends on a few bars on either side), so it can be
precomputed once for the whole dataset just like BB/RSI/MACD. Per candle,
_compute_scores_series now just advances a monotonic pointer over
already-known pivots to whatever is causally confirmable as of that
candle — O(1) amortized across the whole run instead of O(window) or
O(n) per candle. Added an optional precomputed_pivots param to
detect_divergence() (backward compatible) to reuse this for RSI/MACD
divergence too.

Net effect: 16,000 candles went from 16.1s to 1.7s (confirmed empirically,
on top of an earlier ~10x from fixing the raw O(n^2)), and scaling stays
linear at 32,000 candles (3.2s). Walk-forward's timeframe options are now
15m/30m/1h/4h/1d (up from 1h/4h/1d) since 15m at the 3-year default
lookback now costs roughly 30s instead of 5+ minutes. Also wired
walk_forward.py's grid search to actually reuse one computed score series
across all 27 parameter combinations per fold (it was recomputing full
classification for every combination despite the scoring/threshold split
added earlier). 156 backend tests passing (3 new: causal-score regression,
pivot-detection-runs-once, order-block-window-bounded).

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

backend/app/api/v1/walk_forward.py

@@ -30,7 +30,7 @@ router = APIRouter(prefix="/walk-forward", tags=["walk_forward"])
 async def run(
     symbol: str = Query("BTC/USDT"),
     exchange: str = Query("mexc"),
-    timeframe: str = Query("4h", description="1h or 4h recommended — lower timeframes multiply the candle count and runtime"),
+    timeframe: str = Query("4h", description="15m/30m/1h/4h/1d — 1w/1M don't have enough candles over a multi-year lookback to form meaningful folds"),
     total_days: int = Query(1095, ge=180, le=1825, description="Total lookback in days (default ~3 years)"),
     train_days: int = Query(270, ge=30, description="Train window size per fold, in days"),
     test_days: int = Query(90, ge=14, description="Held-out test window size per fold, in days"),