feat: add strategy variant lab and signal context snapshots

Backtest report now includes research-only hold-to-horizon portfolio variants comparing raw vs residual 12-1 momentum, cutoff 80 vs 90, max 10 vs 15 positions, and SPY-200 risk scaling. A dynamic research recommendation panel flags residual momentum, cutoff 90, or regime scaling only when transparent promotion rules pass. Adds signal_context_snapshots with migration 016 and captures one point-in-time context row per newly generated TradeSetup: setup fields, composite/dimensions, latest sentiment, latest fundamentals, and strategy_version=momentum_12_1_rr_time_v1. This is forward-only; no historical sentiment/fundamental backfill is attempted. No live gate, paper-trade exit, or production ranking behavior changes. Verification: 458 backend tests pass, ruff check app/ clean, frontend npm run build clean. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-02 16:25:04 +02:00
parent 13374087db
commit 80b4113280
10 changed files with 885 additions and 28 deletions
@@ -0,0 +1,110 @@
+"""Tests for point-in-time signal context snapshots."""
+
+from __future__ import annotations
+
+import json
+from datetime import date, datetime, timezone
+
+import pytest
+
+from app.models.fundamental import FundamentalData
+from app.models.score import CompositeScore, DimensionScore
+from app.models.sentiment import SentimentScore
+from app.models.signal_context_snapshot import SignalContextSnapshot
+from app.models.ticker import Ticker
+from app.models.trade_setup import TradeSetup
+from app.services import rr_scanner_service as rr
+from tests.conftest import _test_session_factory  # type: ignore
+
+
+@pytest.fixture
+async def session():
+    async with _test_session_factory() as s:
+        yield s
+
+
+async def test_create_signal_context_snapshot_captures_latest_context(session):
+    now = datetime(2026, 7, 2, 12, tzinfo=timezone.utc)
+    ticker = Ticker(symbol="CTX")
+    session.add(ticker)
+    await session.flush()
+
+    session.add_all([
+        DimensionScore(
+            ticker_id=ticker.id,
+            dimension="technical",
+            score=71.0,
+            is_stale=False,
+            computed_at=now,
+        ),
+        DimensionScore(
+            ticker_id=ticker.id,
+            dimension="momentum",
+            score=82.0,
+            is_stale=False,
+            computed_at=now,
+        ),
+        CompositeScore(
+            ticker_id=ticker.id,
+            score=76.5,
+            is_stale=False,
+            weights_json='{"technical": 0.25}',
+            computed_at=now,
+        ),
+        SentimentScore(
+            ticker_id=ticker.id,
+            classification="BULLISH",
+            confidence=78,
+            source="test",
+            timestamp=now,
+            reasoning="",
+            citations_json="[]",
+            recommendation="BUY",
+        ),
+        FundamentalData(
+            ticker_id=ticker.id,
+            pe_ratio=25.0,
+            revenue_growth=0.18,
+            earnings_surprise=0.05,
+            market_cap=1_000_000_000.0,
+            next_earnings_date=date(2026, 8, 1),
+            fetched_at=now,
+            unavailable_fields_json="{}",
+        ),
+    ])
+    setup = TradeSetup(
+        ticker_id=ticker.id,
+        direction="long",
+        entry_price=100.0,
+        stop_loss=95.0,
+        target=120.0,
+        rr_ratio=4.0,
+        composite_score=76.5,
+        detected_at=now,
+        confidence_score=64.0,
+        momentum_percentile=88.0,
+        recommended_action="LONG_HIGH",
+        risk_level="Low",
+    )
+    session.add(setup)
+    await session.flush()
+
+    await rr._create_signal_context_snapshots(session, [setup])
+    await session.commit()
+
+    row = (await session.get(SignalContextSnapshot, 1))
+    assert row is not None
+    assert row.trade_setup_id == setup.id
+    assert row.strategy_version == rr.STRATEGY_VERSION
+    assert row.momentum_percentile == 88.0
+
+    score = json.loads(row.score_context_json)
+    sentiment = json.loads(row.sentiment_context_json)
+    fundamental = json.loads(row.fundamental_context_json)
+
+    assert score["composite_score"] == 76.5
+    assert score["dimensions"]["technical"]["score"] == 71.0
+    assert sentiment["classification"] == "BULLISH"
+    assert sentiment["confidence"] == 78
+    assert fundamental["pe_ratio"] == 25.0
+    assert fundamental["next_earnings_date"] == "2026-08-01"