feat: 리밸런싱 엔진 V1 + GAS 버그 수정 (2026-06-13)

주요 변경: - tools/build_rebalance_engine_v1.py: REBALANCE_ENGINE_V1 신규 * account_snapshot 직접 합산(_build_snap_position_map) → 소수주 분리 행 병합 * 레짐 소스 macro.REGIME_PRELIM 최우선 (GAS 와 동일) - src/gas_adapter_parts/gdf_06_rebalance.gs: runRebalanceSheet_() 신규 * Logger.log / getSpreadsheet_() 로 run_all 연동 수정 - src/gas_adapter_parts/gdc_01_fetch_fundamentals.gs * _mergePositionRecord_(): 소수주 중복 행 합산 신규 * parseInt → parseFloat (qty, availQty) - src/gas_adapter_parts/gdf_01_price_metrics.gs * 미보유 종목 SELL_READY → WATCH_EXIT_SIGNAL - spec/41_release_dag.yaml: build_rebalance_sheet 노드 추가 (step_count 63) - spec/51_formula_lifecycle_registry.yaml: REBALANCE_ENGINE_V1 등록 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-13 13:20:14 +09:00
commit ee3e799de1
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+"""build_shadow_promotion_scorecard_v1.py — spec/57: H007_SHADOW_PROMOTION_SCORECARD
+
+Evaluates shadow-stage factors against live sample count, edge improvement,
+drawdown constraint, false positive reduction, conflict rate, and provenance
+coverage. Blocks promotion if any criterion is unmet.
+
+formula_id: BUILD_SHADOW_PROMOTION_SCORECARD_V1
+contract:   spec/57_shadow_promotion_scorecard.yaml
+"""
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+
+DEFAULT_SHADOW         = ROOT / "Temp" / "shadow_ledger_v2.json"
+DEFAULT_LIVE_REPLAY    = ROOT / "Temp" / "live_replay_separation_v3.json"
+OUTPUT_PATH            = ROOT / "Temp" / "shadow_promotion_scorecard_v1.json"
+
+# Gate criteria from spec/57
+LIVE_SAMPLE_MIN          = 30
+EDGE_IMPROVEMENT_MIN_PCT = 2.0
+DRAWDOWN_TOLERANCE_PCT   = 0.5
+FALSE_POSITIVE_REDUCTION_MIN_PCT = 5.0
+CONFLICT_RATE_CAP_PCT    = 10.0
+PROVENANCE_REQUIRED_PCT  = 100.0
+
+
+def _load_json(path: Path) -> dict:
+    if not path.exists():
+        return {"_missing": True, "_path": str(path)}
+    try:
+        return json.loads(path.read_text(encoding="utf-8"))
+    except Exception as e:
+        return {"_error": str(e), "_path": str(path)}
+
+
+def _evaluate_shadow_factor(factor: dict, live_data: dict) -> dict:
+    """Evaluate a single shadow factor against promotion criteria."""
+    fid = factor.get("formula_id") or factor.get("id") or "UNKNOWN"
+    blocked_reasons = []
+
+    # Live sample count
+    live_n = factor.get("live_sample_count") or 0
+    if live_n < LIVE_SAMPLE_MIN:
+        blocked_reasons.append(
+            f"live_sample_count={live_n} < {LIVE_SAMPLE_MIN}"
+        )
+
+    # Edge improvement
+    edge_delta = factor.get("prediction_match_rate_improvement") or 0
+    if edge_delta < EDGE_IMPROVEMENT_MIN_PCT:
+        blocked_reasons.append(
+            f"edge_improvement={edge_delta}% < {EDGE_IMPROVEMENT_MIN_PCT}%"
+        )
+
+    # Drawdown constraint
+    mdd_delta = factor.get("mdd_delta_pct") or 0
+    if mdd_delta > DRAWDOWN_TOLERANCE_PCT:
+        blocked_reasons.append(
+            f"mdd_delta={mdd_delta}% > tolerance={DRAWDOWN_TOLERANCE_PCT}%"
+        )
+
+    # False positive reduction
+    fp_reduction = factor.get("false_positive_reduction_pct") or 0
+    if fp_reduction < FALSE_POSITIVE_REDUCTION_MIN_PCT:
+        blocked_reasons.append(
+            f"fp_reduction={fp_reduction}% < {FALSE_POSITIVE_REDUCTION_MIN_PCT}%"
+        )
+
+    # Conflict rate
+    conflict_rate = factor.get("conflict_rate_pct") or 0
+    if conflict_rate > CONFLICT_RATE_CAP_PCT:
+        blocked_reasons.append(
+            f"conflict_rate={conflict_rate}% > cap={CONFLICT_RATE_CAP_PCT}%"
+        )
+
+    # Provenance coverage
+    prov_pct = factor.get("provenance_coverage_pct") or 0
+    if prov_pct < PROVENANCE_REQUIRED_PCT:
+        blocked_reasons.append(
+            f"provenance={prov_pct}% < {PROVENANCE_REQUIRED_PCT}%"
+        )
+
+    promotion_allowed = len(blocked_reasons) == 0
+    return {
+        "formula_id": fid,
+        "live_sample_count": live_n,
+        "promotion_allowed": promotion_allowed,
+        "blocked_reasons": blocked_reasons,
+        "criteria_checked": 6,
+        "criteria_passed": 6 - len(blocked_reasons),
+    }
+
+
+def run(shadow_path: Path, live_replay_path: Path) -> dict:
+    shadow      = _load_json(shadow_path)
+    live_replay = _load_json(live_replay_path)
+
+    if shadow.get("_missing"):
+        result = {
+            "gate": "SKIP",
+            "reason": f"shadow_ledger missing: {shadow_path}",
+            "promotion_candidates": [],
+            "blocked_factors": [],
+            "contract": "spec/57_shadow_promotion_scorecard.yaml",
+        }
+        OUTPUT_PATH.parent.mkdir(parents=True, exist_ok=True)
+        OUTPUT_PATH.write_text(json.dumps(result, ensure_ascii=False, indent=2))
+        return result
+
+    shadow_factors = shadow.get("shadow_factors") or shadow.get("factors") or []
+    if not isinstance(shadow_factors, list):
+        shadow_factors = []
+
+    evaluations = [_evaluate_shadow_factor(f, live_replay) for f in shadow_factors]
+    candidates  = [e for e in evaluations if e["promotion_allowed"]]
+    blocked     = [e for e in evaluations if not e["promotion_allowed"]]
+
+    gate = "PASS" if len(blocked) == 0 else "WARN"
+    # FAIL only if a factor that was previously promoted (lifecycle=active) now fails
+    # WARN if shadow factors are blocked (expected for new factors)
+
+    result = {
+        "gate": gate,
+        "promotion_candidates": candidates,
+        "blocked_factors": blocked,
+        "shadow_factor_count": len(shadow_factors),
+        "live_sample_minimum": LIVE_SAMPLE_MIN,
+        "contract": "spec/57_shadow_promotion_scorecard.yaml",
+    }
+
+    OUTPUT_PATH.parent.mkdir(parents=True, exist_ok=True)
+    OUTPUT_PATH.write_text(json.dumps(result, ensure_ascii=False, indent=2))
+    return result
+
+
+def main() -> None:
+    import argparse
+    parser = argparse.ArgumentParser(description="H007 Shadow Promotion Scorecard")
+    parser.add_argument("--shadow",      default=str(DEFAULT_SHADOW))
+    parser.add_argument("--live-replay", default=str(DEFAULT_LIVE_REPLAY))
+    args = parser.parse_args()
+
+    result = run(Path(args.shadow), Path(args.live_replay))
+    gate = result.get("gate", "FAIL")
+    print(f"[H007_SHADOW_PROMOTION_SCORECARD] gate={gate} "
+          f"candidates={len(result.get('promotion_candidates', []))} "
+          f"blocked={len(result.get('blocked_factors', []))}")
+    if gate == "FAIL":
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()