feat(quant-engine): v8.9 제안서 P0-P3 로드맵 채택 — 15개 의사결정 엔진 신규 구현

suggest/quant_investment_engine_v8_9_portfolio_optimizer_canonical_refactored.yaml의 implementation_todo_v8_9(P0~P4) 전체를 spec/tool/golden case 레벨로 구현. - P0: PORTFOLIO_TRANSITION_UTILITY_V1, SELL_LOT_PARETO_SELECTOR_V1, FORECAST_SIMULATION_ENGINE_V1 - P1: SECTOR_EXPOSURE_GRAPH_V1/LEADER_LIFECYCLE_GATE_V1, EXECUTION_CAPACITY_LADDER_V1, MODEL_GOVERNANCE_KILL_SWITCH_V1 - P2: SCENARIO_SHOCK_MATRIX_V1, TRANSITION_SET_ENUMERATOR_V1, IMMUTABLE_DECISION_LEDGER_V1, EXECUTION_PLAN_COMPILER_V1 - P3: STATE_VECTOR_CONSTRUCTOR_V1, WALK_FORWARD_BOOTSTRAP_V1, TRANSITION_SET_ENUMERATOR_V1(MRC/CVaR 확장), REBALANCE_CADENCE_GATE_V1, WEEKLY_LEGACY_TRANSFER_PLAN_V1 기존 regime/cluster 연동 정책 수치(현금방어선, 반도체 cap)는 그대로 유지하고 신규 cap 필드만 추가. spec/09_decision_flow.yaml과 runtime/active_artifact_manifest.yaml에 전 엔진 배선 완료. governance/todo/v8_9_p{0,1,2,3}_adoption_plan.yaml에 각 단계 작업 추적 기록. 검증: validate_specs/validate_golden_coverage_100(100%)/validate_calibration_registry_v1/ validate_schema_model_generation_v1/validate_agents_shrink_v1 전부 PASS. golden test 53/53 PASS. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 00:06:52 +09:00
parent aed1eae421
commit aedabdd37b
82 changed files with 7515 additions and 5 deletions
@@ -0,0 +1,124 @@
+#!/usr/bin/env python3
+"""WALK_FORWARD_BOOTSTRAP_V1 — spec/formulas/domains/simulation.yaml.
+
+Generates net_profit_distribution_after_tax_fee_slippage from historical_returns via
+walk-forward (non-overlapping in/out-of-sample split, block resample on out-of-sample
+only) or regime-matched (filter + resample-with-replacement) bootstrapping.
+governance/todo/v8_9_p3_adoption_plan.yaml P3-B.
+
+Hard rule: no historical_returns or fewer than 2 samples -> DATA_MISSING. Never
+interpolate or fabricate a distribution.
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import random
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+DEFAULT_HISTORICAL_RETURNS = ROOT / "Temp" / "historical_returns_v1.json"
+DEFAULT_OUT = ROOT / "Temp" / "walk_forward_bootstrap_v1.json"
+
+BLOCK_SIZE = 5
+
+
+def _load(path: Path) -> dict:
+    if not path.exists():
+        return {}
+    try:
+        data = json.loads(path.read_text(encoding="utf-8"))
+        return data if isinstance(data, dict) else {}
+    except Exception:
+        return {}
+
+
+def walk_forward_resample(historical_returns: list[dict], resample_count: int, rng: random.Random) -> list[float]:
+    sorted_returns = sorted(historical_returns, key=lambda r: r["date"])
+    split_idx = int(len(sorted_returns) * 0.7)
+    out_of_sample = sorted_returns[split_idx:]
+    if len(out_of_sample) < 2:
+        return []
+
+    values = [r["net_return_after_cost_pct"] for r in out_of_sample]
+    distribution = []
+    for _ in range(resample_count):
+        start = rng.randrange(0, max(1, len(values) - BLOCK_SIZE + 1))
+        block = values[start:start + BLOCK_SIZE]
+        distribution.append(sum(block) / len(block))
+    return distribution
+
+
+def regime_matched_resample(
+    historical_returns: list[dict], current_regime_state: str, resample_count: int, rng: random.Random
+) -> list[float]:
+    filtered = [r["net_return_after_cost_pct"] for r in historical_returns if r.get("regime_state") == current_regime_state]
+    if len(filtered) < 2:
+        return []
+    return [rng.choice(filtered) for _ in range(resample_count)]
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--historical-returns", default=str(DEFAULT_HISTORICAL_RETURNS))
+    ap.add_argument("--current-regime-state", default=None)
+    ap.add_argument("--bootstrap-method", default="walk_forward", choices=["walk_forward", "regime_matched"])
+    ap.add_argument("--resample-count", type=int, default=1000)
+    ap.add_argument("--out", default=str(DEFAULT_OUT))
+    ap.add_argument("--seed", type=int, default=None)
+    args = ap.parse_args()
+
+    doc = _load(Path(args.historical_returns))
+    historical_returns = doc.get("historical_returns") if isinstance(doc.get("historical_returns"), list) else None
+
+    if not historical_returns or len(historical_returns) < 2:
+        result = {
+            "formula_id": "WALK_FORWARD_BOOTSTRAP_V1",
+            "gate": "DATA_MISSING",
+            "net_profit_distribution_after_tax_fee_slippage": None,
+            "sample_count_total": len(historical_returns) if historical_returns else 0,
+            "sample_count_same_regime": 0,
+            "source_paths": [str(Path(args.historical_returns))],
+        }
+        out = Path(args.out)
+        out.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
+        print(json.dumps(result, ensure_ascii=False, indent=2))
+        return 0
+
+    rng = random.Random(args.seed)
+    if args.bootstrap_method == "walk_forward":
+        distribution = walk_forward_resample(historical_returns, args.resample_count, rng)
+    else:
+        distribution = regime_matched_resample(historical_returns, args.current_regime_state, args.resample_count, rng)
+
+    sample_count_same_regime = len(
+        [r for r in historical_returns if r.get("regime_state") == args.current_regime_state]
+    )
+
+    if not distribution:
+        result = {
+            "formula_id": "WALK_FORWARD_BOOTSTRAP_V1",
+            "gate": "DATA_MISSING",
+            "net_profit_distribution_after_tax_fee_slippage": None,
+            "sample_count_total": len(historical_returns),
+            "sample_count_same_regime": sample_count_same_regime,
+            "source_paths": [str(Path(args.historical_returns))],
+        }
+    else:
+        result = {
+            "formula_id": "WALK_FORWARD_BOOTSTRAP_V1",
+            "gate": "PASS",
+            "net_profit_distribution_after_tax_fee_slippage": distribution,
+            "sample_count_total": len(historical_returns),
+            "sample_count_same_regime": sample_count_same_regime,
+            "source_paths": [str(Path(args.historical_returns))],
+        }
+
+    out = Path(args.out)
+    out.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
+    print(json.dumps(result, ensure_ascii=False, indent=2))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())