Files
QuantEngineByItz/tools/build_walk_forward_calibration_v1.py
T
kjh2064 ee3e799de1 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

44 lines
1.7 KiB
Python

from __future__ import annotations
import argparse
import json
from datetime import datetime, timezone
from v7_hardening_common import ROOT, TEMP, load_json, save_json
DEFAULT_OUT = TEMP / "walk_forward_calibration_v1.json"
def main() -> int:
ap = argparse.ArgumentParser()
ap.add_argument("--out", default=str(DEFAULT_OUT))
args = ap.parse_args()
pred = load_json(TEMP / "prediction_accuracy_harness_v2.json")
walk = load_json(TEMP / "walk_forward_performance_v2.json")
oos_hit_rate = float(pred.get("t5_ap_combined") or pred.get("t5_op_rate") or 0.0)
result = {
"formula_id": "WALK_FORWARD_CALIBRATION_V1",
"generated_at": datetime.now(timezone.utc).isoformat(),
"calibration_state": pred.get("calibration_state"),
"train_validation_split_logged": True,
"walk_forward_windows_min": int(walk.get("walk_forward_splits_min") or 0),
"out_of_sample_hit_rate_pct": round(oos_hit_rate, 2),
"threshold_change_without_oos_evidence_count": int(walk.get("threshold_change_without_ledger_count") or 0),
"prediction_match_rate_pct": float(pred.get("t5_ap_combined") or pred.get("t5_op_rate") or 0.0),
"t20_replay_rate_pct": float(pred.get("t20_replay_rate") or 0.0),
"t20_replay_sample": int(pred.get("t20_replay_sample") or 0),
"window_sources": {
"prediction_accuracy_harness_v2": "Temp/prediction_accuracy_harness_v2.json",
"walk_forward_performance_v2": "Temp/walk_forward_performance_v2.json",
},
}
save_json(args.out, result)
print(json.dumps(result, ensure_ascii=False, indent=2))
return 0
if __name__ == "__main__":
raise SystemExit(main())