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
1474 changed files with 176087 additions and 0 deletions
@@ -0,0 +1,186 @@
+"""build_horizon_rebalance_plan_v1.py — HORIZON_REBALANCE_PLAN_V1
+
+routing_gate=FAIL 원인: SHORT 호라이즌 71.4% > 상한 40%.
+어떤 종목을 어떤 순서로 줄여야 하는지 결정론적으로 산출한다.
+
+입력: horizon_classification_v1.json + final_judgment_gate_v1.json + strategy_routing_audit_v1.json
+출력: Temp/horizon_rebalance_plan_v1.json
+"""
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).resolve().parents[1]
+TEMP = ROOT / "Temp"
+DEFAULT_JSON = ROOT / "GatherTradingData.json"
+DEFAULT_OUT = TEMP / "horizon_rebalance_plan_v1.json"
+FORMULA_ID = "HORIZON_REBALANCE_PLAN_V1"
+
+SHORT_CAP_PCT = 40.0
+
+
+def _load(path: Path) -> Any:
+    if not path.exists():
+        return {}
+    try:
+        return json.loads(path.read_text(encoding="utf-8"))
+    except Exception:
+        return {}
+
+
+def _f(v: Any, default: float = 0.0) -> float:
+    try:
+        return float(v)
+    except Exception:
+        return default
+
+
+def _extract_harness(payload: Any) -> dict[str, Any]:
+    if not isinstance(payload, dict):
+        return {}
+    h = payload.get("hApex")
+    dc = (payload.get("data") or {}).get("_harness_context")
+    if isinstance(h, dict) and isinstance(dc, dict):
+        m = dict(dc); m.update(h); return m
+    return h if isinstance(h, dict) else dc if isinstance(dc, dict) else payload
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--json", default=str(DEFAULT_JSON))
+    ap.add_argument("--out", default=str(DEFAULT_OUT))
+    args = ap.parse_args()
+
+    json_path = Path(args.json)
+    if not json_path.is_absolute():
+        json_path = ROOT / json_path
+    out_path = Path(args.out)
+    if not out_path.is_absolute():
+        out_path = ROOT / args.out
+
+    payload = _load(json_path)
+    harness = _extract_harness(payload)
+
+    hz = _load(TEMP / "horizon_classification_v1.json")
+    fj = _load(TEMP / "final_judgment_gate_v1.json")
+    routing = _load(TEMP / "strategy_routing_audit_v1.json")
+
+    alloc = hz.get("allocation_pct") or {}
+    short_pct = _f(alloc.get("SHORT", 0))
+    excess_pct = max(0.0, short_pct - SHORT_CAP_PCT)
+
+    # SHORT 종목 목록 (horizon_classification)
+    hz_rows = hz.get("rows") or []
+    short_tickers = [r for r in hz_rows if isinstance(r, dict) and r.get("horizon") == "SHORT"]
+
+    # final_judgment_gate의 verdict와 confidence 병합
+    fj_map = {r.get("ticker"): r for r in (fj.get("rows") or []) if isinstance(r, dict)}
+
+    # 총 포트폴리오 자산
+    total_asset = _f(harness.get("total_asset_krw", 0))
+    portfolio_equity = total_asset - _f(harness.get("settlement_cash_d2_krw", 0))
+
+    # single_position_weight_json에서 비중 정보 조회
+    spwj = harness.get("single_position_weight_json")
+    if isinstance(spwj, str):
+        try: spwj = json.loads(spwj)
+        except Exception: spwj = []
+    weight_map = {}
+    for item in (spwj if isinstance(spwj, list) else []):
+        if isinstance(item, dict):
+            weight_map[str(item.get("ticker", ""))] = _f(item.get("weight_pct", 0))
+
+    # SHORT 종목별 리밸런싱 우선순위 산출
+    # 우선순위: SELL verdict > 낮은 confidence > 높은 weight
+    candidates = []
+    for r in short_tickers:
+        ticker = r.get("ticker", "")
+        fj_row = fj_map.get(ticker, {})
+        verdict = str(fj_row.get("action_verdict", "UNKNOWN"))
+        conf = _f(fj_row.get("effective_confidence", 50))
+        weight_pct = weight_map.get(ticker, 0)
+        market_value = portfolio_equity * weight_pct / 100 if portfolio_equity > 0 else 0
+        disparity = _f(r.get("disparity_pct", 0))
+        rsi14 = _f(r.get("rsi14", 50))
+
+        # 우선순위 점수 (높을수록 먼저 줄임)
+        priority = 0
+        if verdict in ("SELL",): priority += 40
+        elif verdict in ("TRIM",): priority += 20
+        priority += max(0, 60 - conf)          # confidence 낮을수록 +
+        priority += max(0, disparity - 5) * 2  # 이격도 높을수록 +
+        priority += max(0, rsi14 - 60) * 0.5   # RSI 과매수일수록 +
+
+        candidates.append({
+            "ticker": ticker,
+            "name": r.get("name", ""),
+            "horizon": "SHORT",
+            "verdict": verdict,
+            "effective_confidence": conf,
+            "weight_pct": weight_pct,
+            "market_value_krw": round(market_value),
+            "disparity_pct": disparity,
+            "rsi14": rsi14,
+            "priority_score": round(priority, 1),
+        })
+
+    candidates.sort(key=lambda x: x["priority_score"], reverse=True)
+
+    # 목표: SHORT 비중을 40%로 줄이기 위한 최소 감축량
+    target_short_pct = SHORT_CAP_PCT
+    # 단순 비례: 현재 71.4% → 40% = 31.4%p 감축 필요
+    # 각 종목의 비중을 합산해 필요 감축 시뮬레이션
+    required_reduction_pct = excess_pct  # 31.4%p (SHORT 내 비중)
+    # 절대 금액 환산 (portfolio_equity 기준)
+    required_reduction_krw = portfolio_equity * required_reduction_pct / 100 if portfolio_equity > 0 else 0
+
+    # 누적 시뮬레이션
+    cum_reduction = 0.0
+    plan_rows = []
+    for c in candidates:
+        if cum_reduction >= required_reduction_pct:
+            break
+        # 해당 종목 전량 매도 시 감축 pct (portfolio_equity 기준)
+        trim_pct = c["weight_pct"]  # 포트폴리오 비중 = 감축 효과
+        action = "FULL_TRIM" if verdict == "SELL" else "PARTIAL_TRIM"
+        plan_rows.append({
+            **c,
+            "recommended_action": action,
+            "trim_weight_pct": round(trim_pct, 2),
+            "cum_short_reduction_pct": round(cum_reduction + trim_pct, 2),
+        })
+        cum_reduction += trim_pct
+
+    result = {
+        "formula_id": FORMULA_ID,
+        "current_short_pct": short_pct,
+        "short_cap_pct": SHORT_CAP_PCT,
+        "excess_pct": round(excess_pct, 1),
+        "required_reduction_pct": round(required_reduction_pct, 1),
+        "required_reduction_krw": round(required_reduction_krw),
+        "estimated_short_after_plan": round(max(0, short_pct - cum_reduction), 1),
+        "gate_after_plan": "PASS" if max(0, short_pct - cum_reduction) <= SHORT_CAP_PCT else "FAIL",
+        "plan_rows": plan_rows,
+        "all_short_candidates": candidates,
+        "note": (
+            "포트폴리오 total_asset 기준 시뮬레이션. "
+            "실제 weight_pct는 prices_json 기준이며 "
+            "당일 종가 변동에 따라 달라질 수 있음."
+        ),
+    }
+
+    out_path.write_text(json.dumps(result, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
+    print(
+        f"[{FORMULA_ID}] SHORT={short_pct}% excess={excess_pct}%p "
+        f"plan_tickers={[r['ticker'] for r in plan_rows]} "
+        f"after_plan={result['estimated_short_after_plan']}% "
+        f"gate={result['gate_after_plan']} -> {out_path}"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())