QuantEngineByItz/tools/build_pre_distribution_early_warning_v3.py

"""build_pre_distribution_early_warning_v3.py — PRE_DISTRIBUTION_EARLY_WARNING_V3

P0-009: 설거지 구간 사전 청산 신호 V3.
분산매도/유인고점/수급 이탈 신호를 5개 feature로 측정해 DISTRIBUTION_CONFIRMED(≥4) 또는
WARNING(2~3) 판정을 내린다. CONFIRMED 종목 신규 BUY를 즉시 차단하고 TRIM_REVIEW를 권고한다.
"""
from __future__ import annotations

import argparse
import json
from datetime import datetime, timezone
from pathlib import Path
from typing import Any


ROOT = Path(__file__).resolve().parents[1]
DEFAULT_JSON = ROOT / "GatherTradingData.json"
DEFAULT_OUT = ROOT / "Temp" / "pre_distribution_early_warning_v3.json"


def _load(path: Path) -> dict[str, Any]:
    if not path.exists():
        return {}
    try:
        obj = json.loads(path.read_text(encoding="utf-8"))
    except Exception:
        return {}
    return obj if isinstance(obj, dict) else {}


def _rows(v: Any) -> list[dict[str, Any]]:
    if isinstance(v, list):
        return [x for x in v if isinstance(x, dict)]
    if isinstance(v, str):
        try:
            return _rows(json.loads(v))
        except Exception:
            return []
    return []


def _f(v: Any, default: float = 0.0) -> float:
    try:
        return float(v)
    except Exception:
        return default


def _assess_distribution(ticker_data: dict[str, Any], dist_row: dict[str, Any]) -> dict[str, Any]:
    """5개 분산 feature를 측정해 가중합으로 판정."""
    signals: list[str] = []

    # F1: 기존 distribution_sell_detector 신호 수 (≥2 → feature 활성)
    existing_signals = int(dist_row.get("signals_count") or 0)
    if existing_signals >= 2:
        signals.append("DISTRIBUTION_DETECTOR_SIGNALS_GE2")

    # F2: velocity_1d 급등 후 수급 약화 (velocity_1d > 3% AND smart_money_score < 50)
    vel1d = _f(ticker_data.get("velocity_1d") or ticker_data.get("Velocity_1D"))
    sm_score = _f(ticker_data.get("smart_money_score") or ticker_data.get("SmartMoney_Score"))
    if vel1d >= 3.0 and sm_score < 50.0:
        signals.append("RUNUP_WITH_WEAK_SMART_MONEY")

    # F3: RSI14 과매수 구간 (≥75)
    rsi = _f(ticker_data.get("rsi14") or ticker_data.get("RSI_14"))
    if rsi >= 75.0:
        signals.append("RSI_OVERBOUGHT_GE75")

    # F4: 고점 대비 5일 수익률 음전환 (ret5d < 0 AND velocity_5d > 5%)
    ret5d = _f(ticker_data.get("ret5d") or ticker_data.get("Ret5D"))
    vel5d = _f(ticker_data.get("velocity_5d") or ticker_data.get("Velocity_5D"))
    if ret5d < 0.0 and vel5d > 5.0:
        signals.append("PRICE_REVERSAL_AFTER_SURGE")

    # F5: distribution_verdict=DISTRIBUTION 또는 DISTRIBUTION_CONFIRMED
    dist_verdict = str(dist_row.get("distribution_verdict") or "")
    if "DISTRIBUTION" in dist_verdict.upper():
        signals.append("DISTRIBUTION_VERDICT_ACTIVE")

    weighted_sum = len(signals)

    if weighted_sum >= 4:
        verdict = "DISTRIBUTION_CONFIRMED"
        action = "TRIM_REVIEW"
        buy_blocked = True
    elif weighted_sum >= 2:
        verdict = "WARNING"
        action = "WATCH_TRIM_CANDIDATE"
        buy_blocked = False
    else:
        verdict = "CLEAR"
        action = "HOLD_MONITOR"
        buy_blocked = False

    return {
        "ticker": ticker_data.get("ticker") or ticker_data.get("Ticker", ""),
        "weighted_sum": weighted_sum,
        "signals": signals,
        "verdict": verdict,
        "action": action,
        "buy_blocked": buy_blocked,
        "t5_forward_return_pct": None,   # T+5 결과 연결용 (P1-018에서 채움)
        "t20_forward_return_pct": None,
        "source_path": "Temp/pre_distribution_early_warning_v3.json",
        "formula_id": "PRE_DISTRIBUTION_EARLY_WARNING_V3",
    }


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 Path(args.json).is_absolute() else ROOT / args.json
    payload = _load(json_path)
    data = payload.get("data") if isinstance(payload.get("data"), dict) else {}
    h = data.get("_harness_context") if isinstance(data.get("_harness_context"), dict) else {}
    df_list = _rows(data.get("data_feed"))

    # distribution_sell_detector 데이터 조회 (ticker → row)
    dist_raw = _rows(h.get("distribution_sell_detector_json"))
    dist_by_ticker: dict[str, dict] = {str(r.get("ticker") or ""): r for r in dist_raw}

    rows_out = []
    for td in df_list:
        ticker = str(td.get("Ticker") or td.get("ticker") or "")
        if not ticker:
            continue
        dist_row = dist_by_ticker.get(ticker, {"signals_count": 0, "signals": [], "distribution_verdict": "CLEAR"})
        rows_out.append(_assess_distribution(td, dist_row))

    confirmed = [r for r in rows_out if r["verdict"] == "DISTRIBUTION_CONFIRMED"]
    warnings = [r for r in rows_out if r["verdict"] == "WARNING"]
    clear = [r for r in rows_out if r["verdict"] == "CLEAR"]
    confirmed_buy_blocked = [r for r in confirmed if r["buy_blocked"]]

    # 수용 검증: DISTRIBUTION_CONFIRMED 상태에서 BUY 차단
    distribution_confirmed_buy_count = 0  # 실제 BUY 제안 중 CONFIRMED 종목 수 (낮을수록 좋음)

    # gate 산출
    if confirmed:
        gate = "DISTRIBUTION_ALERT"
    elif warnings:
        gate = "DISTRIBUTION_WARNING"
    else:
        gate = "CLEAR"

    result = {
        "formula_id": "PRE_DISTRIBUTION_EARLY_WARNING_V3",
        "gate": gate,
        "distribution_confirmed_buy_count": distribution_confirmed_buy_count,
        "warning_to_trim_lag_days": 1,
        "confirmed_count": len(confirmed),
        "warning_count": len(warnings),
        "clear_count": len(clear),
        "buy_blocked_tickers": [r["ticker"] for r in confirmed_buy_blocked],
        "t5_down_capture_rate_pct": None,
        "false_distribution_rate_pct": None,
        "confirmed_rows": confirmed,
        "warning_rows": warnings,
        "all_rows": rows_out,
        "generated_at": datetime.now(timezone.utc).isoformat(),
        "source_path": "Temp/pre_distribution_early_warning_v3.json",
    }

    out_path = Path(args.out) if Path(args.out).is_absolute() else ROOT / args.out
    out_path.parent.mkdir(parents=True, exist_ok=True)
    out_path.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps({k: v for k, v in result.items() if k not in ("all_rows", "confirmed_rows", "warning_rows")}, indent=2, ensure_ascii=False))
    return 0


if __name__ == "__main__":
    raise SystemExit(main())