diff --git a/backend/app/services/mean_reversion_strategy.py b/backend/app/services/mean_reversion_strategy.py index 041e1f0..b1d8a60 100644 --- a/backend/app/services/mean_reversion_strategy.py +++ b/backend/app/services/mean_reversion_strategy.py @@ -137,8 +137,12 @@ def calculate_adx(highs: List[float], lows: List[float], closes: List[float], pe if len(dxs) < period: return None - adx_s = _wilder_smooth(dxs) - return round(adx_s[-1], 2) + # ADX 평활: 초기값은 mean(DX[:period]) — ATR/DM과 달리 합산이 아닌 평균 + # _wilder_smooth()는 초기값이 sum이므로 ADX에는 인라인 계산 사용 + adx_val = sum(dxs[:period]) / period # 초기값 = 평균 + for dx_v in dxs[period:]: + adx_val = adx_val - adx_val / period + dx_v + return round(adx_val, 2) def detect_market_regime(index_closes: List[float], diff --git a/backend/app/services/swing/exit_service.py b/backend/app/services/swing/exit_service.py index 68bd58f..91298d1 100644 --- a/backend/app/services/swing/exit_service.py +++ b/backend/app/services/swing/exit_service.py @@ -251,6 +251,15 @@ async def check_and_execute_exit_v2(db: AsyncSession) -> list[dict]: # ── 고정 비율 폴백 손절 ─────────────────────────────────── if exit_signal is None: stop_loss_pct = abs(float(getattr(settings, "STOP_LOSS_PERCENT", 6.0))) + # 적응형 모드(Crisis 등)의 손절값과 비교하여 타이트한 쪽 적용 + try: + from app.services.adaptive_strategy import get_current_adaptive_params + _adaptive = get_current_adaptive_params() + if not _adaptive.fallback_used: + _adaptive_sl = abs(_adaptive.stop_loss_pct) + stop_loss_pct = min(stop_loss_pct, _adaptive_sl) + except Exception: + pass # 적응형 전략 로드 실패 시 기본값 유지 profit_rate = ((latest_price - avg_price) / avg_price) * 100 if profit_rate <= -stop_loss_pct: from app.services.mean_reversion_strategy import ExitSignal