수정

backend/app/core/config.py

@@ -231,6 +231,7 @@ class Settings(BaseSettings):
     DAY_TRADE_ORB_MARGIN_CHECK: float = 0.03  # ORB 목표가 최소 마진 (3%)
     DAY_TRADE_TRAILING_DEFAULT: float = 0.02  # 트레일링 기본값 -2% (ATR 없을 때)
     DAY_TRADE_TRAILING_MIN_HOLD_SEC: int = 300  # 트레일링 활성화 최소 보유 시간 (초, 5분)
+    DAY_TRADE_MIN_STOP_LOSS_PCT: float = 0.01  # 최소 손절폭 -1.0% (너무 타이트한 ATR 손절 방지)
 
     # ═════════════════════════════════════════════════════════════════════════════
     # 코스닥 스캐너 (섹션 7.1)

backend/app/services/day_trading_strategy.py

@@ -349,6 +349,9 @@ def check_orb_signal(
         orb_stop = max(orb_stop, atr_floor)
     # 상한 클램프: 일일 손실 한도 대비 종목당 최대 한도
     stop_loss = max(orb_stop, hard_stop)
+    # 최소 손절폭 보장: ATR/ORB가 너무 좁으면 노이즈에 즉시 손절 → 최소 -1.0% 확보
+    min_stop = current_price * (1 - settings.DAY_TRADE_MIN_STOP_LOSS_PCT)
+    stop_loss = min(stop_loss, min_stop)
     risk = current_price - stop_loss
     if risk <= 0:
         return None  # 손절폭이 0 이하면 진입 무의미
@@ -412,6 +415,9 @@ def check_vwap_bounce_signal(
     raw_stop = (current_price - settings.DAY_TRADE_VWAP_ATR_MULT * atr) if atr else current_price * (1 - settings.DAY_TRADE_ORB_STOP_LOSS_PCT)
     hard_stop_vwap = current_price * (1 - settings.DAY_TRADE_REVERSION_STOP_LOSS_PCT)
     stop_loss = max(raw_stop, hard_stop_vwap, 1.0)  # 타이트한 쪽 = 진입가에 가까운 = 높은 가격, 최소 1원 보장
+    # 최소 손절폭 보장: ATR이 너무 작으면 노이즈에 즉시 손절 → 최소 -1.0% 확보
+    min_stop = current_price * (1 - settings.DAY_TRADE_MIN_STOP_LOSS_PCT)
+    stop_loss = min(stop_loss, min_stop)
     target = (current_price + settings.DAY_TRADE_TARGET_MULTIPLIER * atr) if atr else vwap * 1.03
 
     return DayTradeSignal(
@@ -471,6 +477,9 @@ def check_rsi_bb_signal(
     raw_stop = (current_price - settings.DAY_TRADE_RSI_BB_ATR_MULT * atr) if atr else current_price * (1 - settings.DAY_TRADE_ORB_STOP_LOSS_PCT)
     hard_stop_rsi = current_price * (1 - settings.DAY_TRADE_REVERSION_STOP_LOSS_PCT)
     stop_loss = max(raw_stop, hard_stop_rsi, 1.0)  # 타이트한 쪽 = 진입가에 가까운 = 높은 가격, 최소 1원 보장
+    # 최소 손절폭 보장: ATR이 너무 작으면 노이즈에 즉시 손절 → 최소 -1.0% 확보
+    min_stop = current_price * (1 - settings.DAY_TRADE_MIN_STOP_LOSS_PCT)
+    stop_loss = min(stop_loss, min_stop)
     # 최소 1.5R 보장: bb_middle이 너무 가까우면 R:R 확보를 위해 목표 상향
     risk = current_price - stop_loss
     target = max(bb_middle, current_price + risk * 1.5)  # 1.5R 보장

backend/app/services/trade_analyzer.py

@@ -36,8 +36,19 @@ def _to_float(val) -> float:
         return 0.0
 
 
-def _parse_strategy(entry_reason: Optional[str]) -> str:
+def _parse_strategy(entry_reason: Optional[str], strategy_type: Optional[str] = None) -> str:
-    """entry_reason 문자열에서 전략 이름 추출."""
+    """strategy_type 컬럼 우선, 없으면 entry_reason 문자열에서 전략 이름 추출."""
+    # strategy_type 컬럼이 있으면 우선 사용
+    if strategy_type and strategy_type.strip():
+        st = strategy_type.strip().lower()
+        _type_map = {
+            "swing": "mean_reversion",
+            "daytrading": "day_trade",
+            "kosdaq_scan": "kosdaq_scanner",
+            "short_term": "short_term",
+        }
+        return _type_map.get(st, st)
+
     if not entry_reason:
         return "unknown"
     reason = entry_reason.lower()
@@ -439,7 +450,7 @@ async def analyze_performance(db: AsyncSession, days: int = 30) -> Dict[str, Any
     # ── 전략별 성과 ──────────────────────────────────────────────────────
     by_strategy: Dict[str, list] = {}
     for t in trades:
-        strat = _parse_strategy(t.entry_reason)
+        strat = _parse_strategy(t.entry_reason, getattr(t, "strategy_type", None))
         by_strategy.setdefault(strat, []).append(_to_float(t.profit_loss_rate))
 
     strategy_stats = {}
@@ -491,8 +502,9 @@ async def analyze_performance(db: AsyncSession, days: int = 30) -> Dict[str, Any
         stock_pnl[code] = stock_pnl.get(code, 0.0) + _to_float(t.net_profit_loss)
 
     sorted_stocks = sorted(stock_pnl.items(), key=lambda x: x[1])
-    worst_stocks = [{"stock_code": c, "net_pnl": round(p, 2)} for c, p in sorted_stocks[:5]]
+    # 손실 종목만 (음수), 수익 종목만 (양수) 필터링하여 색상 혼동 방지
-    best_stocks = [{"stock_code": c, "net_pnl": round(p, 2)} for c, p in sorted_stocks[-5:][::-1]]
+    worst_stocks = [{"stock_code": c, "net_pnl": round(p, 2)} for c, p in sorted_stocks if p < 0][:5]
+    best_stocks = [{"stock_code": c, "net_pnl": round(p, 2)} for c, p in sorted_stocks[::-1] if p > 0][:5]
 
     # ── 리스크 조정 수익률 지표 ────────────────────────────────────────────
     risk_metrics = _calc_risk_adjusted_metrics(trades)
@@ -660,7 +672,7 @@ def generate_journal_for_trade(trade: TradeHistory, perf_context: Optional[Dict]
     pl_amount = _to_float(trade.net_profit_loss)
     exec_price = _to_float(trade.executed_price)
     exec_qty = trade.executed_quantity or trade.order_quantity or 0
-    strategy = _parse_strategy(trade.entry_reason)
+    strategy = _parse_strategy(trade.entry_reason, getattr(trade, "strategy_type", None))
     exit_type = _parse_exit_type(trade.exit_reason)
 
     # 결과 평가
@@ -729,7 +741,7 @@ async def create_journal_record(
 ) -> TradeJournal:
     """TradeJournal 레코드를 DB에 저장 후 반환."""
     pl_rate = _to_float(trade.profit_loss_rate)
-    strategy = _parse_strategy(trade.entry_reason)
+    strategy = _parse_strategy(trade.entry_reason, getattr(trade, "strategy_type", None))
     exit_type = _parse_exit_type(trade.exit_reason)
 
     mood = "positive" if pl_rate > 0 else ("neutral" if pl_rate > -3.0 else "negative")

frontend/src/pages/Analysis.tsx

@@ -466,7 +466,7 @@ export default function Analysis() {
                             {perf.worst_stocks.map((s) => (
                                 <div key={s.stock_code} className="flex justify-between text-sm">
                                     <span className="text-gray-200">{s.stock_code}</span>
-                                    <span className="text-red-400">{fmtKRW(s.net_pnl)}</span>
+                                    <span className={s.net_pnl < 0 ? "text-red-400" : "text-green-400"}>{fmtKRW(s.net_pnl)}</span>
                                 </div>
                             ))}
                         </div>
@@ -477,7 +477,7 @@ export default function Analysis() {
                             {perf.best_stocks.map((s) => (
                                 <div key={s.stock_code} className="flex justify-between text-sm">
                                     <span className="text-gray-200">{s.stock_code}</span>
-                                    <span className="text-green-400">{fmtKRW(s.net_pnl)}</span>
+                                    <span className={s.net_pnl > 0 ? "text-green-400" : "text-red-400"}>{fmtKRW(s.net_pnl)}</span>
                                 </div>
                             ))}
                         </div>

frontend/src/pages/TradeHistory.tsx

@@ -6,6 +6,15 @@ import HtsPage from '../components/HtsPage'
 import api from '../lib/api'
 import { useState, Fragment } from 'react'
 
+/** DB에서 KST로 저장된 datetime 문자열을 Date 객체로 변환
+ *  trade_executor가 _get_kst_now()로 KST naive datetime을 저장하므로 +09:00 보정 */
+const toKST = (dtStr: string) => {
+    if (!dtStr) return new Date()
+    const s = dtStr.trim()
+    if (s.includes('+') || s.endsWith('Z')) return new Date(s)
+    return new Date(s + '+09:00')
+}
+
 interface Trade {
     id: string
     created_at: string
@@ -76,13 +85,13 @@ function buildPairs(trades: Trade[]): TradePair[] {
             // 매수 이후 가장 가까운 매도 찾기
             const sell = sells.find(s =>
                 !usedSells.has(s.id) &&
-                new Date(s.created_at) >= new Date(buy.created_at)
+                toKST(s.created_at) >= toKST(buy.created_at)
             ) ?? null
 
             if (sell) usedSells.add(sell.id)
 
             const holdMinutes = sell
-                ? differenceInMinutes(new Date(sell.created_at), new Date(buy.created_at))
+                ? differenceInMinutes(toKST(sell.created_at), toKST(buy.created_at))
                 : null
 
             const pl = sell
@@ -96,7 +105,7 @@ function buildPairs(trades: Trade[]): TradePair[] {
     }
     // 최신 매수 기준 내림차순
     return pairs.sort((a, b) =>
-        new Date(b.buy.created_at).getTime() - new Date(a.buy.created_at).getTime()
+        toKST(b.buy.created_at).getTime() - toKST(a.buy.created_at).getTime()
     )
 }
 
@@ -138,7 +147,7 @@ function PairView({ pairs }: { pairs: TradePair[] }) {
                                     </div>
                                 </td>
                                 <td className="py-2.5 px-3 text-xs text-blue-300 whitespace-nowrap">
-                                    {format(new Date(p.buy.created_at), 'MM/dd HH:mm', { locale: ko })}
+                                    {format(toKST(p.buy.created_at), 'MM/dd HH:mm', { locale: ko })}
                                 </td>
                                 <td className="py-2.5 px-3 text-right text-white tabular-nums">
                                     {fmtPrice(p.buy.executed_price ?? p.buy.order_price)}
@@ -146,7 +155,7 @@ function PairView({ pairs }: { pairs: TradePair[] }) {
                                 <td className="py-2.5 px-3 text-xs whitespace-nowrap">
                                     {isOpen
                                         ? <span className="text-yellow-400 font-medium">미청산</span>
-                                        : <span className="text-red-300">{format(new Date(p.sell!.created_at), 'MM/dd HH:mm', { locale: ko })}</span>
+                                        : <span className="text-red-300">{format(toKST(p.sell!.created_at), 'MM/dd HH:mm', { locale: ko })}</span>
                                     }
                                 </td>
                                 <td className="py-2.5 px-3 text-right tabular-nums text-slate-300">