수정본

backend/app/services/us_backtest_engine.py

@@ -5,6 +5,7 @@ us_stock_strategy의 매수/매도 신호를 과거 데이터에 적용하여
 """
 import logging
 import math
+import random
 from datetime import date, datetime, timedelta
 from typing import Dict, List, Any, Optional
 from dataclasses import dataclass, asdict
@@ -25,6 +26,27 @@ logger = logging.getLogger(__name__)
 US_COMMISSION_RATE = 0.001    # 해외 주식 수수료 약 0.1% (매수+매도 각각)
 RISK_FREE_RATE = 0.04         # 무위험 수익률 4% (연간, USD 기준)
 TRADING_DAYS_PER_YEAR = 252
+US_SLIPPAGE_PCT = 0.0005      # +/-0.05% (미국 주식은 유동성이 높아 슬리피지가 낮음)
+
+
+def _apply_us_buy_slippage(price: float, seed: Optional[int] = None) -> float:
+    """매수 시 슬리피지: 시장가 주문 시 약간 높은 가격에 체결
+
+    미국 주식은 유동성이 높아 국내(0.1%) 대비 낮은 0~0.05% 적용.
+    """
+    rng = random.Random(seed)
+    slip = rng.uniform(0, US_SLIPPAGE_PCT)
+    return price * (1 + slip)
+
+
+def _apply_us_sell_slippage(price: float, seed: Optional[int] = None) -> float:
+    """매도 시 슬리피지: 시장가 주문 시 약간 낮은 가격에 체결
+
+    미국 주식은 유동성이 높아 국내(0.1%) 대비 낮은 0~0.05% 적용.
+    """
+    rng = random.Random(seed)
+    slip = rng.uniform(0, US_SLIPPAGE_PCT)
+    return price * (1 - slip)
 
 
 @dataclass
@@ -229,6 +251,10 @@ async def run_us_backtest(
     indicators = _calculate_indicators(daily_data)
 
     # 3) 시뮬레이션 실행
+    #
+    # [Look-ahead bias 수정]
+    # T일 close로 신호 생성 -> T+1일 open + 슬리피지로 체결.
+    # 마지막 봉 신호는 다음 봉이 없으므로 무시합니다.
     cash = initial_capital_usd
     position_qty = 0
     position_avg_price = 0.0
@@ -236,96 +262,114 @@ async def run_us_backtest(
     trades: List[Dict] = []
     equity_curve: List[Dict] = []
 
+    # 전일 발생한 신호를 저장 (T일 close 신호 -> T+1일 open 체결)
+    pending_buy_signal: Optional[Dict] = None
+    pending_sell_signal: Optional[str] = None
+
     for i in range(20, len(daily_data)):  # 지표 계산에 최소 20일 필요
         bar = daily_data[i]
         ind = indicators[i]
         close = bar["close"]
         bar_date = bar["date"]
+        bar_open = bar["open"]
 
-        # 포지션 보유 시: 매도 조건 체크
+        # -- 1단계: 전일 신호를 오늘 open + 슬리피지로 체결 --
+        if pending_sell_signal is not None and position_qty > 0:
+            exec_price = _apply_us_sell_slippage(bar_open)
+            amount = position_qty * exec_price
+            commission = amount * US_COMMISSION_RATE
+            pnl = (exec_price - position_avg_price) * position_qty - commission
+            pnl_pct = ((exec_price - position_avg_price) / position_avg_price * 100) if position_avg_price > 0 else 0.0
+
+            trade = {
+                "date": bar_date,
+                "action": "SELL",
+                "ticker": ticker,
+                "price": round(exec_price, 4),
+                "quantity": position_qty,
+                "amount": round(amount, 2),
+                "commission": round(commission, 2),
+                "reason": pending_sell_signal,
+                "pnl": round(pnl, 2),
+                "pnl_pct": round(pnl_pct, 2),
+            }
+            trades.append(trade)
+            cash += amount - commission
+            position_qty = 0
+            position_avg_price = 0.0
+            position_high = 0.0
+            pending_sell_signal = None
+
+        if pending_buy_signal is not None and position_qty == 0:
+            exec_price = _apply_us_buy_slippage(bar_open)
+            buy_amount = min(cash * 0.95, cash)
+            if buy_amount > 10:
+                quantity = int(buy_amount / exec_price)
+                if quantity > 0:
+                    cost = quantity * exec_price
+                    commission = cost * US_COMMISSION_RATE
+                    total_cost = cost + commission
+
+                    if total_cost <= cash:
+                        cash -= total_cost
+                        position_qty = quantity
+                        position_avg_price = exec_price
+                        position_high = exec_price
+
+                        trade = {
+                            "date": bar_date,
+                            "action": "BUY",
+                            "ticker": ticker,
+                            "price": round(exec_price, 4),
+                            "quantity": quantity,
+                            "amount": round(cost, 2),
+                            "commission": round(commission, 2),
+                            "reason": pending_buy_signal.get("reason", "buy_signal"),
+                            "pnl": 0.0,
+                            "pnl_pct": 0.0,
+                        }
+                        trades.append(trade)
+            pending_buy_signal = None
+
+        # -- 2단계: 오늘 close 기준으로 신호 생성 (체결은 내일 open) --
+        is_last_bar = (i == len(daily_data) - 1)
+
+        # 트레일링 스탑용 최고가 갱신 (close 기준)
         if position_qty > 0:
-            # 트레일링 스탑용 최고가 갱신
             if close > position_high:
                 position_high = close
 
-            sell_signal = _check_backtest_sell(
-                close=close,
-                avg_price=position_avg_price,
-                high_since_entry=position_high,
-                rsi=ind.get("rsi", 50),
-                bb_middle=ind.get("bb_middle", close),
-                bb_upper=ind.get("bb_upper", close),
-            )
+        if not is_last_bar:
+            # 매도 신호 체크
+            if position_qty > 0:
+                sell_signal = _check_backtest_sell(
+                    close=close,
+                    avg_price=position_avg_price,
+                    high_since_entry=position_high,
+                    rsi=ind.get("rsi", 50),
+                    bb_middle=ind.get("bb_middle", close),
+                    bb_upper=ind.get("bb_upper", close),
+                )
+                if sell_signal:
+                    pending_sell_signal = sell_signal
 
-            if sell_signal:
-                amount = position_qty * close
-                commission = amount * US_COMMISSION_RATE
-                pnl = (close - position_avg_price) * position_qty - commission
-                pnl_pct = ((close - position_avg_price) / position_avg_price * 100) if position_avg_price > 0 else 0.0
+            # 매수 신호 체크
+            if position_qty == 0 and pending_sell_signal is None:
+                prev_rsi = indicators[i - 3].get("rsi") if i >= 3 else None
 
-                trade = {
-                    "date": bar_date,
-                    "action": "SELL",
-                    "ticker": ticker,
-                    "price": close,
-                    "quantity": position_qty,
-                    "amount": round(amount, 2),
-                    "commission": round(commission, 2),
-                    "reason": sell_signal,
-                    "pnl": round(pnl, 2),
-                    "pnl_pct": round(pnl_pct, 2),
-                }
-                trades.append(trade)
-                cash += amount - commission
-                position_qty = 0
-                position_avg_price = 0.0
-                position_high = 0.0
-
-        # 포지션 없을 때: 매수 조건 체크
-        if position_qty == 0:
-            prev_rsi = indicators[i - 3].get("rsi") if i >= 3 else None
-
-            buy_signal = check_us_buy_signal(
-                rsi=ind.get("rsi", 50),
-                close=close,
-                bb_upper=ind.get("bb_upper", close),
-                bb_middle=ind.get("bb_middle", close),
-                bb_lower=ind.get("bb_lower", close),
-                avg_volume_20d=ind.get("avg_volume_20d", 0),
-                current_volume=bar.get("volume", 0),
-                current_price_usd=close,
-                rsi_prev=prev_rsi,
-            )
-
-            if buy_signal:
-                # 전체 자본의 최대 95% 투입 (여유 현금 확보)
-                buy_amount = min(cash * 0.95, cash)
-                if buy_amount > 10:  # 최소 $10 이상
-                    quantity = int(buy_amount / close)
-                    if quantity > 0:
-                        cost = quantity * close
-                        commission = cost * US_COMMISSION_RATE
-                        total_cost = cost + commission
-
-                        if total_cost <= cash:
-                            cash -= total_cost
-                            position_qty = quantity
-                            position_avg_price = close
-                            position_high = close
-
-                            trade = {
-                                "date": bar_date,
-                                "action": "BUY",
-                                "ticker": ticker,
-                                "price": close,
-                                "quantity": quantity,
-                                "amount": round(cost, 2),
-                                "commission": round(commission, 2),
-                                "reason": buy_signal.get("reason", "buy_signal"),
-                                "pnl": 0.0,
-                                "pnl_pct": 0.0,
-                            }
-                            trades.append(trade)
+                buy_signal = check_us_buy_signal(
+                    rsi=ind.get("rsi", 50),
+                    close=close,
+                    bb_upper=ind.get("bb_upper", close),
+                    bb_middle=ind.get("bb_middle", close),
+                    bb_lower=ind.get("bb_lower", close),
+                    avg_volume_20d=ind.get("avg_volume_20d", 0),
+                    current_volume=bar.get("volume", 0),
+                    current_price_usd=close,
+                    rsi_prev=prev_rsi,
+                )
+                if buy_signal:
+                    pending_buy_signal = buy_signal
 
         # 일별 자산 기록
         position_value = position_qty * close if position_qty > 0 else 0.0
@@ -337,19 +381,20 @@ async def run_us_backtest(
             "position_value": round(position_value, 2),
         })
 
-    # 4) 미청산 포지션 강제 청산 (백테스트 종료)
+    # 4) 미청산 포지션 강제 청산 (백테스트 종료, 슬리피지 적용)
     if position_qty > 0 and daily_data:
         last_close = daily_data[-1]["close"]
-        amount = position_qty * last_close
+        exec_price = _apply_us_sell_slippage(last_close)
+        amount = position_qty * exec_price
         commission = amount * US_COMMISSION_RATE
-        pnl = (last_close - position_avg_price) * position_qty - commission
-        pnl_pct = ((last_close - position_avg_price) / position_avg_price * 100) if position_avg_price > 0 else 0.0
+        pnl = (exec_price - position_avg_price) * position_qty - commission
+        pnl_pct = ((exec_price - position_avg_price) / position_avg_price * 100) if position_avg_price > 0 else 0.0
 
         trades.append({
             "date": daily_data[-1]["date"],
             "action": "SELL",
             "ticker": ticker,
-            "price": last_close,
+            "price": round(exec_price, 4),
             "quantity": position_qty,
             "amount": round(amount, 2),
             "commission": round(commission, 2),