refactor: create technical_indicators.py

backend/app/services/technical_indicators.py

@@ -0,0 +1,346 @@
+import logging
+from typing import Optional
+
+from app.core.config import settings
+from app.services.mean_reversion_strategy import calculate_adx
+
+logger = logging.getLogger(__name__)
+
+# Trend filter defaults (configurable via settings)
+TREND_FILTER_ENABLED = getattr(settings, "TREND_FILTER_ENABLED", True)
+TREND_MA_SHORT = int(getattr(settings, "TREND_MA_SHORT", 20))
+TREND_MA_LONG = int(getattr(settings, "TREND_MA_LONG", 60))
+TREND_TOLERANCE_PCT = float(getattr(settings, "TREND_TOLERANCE_PCT", 0.005))
+
+# 급등 과열 필터 defaults
+OVERHEAT_FILTER_ENABLED = getattr(settings, "OVERHEAT_FILTER_ENABLED", True)
+OVERHEAT_3DAY_MAX = float(getattr(settings, "OVERHEAT_3DAY_MAX", 15.0))
+OVERHEAT_5DAY_MAX = float(getattr(settings, "OVERHEAT_5DAY_MAX", 20.0))
+OVERHEAT_10DAY_MAX = float(getattr(settings, "OVERHEAT_10DAY_MAX", 30.0))
+OVERHEAT_DISPARITY_MAX = float(getattr(settings, "OVERHEAT_DISPARITY_MAX", 108.0))
+
+
+def _ma(values: list, window: int) -> Optional[float]:
+    try:
+        if len(values) < window:
+            return None
+        return sum(values[-window:]) / window
+    except Exception:
+        return None
+
+
+def _passes_uptrend(closes: list, ma_short: int = TREND_MA_SHORT, ma_long: int = TREND_MA_LONG, tol: float = TREND_TOLERANCE_PCT) -> Optional[bool]:
+    if not closes or len(closes) < max(ma_short, ma_long):
+        return None
+    ma_s = _ma(closes, ma_short)
+    ma_l = _ma(closes, ma_long)
+    close = closes[-1]
+    if ma_s is None or ma_l is None:
+        return None
+    # 허용 오차 적용: 거의 골든크로스/이탈 직후도 허용
+    return (ma_s >= ma_l * (1 - tol)) and (close >= ma_s * (1 - tol))
+
+
+def analyze_overheat(closes: list, ma20: Optional[float]) -> dict:
+    """급등 과열 필터 - 단기 급등 종목 매수 차단"""
+    details = {}
+    reasons = []
+
+    if len(closes) >= 4:
+        gain_3d = ((closes[-1] - closes[-4]) / closes[-4]) * 100 if closes[-4] > 0 else 0
+        details["gain_3d"] = round(gain_3d, 1)
+        if gain_3d > OVERHEAT_3DAY_MAX:
+            reasons.append(f"3일 +{gain_3d:.1f}% (>{OVERHEAT_3DAY_MAX}%)")
+
+    if len(closes) >= 6:
+        gain_5d = ((closes[-1] - closes[-6]) / closes[-6]) * 100 if closes[-6] > 0 else 0
+        details["gain_5d"] = round(gain_5d, 1)
+        if gain_5d > OVERHEAT_5DAY_MAX:
+            reasons.append(f"5일 +{gain_5d:.1f}% (>{OVERHEAT_5DAY_MAX}%)")
+
+    if len(closes) >= 11:
+        gain_10d = ((closes[-1] - closes[-11]) / closes[-11]) * 100 if closes[-11] > 0 else 0
+        details["gain_10d"] = round(gain_10d, 1)
+        if gain_10d > OVERHEAT_10DAY_MAX:
+            reasons.append(f"10일 +{gain_10d:.1f}% (>{OVERHEAT_10DAY_MAX}%)")
+
+    if ma20 and ma20 > 0:
+        disparity = (closes[-1] / ma20) * 100
+        details["disparity_20"] = round(disparity, 1)
+        if disparity > OVERHEAT_DISPARITY_MAX:
+            reasons.append(f"이격도 {disparity:.1f}% (>{OVERHEAT_DISPARITY_MAX}%)")
+
+    blocked = len(reasons) > 0
+    reason = "급등과열: " + ", ".join(reasons) if blocked else ""
+
+    return {"blocked": blocked, "reason": reason, "details": details}
+
+
+def analyze_custom_signals(chart_data):
+    """커스텀 매매 공식 기반 신호 분석 - 이격도 필터 적용"""
+    closes = [float(item.get("stck_clpr", 0)) for item in chart_data]
+    if len(closes) < 120:
+        return None
+    
+    ma20 = sum(closes[-20:]) / 20
+    ma60 = sum(closes[-60:]) / 60
+    ma120 = sum(closes[-120:]) / 120
+    close = closes[-1]
+    
+    disparity = (close / ma20) * 100 if ma20 else 100
+
+    if len(closes) >= 4:
+        price_3days_ago = closes[-4]
+        recent_gain = ((close - price_3days_ago) / price_3days_ago) * 100 if price_3days_ago > 0 else 0
+        if recent_gain > 10:
+            return {"signal": None, "description": f"급등 종목 추격 금지 (3일 +{recent_gain:.1f}%)"}
+
+    if ma20 > ma60 > ma120 and close > ma20:
+        if disparity <= 102:
+            return {"signal": "buy", "description": "정배열 눌림목 매수 (이격도 안정)"}
+        else:
+            return {"signal": None, "description": f"정배열이나 이격 과열 ({disparity:.1f}%)"}
+
+    elif ma20 < ma60 < ma120 and close < ma20:
+        return {"signal": "sell", "description": "역배열 하락 매도타점"}
+
+    recent_lows = [float(item.get("stck_lwpr", 0)) for item in chart_data[-5:]]
+    if any(low < ma20 for low in recent_lows) and close > ma20:
+        if disparity <= 101:
+            return {"signal": "buy", "description": "눌림목 진입 매수타점"}
+        else:
+            return {"signal": None, "description": f"눌림목이나 이격 과열 ({disparity:.1f}%)"}
+    
+    stop_loss_line = ma60
+    take_profit_line = ma20 * 1.05
+    if close < stop_loss_line:
+        return {"signal": "exit", "description": "손절라인 이탈"}
+    if close > take_profit_line:
+        return {"signal": "take_profit", "description": "익절라인 돌파"}
+    
+    return None
+
+
+def analyze_macd(chart_data: list) -> dict:
+    if len(chart_data) < 26:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    prices = [float(item.get("stck_clpr", 0)) for item in chart_data[-26:]]
+    
+    if len(prices) < 26:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    def calculate_ema(prices, period):
+        ema = [sum(prices[:period]) / period]
+        multiplier = 2 / (period + 1)
+        for price in prices[period:]:
+            ema.append((price - ema[-1]) * multiplier + ema[-1])
+        return ema
+    
+    ema12 = calculate_ema(prices, 12)
+    ema26 = calculate_ema(prices, 26)
+    
+    if len(ema12) < 2 or len(ema26) < 2:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    macd = [ema12[i] - ema26[i] for i in range(len(ema26))]
+    signal = calculate_ema(macd, 9)
+    
+    if len(signal) < 2:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    if macd[-2] <= signal[-2] and macd[-1] > signal[-1]:
+        return {"signal": "buy", "description": "MACD 골든크로스"}
+    elif macd[-2] >= signal[-2] and macd[-1] < signal[-1]:
+        return {"signal": "sell", "description": "MACD 데드크로스"}
+    
+    return {"signal": None, "description": "신호 없음"}
+
+
+def analyze_rsi(chart_data: list) -> dict:
+    if len(chart_data) < 15:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    prices = [float(item.get("stck_clpr", 0)) for item in chart_data[-15:]]
+    gains = []
+    losses = []
+    for i in range(1, len(prices)):
+        change = prices[i] - prices[i-1]
+        if change > 0:
+            gains.append(change)
+            losses.append(0)
+        else:
+            gains.append(0)
+            losses.append(abs(change))
+    
+    avg_gain = sum(gains[-14:]) / 14
+    avg_loss = sum(losses[-14:]) / 14
+    
+    if avg_loss == 0:
+        rsi = 100
+    else:
+        rs = avg_gain / avg_loss
+        rsi = 100 - (100 / (1 + rs))
+    
+    if len(chart_data) >= 16:
+        prev_prices = [float(item.get("stck_clpr", 0)) for item in chart_data[-16:-1]]
+        prev_gains = []
+        prev_losses = []
+        for i in range(1, len(prev_prices)):
+            change = prev_prices[i] - prev_prices[i-1]
+            if change > 0:
+                prev_gains.append(change)
+                prev_losses.append(0)
+            else:
+                prev_gains.append(0)
+                prev_losses.append(abs(change))
+        
+        prev_avg_gain = sum(prev_gains[-14:]) / 14
+        prev_avg_loss = sum(prev_losses[-14:]) / 14
+        if prev_avg_loss == 0:
+            rsi_prev = 100
+        else:
+            prev_rs = prev_avg_gain / prev_avg_loss
+            rsi_prev = 100 - (100 / (1 + prev_rs))
+    else:
+        rsi_prev = rsi
+    
+    if rsi < 30:
+        return {"signal": None, "description": f"RSI 과매도 심화 ({rsi:.1f}) - 반등 대기"}
+    elif 30 <= rsi <= 45 and rsi > rsi_prev:
+        return {"signal": "buy", "description": f"RSI 바닥 탈출 반등 ({rsi:.1f})"}
+    elif rsi > 70:
+        return {"signal": "sell", "description": f"RSI 과매수 ({rsi:.1f})"}
+    elif 45 <= rsi <= 60:
+        return {"signal": "buy", "description": f"RSI 안정 상승 ({rsi:.1f})"}
+    
+    return {"signal": None, "description": f"RSI 중립 ({rsi:.1f})"}
+
+
+def analyze_bollinger(chart_data: list) -> dict:
+    if len(chart_data) < 20:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    prices = [float(item.get("stck_clpr", 0)) for item in chart_data[-20:]]
+    ma20 = sum(prices) / len(prices)
+    variance = sum((p - ma20) ** 2 for p in prices) / len(prices)
+    std_dev = variance ** 0.5
+    
+    upper_band = ma20 + (2 * std_dev)
+    lower_band = ma20 - (2 * std_dev)
+    current_price = prices[-1]
+    
+    if current_price < lower_band:
+        return {"signal": "buy", "description": "볼린저 하한선 터치"}
+    elif current_price > upper_band:
+        return {"signal": "sell", "description": "볼린저 상한선 돌파"}
+    
+    return {"signal": None, "description": "볼린저 중립"}
+
+
+def analyze_moving_average(chart_data: list) -> dict:
+    if len(chart_data) < 60:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    prices = [float(item.get("stck_clpr", 0)) for item in chart_data[-60:]]
+    ma5 = sum(prices[-5:]) / 5
+    ma20 = sum(prices[-20:]) / 20
+    ma60 = sum(prices[-60:]) / 60
+    current_price = prices[-1]
+    
+    if ma5 > ma20 and current_price > ma5:
+        return {"signal": "buy", "description": "5일선 > 20일선"}
+    elif ma20 > ma60 and current_price > ma20:
+        return {"signal": "buy", "description": "20일선 > 60일선"}
+    elif ma5 < ma20 < ma60 and current_price < ma5:
+        return {"signal": "sell", "description": "이동평균 역배열"}
+    
+    return {"signal": None, "description": "이동평균 중립"}
+
+
+def analyze_stochastic(chart_data: list) -> dict:
+    if len(chart_data) < 14:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    recent_data = chart_data[-14:]
+    highs = [float(item.get("stck_hgpr", 0)) for item in recent_data]
+    lows = [float(item.get("stck_lwpr", 0)) for item in recent_data]
+    closes = [float(item.get("stck_clpr", 0)) for item in recent_data]
+    
+    highest_high = max(highs)
+    lowest_low = min(lows)
+    current_close = closes[-1]
+    
+    if highest_high == lowest_low:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    k = ((current_close - lowest_low) / (highest_high - lowest_low)) * 100
+    
+    if k < 30:
+        return {"signal": "buy", "description": f"스토캐스틱 과매도 (%K: {k:.1f})"}
+    elif k > 70:
+        return {"signal": "sell", "description": f"스토캐스틱 과매수 (%K: {k:.1f})"}
+    
+    return {"signal": None, "description": f"스토캐스틱 중립 (%K: {k:.1f})"}
+
+
+def analyze_volatility_breakout(chart_data: list, k: float = 0.5) -> dict:
+    if len(chart_data) < 2:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    today = chart_data[-1]
+    yesterday = chart_data[-2]
+    
+    current_price = float(today.get("stck_clpr", 0))
+    open_price = float(today.get("stck_oprc", 0))
+    
+    prev_high = float(yesterday.get("stck_hgpr", 0))
+    prev_low = float(yesterday.get("stck_lwpr", 0))
+    prev_range = prev_high - prev_low
+    
+    if prev_range == 0 or open_price == 0:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    target_price = open_price + (prev_range * k)
+    
+    if current_price >= target_price:
+        return {"signal": "buy", "description": f"변동성 돌파 발생 (목표가: {target_price:.0f})"}
+    
+    return {"signal": None, "description": "변동성 돌파 미달"}
+
+
+def analyze_adx(chart_data: list) -> dict:
+    if len(chart_data) < 29:
+        return {"signal": None, "description": "데이터 부족", "adx": None}
+
+    highs = [float(item.get("stck_hgpr", 0)) for item in chart_data]
+    lows = [float(item.get("stck_lwpr", 0)) for item in chart_data]
+    closes = [float(item.get("stck_clpr", 0)) for item in chart_data]
+
+    adx = calculate_adx(highs, lows, closes)
+    if adx is None:
+        return {"signal": None, "description": "ADX 계산 불가", "adx": None}
+
+    if adx < 20:
+        return {"signal": "buy", "description": f"ADX({adx:.0f}<20) 횡보장 — 평균회귀 유리", "adx": adx}
+    if adx > 30:
+        return {"signal": "sell", "description": f"ADX({adx:.0f}>30) 강추세 — 평균회귀 위험", "adx": adx}
+    return {"signal": None, "description": f"ADX({adx:.0f}) 중립", "adx": adx}
+
+
+def analyze_obv(chart_data: list) -> dict:
+    if len(chart_data) < 2:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    volumes = [int(item.get("acml_vol", 0)) for item in chart_data[-5:]]
+    closes = [float(item.get("stck_clpr", 0)) for item in chart_data[-5:]]
+    
+    if len(volumes) < 2 or len(closes) < 2:
+        return {"signal": None, "description": "데이터 부족"}
+    
+    if volumes[-1] > volumes[-2] * 1.5 and closes[-1] > closes[-2]:
+        return {"signal": "buy", "description": "거래량 증가와 상승"}
+    elif volumes[-1] < volumes[-2] * 0.5 and closes[-1] < closes[-2]:
+        return {"signal": "sell", "description": "거래량 감소와 하락"}
+    
+    return {"signal": None, "description": "거래량 중립"}