diff options
Diffstat (limited to 'services/strategy-engine/strategies')
5 files changed, 111 insertions, 70 deletions
diff --git a/services/strategy-engine/strategies/asian_session_rsi.py b/services/strategy-engine/strategies/asian_session_rsi.py index f22c3eb..741cd63 100644 --- a/services/strategy-engine/strategies/asian_session_rsi.py +++ b/services/strategy-engine/strategies/asian_session_rsi.py @@ -2,9 +2,10 @@ 규칙: - SOL/USDT 5분봉 -- 매수: RSI(14) < 25 + 볼륨 > 평균 +- 매수: RSI(14) < 25 + 볼륨 > 평균 + 센티먼트 OK - 익절: +1.5%, 손절: -0.7%, 시간청산: 11:00 KST (02:00 UTC) - 하루 최대 3회, 2연패 시 중단 +- 센티먼트 필터: Fear & Greed > 80이면 매수 차단, 뉴스 극도 부정이면 차단 """ from collections import deque @@ -14,6 +15,7 @@ from datetime import datetime import pandas as pd from shared.models import Candle, Signal, OrderSide +from shared.sentiment import SentimentData from strategies.base import BaseStrategy @@ -33,6 +35,9 @@ class AsianSessionRsiStrategy(BaseStrategy): self._session_end_utc: int = 2 self._max_trades_per_day: int = 3 self._max_consecutive_losses: int = 2 + self._use_sentiment: bool = True + # Sentiment (updated externally before each session) + self._sentiment: SentimentData | None = None # State self._closes: deque[float] = deque(maxlen=200) self._volumes: deque[float] = deque(maxlen=50) @@ -57,6 +62,7 @@ class AsianSessionRsiStrategy(BaseStrategy): self._session_end_utc = int(params.get("session_end_utc", 2)) self._max_trades_per_day = int(params.get("max_trades_per_day", 3)) self._max_consecutive_losses = int(params.get("max_consecutive_losses", 2)) + self._use_sentiment = bool(params.get("use_sentiment", True)) if self._quantity <= 0: raise ValueError(f"Quantity must be positive, got {self._quantity}") @@ -82,6 +88,17 @@ class AsianSessionRsiStrategy(BaseStrategy): self._consecutive_losses = 0 self._in_position = False self._entry_price = 0.0 + self._sentiment = None + + def update_sentiment(self, sentiment: SentimentData) -> None: + """Update sentiment data. Call before each trading session.""" + self._sentiment = sentiment + + def _check_sentiment(self) -> bool: + """Check if sentiment allows buying. Returns True if OK.""" + if not self._use_sentiment or self._sentiment is None: + return True # No sentiment data, allow by default + return not self._sentiment.should_block def _is_session_active(self, dt: datetime) -> bool: """Check if current time is within trading session.""" @@ -135,29 +152,33 @@ class AsianSessionRsiStrategy(BaseStrategy): if pnl_pct >= self._take_profit_pct: self._in_position = False self._consecutive_losses = 0 - return self._apply_filters(Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - conviction=0.9, - reason=f"Take profit {pnl_pct:.2f}% >= {self._take_profit_pct}%", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.SELL, + price=candle.close, + quantity=self._quantity, + conviction=0.9, + reason=f"Take profit {pnl_pct:.2f}% >= {self._take_profit_pct}%", + ) + ) # Stop loss if pnl_pct <= -self._stop_loss_pct: self._in_position = False self._consecutive_losses += 1 - return self._apply_filters(Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - conviction=1.0, - reason=f"Stop loss {pnl_pct:.2f}% <= -{self._stop_loss_pct}%", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.SELL, + price=candle.close, + quantity=self._quantity, + conviction=1.0, + reason=f"Stop loss {pnl_pct:.2f}% <= -{self._stop_loss_pct}%", + ) + ) # Time exit: session ended while in position if not self._is_session_active(candle.open_time): @@ -166,15 +187,17 @@ class AsianSessionRsiStrategy(BaseStrategy): self._consecutive_losses += 1 else: self._consecutive_losses = 0 - return self._apply_filters(Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - conviction=0.5, - reason=f"Time exit (session ended), PnL {pnl_pct:.2f}%", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.SELL, + price=candle.close, + quantity=self._quantity, + conviction=0.5, + reason=f"Time exit (session ended), PnL {pnl_pct:.2f}%", + ) + ) return None # Still in position, no action @@ -188,6 +211,9 @@ class AsianSessionRsiStrategy(BaseStrategy): if self._consecutive_losses >= self._max_consecutive_losses: return None # Consecutive loss limit + if not self._check_sentiment(): + return None # Sentiment blocked (extreme greed or very negative news) + rsi = self._compute_rsi() if rsi is None: return None @@ -204,16 +230,18 @@ class AsianSessionRsiStrategy(BaseStrategy): sl = candle.close * (1 - Decimal(str(self._stop_loss_pct / 100))) tp = candle.close * (1 + Decimal(str(self._take_profit_pct / 100))) - return self._apply_filters(Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - conviction=conv, - stop_loss=sl, - take_profit=tp, - reason=f"RSI {rsi:.1f} < {self._rsi_oversold} (session active, vol OK)", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.BUY, + price=candle.close, + quantity=self._quantity, + conviction=conv, + stop_loss=sl, + take_profit=tp, + reason=f"RSI {rsi:.1f} < {self._rsi_oversold} (session active, vol OK)", + ) + ) return None diff --git a/services/strategy-engine/strategies/bollinger_strategy.py b/services/strategy-engine/strategies/bollinger_strategy.py index a195cb8..ebe7967 100644 --- a/services/strategy-engine/strategies/bollinger_strategy.py +++ b/services/strategy-engine/strategies/bollinger_strategy.py @@ -102,27 +102,31 @@ class BollingerStrategy(BaseStrategy): if price > sma: # Breakout upward conv = min(0.5 + squeeze_duration * 0.1, 1.0) - return self._apply_filters(Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - conviction=conv, - reason=f"Bollinger squeeze breakout UP after {squeeze_duration} bars", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.BUY, + price=candle.close, + quantity=self._quantity, + conviction=conv, + reason=f"Bollinger squeeze breakout UP after {squeeze_duration} bars", + ) + ) else: # Breakout downward conv = min(0.5 + squeeze_duration * 0.1, 1.0) - return self._apply_filters(Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - conviction=conv, - reason=f"Bollinger squeeze breakout DOWN after {squeeze_duration} bars", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.SELL, + price=candle.close, + quantity=self._quantity, + conviction=conv, + reason=f"Bollinger squeeze breakout DOWN after {squeeze_duration} bars", + ) + ) # Bandwidth filter: skip sideways markets if sma != 0 and bandwidth < self._min_bandwidth: diff --git a/services/strategy-engine/strategies/combined_strategy.py b/services/strategy-engine/strategies/combined_strategy.py index 907d9c5..ba92485 100644 --- a/services/strategy-engine/strategies/combined_strategy.py +++ b/services/strategy-engine/strategies/combined_strategy.py @@ -53,7 +53,9 @@ class CombinedStrategy(BaseStrategy): self._trade_history[strategy_name].append(is_win) # Keep only last N results if len(self._trade_history[strategy_name]) > self._history_window: - self._trade_history[strategy_name] = self._trade_history[strategy_name][-self._history_window:] + self._trade_history[strategy_name] = self._trade_history[strategy_name][ + -self._history_window : + ] def _get_adaptive_weight(self, strategy_name: str, base_weight: float) -> float: """Get weight adjusted by recent performance.""" @@ -90,10 +92,14 @@ class CombinedStrategy(BaseStrategy): effective_weight = self._get_adaptive_weight(strategy.name, weight) if signal.side == OrderSide.BUY: score += effective_weight * signal.conviction - reasons.append(f"{strategy.name}:BUY({effective_weight}*{signal.conviction:.2f})") + reasons.append( + f"{strategy.name}:BUY({effective_weight}*{signal.conviction:.2f})" + ) elif signal.side == OrderSide.SELL: score -= effective_weight * signal.conviction - reasons.append(f"{strategy.name}:SELL({effective_weight}*{signal.conviction:.2f})") + reasons.append( + f"{strategy.name}:SELL({effective_weight}*{signal.conviction:.2f})" + ) normalized = score / total_weight # Range: -1.0 to 1.0 diff --git a/services/strategy-engine/strategies/grid_strategy.py b/services/strategy-engine/strategies/grid_strategy.py index 07ccaba..283bfe5 100644 --- a/services/strategy-engine/strategies/grid_strategy.py +++ b/services/strategy-engine/strategies/grid_strategy.py @@ -40,9 +40,7 @@ class GridStrategy(BaseStrategy): f"got lower={self._lower_price}, upper={self._upper_price}" ) if self._exit_threshold_pct <= 0: - raise ValueError( - f"exit_threshold_pct must be > 0, got {self._exit_threshold_pct}" - ) + raise ValueError(f"exit_threshold_pct must be > 0, got {self._exit_threshold_pct}") if self._grid_count < 2: raise ValueError(f"Grid grid_count must be >= 2, got {self._grid_count}") if self._quantity <= 0: @@ -90,12 +88,17 @@ class GridStrategy(BaseStrategy): if not self._out_of_range: self._out_of_range = True # Exit signal — close positions - return self._apply_filters(Signal( - strategy=self.name, symbol=candle.symbol, - side=OrderSide.SELL, price=candle.close, - quantity=self._quantity, conviction=0.8, - reason=f"Grid: price {price:.2f} broke out of range [{self._grid_levels[0]:.2f}, {self._grid_levels[-1]:.2f}]", - )) + return self._apply_filters( + Signal( + strategy=self.name, + symbol=candle.symbol, + side=OrderSide.SELL, + price=candle.close, + quantity=self._quantity, + conviction=0.8, + reason=f"Grid: price {price:.2f} broke out of range [{self._grid_levels[0]:.2f}, {self._grid_levels[-1]:.2f}]", + ) + ) return None # Already out of range, no more signals else: self._out_of_range = False diff --git a/services/strategy-engine/strategies/vwap_strategy.py b/services/strategy-engine/strategies/vwap_strategy.py index 0348752..d64950e 100644 --- a/services/strategy-engine/strategies/vwap_strategy.py +++ b/services/strategy-engine/strategies/vwap_strategy.py @@ -110,7 +110,7 @@ class VwapStrategy(BaseStrategy): diffs = [tp - v for tp, v in zip(self._tp_values, self._vwap_values)] mean_diff = sum(diffs) / len(diffs) variance = sum((d - mean_diff) ** 2 for d in diffs) / len(diffs) - std_dev = variance ** 0.5 + std_dev = variance**0.5 deviation = (close - vwap) / vwap |