refactor: remove all crypto/Binance code, update to US stock symbols

3 files changed, 3 insertions, 283 deletions

diff --git a/services/strategy-engine/strategies/asian_session_rsi.py b/services/strategy-engine/strategies/asian_session_rsi.py
deleted file mode 100644
index 1874591..0000000
--- a/services/strategy-engine/strategies/asian_session_rsi.py
+++ /dev/null
@@ -1,266 +0,0 @@
-"""Asian Session RSI Strategy — 한국시간 9:00~11:00 단타.
-
-규칙:
-- SOL/USDT 5분봉
-- 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
-from decimal import Decimal
-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
-
-
-class AsianSessionRsiStrategy(BaseStrategy):
-    name: str = "asian_session_rsi"
-
-    def __init__(self) -> None:
-        super().__init__()
-        self._rsi_period: int = 14
-        self._rsi_oversold: float = 25.0
-        self._rsi_overbought: float = 75.0
-        self._quantity: Decimal = Decimal("0.1")
-        self._take_profit_pct: float = 1.5
-        self._stop_loss_pct: float = 0.7
-        # Session: 00:00~02:00 UTC = 09:00~11:00 KST
-        self._session_start_utc: int = 0
-        self._session_end_utc: int = 2
-        self._max_trades_per_day: int = 3
-        self._max_consecutive_losses: int = 2
-        self._use_sentiment: bool = True
-        self._ema_period: int = 20
-        self._require_bullish_candle: bool = True
-        self._prev_candle_bullish: bool = False
-        # 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)
-        self._today: str | None = None
-        self._trades_today: int = 0
-        self._consecutive_losses: int = 0
-        self._in_position: bool = False
-        self._entry_price: float = 0.0
-
-    @property
-    def warmup_period(self) -> int:
-        return self._rsi_period + 1
-
-    def configure(self, params: dict) -> None:
-        self._rsi_period = int(params.get("rsi_period", 14))
-        self._rsi_oversold = float(params.get("rsi_oversold", 25.0))
-        self._rsi_overbought = float(params.get("rsi_overbought", 75.0))
-        self._quantity = Decimal(str(params.get("quantity", "0.1")))
-        self._take_profit_pct = float(params.get("take_profit_pct", 1.5))
-        self._stop_loss_pct = float(params.get("stop_loss_pct", 0.7))
-        self._session_start_utc = int(params.get("session_start_utc", 0))
-        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))
-        self._ema_period = int(params.get("ema_period", 20))
-        self._require_bullish_candle = bool(params.get("require_bullish_candle", True))
-
-        if self._quantity <= 0:
-            raise ValueError(f"Quantity must be positive, got {self._quantity}")
-        if self._stop_loss_pct <= 0:
-            raise ValueError(f"Stop loss must be positive, got {self._stop_loss_pct}")
-        if self._take_profit_pct <= 0:
-            raise ValueError(f"Take profit must be positive, got {self._take_profit_pct}")
-
-        self._init_filters(
-            require_trend=False,
-            adx_threshold=25.0,
-            min_volume_ratio=0.5,
-            atr_stop_multiplier=1.5,
-            atr_tp_multiplier=2.0,
-        )
-
-    def reset(self) -> None:
-        super().reset()
-        self._closes.clear()
-        self._volumes.clear()
-        self._today = None
-        self._trades_today = 0
-        self._consecutive_losses = 0
-        self._in_position = False
-        self._entry_price = 0.0
-        self._sentiment = None
-        self._prev_candle_bullish = False
-
-    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."""
-        hour = dt.hour
-        if self._session_start_utc <= self._session_end_utc:
-            return self._session_start_utc <= hour < self._session_end_utc
-        # Wrap around midnight
-        return hour >= self._session_start_utc or hour < self._session_end_utc
-
-    def _compute_rsi(self) -> float | None:
-        if len(self._closes) < self._rsi_period + 1:
-            return None
-        series = pd.Series(list(self._closes))
-        delta = series.diff()
-        gain = delta.clip(lower=0)
-        loss = -delta.clip(upper=0)
-        avg_gain = gain.ewm(com=self._rsi_period - 1, min_periods=self._rsi_period).mean()
-        avg_loss = loss.ewm(com=self._rsi_period - 1, min_periods=self._rsi_period).mean()
-        rs = avg_gain / avg_loss.replace(0, float("nan"))
-        rsi = 100 - (100 / (1 + rs))
-        val = rsi.iloc[-1]
-        if pd.isna(val):
-            return None
-        return float(val)
-
-    def _volume_above_average(self) -> bool:
-        if len(self._volumes) < 20:
-            return True  # Not enough data, allow
-        avg = sum(self._volumes) / len(self._volumes)
-        return self._volumes[-1] >= avg
-
-    def _price_above_ema(self) -> bool:
-        """Check if current price is above short-term EMA."""
-        if len(self._closes) < self._ema_period:
-            return True  # Not enough data, allow by default
-        series = pd.Series(list(self._closes))
-        ema_val = series.ewm(span=self._ema_period, adjust=False).mean().iloc[-1]
-        return self._closes[-1] >= ema_val
-
-    def on_candle(self, candle: Candle) -> Signal | None:
-        self._update_filter_data(candle)
-
-        close = float(candle.close)
-        self._closes.append(close)
-        self._volumes.append(float(candle.volume))
-
-        # Track candle direction for bullish confirmation
-        is_bullish = float(candle.close) >= float(candle.open)
-
-        # Daily reset
-        day = candle.open_time.strftime("%Y-%m-%d")
-        if self._today != day:
-            self._today = day
-            self._trades_today = 0
-            # Don't reset consecutive_losses — carries across days
-
-        # Check exit conditions first (if in position)
-        if self._in_position:
-            pnl_pct = (close - self._entry_price) / self._entry_price * 100
-
-            # Take profit
-            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}%",
-                    )
-                )
-
-            # 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}%",
-                    )
-                )
-
-            # Time exit: session ended while in position
-            if not self._is_session_active(candle.open_time):
-                self._in_position = False
-                if pnl_pct < 0:
-                    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 None  # Still in position, no action
-
-        # Entry conditions
-        if not self._is_session_active(candle.open_time):
-            return None  # Outside trading hours
-
-        if self._trades_today >= self._max_trades_per_day:
-            return None  # Daily limit reached
-
-        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
-
-        if rsi < self._rsi_oversold and self._volume_above_average() and self._price_above_ema():
-            if self._require_bullish_candle and not is_bullish:
-                return None  # Wait for bullish candle confirmation
-            self._in_position = True
-            self._entry_price = close
-            self._trades_today += 1
-
-            # Conviction: lower RSI = stronger signal
-            conv = min((self._rsi_oversold - rsi) / self._rsi_oversold, 1.0)
-            conv = max(conv, 0.3)
-
-            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 None
diff --git a/services/strategy-engine/strategies/config/asian_session_rsi.yaml b/services/strategy-engine/strategies/config/asian_session_rsi.yaml
deleted file mode 100644
index bc7c5c9..0000000
--- a/services/strategy-engine/strategies/config/asian_session_rsi.yaml
+++ /dev/null
@@ -1,14 +0,0 @@
-# Asian Session RSI — SOL/USDT 5분봉 단타
-# 한국시간 9:00~11:00 (UTC 0:00~2:00)
-rsi_period: 14
-rsi_oversold: 25
-rsi_overbought: 75
-quantity: "0.5"           # SOL 0.5개 (~$75, 100만원의 10%)
-take_profit_pct: 1.5      # 익절 1.5%
-stop_loss_pct: 0.7        # 손절 0.7%
-session_start_utc: 0      # UTC 0시 = KST 9시
-session_end_utc: 2        # UTC 2시 = KST 11시
-max_trades_per_day: 3     # 하루 최대 3회
-max_consecutive_losses: 2  # 2연패 시 중단
-ema_period: 20
-require_bullish_candle: true
diff --git a/services/strategy-engine/strategies/config/grid_strategy.yaml b/services/strategy-engine/strategies/config/grid_strategy.yaml
index 607f3df..338bb4c 100644
--- a/services/strategy-engine/strategies/config/grid_strategy.yaml
+++ b/services/strategy-engine/strategies/config/grid_strategy.yaml
@@ -1,4 +1,4 @@
-lower_price: 60000
-upper_price: 70000
+lower_price: 170
+upper_price: 190
 grid_count: 5
-quantity: "0.01"
+quantity: "1"