Initial commit: Touch & Turn Scalping Bot with fully automated execution, backtesting, and ISA screening

src/strategy/touch_turn.py

@@ -0,0 +1,129 @@
+import pandas as pd
+import pandas_ta as ta
+import yfinance as yf
+from datetime import datetime, time, timedelta
+import pytz
+import logging
+
+logger = logging.getLogger(__name__)
+
+class TouchTurnStrategy:
+    """
+    Implements the 'Touch & Turn' (Opening Range Reversal) strategy.
+    
+    1. Captures the 09:30-09:45 EST 15m candle.
+    2. Checks if range > 25% of 14-day ATR.
+    3. Bearish candle -> Long at Low, Target @ 38.2% Fib.
+    4. Bullish candle -> Short at High, Target @ 38.2% Fib.
+    """
+    
+    def __init__(self, ticker: str, risk_percent_atr: float = 25.0, rr_ratio: float = 2.0):
+        self.ticker = ticker
+        self.risk_percent_atr = risk_percent_atr
+        self.rr_ratio = rr_ratio
+        self.tz = pytz.timezone('US/Eastern')
+        
+        self.valid_setup = False
+        self.direction = 0 # 1 for Short (from High), -1 for Long (from Low)
+        self.entry_price = 0.0
+        self.target_price = 0.0
+        self.stop_loss = 0.0
+        
+    def get_market_data(self):
+        """Fetches 15m candles and daily data for ATR."""
+        now = datetime.now(self.tz)
+        
+        # 1. Fetch Daily Data for ATR (need at least 15+ days)
+        daily_data = yf.download(self.ticker, period="1mo", interval="1d", progress=False)
+        if daily_data.empty or len(daily_data) < 15:
+            logger.error(f"Insufficient daily data for {self.ticker}")
+            return None, None
+            
+        # Clean column names (yfinance multi-index issue)
+        if isinstance(daily_data.columns, pd.MultiIndex):
+            daily_data.columns = daily_data.columns.droplevel(1)
+            
+        # Calculate ATR
+        daily_data.ta.atr(length=14, append=True)
+        daily_atr = daily_data['ATRr_14'].iloc[-2] # Use yesterday's ATR
+        
+        # 2. Fetch 15m Candle for today's opening (09:30 - 09:45)
+        # Note: yfinance 15m candles are labeled by start time.
+        start_date = now.strftime('%Y-%m-%d')
+        intraday_data = yf.download(self.ticker, start=start_date, interval="15m", progress=False)
+        
+        if intraday_data.empty:
+            logger.warning(f"No intraday data yet for {self.ticker}")
+            return daily_atr, None
+            
+        if isinstance(intraday_data.columns, pd.MultiIndex):
+            intraday_data.columns = intraday_data.columns.droplevel(1)
+            
+        # The first candle of the session (09:30)
+        opening_candle = intraday_data.between_time('09:30', '09:30')
+        if opening_candle.empty:
+            logger.warning(f"Opening 15m candle (09:30) not yet available for {self.ticker}")
+            return daily_atr, None
+            
+        return daily_atr, opening_candle.iloc[0]
+
+    def check_setup(self):
+        """Evaluates the strategy criteria based on the opening candle."""
+        daily_atr, opening_candle = self.get_market_data()
+        
+        if daily_atr is None or opening_candle is None:
+            return False
+            
+        high = opening_candle['High']
+        low = opening_candle['Low']
+        open_p = opening_candle['Open']
+        close_p = opening_candle['Close']
+        range_size = high - low
+        
+        # 1. Liquidity Filter
+        if range_size < (daily_atr * self.risk_percent_atr / 100):
+            logger.info(f"Setup invalid: Range ({range_size:.2f}) < 25% of ATR ({daily_atr:.2f})")
+            self.valid_setup = False
+            return False
+            
+        # 2. Determine Direction
+        if close_p < open_p:
+            self.direction = -1 # Bearish candle -> Long setup
+            self.entry_price = low
+            logger.info(f"Bearish opening candle detected. Preparing LONG at {self.entry_price:.2f}")
+        else:
+            self.direction = 1 # Bullish candle -> Short setup
+            self.entry_price = high
+            logger.info(f"Bullish opening candle detected. Preparing SHORT at {self.entry_price:.2f}")
+            
+        # 3. Calculate Fibonacci 38.2% Target
+        # For LONG (from Low): target is 38.2% up from the Low
+        # For SHORT (from High): target is 38.2% down from the High
+        if self.direction == -1: # LONG
+            self.target_price = low + (range_size * 0.382)
+            target_distance = self.target_price - self.entry_price
+            stop_distance = target_distance / self.rr_ratio
+            self.stop_loss = self.entry_price - stop_distance
+        else: # SHORT
+            self.target_price = high - (range_size * 0.382)
+            target_distance = self.entry_price - self.target_price
+            stop_distance = target_distance / self.rr_ratio
+            self.stop_loss = self.entry_price + stop_distance
+
+            
+        self.valid_setup = True
+        logger.info(f"Valid Setup! Entry: {self.entry_price:.2f}, Target: {self.target_price:.2f}, SL: {self.stop_loss:.2f}")
+        return True
+
+    def get_trade_params(self):
+        """Returns the parameters for the trade execution."""
+        if not self.valid_setup:
+            return None
+            
+        return {
+            "ticker": self.ticker,
+            "direction": "BUY" if self.direction == -1 else "SELL",
+            "entry_price": self.entry_price,
+            "target_price": self.target_price,
+            "stop_loss": self.stop_loss
+        }