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fix: simplify logging for systemd compatibility and add ATR-based Stop Loss padding

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pie
2026-06-01 16:27:30 +01:00
parent 17ad49c22e
commit 6010f66323
2 changed files with 28 additions and 38 deletions
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src/strategy/touch_turn.py
+18 -8
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@@ -17,10 +17,11 @@ class TouchTurnStrategy:
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):
def __init__(self, ticker: str, risk_percent_atr: float = 25.0, rr_ratio: float = 2.0, min_stop_atr_pct: float = 10.0):
self.ticker = ticker
self.risk_percent_atr = risk_percent_atr
self.rr_ratio = rr_ratio
self.min_stop_atr_pct = min_stop_atr_pct
self.tz = pytz.timezone('US/Eastern')
self.valid_setup = False
@@ -48,7 +49,6 @@ class TouchTurnStrategy:
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)
@@ -59,13 +59,12 @@ class TouchTurnStrategy:
if isinstance(intraday_data.columns, pd.MultiIndex):
intraday_data.columns = intraday_data.columns.droplevel(1)
# Timezone Correction: Convert the index to Eastern Time before filtering
# Timezone Correction
if intraday_data.index.tz is None:
intraday_data.index = intraday_data.index.tz_localize('UTC').tz_convert(self.tz)
else:
intraday_data.index = intraday_data.index.tz_convert(self.tz)
# 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}")
@@ -103,22 +102,33 @@ class TouchTurnStrategy:
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
# 3. Calculate Fibonacci 38.2% Target and Stop Loss with ATR Padding
if self.direction == -1: # LONG
self.target_price = low + (self.range_size * 0.382)
target_distance = self.target_price - self.entry_price
stop_distance = target_distance / self.rr_ratio
# SL Padding: Ensure SL is at least X% of ATR away to avoid noise
min_stop = daily_atr * (self.min_stop_atr_pct / 100.0)
if stop_distance < min_stop:
logger.info(f"Widening SL for {self.ticker} from {stop_distance:.2f} to min ATR distance {min_stop:.2f}")
stop_distance = min_stop
self.stop_loss = self.entry_price - stop_distance
else: # SHORT
self.target_price = high - (self.range_size * 0.382)
target_distance = self.entry_price - self.target_price
stop_distance = target_distance / self.rr_ratio
min_stop = daily_atr * (self.min_stop_atr_pct / 100.0)
if stop_distance < min_stop:
logger.info(f"Widening SL for {self.ticker} from {stop_distance:.2f} to min ATR distance {min_stop:.2f}")
stop_distance = min_stop
self.stop_loss = self.entry_price + stop_distance
# 4. Calculate Percentage Move (needed for ETP scaling)
# We use absolute percentage move relative to the entry price
target_distance = abs(self.entry_price - self.target_price)
self.target_percent = (target_distance / self.entry_price) * 100
self.valid_setup = True