cbazzaandClaude Opus 4.5
ce4e961541
Deploy to Windows VPS / deploy (push) Has been cancelled
New features: - Reversal Detector with 5 detection signals: - RSI Divergence (bearish/bullish) - EMA Slope Change detection - Volume Spike analysis - Candlestick patterns (Doji, Engulfing, Hammer, Pin Bar) - Break of Structure detection - Integrated into enhanced_trading_check_wrapper (SCHRITT 2.5) - Defensive mode: blocks trades at 70%+ reversal score - Lot size reduction at 30-69% reversal score - Enable Overlap session (13:00-16:00 UTC) Files added: - reversal_detector.py: Core detection algorithms - reversal_integration.py: Bot integration wrapper - REVERSAL_DETECTOR_INTEGRATION.md: Documentation Modified: - TradingBot notebook: Added reversal check integration - session_filter_patch.py: Enabled overlap session Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
288 lines
9.2 KiB
Python
288 lines
9.2 KiB
Python
#!/usr/bin/env python3
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"""
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🔄 REVERSAL DETECTOR INTEGRATION
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Integriert den Reversal Detector in den Trading Bot
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VERWENDUNG IM NOTEBOOK:
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# Am Anfang importieren (nach den anderen Imports):
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from reversal_integration import reversal_detector, check_reversal_risk
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# In enhanced_trading_check_wrapper nach Signal Analysis:
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reversal_result = check_reversal_risk(signal_info, symbol)
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if not reversal_result['should_trade']:
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print(f"⛔ TRADE BLOCKIERT durch Reversal Detector")
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return None
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# Lot Multiplier anpassen:
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lot_multiplier *= reversal_result['lot_multiplier']
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"""
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import logging
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from typing import Dict, Optional
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import pandas as pd
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# Import the reversal detector
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from reversal_detector import ReversalDetector
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logger = logging.getLogger(__name__)
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# ==========================================
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# GLOBAL REVERSAL DETECTOR INSTANCE
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# ==========================================
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# Initialize with defensive mode (blocks/reduces trades at high reversal risk)
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reversal_detector = ReversalDetector(
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rsi_period=14,
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ema_fast=9,
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ema_slow=21,
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volume_spike_mult=2.0,
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divergence_lookback=10,
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mode="defensive" # "defensive" or "info"
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)
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# ==========================================
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# CONFIGURATION
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# ==========================================
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REVERSAL_CONFIG = {
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'enabled': True, # Reversal Check aktiviert
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'block_threshold': 70, # Score >= 70 = Trade blockieren
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'reduce_threshold': 50, # Score >= 50 = Lot reduzieren
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'caution_threshold': 30, # Score >= 30 = Warnung
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'use_m15_data': True, # M15 für Analyse verwenden
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'use_h1_confirmation': True, # H1 für Bestätigung
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}
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# ==========================================
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# INTEGRATION FUNCTION
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# ==========================================
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def check_reversal_risk(signal_info: Dict, symbol: str = "XAUUSD") -> Dict:
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"""
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Prüft Reversal-Risiko basierend auf Signal-Info
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Args:
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signal_info: Dict von extended_top_down_v2_adaptive()
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symbol: Trading Symbol
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Returns:
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Dict mit:
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- should_trade: bool
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- reversal_score: int (0-100)
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- lot_multiplier: float (1.0, 0.75, 0.5, 0.0)
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- action: str (ALLOW, CAUTION, REDUCE, BLOCK)
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- reason: str
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"""
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if not REVERSAL_CONFIG['enabled']:
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return {
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'should_trade': True,
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'reversal_score': 0,
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'lot_multiplier': 1.0,
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'action': 'ALLOW',
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'reason': 'Reversal check disabled'
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}
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if signal_info is None:
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return {
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'should_trade': True,
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'reversal_score': 0,
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'lot_multiplier': 1.0,
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'action': 'ALLOW',
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'reason': 'No signal info available'
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}
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try:
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# Bestimme aktuellen Trend
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entry_signal = signal_info.get('entry_signal', 0)
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standard_trend = signal_info.get('standard_trend', 'sideways')
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# Trend aus entry_signal ableiten falls standard_trend nicht verfügbar
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if standard_trend == 'sideways' and entry_signal != 0:
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current_trend = 'uptrend' if entry_signal == 1 else 'downtrend'
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else:
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current_trend = standard_trend
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# Hole M15 DataFrame aus trend_info
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trend_info = signal_info.get('trend_info', {})
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df_m15 = None
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df_h1 = None
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# Versuche M15 Daten zu holen
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if REVERSAL_CONFIG['use_m15_data'] and 'M15' in trend_info:
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m15_info = trend_info['M15']
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if isinstance(m15_info, dict) and 'df' in m15_info:
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df_m15 = m15_info['df']
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elif hasattr(m15_info, 'df'):
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df_m15 = m15_info.df
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# Versuche H1 Daten zu holen
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if REVERSAL_CONFIG['use_h1_confirmation'] and 'H1' in trend_info:
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h1_info = trend_info['H1']
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if isinstance(h1_info, dict) and 'df' in h1_info:
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df_h1 = h1_info['df']
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elif hasattr(h1_info, 'df'):
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df_h1 = h1_info.df
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# Falls keine DataFrame verfügbar, versuche get_rates
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if df_m15 is None:
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try:
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# Import get_rates falls verfügbar
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import sys
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if 'get_rates' in dir(sys.modules.get('__main__', {})):
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from __main__ import get_rates
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df_m15 = get_rates('m15', 100, symbol)
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except Exception as e:
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logger.debug(f"Could not get M15 data: {e}")
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if df_m15 is None or len(df_m15) < 50:
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print(f"⚠️ Reversal Check: Not enough M15 data, skipping")
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return {
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'should_trade': True,
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'reversal_score': 0,
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'lot_multiplier': 1.0,
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'action': 'ALLOW',
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'reason': 'Insufficient data for reversal check'
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}
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# Führe Reversal-Analyse durch
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result = reversal_detector.analyze(
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df=df_m15,
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current_trend=current_trend,
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df_higher_tf=df_h1
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)
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reversal_score = result['reversal_score']
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# Bestimme Aktion basierend auf Config-Thresholds
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if reversal_score >= REVERSAL_CONFIG['block_threshold']:
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action = 'BLOCK'
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lot_multiplier = 0.0
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should_trade = False
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reason = f"High reversal risk ({reversal_score}% >= {REVERSAL_CONFIG['block_threshold']}%)"
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elif reversal_score >= REVERSAL_CONFIG['reduce_threshold']:
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action = 'REDUCE'
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lot_multiplier = 0.5
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should_trade = True
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reason = f"Moderate reversal risk ({reversal_score}%), lot reduced to 50%"
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elif reversal_score >= REVERSAL_CONFIG['caution_threshold']:
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action = 'CAUTION'
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lot_multiplier = 0.75
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should_trade = True
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reason = f"Low reversal risk ({reversal_score}%), lot reduced to 75%"
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else:
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action = 'ALLOW'
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lot_multiplier = 1.0
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should_trade = True
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reason = f"No significant reversal risk ({reversal_score}%)"
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return {
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'should_trade': should_trade,
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'reversal_score': reversal_score,
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'lot_multiplier': lot_multiplier,
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'action': action,
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'reason': reason,
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'reversal_type': result.get('reversal_type', 'NONE'),
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'signals': result.get('signals', {})
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}
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except Exception as e:
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logger.error(f"Reversal check error: {e}")
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print(f"⚠️ Reversal Check Error: {e}")
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return {
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'should_trade': True,
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'reversal_score': 0,
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'lot_multiplier': 1.0,
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'action': 'ALLOW',
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'reason': f'Error: {e}'
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}
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def get_reversal_status() -> str:
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"""Gibt aktuellen Reversal Detector Status zurück"""
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status = []
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status.append("=" * 60)
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status.append("🔄 REVERSAL DETECTOR STATUS")
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status.append("=" * 60)
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status.append(f" Enabled: {REVERSAL_CONFIG['enabled']}")
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status.append(f" Mode: {reversal_detector.mode}")
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status.append(f" Block Threshold: {REVERSAL_CONFIG['block_threshold']}%")
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status.append(f" Reduce Threshold: {REVERSAL_CONFIG['reduce_threshold']}%")
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status.append(f" Caution Threshold: {REVERSAL_CONFIG['caution_threshold']}%")
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status.append("=" * 60)
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return "\n".join(status)
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def enable_reversal_check():
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"""Aktiviert den Reversal Check"""
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REVERSAL_CONFIG['enabled'] = True
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print("✅ Reversal Check ENABLED")
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def disable_reversal_check():
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"""Deaktiviert den Reversal Check"""
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REVERSAL_CONFIG['enabled'] = False
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print("⚠️ Reversal Check DISABLED")
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def set_reversal_mode(mode: str):
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"""
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Setzt den Reversal Detector Mode
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Args:
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mode: "defensive" (blockiert Trades) oder "info" (nur Logging)
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"""
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global reversal_detector
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reversal_detector = ReversalDetector(
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rsi_period=14,
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ema_fast=9,
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ema_slow=21,
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volume_spike_mult=2.0,
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divergence_lookback=10,
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mode=mode
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)
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print(f"✅ Reversal Detector mode set to: {mode.upper()}")
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# ==========================================
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# STANDALONE TEST
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# ==========================================
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if __name__ == "__main__":
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print(get_reversal_status())
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# Test mit simulierten Daten
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import numpy as np
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np.random.seed(42)
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n = 100
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prices = np.linspace(100, 110, n) + np.random.normal(0, 0.5, n)
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df = pd.DataFrame({
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'open': prices - np.random.uniform(0, 0.3, n),
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'high': prices + np.random.uniform(0.3, 0.8, n),
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'low': prices - np.random.uniform(0.3, 0.8, n),
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'close': prices,
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'tick_volume': np.random.randint(100, 500, n)
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})
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# Simuliere signal_info
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mock_signal_info = {
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'entry_signal': 1,
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'standard_trend': 'uptrend',
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'trend_info': {
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'M15': {'df': df}
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}
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}
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print("\n🧪 Testing Reversal Check...")
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result = check_reversal_risk(mock_signal_info, "XAUUSD")
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print(f"\n📊 Result:")
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print(f" Should Trade: {result['should_trade']}")
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print(f" Reversal Score: {result['reversal_score']}%")
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print(f" Action: {result['action']}")
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print(f" Lot Multiplier: {result['lot_multiplier']}")
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print(f" Reason: {result['reason']}")
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