#!/usr/bin/env python3 """ RECHERCHE EDGE V2 - Edges plus créatifs Tests: - Attendre après pertes (mean reversion) - Filtrer par volatilité - Only LONG ou Only SHORT - Combos avancés """ from martingale_backtester import MartingaleBacktester from martingale_strategy import MartingaleStrategy import numpy as np print("="*80) print("🔬 RECHERCHE EDGE V2 - STRATÉGIES CRÉATIVES") print("="*80) backtester = MartingaleBacktester( initial_capital=1000.0, trading_fee_pct=0.0005, timeout_minutes=60 ) print("\n📥 Téléchargement données...") df = backtester.fetch_binance_data('BTCUSDT', '1m', 1000) if df is None: exit(1) print(f"✅ {len(df)} bougies\n") # ============ EDGES CRÉATIFS ============ class CreativeEdgeStrategy(MartingaleStrategy): def __init__(self, edge_type, **kwargs): super().__init__(**kwargs) self.edge_type = edge_type self.wait_count = 0 self.force_side = None def get_martingale_multiplier(self): return 0.5 ** self.current_level # Anti-martingale def generate_signal(self, df): # EDGE: Wait après 3 pertes (attendre mean reversion) if self.edge_type == 'wait_after_3_losses': if self.consecutive_losses >= 3: if self.wait_count < 5: # Wait 5 bougies self.wait_count += 1 return None else: self.wait_count = 0 # EDGE: Only trade dans direction du trend if self.edge_type == 'trend_only': # EMA 50 comme trend if len(df) >= 50: ema50 = df['close'].ewm(span=50).mean().iloc[-1] current_price = df.iloc[-1]['close'] signal = super().generate_signal(df) if signal: if current_price > ema50 and signal.side == 'SHORT': return None # Skip SHORT en uptrend if current_price < ema50 and signal.side == 'LONG': return None # Skip LONG en downtrend return signal # EDGE: Only LONG (jamais SHORT) if self.edge_type == 'only_long': signal = super().generate_signal(df) if signal and signal.side == 'SHORT': return None return signal # EDGE: Only SHORT (jamais LONG) if self.edge_type == 'only_short': signal = super().generate_signal(df) if signal and signal.side == 'LONG': return None return signal # EDGE: Reverse après 3 pertes + Wait 3 bougies if self.edge_type == 'reverse_and_wait': if self.consecutive_losses >= 3: if self.wait_count < 3: self.wait_count += 1 return None else: self.wait_count = 0 signal = super().generate_signal(df) if signal: # Reverse signal.side = 'SHORT' if signal.side == 'LONG' else 'LONG' signal.stop_loss, signal.take_profit = signal.take_profit, signal.stop_loss return signal # EDGE: TP adaptatif selon volatilité if self.edge_type == 'adaptive_tp': signal = super().generate_signal(df) if signal and len(df) >= 20: # Calculer ATR high_low = df['high'] - df['low'] atr = high_low.rolling(14).mean().iloc[-1] volatility_ratio = atr / df['close'].iloc[-1] # TP plus large si volatilité haute if volatility_ratio > 0.005: # Volatile if signal.side == 'LONG': signal.take_profit = signal.entry_price * (1 + 0.015) # 1.5% TP else: signal.take_profit = signal.entry_price * (1 - 0.015) return signal # EDGE: Trade seulement si volume élevé if self.edge_type == 'high_volume_only': signal = super().generate_signal(df) if signal and len(df) >= 20: vol_ma = df['volume'].rolling(20).mean().iloc[-1] current_vol = df['volume'].iloc[-1] if current_vol < vol_ma * 1.5: # Skip si volume faible return None return signal # EDGE: Reverse après 2 pertes + TP x2 if self.edge_type == 'reverse2_tp2x': signal = super().generate_signal(df) if signal and self.consecutive_losses >= 2: # Reverse signal.side = 'SHORT' if signal.side == 'LONG' else 'LONG' signal.stop_loss, signal.take_profit = signal.take_profit, signal.stop_loss # Double TP if signal.side == 'LONG': tp_dist = signal.take_profit - signal.entry_price signal.take_profit = signal.entry_price + tp_dist * 2 else: tp_dist = signal.entry_price - signal.take_profit signal.take_profit = signal.entry_price - tp_dist * 2 return signal # EDGE: Martingale normale (x2) au lieu d'anti if self.edge_type == 'normal_martingale_x2': # Override multiplier self.get_martingale_multiplier = lambda: 2 ** self.current_level return super().generate_signal(df) # EDGE: Fibonacci multiplier if self.edge_type == 'fibo_multi': # Fibonacci: 1, 1, 2, 3, 5, 8 fibs = [1, 1, 2, 3, 5, 8] level = min(self.current_level, len(fibs)-1) self.get_martingale_multiplier = lambda: fibs[level] return super().generate_signal(df) return super().generate_signal(df) def update_after_trade(self, won): super().update_after_trade(won) if won: self.wait_count = 0 # ============ TESTS ============ edges = [ 'base', 'wait_after_3_losses', 'trend_only', 'only_long', 'only_short', 'reverse_and_wait', 'adaptive_tp', 'high_volume_only', 'reverse2_tp2x' ] results = [] for i, edge in enumerate(edges, 1): print(f"\n{'='*80}") print(f"🧪 TEST {i}/{len(edges)}: {edge.upper()}") print(f"{'='*80}") if edge == 'base': # Base anti-martingale class AntiMartingale(MartingaleStrategy): def get_martingale_multiplier(self): return 0.5 ** self.current_level strategy = AntiMartingale( base_position_size=10.0, max_martingale_level=5, base_leverage=100, max_leverage=1000, stop_loss_pct=0.003, take_profit_ratio=3.0, min_signal_score=0.6 ) else: strategy = CreativeEdgeStrategy( edge_type=edge, base_position_size=10.0, max_martingale_level=5, base_leverage=100, max_leverage=1000, stop_loss_pct=0.003, take_profit_ratio=3.0, min_signal_score=0.6 ) result = backtester.run_backtest(df, 'BTCUSDT', strategy) if result: results.append({ 'edge': edge, 'roi': result.total_return_pct, 'win_rate': result.win_rate, 'pf': result.profit_factor, 'trades': result.total_trades, 'dd': result.max_drawdown_pct, 'capital': result.final_capital }) else: results.append({ 'edge': edge, 'roi': 0, 'win_rate': 0, 'pf': 0, 'trades': 0, 'dd': 0, 'capital': 1000 }) # ============ RÉSULTATS ============ print("\n" + "="*80) print("🏆 CLASSEMENT EDGES CRÉATIFS") print("="*80) results.sort(key=lambda x: x['roi'], reverse=True) print(f"\n{'RANG':<5} {'EDGE':<30} {'ROI %':>10} {'WR %':>8} {'PF':>6} {'Trades':>7} {'DD %':>8}") print("-"*80) for rank, res in enumerate(results, 1): emoji = "🥇" if rank == 1 else "🥈" if rank == 2 else "🥉" if rank == 3 else f"{rank:2}" status = "✅" if res['roi'] > 0 else "⚠️" if res['roi'] > -1 else "❌" print(f"{emoji:<5} {res['edge']:<30} {res['roi']:>9.2f}% {res['win_rate']*100:>7.1f}% " f"{res['pf']:>5.2f} {res['trades']:>7} {res['dd']:>7.2f}% {status}") best = results[0] print(f"\n{'='*80}") print(f"🏆 MEILLEUR: {best['edge'].upper()}") print(f"{'='*80}") print(f" ROI: {best['roi']:+.2f}% {'✅ PROFITABLE!' if best['roi'] > 0 else '❌'}") print(f" Capital: ${best['capital']:.2f} ({'gain' if best['capital'] > 1000 else 'perte'} de ${abs(best['capital']-1000):.2f})") print(f" WR: {best['win_rate']*100:.1f}%") print(f" Trades: {best['trades']}") print(f" DD: {best['dd']:.2f}%") print(f"{'='*80}") # Sauvegarder import json with open('edge_v2_results.json', 'w') as f: json.dump(results, f, indent=2) print("\n💾 Résultats: edge_v2_results.json") if best['roi'] > 0: print(f"\n🎉 EDGE TROUVÉ! La stratégie {best['edge'].upper()} est PROFITABLE!") # Sauvegarder comme config with open('winning_edge_config.txt', 'w') as f: f.write(f"WINNING EDGE: {best['edge']}\n") f.write(f"ROI: {best['roi']:.2f}%\n") f.write(f"Capital: ${best['capital']:.2f}\n") print("✅ Config sauvegardée: winning_edge_config.txt")