#!/usr/bin/env python3 """ RECHERCHE D'UN EDGE - Trouve l'avantage qui rend la stratégie profitable Tests: 1. Inverser côté après N pertes 2. Doubler TP après N pertes 3. Skip trades après N pertes 4. Combinations """ from martingale_backtester import MartingaleBacktester from martingale_strategy import MartingaleStrategy import copy print("="*80) print("🔍 RECHERCHE D'UN EDGE - TROUVER L'AVANTAGE GAGNANT") print("="*80) # Fetch data 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: print("❌ Erreur") exit(1) print(f"✅ {len(df)} bougies chargées\n") # ============ EDGES À TESTER ============ edges = [ { 'name': '1. BASE (anti-martingale)', 'reverse_after_losses': None, 'double_tp_after_losses': None, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '2. REVERSE après 2 pertes', 'reverse_after_losses': 2, 'double_tp_after_losses': None, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '3. REVERSE après 3 pertes 🎯', 'reverse_after_losses': 3, 'double_tp_after_losses': None, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '4. REVERSE après 4 pertes', 'reverse_after_losses': 4, 'double_tp_after_losses': None, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '5. DOUBLE TP après 2 pertes', 'reverse_after_losses': None, 'double_tp_after_losses': 2, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '6. DOUBLE TP après 3 pertes', 'reverse_after_losses': None, 'double_tp_after_losses': 3, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '7. SKIP 1 trade après 3 pertes', 'reverse_after_losses': None, 'double_tp_after_losses': None, 'skip_after_losses': 3, 'reduce_leverage_after_losses': None }, { 'name': '8. REDUCE leverage 50% après 2 pertes', 'reverse_after_losses': None, 'double_tp_after_losses': None, 'skip_after_losses': None, 'reduce_leverage_after_losses': 2 }, { 'name': '9. REVERSE + DOUBLE TP après 3 pertes', 'reverse_after_losses': 3, 'double_tp_after_losses': 3, 'skip_after_losses': None, 'reduce_leverage_after_losses': None }, { 'name': '10. REVERSE + REDUCE LEV après 3 pertes', 'reverse_after_losses': 3, 'double_tp_after_losses': None, 'skip_after_losses': None, 'reduce_leverage_after_losses': 3 }, { 'name': '11. REVERSE après 2 + SKIP après 4', 'reverse_after_losses': 2, 'double_tp_after_losses': None, 'skip_after_losses': 4, 'reduce_leverage_after_losses': None }, { 'name': '12. REVERSE après 3 + DOUBLE TP après 2', 'reverse_after_losses': 3, 'double_tp_after_losses': 2, 'skip_after_losses': None, 'reduce_leverage_after_losses': None } ] # ============ STRATÉGIE AVEC EDGES ============ class EdgeStrategy(MartingaleStrategy): def __init__(self, edge_config, **kwargs): super().__init__(**kwargs) self.edge_config = edge_config self.side_reversed = False self.skip_next = False def get_martingale_multiplier(self): # Anti-martingale return 0.5 ** self.current_level def get_leverage_for_level(self): base_lev = super().get_leverage_for_level() # Edge: Reduce leverage après N pertes if (self.edge_config['reduce_leverage_after_losses'] and self.consecutive_losses >= self.edge_config['reduce_leverage_after_losses']): return int(base_lev * 0.5) return base_lev def generate_signal(self, df): # Edge: Skip après N pertes if (self.edge_config['skip_after_losses'] and self.consecutive_losses >= self.edge_config['skip_after_losses']): if self.skip_next: self.skip_next = False return None else: self.skip_next = True signal = super().generate_signal(df) if not signal: return None # Edge: Reverse côté après N pertes if (self.edge_config['reverse_after_losses'] and self.consecutive_losses >= self.edge_config['reverse_after_losses']): if not self.side_reversed: signal.side = 'SHORT' if signal.side == 'LONG' else 'LONG' # Swap SL/TP signal.stop_loss, signal.take_profit = signal.take_profit, signal.stop_loss self.side_reversed = True # Edge: Double TP après N pertes if (self.edge_config['double_tp_after_losses'] and self.consecutive_losses >= self.edge_config['double_tp_after_losses']): if signal.side == 'LONG': new_tp = signal.entry_price + (signal.take_profit - signal.entry_price) * 2 signal.take_profit = new_tp else: new_tp = signal.entry_price - (signal.entry_price - signal.take_profit) * 2 signal.take_profit = new_tp return signal def update_after_trade(self, won): super().update_after_trade(won) # Reset reverse flag quand on gagne if won: self.side_reversed = False self.skip_next = False # ============ TESTER CHAQUE EDGE ============ results_summary = [] for i, edge in enumerate(edges, 1): print(f"\n{'='*80}") print(f"🧪 TEST {i}/{len(edges)}: {edge['name']}") print(f"{'='*80}") strategy = EdgeStrategy( edge_config=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_summary.append({ 'name': edge['name'], 'roi': result.total_return_pct, 'win_rate': result.win_rate, 'profit_factor': result.profit_factor, 'trades': result.total_trades, 'max_dd': result.max_drawdown_pct, 'final_capital': result.final_capital }) else: results_summary.append({ 'name': edge['name'], 'roi': 0, 'win_rate': 0, 'profit_factor': 0, 'trades': 0, 'max_dd': 0, 'final_capital': 1000 }) # ============ CLASSEMENT ============ print("\n" + "="*80) print("🏆 CLASSEMENT DES EDGES") print("="*80) results_summary.sort(key=lambda x: x['roi'], reverse=True) print(f"\n{'RANG':<5} {'EDGE':<45} {'ROI %':>10} {'WR %':>8} {'PF':>6} {'Trades':>7} {'DD %':>8}") print("-"*80) for rank, res in enumerate(results_summary, 1): emoji = "🥇" if rank == 1 else "🥈" if rank == 2 else "🥉" if rank == 3 else f"{rank:2}" roi_emoji = "✅" if res['roi'] > 0 else "⚠️" if res['roi'] > -2 else "❌" print(f"{emoji:<5} {res['name']:<45} {res['roi']:>9.2f}% {res['win_rate']*100:>7.1f}% " f"{res['profit_factor']:>5.2f} {res['trades']:>7} {res['max_dd']:>7.2f}% {roi_emoji}") # Meilleur edge best = results_summary[0] print(f"\n{'='*80}") print(f"🏆 MEILLEUR EDGE: {best['name']}") print(f"{'='*80}") print(f" ROI: {best['roi']:+.2f}% {'✅ POSITIF!' if best['roi'] > 0 else '❌ Négatif'}") print(f" Win Rate: {best['win_rate']*100:.1f}%") print(f" Profit Factor: {best['profit_factor']:.2f}") print(f" Trades: {best['trades']}") print(f" Max DD: {best['max_dd']:.2f}%") print(f" Capital Final: ${best['final_capital']:.2f}") if best['roi'] > 0: print(f"\n🎉 EDGE TROUVÉ! Stratégie PROFITABLE!") print(f" Gain: ${best['final_capital'] - 1000:.2f}") else: print(f"\n⚠️ Meilleur edge mais toujours négatif") print(f" Continuer la recherche avec d'autres combinaisons") print(f"{'='*80}") # Sauvegarder import json with open('edge_test_results.json', 'w') as f: json.dump(results_summary, f, indent=2) print("\n💾 Résultats: edge_test_results.json")