Initial commit — Trading AI Secure project complet

Architecture Docker (8 services), FastAPI, TimescaleDB, Redis, Streamlit.
Stratégies : scalping, intraday, swing. MLEngine + RegimeDetector (HMM).
BacktestEngine + WalkForwardAnalyzer + Optuna optimizer.
Routes API complètes dont /optimize async.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

examples/simple_backtest.py

@@ -0,0 +1,148 @@
+"""
+Exemple Simple - Premier Backtest.
+
+Cet exemple montre comment:
+1. Configurer le système
+2. Charger une stratégie
+3. Lancer un backtest
+4. Analyser les résultats
+"""
+
+import asyncio
+import sys
+from pathlib import Path
+from datetime import datetime, timedelta
+
+# Ajouter src au path
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from src.core.risk_manager import RiskManager
+from src.core.strategy_engine import StrategyEngine
+from src.backtesting.backtest_engine import BacktestEngine
+from src.utils.logger import setup_logger
+
+
+async def main():
+    """Fonction principale."""
+    
+    # 1. Setup logging
+    setup_logger(level='INFO')
+    
+    print("=" * 60)
+    print("EXEMPLE SIMPLE - PREMIER BACKTEST")
+    print("=" * 60)
+    
+    # 2. Configuration
+    config = {
+        'risk_limits': {
+            'initial_capital': 10000.0,
+            'global_limits': {
+                'max_portfolio_risk': 0.05,
+                'max_position_size': 0.10,
+                'max_drawdown': 0.15,
+                'max_daily_loss': 0.03,
+                'max_correlation': 0.7,
+            },
+            'strategy_limits': {
+                'intraday': {
+                    'risk_per_trade': 0.02,
+                    'max_trades_per_day': 20,
+                }
+            }
+        },
+        'strategy_params': {
+            'intraday_strategy': {
+                'name': 'intraday',
+                'timeframe': '1h',
+                'risk_per_trade': 0.02,
+                'max_holding_time': 28800,
+                'max_trades_per_day': 20,
+                'adaptive_params': {
+                    'ema_fast': 9,
+                    'ema_slow': 21,
+                    'ema_trend': 50,
+                    'adx_threshold': 25,
+                }
+            }
+        },
+        'backtesting_config': {
+            'transaction_costs': {
+                'commission_pct': 0.0001,
+                'slippage_pct': 0.0005,
+                'spread_pct': 0.0002,
+            }
+        }
+    }
+    
+    # 3. Initialiser Risk Manager
+    print("\n📊 Initialisation du Risk Manager...")
+    risk_manager = RiskManager()
+    risk_manager.initialize(config['risk_limits'])
+    
+    # 4. Initialiser Strategy Engine
+    print("🎯 Initialisation du Strategy Engine...")
+    strategy_engine = StrategyEngine(
+        config=config['strategy_params'],
+        risk_manager=risk_manager
+    )
+    
+    # 5. Charger stratégie Intraday
+    print("📈 Chargement de la stratégie Intraday...")
+    await strategy_engine.load_strategy('intraday')
+    
+    # 6. Créer Backtest Engine
+    print("🔄 Création du Backtest Engine...")
+    backtest_engine = BacktestEngine(
+        strategy_engine=strategy_engine,
+        config=config
+    )
+    
+    # 7. Lancer backtest
+    print("\n🚀 Lancement du backtest...")
+    print("Symbole: EURUSD")
+    print("Période: 6 mois")
+    print("Capital initial: $10,000")
+    
+    results = await backtest_engine.run(
+        symbols=['EURUSD'],
+        period='6m',
+        initial_capital=10000.0
+    )
+    
+    # 8. Afficher résultats
+    if results:
+        print("\n" + "=" * 60)
+        print("RÉSULTATS DU BACKTEST")
+        print("=" * 60)
+        
+        metrics = results['metrics']
+        
+        print(f"\n📈 PERFORMANCE")
+        print(f"Return Total:      {metrics['total_return']:>10.2%}")
+        print(f"Sharpe Ratio:      {metrics['sharpe_ratio']:>10.2f}")
+        print(f"Max Drawdown:      {metrics['max_drawdown']:>10.2%}")
+        
+        print(f"\n💼 TRADING")
+        print(f"Total Trades:      {metrics['total_trades']:>10}")
+        print(f"Win Rate:          {metrics['win_rate']:>10.2%}")
+        print(f"Profit Factor:     {metrics['profit_factor']:>10.2f}")
+        
+        print("\n" + "=" * 60)
+        
+        # 9. Validation
+        if results['is_valid']:
+            print("✅ STRATÉGIE VALIDE pour paper trading!")
+            print("\nProchaine étape: Lancer paper trading pendant 30 jours")
+        else:
+            print("❌ STRATÉGIE NON VALIDE")
+            print("\nActions recommandées:")
+            print("1. Optimiser les paramètres")
+            print("2. Tester sur différentes périodes")
+            print("3. Analyser les trades perdants")
+    
+    else:
+        print("\n❌ Backtest échoué - Vérifier les logs")
+
+
+if __name__ == '__main__':
+    asyncio.run(main())