feat: finalize portfolio system and quantitative validation- Finalized MA_Crossover(30,100) and TrendFiltered_MA(30,100,ADX=15)

- Implemented portfolio engine with risk-based allocation (50/50)
- Added equity-based metrics for system-level evaluation
- Validated portfolio against standalone strategies
- Reduced max drawdown and volatility at system level
- Quantitative decision closed before paper trading phase

backtest.py

@@ -9,8 +9,8 @@ from datetime import datetime, timedelta
 
 from src.utils.logger import log
 from src.data.storage import StorageManager
-from src.backtest.engine import BacktestEngine
-from src.backtest.metrics import print_backtest_report, calculate_all_metrics
+from src.core.engine import Engine
+from src.core.metrics import print_backtest_report, calculate_all_metrics
 from src.strategies import MovingAverageCrossover, BuyAndHold, RSIStrategy
 
 def setup_environment():
@@ -76,7 +76,7 @@ def run_backtest_demo():
     )
     
     # Crear motor de backtesting
-    engine = BacktestEngine(
+    engine = Engine(
         strategy=strategy,
         initial_capital=10000,
         commission=0.001,  # 0.1%
@@ -172,7 +172,7 @@ def compare_strategies_demo():
     for name, strategy in strategies:
         log.info(f"\n🧪 Testeando: {name}")
         
-        engine = BacktestEngine(
+        engine = Engine(
             strategy=strategy,
             initial_capital=10000,
             commission=0.001,
@@ -187,7 +187,7 @@ def compare_strategies_demo():
         log.info(f"   Win Rate: {results['win_rate_pct']:.2f}%")
     
     # Comparar resultados
-    from src.backtest.metrics import compare_strategies
+    from src.core.metrics import compare_strategies
     compare_strategies(all_results)
     
     storage.close()