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

src/strategies/breakout.py

@@ -0,0 +1,64 @@
+# src/strategies/breakout.py
+import pandas as pd
+
+from src.strategies.base import Strategy
+from src.core.strategy import Signal
+
+class DonchianBreakout(Strategy):
+    """
+    Estrategia de ruptura de canales Donchian
+
+    Señales:
+    - BUY: El precio rompe el máximo de los últimos N periodos
+    - SELL: El precio rompe el mínimo de los últimos N periodos
+    - HOLD: En cualquier otro caso
+
+    Parámetros:
+        lookback: Ventana de cálculo del canal
+
+    Valores por defecto:
+        lookback = 20
+        ≈ 1 día en timeframe 1h
+        Parámetro clásico del sistema Turtle
+
+    Notas:
+        - Es una estrategia de momentum puro
+        - No intenta comprar barato, compra fortaleza
+        - Filtra ruido al exigir ruptura real
+    """
+
+    def __init__(self, lookback: int = 20):
+        params = {
+            "lookback": lookback
+        }
+
+        super().__init__(name="DonchianBreakout", params=params)
+
+        self.lookback = lookback
+
+    # ------------------------------------------------------------------
+
+    def init_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
+        data["donchian_high"] = data["high"].rolling(self.lookback).max()
+        data["donchian_low"] = data["low"].rolling(self.lookback).min()
+        return data
+
+    def generate_signal(self, idx: int) -> Signal:
+        if idx < self.lookback:
+            return Signal.HOLD
+        
+        high = self.data["high"]
+        low = self.data["low"]
+        close = self.data["close"]
+
+        max_high = high.iloc[idx - self.lookback : idx].max()
+        min_low = low.iloc[idx - self.lookback : idx].min()
+
+        price = close.iloc[idx]
+
+        if price > max_high:
+            return Signal.BUY
+        elif price < min_low:
+            return Signal.SELL
+        
+        return Signal.HOLD