ADD: added optimizer workflow

strategies.py

@@ -0,0 +1,92 @@
+import pandas as pd
+import pandas_ta as ta
+from backtesting import Strategy
+from backtesting.lib import crossover
+
+
+class RsiStrategy(Strategy):
+    # Default parameters (can be overridden by optimizer)
+    rsi_period = 14
+    rsi_lower = 30
+    rsi_upper = 70
+    # Position sizing and ATR stop parameters
+    position_size_pct = 0.1
+    min_shares = 1
+    atr_period = 14
+    stop_loss_atr_multiplier = 3.0
+
+    def init(self):
+        self.rsi = self.I(ta.rsi, pd.Series(self.data.Close), length=self.rsi_period)
+        self.atr = self.I(
+            ta.atr,
+            pd.Series(self.data.High),
+            pd.Series(self.data.Low),
+            pd.Series(self.data.Close),
+            length=self.atr_period,
+        )
+
+    def next(self):
+        if crossover(self.rsi, self.rsi_lower):
+            price = float(self.data.Close[-1])
+            max_invest = max(0, self.equity * self.position_size_pct)
+            shares = int(max_invest // price)
+            if shares < self.min_shares:
+                shares = self.min_shares
+
+            atr_value = float(self.atr[-1]) if not pd.isna(self.atr[-1]) else None
+            if atr_value and atr_value > 0:
+                stop_price = round(price - (self.stop_loss_atr_multiplier * atr_value), 6)
+                if stop_price >= price:
+                    stop_price = round(price * 0.99, 6)
+            else:
+                stop_price = round(price * 0.98, 6)
+
+            self.buy(size=shares, sl=stop_price)
+        elif crossover(self.rsi_upper, self.rsi):
+            if self.position:
+                self.position.close()
+
+
+class CrossEmaStrategy(Strategy):
+    """EMA crossover strategy with ATR-based stop-loss."""
+    short_ema = 12
+    long_ema = 26
+    position_size_pct = 0.1
+    min_shares = 1
+    atr_period = 14
+    stop_loss_atr_multiplier = 3.0
+
+    def init(self):
+        self.ema_short = self.I(ta.ema, pd.Series(self.data.Close), length=self.short_ema)
+        self.ema_long = self.I(ta.ema, pd.Series(self.data.Close), length=self.long_ema)
+        self.atr = self.I(
+            ta.atr,
+            pd.Series(self.data.High),
+            pd.Series(self.data.Low),
+            pd.Series(self.data.Close),
+            length=self.atr_period,
+        )
+
+    def next(self):
+        price = float(self.data.Close[-1])
+        # Buy when short EMA crosses above long EMA
+        if crossover(self.ema_short, self.ema_long):
+            max_invest = max(0, self.equity * self.position_size_pct)
+            shares = int(max_invest // price)
+            if shares < self.min_shares:
+                shares = self.min_shares
+
+            atr_value = float(self.atr[-1]) if not pd.isna(self.atr[-1]) else None
+            if atr_value and atr_value > 0:
+                stop_price = round(price - (self.stop_loss_atr_multiplier * atr_value), 6)
+                if stop_price >= price:
+                    stop_price = round(price * 0.99, 6)
+            else:
+                stop_price = round(price * 0.98, 6)
+
+            self.buy(size=shares, sl=stop_price)
+
+        # Sell when short EMA crosses below long EMA
+        elif crossover(self.ema_long, self.ema_short):
+            if self.position:
+                self.position.close()