diff --git a/src/pages/backtesting/backtesting_page.py b/src/pages/backtesting/backtesting_page.py
index d75392d..49db1e4 100644
--- a/src/pages/backtesting/backtesting_page.py
+++ b/src/pages/backtesting/backtesting_page.py
@@ -19,19 +19,22 @@ class DynamicStrategy(Strategy):
         for ind_name, ind_config in self.indicator_configs.items():
             if ind_config['type'] == 'SMA':
                 def sma_calc(x):
-                    result = ta.sma(x, length=int(ind_config['params']['length']))
+                    series = pd.Series(x)
+                    result = ta.sma(series, length=int(ind_config['params']['length']))
                     return result.fillna(method='ffill').fillna(0).values
                 self.indicators[ind_name] = self.I(sma_calc, self.data.Close)
                 
             elif ind_config['type'] == 'EMA':
                 def ema_calc(x):
-                    result = ta.ema(x, length=int(ind_config['params']['length']))
+                    series = pd.Series(x)
+                    result = ta.ema(series, length=int(ind_config['params']['length']))
                     return result.fillna(method='ffill').fillna(0).values
                 self.indicators[ind_name] = self.I(ema_calc, self.data.Close)
                 
             elif ind_config['type'] == 'RSI':
                 def rsi_calc(x):
-                    result = ta.rsi(x, length=int(ind_config['params']['length']))
+                    series = pd.Series(x)
+                    result = ta.rsi(series, length=int(ind_config['params']['length']))
                     return result.fillna(method='ffill').fillna(0).values
                 self.indicators[ind_name] = self.I(rsi_calc, self.data.Close)
                 
@@ -41,11 +44,18 @@ class DynamicStrategy(Strategy):
                 signal = int(ind_config['params']['signal'])
                 
                 def macd_calc(x):
-                    result = ta.macd(x, fast=fast, slow=slow, signal=signal)
+                    series = pd.Series(x)
+                    result = ta.macd(series, fast=fast, slow=slow, signal=signal)
                     if result is None or result.empty:
                         return np.zeros(len(x)), np.zeros(len(x))
-                    return (result.iloc[:,0].fillna(method='ffill').fillna(0).values,
-                           result.iloc[:,2].fillna(method='ffill').fillna(0).values)
+                        
+                    macd_col = result.columns[0]
+                    signal_col = result.columns[2]
+                    
+                    macd_vals = result[macd_col].fillna(method='ffill').fillna(0).values
+                    signal_vals = result[signal_col].fillna(method='ffill').fillna(0).values
+                    
+                    return macd_vals, signal_vals
                 
                 macd_vals = self.I(macd_calc, self.data.Close)
                 self.indicators[f"{ind_name}_macd"] = macd_vals[0]