diff --git a/src/pages/backtesting/backtesting_page.py b/src/pages/backtesting/backtesting_page.py
index c504464..d6ec03f 100644
--- a/src/pages/backtesting/backtesting_page.py
+++ b/src/pages/backtesting/backtesting_page.py
@@ -477,25 +477,31 @@ def run_multi_ticker_backtest(tickers: list, start_date: datetime, end_date: dat
             bt = Backtest(df, DynamicStrategy, cash=100000, commission=.002)
             stats = bt.run()
             
-            # Store results
+            # Print raw stats for debugging
+            print("Debug - Available stats keys:", stats.keys())
+            
+            # Store results with error handling for each metric
             result = {
                 'Ticker': ticker,
-                'Return [%]': stats['Return [%]'],
-                'Sharpe Ratio': stats['Sharpe Ratio'],
-                'Max Drawdown [%]': stats['Max. Drawdown [%]'],
-                'Win Rate [%]': stats['Win Rate [%]'],
-                'Number of Trades': stats['# Trades']
+                'Return [%]': stats.get('Return [%]', stats.get('Return', 0)),
+                'Sharpe Ratio': stats.get('Sharpe Ratio', 0),
+                'Max Drawdown [%]': stats.get('Max. Drawdown [%]', stats.get('Max Drawdown', 0)),
+                'Win Rate [%]': stats.get('Win Rate [%]', stats.get('Win Rate', 0)),
+                'Number of Trades': stats.get('# Trades', stats.get('Number of Trades', 0))
             }
             all_results.append(result)
             
-            print(f"{ticker} - Return: {stats['Return [%]']:.2f}%, "
-                  f"Sharpe: {stats['Sharpe Ratio']:.2f}, "
-                  f"Drawdown: {stats['Max. Drawdown [%]']:.2f}%")
+            print(f"{ticker} - Return: {result['Return [%]']:.2f}%, "
+                  f"Sharpe: {result['Sharpe Ratio']:.2f}, "
+                  f"Drawdown: {result['Max Drawdown [%]']:.2f}%")
             
         except Exception as e:
             print(f"Error processing {ticker}: {str(e)}")
             continue
     
+    if not all_results:
+        raise ValueError("No valid results were generated from any ticker")
+        
     return pd.DataFrame(all_results)
 
 def display_backtest_results(results: Dict):