diff --git a/src/pages/backtesting/backtesting_page.py b/src/pages/backtesting/backtesting_page.py
index 801f862..adfedbe 100644
--- a/src/pages/backtesting/backtesting_page.py
+++ b/src/pages/backtesting/backtesting_page.py
@@ -461,19 +461,28 @@ def run_multi_ticker_backtest(tickers: list, start_date: datetime, end_date: dat
     """Run backtest across multiple tickers and aggregate results"""
     all_results = []
     
+    if not indicator_settings:
+        print("Error: No indicators selected")
+        raise ValueError("Please select at least one indicator")
+    
     # Convert indicator settings to the correct format
     processed_settings = {}
     for ind_name, ind_config in indicator_settings.items():
+        processed_settings[ind_name] = {
+            'type': ind_config['type'],
+            'params': {}
+        }
+        # Handle both optimization and non-optimization cases
         if isinstance(ind_config['params'], dict):
-            # If params is a dictionary of parameter values (non-optimization mode)
-            processed_settings[ind_name] = {
-                'type': ind_config['type'],
-                'params': {k: float(v) if isinstance(v, (int, float)) else v 
-                          for k, v in ind_config['params'].items()}
-            }
-        else:
-            # If params is a dictionary of parameter ranges (optimization mode)
-            processed_settings[ind_name] = ind_config
+            for param_name, param_value in ind_config['params'].items():
+                # Handle both direct values and range dictionaries
+                if isinstance(param_value, dict):
+                    # Use the minimum value from the range for non-optimization run
+                    processed_settings[ind_name]['params'][param_name] = float(param_value['min'])
+                else:
+                    processed_settings[ind_name]['params'][param_name] = float(param_value)
+
+    print(f"Processed indicator settings: {processed_settings}")
     
     for ticker in tickers:
         try:
@@ -499,21 +508,24 @@ def run_multi_ticker_backtest(tickers: list, start_date: datetime, end_date: dat
             
             # Run backtest
             try:
+                # Set the indicator configs before creating the Backtest instance
                 DynamicStrategy.indicator_configs = processed_settings
+                print(f"Strategy configured with settings: {processed_settings}")
+                    
                 bt = Backtest(df, DynamicStrategy, cash=100000, commission=.002)
                 stats = bt.run()
-                
+                    
                 print(f"Backtest completed for {ticker}")
                 print("Available stats keys:", stats.keys())
-                
+                    
                 # Store results with error handling for each metric
                 result = {
                     'Ticker': ticker,
-                    'Return [%]': float(stats.get('Return [%]', stats.get('Return', 0))),
-                    'Sharpe Ratio': float(stats.get('Sharpe Ratio', 0)),
-                    'Max Drawdown [%]': float(stats.get('Max. Drawdown [%]', stats.get('Max Drawdown', 0))),
-                    'Win Rate [%]': float(stats.get('Win Rate [%]', stats.get('Win Rate', 0))),
-                    'Number of Trades': int(stats.get('# Trades', stats.get('Number of Trades', 0)))
+                    'Return [%]': float(stats['Return [%]']),  # Use direct key access
+                    'Sharpe Ratio': float(stats['Sharpe Ratio']),
+                    'Max Drawdown [%]': float(stats['Max. Drawdown [%]']),
+                    'Win Rate [%]': float(stats['Win Rate [%]']),
+                    'Number of Trades': int(stats['# Trades'])
                 }
                 
                 # Verify results are valid
@@ -537,12 +549,10 @@ def run_multi_ticker_backtest(tickers: list, start_date: datetime, end_date: dat
             continue
     
     if not all_results:
-        print("No valid results were generated. Check the following:")
-        print("1. Are the tickers valid?")
-        print("2. Is there data available for the selected date range?")
-        print("3. Are the indicator settings valid?")
-        print("4. Are there any errors in the strategy logic?")
-        print(f"Last used indicator settings: {processed_settings}")
+        print("\nNo valid results were generated. Debug information:")
+        print(f"Number of tickers processed: {len(tickers)}")
+        print(f"Indicator settings used: {processed_settings}")
+        print(f"Date range: {start_date} to {end_date}")
         raise ValueError("No valid results were generated from any ticker")
         
     return pd.DataFrame(all_results)