From 8c2b8233cfcfa97339a0246321fa200843636f6e Mon Sep 17 00:00:00 2001
From: "Bobby (aider)" <bobby@abellana.work>
Date: Fri, 14 Feb 2025 00:04:40 -0800
Subject: [PATCH] refactor: Enhance multi-ticker backtest error handling and
 debugging

---
 src/pages/backtesting/backtesting_page.py | 73 ++++++++++++++++-------
 1 file changed, 50 insertions(+), 23 deletions(-)

diff --git a/src/pages/backtesting/backtesting_page.py b/src/pages/backtesting/backtesting_page.py
index d6ec03f..be32a30 100644
--- a/src/pages/backtesting/backtesting_page.py
+++ b/src/pages/backtesting/backtesting_page.py
@@ -466,40 +466,67 @@ def run_multi_ticker_backtest(tickers: list, start_date: datetime, end_date: dat
             print(f"\nTesting strategy on {ticker}")
             df = get_stock_data(ticker, start_date, end_date, 'daily')
             
-            if df.empty:
+            if df is None or df.empty:
                 print(f"No data available for {ticker}")
                 continue
                 
-            df = prepare_data_for_backtest(df)
+            print(f"Data shape for {ticker}: {df.shape}")
+            print(f"Date range: {df.index.min()} to {df.index.max()}")
+            print(f"Columns: {df.columns.tolist()}")
+            
+            try:
+                df = prepare_data_for_backtest(df)
+            except Exception as e:
+                print(f"Error preparing data for {ticker}: {str(e)}")
+                continue
+                
+            print(f"Prepared data shape: {df.shape}")
+            print(f"Final columns: {df.columns.tolist()}")
             
             # Run backtest
-            DynamicStrategy.indicator_configs = indicator_settings
-            bt = Backtest(df, DynamicStrategy, cash=100000, commission=.002)
-            stats = bt.run()
-            
-            # 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.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: {result['Return [%]']:.2f}%, "
-                  f"Sharpe: {result['Sharpe Ratio']:.2f}, "
-                  f"Drawdown: {result['Max Drawdown [%]']:.2f}%")
+            try:
+                DynamicStrategy.indicator_configs = indicator_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)))
+                }
+                
+                # Verify results are valid
+                if any(pd.isna(val) for val in result.values()):
+                    print(f"Warning: NaN values in results for {ticker}")
+                    continue
+                    
+                all_results.append(result)
+                
+                print(f"Success - {ticker} results:")
+                for key, value in result.items():
+                    print(f"{key}: {value}")
+                
+            except Exception as e:
+                print(f"Error during backtest for {ticker}: {str(e)}")
+                continue
             
         except Exception as e:
             print(f"Error processing {ticker}: {str(e)}")
             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?")
         raise ValueError("No valid results were generated from any ticker")
         
     return pd.DataFrame(all_results)