加入一个回测，

generate_backtest_chart.py

@@ -28,12 +28,12 @@ class BitMartETH5M(Model):
 
 
 def calculate_bollinger_bands(df, period=10, std_dev=2.5):
-    """计算布林带"""
+    """计算布林带（右移1根，与回测口径一致）"""
     df['sma'] = df['close'].rolling(window=period).mean()
     df['std'] = df['close'].rolling(window=period).std()
-    df['bb_upper'] = df['sma'] + std_dev * df['std']
-    df['bb_mid'] = df['sma']
-    df['bb_lower'] = df['sma'] - std_dev * df['std']
+    df['bb_upper'] = (df['sma'] + std_dev * df['std']).shift(1)
+    df['bb_mid'] = df['sma'].shift(1)
+    df['bb_lower'] = (df['sma'] - std_dev * df['std']).shift(1)
     return df
 
 
@@ -503,21 +503,25 @@ if __name__ == '__main__':
     
     try:
         print("正在生成回测可视化图表...")
+
+        output_dir = Path(__file__).parent / 'backtest_outputs' / 'charts'
+        output_dir.mkdir(parents=True, exist_ok=True)
         
         # 生成图表数据
         chart_data, trades_markers = generate_chart_data(
             start_date='2026-03-01',
             end_date='2026-03-03',
-            trades_file='bb_backtest_march_2026_trades.csv'
+            trades_file=str(Path(__file__).parent / 'backtest_outputs' / 'trades' / 'bb_backtest_march_2026_trades.csv')
         )
         
         print(f"📊 K线数据: {len(chart_data)} 根")
         print(f"📍 交易标记: {len(trades_markers)} 个")
         
         # 生成HTML
-        generate_html(chart_data, trades_markers, 'bb_backtest_visualization.html')
+        output_file = output_dir / 'bb_backtest_visualization.html'
+        generate_html(chart_data, trades_markers, str(output_file))
         
-        print("\n🎉 完成！请在浏览器中打开 bb_backtest_visualization.html 查看图表")
+        print(f"\n🎉 完成！请在浏览器中打开 {output_file} 查看图表")
         
     finally:
         db.close()