diff --git a/datasource/hybrid_source.py b/datasource/hybrid_source.py
index 0be74d0..be411a7 100644
--- a/datasource/hybrid_source.py
+++ b/datasource/hybrid_source.py
@@ -200,7 +200,7 @@ class HybridDataSource:
                     etf_data_list.append(etf_data[['code', 'close']])
                     
                     price_count = len(etf_data)
-                    nav_count = len(etf_nav) if etf_nav else 0
+                    nav_count = len(etf_nav) if etf_nav is not None else 0
                     
                     print(f"✓ 价格{price_count}条 净值{nav_count}条")
                 else:
@@ -214,17 +214,32 @@ class HybridDataSource:
         index_data = None
         if index_data_list:
             index_data = pd.concat(index_data_list)
-            index_data = index_data.pivot(columns='code', values='close')
+            if 'code' in index_data.columns and 'close' in index_data.columns:
+                index_data = index_data.reset_index()
+                if 'index' in index_data.columns:
+                    index_data = index_data.rename(columns={'index': 'date'})
+                index_data['date'] = pd.to_datetime(index_data['date']).dt.normalize()
+                index_data = index_data.pivot_table(index='date', columns='code', values='close')
         
         etf_data = None
         if etf_data_list:
             etf_data = pd.concat(etf_data_list)
-            etf_data = etf_data.pivot(columns='code', values='close')
+            if 'code' in etf_data.columns and 'close' in etf_data.columns:
+                etf_data = etf_data.reset_index()
+                if 'index' in etf_data.columns:
+                    etf_data = etf_data.rename(columns={'index': 'date'})
+                etf_data['date'] = pd.to_datetime(etf_data['date']).dt.normalize()
+                etf_data = etf_data.pivot_table(index='date', columns='code', values='close')
         
         etf_nav_data = None
         if etf_nav_data_list:
             etf_nav_data = pd.concat(etf_nav_data_list)
-            etf_nav_data = etf_nav_data.pivot(columns='code', values='nav')
+            if 'code' in etf_nav_data.columns and 'nav' in etf_nav_data.columns:
+                etf_nav_data = etf_nav_data.reset_index()
+                if 'index' in etf_nav_data.columns:
+                    etf_nav_data = etf_nav_data.rename(columns={'index': 'date'})
+                etf_nav_data['date'] = pd.to_datetime(etf_nav_data['date']).dt.normalize()
+                etf_nav_data = etf_nav_data.pivot_table(index='date', columns='code', values='nav')
         
         # 基准数据
         benchmark_data = self._tushare.fetch_index(benchmark_code, start_date, end_date)
diff --git a/datasource/tushare_source.py b/datasource/tushare_source.py
index 71551c4..0ba9ce4 100644
--- a/datasource/tushare_source.py
+++ b/datasource/tushare_source.py
@@ -104,13 +104,14 @@ class TushareSource:
         original_proxy = self._clear_proxy()
         
         try:
+            import tushare as ts
             pro = self._get_pro_api()
             
-            df = pro.futures_daily(
+            # 使用 fut_daily 接口
+            df = pro.fut_daily(
                 ts_code=code,
                 start_date=start_date.replace("-", ""),
-                end_date=end_date.replace("-", ""),
-                exchange=''
+                end_date=end_date.replace("-", "")
             )
             
             if df is None or len(df) == 0:
diff --git a/strategies/rotation/strategy.py b/strategies/rotation/strategy.py
index ad86c44..a475e4e 100644
--- a/strategies/rotation/strategy.py
+++ b/strategies/rotation/strategy.py
@@ -197,14 +197,33 @@ class RotationStrategy(StrategyBase):
         
         # 4. 执行回测
         print("\n执行回测...")
-        returns_data = {}
-        first_code = valid_codes[0]
-        for code in valid_codes:
-            df = index_data[code]
-            returns_data[f'日收益率_{code}'] = df['close'].pct_change()
         
-        returns_df = pd.DataFrame(returns_data)
-        returns_df.index = index_data[first_code].index
+        # 使用对齐后的指数收盘价数据获取日期基准
+        index_close = data.get('index_close')
+        
+        # 计算日收益率（使用对齐后的收盘价数据）
+        if index_close is not None and not index_close.empty:
+            returns_df = index_close.pct_change()
+            returns_df.columns = [f'日收益率_{col}' for col in returns_df.columns]
+        else:
+            # 回退到原始数据
+            returns_data = {}
+            for code in valid_codes:
+                if code in index_data:
+                    df = index_data[code]
+                    returns_data[f'日收益率_{code}'] = df['close'].pct_change()
+            returns_df = pd.DataFrame(returns_data)
+            
+            if valid_codes:
+                first_code = valid_codes[0]
+                returns_df.index = index_data[first_code].index
+        
+        # 确保信号和收益率数据日期对齐
+        common_dates = signals.index.intersection(returns_df.index)
+        signals = signals.loc[common_dates]
+        returns_df = returns_df.loc[common_dates]
+        
+        print(f"  对齐后日期: {len(common_dates)} 天")
         
         executor = BacktestExecutor(
             initial_capital=100000,