diff --git a/strategies/rotation/strategy.py b/strategies/rotation/strategy.py
index cfd7939..930c8e2 100644
--- a/strategies/rotation/strategy.py
+++ b/strategies/rotation/strategy.py
@@ -9,6 +9,10 @@ import yaml
 from datetime import datetime
 from pathlib import Path
 
+# 加载环境变量
+from dotenv import load_dotenv
+load_dotenv()
+
 from framework.factors import FactorRegistry, FactorCombiner
 from framework.signals import SignalGenerator
 from framework.execution import BacktestExecutor
@@ -104,9 +108,10 @@ class RotationStrategy(StrategyBase):
     def get_data(self) -> dict:
         """获取数据（复用归档的数据源）"""
         code_list_config = self.config.get('code_list', {})
-        code_list = list(code_list_config.keys())
+        benchmark_config = self.config.get('benchmark', {})
+        benchmark_code = benchmark_config.get('code', '000300.SH')
         
-        if not code_list:
+        if not code_list_config:
             raise ValueError("配置中未找到 code_list")
         
         # 使用归档的HybridDataSource
@@ -129,17 +134,22 @@ class RotationStrategy(StrategyBase):
             use_cache=self.config.get('use_cache', True)
         )
         
-        # 获取数据
-        index_data = {}
-        all_data = data_source.fetch_batch(code_list, self.start_date, self.end_date)
-        
-        for code, df in all_data.items():
-            if df is not None and not df.empty:
-                index_data[code] = df
+        # 调用 fetch_all（返回元组）
+        index_data, etf_data, etf_nav_data, benchmark_data, valid_codes, index_ohlcv_data = \
+            data_source.fetch_all(
+                code_config=code_list_config,
+                benchmark_code=benchmark_code,
+                start_date=self.start_date,
+                end_date=self.end_date
+            )
         
         return {
-            'index_data': index_data,
-            'valid_codes': list(index_data.keys())
+            'index_data': index_ohlcv_data,  # 原始OHLCV数据
+            'index_close': index_data,       # 对齐后的收盘价（宽格式）
+            'etf_data': etf_data,
+            'etf_nav_data': etf_nav_data,
+            'benchmark_data': benchmark_data,
+            'valid_codes': valid_codes
         }
     
     def compute_factors(self, data: dict) -> pd.DataFrame: