diff --git a/config/strategies/rotation.yaml b/config/strategies/rotation.yaml
index c7b5900..3846d02 100644
--- a/config/strategies/rotation.yaml
+++ b/config/strategies/rotation.yaml
@@ -97,14 +97,14 @@ code_list:
     market: "FUTURES"     # 期货合约，交易时间含夜盘，数据逻辑类似加密货币
   
   # 加密货币 (使用 CCXT/OKX 现货) - 通过 SSH->HTTP 代理访问
-  "BTC":
-    name: "比特币"
-    etf: null              # 无ETF，直接交易
-    market: "CRYPTO"
-  "ETH":
-    name: "以太坊"
-    etf: null              # 无ETF，直接交易
-    market: "CRYPTO"
+  # "BTC":
+  #   name: "比特币"
+  #   etf: null              # 无ETF，直接交易
+  #   market: "CRYPTO"
+  # "ETH":
+  #   name: "以太坊"
+  #   etf: null              # 无ETF，直接交易
+  #   market: "CRYPTO"
 
 # 主市场配置（用于确定交易日历）
 primary_market:
diff --git a/scripts/export_rotation_data.py b/scripts/export_rotation_data.py
new file mode 100644
index 0000000..bd271fc
--- /dev/null
+++ b/scripts/export_rotation_data.py
@@ -0,0 +1,137 @@
+"""
+导出轮动策略回测所用的原始数据到本地文件夹
+
+导出内容：
+1. index_data.csv   - 指数价格数据（宽格式，用于因子计算）
+2. etf_data.csv     - ETF价格数据（宽格式，用于收益计算）
+3. etf_nav_data.csv - ETF净值数据（宽格式，用于溢价率计算）
+4. benchmark_data.csv - 基准数据
+5. config_snapshot.yaml - 当时使用的策略配置快照
+"""
+
+import sys
+import os
+import time
+import shutil
+from datetime import datetime
+from pathlib import Path
+
+# 添加项目根目录
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+import yaml
+import pandas as pd
+from dotenv import load_dotenv
+
+load_dotenv()
+
+from strategies.rotation.engine import RotationStrategy
+from config.settings import DEFAULT_BENCHMARK_CODE
+
+
+def main():
+    # 加载配置
+    config_path = Path(__file__).parent.parent / "config" / "strategies" / "rotation.yaml"
+    with open(config_path, "r", encoding="utf-8") as f:
+        config = yaml.safe_load(f)
+
+    # 如果未设置 end_date，默认使用今天
+    if not config.get("end_date"):
+        config["end_date"] = datetime.now().strftime("%Y-%m-%d")
+
+    start_date = config["start_date"]
+    end_date = config["end_date"]
+
+    print("=" * 60)
+    print("  导出轮动策略回测数据")
+    print("=" * 60)
+    print(f"  回测区间: {start_date} ~ {end_date}")
+    print(f"  候选标的: {len(config.get('code_list', {}))} 只")
+
+    # 创建输出目录
+    export_dir = Path(__file__).parent.parent / "data" / "rotation_backtest_data"
+    export_dir.mkdir(parents=True, exist_ok=True)
+    print(f"  输出目录: {export_dir}")
+
+    # 创建策略实例（仅用于获取数据）
+    strategy = RotationStrategy(config)
+
+    # 获取数据
+    print("\n" + "=" * 60)
+    print("开始下载数据...")
+    print("=" * 60)
+
+    benchmark_code = config.get("benchmark", {}).get("code", DEFAULT_BENCHMARK_CODE)
+    code_config = config.get("code_list", {})
+
+    with strategy.data_source:
+        index_data, etf_data, etf_nav_data, benchmark_data, valid_codes = (
+            strategy.data_source.fetch_all(
+                code_config, benchmark_code, start_date, end_date
+            )
+        )
+
+    # 保存数据
+    print("\n" + "=" * 60)
+    print("保存数据到本地...")
+    print("=" * 60)
+
+    saved_files = []
+
+    # 1. 指数价格数据
+    if index_data is not None:
+        path = export_dir / "index_data.csv"
+        index_data.to_csv(path)
+        saved_files.append(("index_data.csv", index_data.shape, "指数价格（因子计算用）"))
+        print(f"  ✓ index_data.csv: {index_data.shape[0]} 行 × {index_data.shape[1]} 列")
+
+    # 2. ETF价格数据
+    if etf_data is not None:
+        path = export_dir / "etf_data.csv"
+        etf_data.to_csv(path)
+        saved_files.append(("etf_data.csv", etf_data.shape, "ETF价格（收益计算用）"))
+        print(f"  ✓ etf_data.csv: {etf_data.shape[0]} 行 × {etf_data.shape[1]} 列")
+
+    # 3. ETF净值数据
+    if etf_nav_data is not None:
+        path = export_dir / "etf_nav_data.csv"
+        etf_nav_data.to_csv(path)
+        saved_files.append(("etf_nav_data.csv", etf_nav_data.shape, "ETF净值（溢价率计算用）"))
+        print(f"  ✓ etf_nav_data.csv: {etf_nav_data.shape[0]} 行 × {etf_nav_data.shape[1]} 列")
+
+    # 4. 基准数据
+    if benchmark_data is not None:
+        path = export_dir / "benchmark_data.csv"
+        benchmark_data.to_csv(path)
+        saved_files.append(("benchmark_data.csv", benchmark_data.shape, "基准指数"))
+        print(f"  ✓ benchmark_data.csv: {benchmark_data.shape[0]} 行")
+
+    # 5. 有效代码列表
+    codes_path = export_dir / "valid_codes.txt"
+    with open(codes_path, "w") as f:
+        for code in valid_codes:
+            name = code_config.get(code, {}).get("name", code)
+            etf = code_config.get(code, {}).get("etf", "")
+            market = code_config.get(code, {}).get("market", "")
+            f.write(f"{code}\t{name}\t{etf or '-'}\t{market}\n")
+    print(f"  ✓ valid_codes.txt: {len(valid_codes)} 只有效标的")
+
+    # 6. 策略配置快照
+    config_snapshot_path = export_dir / "config_snapshot.yaml"
+    shutil.copy2(config_path, config_snapshot_path)
+    print(f"  ✓ config_snapshot.yaml: 策略配置快照")
+
+    # 汇总
+    print("\n" + "=" * 60)
+    print("导出完成！")
+    print("=" * 60)
+    print(f"  目录: {export_dir}")
+    print(f"  文件数: {len(saved_files) + 2}")
+    print(f"  数据区间: {start_date} ~ {end_date}")
+    print(f"  有效标的: {len(valid_codes)} 只")
+    for fname, shape, desc in saved_files:
+        print(f"    - {fname}: {shape} ({desc})")
+
+
+if __name__ == "__main__":
+    main()