diff --git a/czsc/traders/weight_backtest.py b/czsc/traders/weight_backtest.py
index 1e103b45f..df5ead171 100644
--- a/czsc/traders/weight_backtest.py
+++ b/czsc/traders/weight_backtest.py
@@ -68,13 +68,13 @@ class WeightBacktest:
     def __init__(self, dfw, digits=2, **kwargs) -> None:
         """持仓权重回测
         
-        :param dfw: pd.DataFrame, columns = ['dt', 'symbol', 'weight', 'price'], 持仓权重数据，
-            其中 
-                dt      为结束时间，
-                symbol  为合约代码，
-                weight  为持仓权重，
-                price   为结束时间对应的交易价格，可以是当前K线的收盘价，或者下一根K线的开盘价，或者未来N根K线的TWAP、VWAP等
-            
+        :param dfw: pd.DataFrame, columns = ['dt', 'symbol', 'weight', 'price'], 持仓权重数据，其中
+
+            dt      为K线结束时间，
+            symbol  为合约代码，
+            weight  为K线结束时间对应的持仓权重，
+            price   为结束时间对应的交易价格，可以是当前K线的收盘价，或者下一根K线的开盘价，或者未来N根K线的TWAP、VWAP等
+        
             数据样例如下：
             ===================  ========  ========  =======
             dt                   symbol      weight    price
@@ -88,7 +88,10 @@ def __init__(self, dfw, digits=2, **kwargs) -> None:
             
         :param digits: int, 权重列保留小数位数
         :param kwargs:
+
             - fee_rate: float，单边交易成本，包括手续费与冲击成本, 默认为 0.0002
+            - res_path: str，回测结果保存路径，默认为 "weight_backtest"
+            
         """
         self.kwargs = kwargs
         self.dfw = dfw.copy()
@@ -139,10 +142,7 @@ def get_symbol_daily(self, symbol):
     def get_symbol_pairs(self, symbol):
         """获取某个合约的开平交易记录"""
         dfs = self.dfw[self.dfw['symbol'] == symbol].copy()
-        dfs['direction'] = 0
-        dfs.loc[dfs['weight'] > 0, 'direction'] = 1
-        dfs.loc[dfs['weight'] < 0, 'direction'] = -1
-        dfs['volume'] = (dfs['weight'] * pow(10, self.digits)).astype(int) * dfs['direction']
+        dfs['volume'] = (dfs['weight'] * pow(10, self.digits)).astype(int)
         dfs['bar_id'] = list(range(1, len(dfs)+1))
 
         # 根据权重变化生成开平仓记录
@@ -227,7 +227,9 @@ def backtest(self):
         dret = pd.concat([v['daily'] for v in res.values()], ignore_index=True)
         dret = pd.pivot_table(dret, index='date', columns='symbol', values='return').fillna(0)
         dret['total'] = dret[list(res.keys())].mean(axis=1)
-        logger.info(f"品种等权费后日收益率：{daily_performance(dret['total'])}")
+        stats = {"开始日期": dret.index.min().strftime("%Y%m%d"), "结束日期": dret.index.max().strftime("%Y%m%d")}
+        stats.update(daily_performance(dret['total']))
+        logger.info(f"品种等权费后日收益率：{stats}")
         dret.to_excel(self.res_path.joinpath("daily_return.xlsx"), index=True)
         logger.info(f"品种等权费后日收益率已保存到 {self.res_path.joinpath('daily_return.xlsx')}")
 
@@ -243,7 +245,8 @@ def backtest(self):
         pairs_stats = evaluate_pairs(dfp)
         pairs_stats = {k: v for k, v in pairs_stats.items() if k in ['单笔收益', '持仓K线数', '交易胜率', '持仓天数']}
         logger.info(f"所有开平交易记录的表现：{pairs_stats}")
-        save_json(pairs_stats, self.res_path.joinpath("pairs_stats.json"))
-        logger.info(f"所有开平交易记录的表现已保存到 {self.res_path.joinpath('pairs_stats.json')}")
-
+        stats.update(pairs_stats)
+        logger.info(f"策略评价：{stats}")
+        save_json(stats, self.res_path.joinpath("stats.json"))
+        res['stats'] = stats
         return res
diff --git a/examples/cal_ensemble_weight.py b/examples/cal_ensemble_weight.py
new file mode 100644
index 000000000..9fabd25d0
--- /dev/null
+++ b/examples/cal_ensemble_weight.py
@@ -0,0 +1,22 @@
+import czsc
+import pandas as pd
+
+
+def run_by_weights():
+    """从持仓权重样例数据中回测"""
+    dfw = pd.read_feather(r"C:\Users\zengb\Desktop\230814\weight_example.feather")
+    wb = czsc.WeightBacktest(dfw, digits=1, fee_rate=0.0002, res_path=r"C:\Users\zengb\Desktop\230814\weight_example")
+    res = wb.backtest()
+
+
+def run_by_ensemble():
+    """从单个 trader 中获取持仓权重，然后回测"""
+    trader = czsc.dill_load(r"C:\Users\zengb\Desktop\230814\DLi9001.trader")
+
+    def __ensemble_method(x):
+        return x['A股日线SMA#5多头'] + 0.5 * x['A股日线SMA#5空头']
+    
+    dfw = czsc.get_ensemble_weight(trader, method=__ensemble_method)
+    wb = czsc.WeightBacktest(dfw, digits=1, fee_rate=0.0002, res_path=r"C:\Users\zengb\Desktop\230814\DLi9001_ensemble")
+    res = wb.backtest()
+