diff --git a/qlib/backtest/high_performance_ds.py b/qlib/backtest/high_performance_ds.py
index d556f303c..123725832 100644
--- a/qlib/backtest/high_performance_ds.py
+++ b/qlib/backtest/high_performance_ds.py
@@ -82,7 +82,7 @@ class BaseQuote:
             the columns of data to fetch
         method : Union[str, Callable]
             the method apply to data.
-            e.g ["None", "last", "all", "sum", "mean", "any", qlib/utils/resam.py/ts_data_last]
+            e.g [None, "last", "all", "sum", "mean", "any", qlib/utils/resam.py/ts_data_last]
 
         Return
         ----------
@@ -177,19 +177,19 @@ class BaseSingleMetric:
 
     def add(self, other: "BaseSingleMetric", fill_value: float = None) -> "BaseSingleMetric":
         """Replace np.NaN with fill_value in two metrics and add them."""
-        
+
         raise NotImplementedError(f"Please implement the `add` method")
 
     def replace(self, replace_dict: dict) -> "BaseSingleMetric":
         """Replace the value of metric according to replace_dict."""
-        
+
         raise NotImplementedError(f"Please implement the `replace` method")
 
     def apply(self, func: dict) -> "BaseSingleMetric":
         """Replace the value of metric with func(metric).
-           Currently, the func is only qlib/backtest/order/Order.parse_dir.
+        Currently, the func is only qlib/backtest/order/Order.parse_dir.
         """
-        
+
         raise NotImplementedError(f"Please implement the 'apply' method")
 
 
@@ -426,11 +426,6 @@ class PandasOrderIndicator(BaseOrderIndicator):
         for metric in metrics:
             tmp_metric = PandasSingleMetric({})
             for indicator in indicators:
-                if(metric == "trade_price"):
-                    tmp_metric = tmp_metric.add(
-                        indicator.data["trade_price"] * indicator.data["deal_amount"], fill_value
-                    )
-                else:
-                    tmp_metric = tmp_metric.add(indicator.data[metric], fill_value)
+                tmp_metric = tmp_metric.add(indicator.data[metric], fill_value)
             metric_dict[metric] = tmp_metric.metric
         return metric_dict
diff --git a/qlib/backtest/report.py b/qlib/backtest/report.py
index 64d00b436..e37642244 100644
--- a/qlib/backtest/report.py
+++ b/qlib/backtest/report.py
@@ -308,8 +308,9 @@ class Indicator:
 
     def _update_order_fulfill_rate(self):
         def func(deal_amount, amount):
+            # deal_amount is np.NaN when there is no inner decision. So full fill rate is 0.
             tmp_deal_amount = deal_amount.replace({np.NaN: 0})
-            return deal_amount / tmp_deal_amount
+            return tmp_deal_amount / amount
 
         self.order_indicator.transfer(func, "ffr")
 
@@ -318,12 +319,21 @@ class Indicator:
         self._update_order_fulfill_rate()
 
     def _agg_order_trade_info(self, inner_order_indicators: List[Dict[str, pd.Series]]):
+        # calculate total trade amount with each inner order indicator.
+        def trade_amount_func(deal_amount, trade_price):
+            return deal_amount * trade_price
+
+        for indicator in inner_order_indicators:
+            indicator.transfer(trade_amount_func, "trade_price")
+
+        # sum inner order indicators with same metric.
         all_metric = ["inner_amount", "deal_amount", "trade_price", "trade_value", "trade_cost", "trade_dir"]
         metric_dict = self.order_indicator_cls.sum_all_indicators(inner_order_indicators, all_metric, fill_value=0)
         for metric in metric_dict:
             self.order_indicator.assign(metric, metric_dict[metric])
 
         def func(trade_price, deal_amount):
+            # trade_price is np.NaN instead of inf when deal_amount is zero.
             tmp_deal_amount = deal_amount.replace({0: np.NaN})
             return trade_price / tmp_deal_amount