From 2c1689089d2465b2d5fe6f896f52d7916fcd34a1 Mon Sep 17 00:00:00 2001
From: aszerW <aszer27937@gmail.com>
Date: Sat, 16 May 2026 00:34:12 +0800
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- 恢复原逻辑: 按实际持仓数量等权分配
- 选出2只时每只权重50%，选出1只时权重100%
- 收益计算恢复为 np.mean(returns)
- 交易成本恢复为 swapped/len(old)
- 固定仓位逻辑记录在 docs/experiments/仓位分配逻辑修改分析.md
---
 framework/execution/__init__.py | 34 ++++++++-------------------------
 1 file changed, 8 insertions(+), 26 deletions(-)

diff --git a/framework/execution/__init__.py b/framework/execution/__init__.py
index 47958ba..671c131 100644
--- a/framework/execution/__init__.py
+++ b/framework/execution/__init__.py
@@ -228,29 +228,18 @@ class BacktestExecutor(Executor):
             
             result['策略日收益率'] = result.apply(calc_return, axis=1)
         else:
-            # 多标的策略（固定仓位分配）
-            # 核心逻辑：按select_num固定分配仓位，缺失标的用现金替代
-            # 例如：select_num=3，选出2只标的 → 权重=1/3+1/3，现金权重=1/3（收益为0）
+            # 多标的策略（等权组合）
+            # 按实际持仓数量等权分配：选出2只时每只50%，选出1只时100%
             def calc_multi_return(row):
                 codes = [c for c in row[signal_col].split(',') if c]
                 if not codes:
-                    # 空仓：全部现金，收益为0
                     return 0.0
-                
-                # 固定仓位权重：每只标的权重 = 1 / select_num
-                unit_weight = 1.0 / self.select_num
-                
-                # 计算实际持仓收益（缺失标的用现金替代，收益为0）
-                total_return = 0.0
+                returns = []
                 for c in codes:
                     ret = data.loc[row.name, f'日收益率_{c}'] if f'日收益率_{c}' in data.columns else None
                     if ret is not None and pd.notna(ret):
-                        total_return += ret * unit_weight
-                    # 如果数据缺失，视为现金（收益为0，不累加）
-                
-                # 缺失标的的仓位自动变成现金（收益为0）
-                # 总收益 = sum(实际持仓收益) + 0 * (缺失仓位)
-                return total_return
+                        returns.append(ret)
+                return np.mean(returns) if returns else 0.0
             
             result['策略日收益率'] = result.apply(calc_multi_return, axis=1)
         
@@ -268,9 +257,7 @@ class BacktestExecutor(Executor):
             changed = (signals[signal_col] != prev_signal) & prev_signal.notna()
             result.loc[changed, '策略日收益率'] -= self.trade_cost
         else:
-            # 多标的策略：按固定仓位比例扣除成本
-            # 核心逻辑：每只标的权重固定为1/select_num
-            # 换手率 = (调出数量 + 调入数量) / select_num
+            # 多标的策略：按换手率比例扣除成本
             turnover_list = []
             for curr, prev in zip(signals[signal_col], prev_signal):
                 if pd.isna(prev) or curr == prev:
@@ -278,13 +265,8 @@ class BacktestExecutor(Executor):
                 else:
                     old = set(prev.split(','))
                     new = set(curr.split(','))
-                    # 调出的标的数量（这些仓位需要卖出）
-                    exit_count = len(old - new)
-                    # 调入的标的数量（这些仓位需要买入）
-                    enter_count = len(new - old)
-                    # 换手率 = (卖出 + 买入) / select_num
-                    # 每次调仓涉及的仓位比例
-                    turnover = (exit_count + enter_count) / self.select_num
+                    swapped = len(old - new)
+                    turnover = swapped / len(old) if old else 0.0
                     turnover_list.append(turnover)
             
             result['换手率'] = turnover_list