From 444dc0e75134f9ff00b99221c2f9c98a730f2a1f Mon Sep 17 00:00:00 2001
From: aszerW <aszer27937@gmail.com>
Date: Sat, 16 May 2026 00:18:19 +0800
Subject: [PATCH] =?UTF-8?q?refactor(execution):=20=E6=94=B9=E4=B8=BA?=
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- 原逻辑: 按实际持仓数量等权(选出2只时权重50%)
- 新逻辑: 按select_num固定等权(选出2只时权重33.3%+现金33.3%)
- 缺失仓位用现金替代，收益为0
- 交易成本按固定仓位比例计算
- 目的: 保持稳定风险敞口，避免仓位不足时波动放大
---
 framework/execution/__init__.py | 33 ++++++++++++++++++++++++++-------
 1 file changed, 26 insertions(+), 7 deletions(-)

diff --git a/framework/execution/__init__.py b/framework/execution/__init__.py
index 700248e..47958ba 100644
--- a/framework/execution/__init__.py
+++ b/framework/execution/__init__.py
@@ -228,17 +228,29 @@ class BacktestExecutor(Executor):
             
             result['策略日收益率'] = result.apply(calc_return, axis=1)
         else:
-            # 多标的策略（等权组合）
+            # 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）
             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
-                returns = []
+                
+                # 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
                 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):
-                        returns.append(ret)
-                return np.mean(returns) if returns else 0.0
+                        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
             
             result['策略日收益率'] = result.apply(calc_multi_return, axis=1)
         
@@ -256,7 +268,9 @@ 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：按换手率比例扣除成本
+            # 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
             turnover_list = []
             for curr, prev in zip(signals[signal_col], prev_signal):
                 if pd.isna(prev) or curr == prev:
@@ -264,8 +278,13 @@ class BacktestExecutor(Executor):
                 else:
                     old = set(prev.split(','))
                     new = set(curr.split(','))
-                    swapped = len(old - new)
-                    turnover = swapped / len(old) if old else 0.0
+                    # 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
                     turnover_list.append(turnover)
             
             result['换手率'] = turnover_list