diff --git a/strategies/rotation/report.py b/strategies/rotation/report.py
index a66cd24..0c578dc 100644
--- a/strategies/rotation/report.py
+++ b/strategies/rotation/report.py
@@ -163,6 +163,21 @@ def generate_performance_report(
     with open(metrics_path, 'w', encoding='utf-8') as f:
         json.dump(metrics_dict, f, indent=2, ensure_ascii=False)
     print(f"策略指标已保存: {metrics_path}")
+    
+    # 保存净值曲线数据到CSV文件
+    nav_df = pd.DataFrame({
+        '日期': strategy_nav.index.strftime('%Y-%m-%d'),
+        '策略净值': strategy_nav.values,
+        '基准净值': benchmark_nav.values,
+    })
+    # 添加各品种净值
+    for code in code_list:
+        if f"净值_{code}" in backtest_result.columns:
+            nav_df[f"净值_{code}"] = backtest_result[f"净值_{code}"].values
+    
+    nav_path = f"{save_path}_nav.csv"
+    nav_df.to_csv(nav_path, index=False)
+    print(f"净值曲线已保存: {nav_path}")
 
     # 返回指标字典
     return {
diff --git a/visualization/report_generator/generate_report.py b/visualization/report_generator/generate_report.py
index 0e7226c..fa5c352 100644
--- a/visualization/report_generator/generate_report.py
+++ b/visualization/report_generator/generate_report.py
@@ -26,6 +26,7 @@ class ReportGenerator:
         self.summary_df = None
         self.trades_df = None
         self.metrics = None  # 从JSON加载的策略KPI
+        self.nav_df = None   # 从CSV加载的净值曲线
         
     def load_data(self):
         """加载回测数据"""
@@ -59,6 +60,15 @@ class ReportGenerator:
         else:
             print(f"⚠️ 未找到策略指标文件: {metrics_path}")
         
+        # 加载净值曲线CSV文件（如果存在）
+        nav_path = os.path.join(self.results_dir, 'report_nav.csv')
+        if os.path.exists(nav_path):
+            self.nav_df = pd.read_csv(nav_path)
+            self.nav_df['日期'] = pd.to_datetime(self.nav_df['日期'])
+            print(f"✅ 加载净值曲线: {nav_path} ({len(self.nav_df)} 条记录)")
+        else:
+            print(f"⚠️ 未找到净值曲线文件: {nav_path}")
+        
         print(f"✅ 数据加载成功: {len(self.trades_df)} 条交易记录")
         
     def calculate_kpis(self, trades_filtered=None):
@@ -179,7 +189,70 @@ class ReportGenerator:
         }
     
     def prepare_chart_data(self, trades_filtered=None):
-        """准备图表数据"""
+        """准备图表数据 - 优先使用轮动策略输出的净值曲线"""
+        
+        # 如果有从CSV加载的净值曲线，直接使用
+        if self.nav_df is not None:
+            print("✅ 使用轮动策略输出的净值曲线")
+            
+            # 净值曲线数据 - 直接读取
+            nav_dates = self.nav_df['日期'].dt.strftime('%Y-%m-%d').tolist()
+            nav_values = self.nav_df['策略净值'].round(4).tolist()
+            benchmark_values = self.nav_df['基准净值'].round(4).tolist()
+            
+            # 月度收益数据 - 从净值计算
+            self.nav_df['年月'] = self.nav_df['日期'].dt.to_period('M')
+            monthly_nav = self.nav_df.groupby('年月').agg({
+                '策略净值': 'last'
+            }).reset_index()
+            monthly_nav.columns = ['年月', 'nav']
+            monthly_nav = monthly_nav.sort_values('年月')
+            monthly_nav['nav_change'] = monthly_nav['nav'].pct_change() * 100
+            monthly_nav['nav_change'] = monthly_nav['nav_change'].fillna(0)
+            monthly_nav['年月_str'] = monthly_nav['年月'].astype(str)
+            monthly_dates = monthly_nav['年月_str'].tolist()
+            monthly_values = monthly_nav['nav_change'].round(2).tolist()
+            
+            # 盈亏分布 - 从trades数据计算
+            df = trades_filtered if trades_filtered is not None else self.trades_df
+            if df['持仓收益'].dtype == 'object':
+                df = df.copy()
+                df['持仓收益_num'] = df['持仓收益'].str.rstrip('%').astype(float)
+            else:
+                df = df.copy()
+                df['持仓收益_num'] = df['持仓收益']
+            
+            positive_returns = df[df['持仓收益_num'] > 0]['持仓收益_num'].tolist()
+            negative_returns = df[df['持仓收益_num'] <= 0]['持仓收益_num'].tolist()
+            
+            # 品种收益排行 - 使用累计收益列
+            symbol_returns = self.summary_df.set_index('品种代码')['累计收益']
+            symbol_returns = symbol_returns.sort_values()
+            symbol_names = []
+            symbol_returns_list = []
+            
+            for code, ret in symbol_returns.items():
+                name = self.summary_df[self.summary_df['品种代码'] == code]
+                if len(name) > 0:
+                    symbol_names.append(name.iloc[0]['品种名称'])
+                else:
+                    symbol_names.append(code)
+                symbol_returns_list.append(ret)
+            
+            return {
+                'nav_dates': nav_dates,
+                'nav_values': nav_values,
+                'benchmark_values': benchmark_values,
+                'monthly_dates': monthly_dates,
+                'monthly_values': monthly_values,
+                'positive_returns': positive_returns,
+                'negative_returns': negative_returns,
+                'symbol_names': symbol_names,
+                'symbol_returns': symbol_returns_list,
+            }
+        
+        # 否则重新计算（备用方案）
+        print("⚠️ 未找到净值曲线，重新计算...")
         df = trades_filtered if trades_filtered is not None else self.trades_df
         
         # 转换持仓收益为数值
@@ -203,6 +276,7 @@ class ReportGenerator:
         
         nav_values = daily_nav['nav'].round(4).tolist()
         nav_dates = daily_nav['date'].dt.strftime('%Y-%m-%d').tolist()
+        benchmark_values = []  # 备用方案无基准数据
         
         # 月度收益数据 - 使用净值变化计算
         df_copy = df_sorted.copy()