diff --git a/app/api/v1/app_valuations/app_valuations.py b/app/api/v1/app_valuations/app_valuations.py
index 75faaea..ca5b369 100644
--- a/app/api/v1/app_valuations/app_valuations.py
+++ b/app/api/v1/app_valuations/app_valuations.py
@@ -1,4 +1,5 @@
 from random import random
+import statistics
 
 from datetime import datetime
 from fastapi import APIRouter, Depends, HTTPException, status, BackgroundTasks
@@ -476,7 +477,25 @@ async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str,
     # expert_valuations: 专家估值列表(系统配置)
     transaction_data: Dict = None
     manual_bids: List[float] = None
-    # TODO 需要客户确认 三个数值
+    
+    # 处理月交易额波动区间的三个关键数值：最高价、最低价、中位数
+    # 已实现：从data.price_fluctuation中提取并计算三个数值
+    price_fluctuation_median = None  # 中位数
+    price_fluctuation_max = None     # 最高价
+    price_fluctuation_min = None     # 最低价
+    
+    if hasattr(data, 'price_fluctuation') and data.price_fluctuation:
+        try:
+            # 将price_fluctuation转换为浮点数列表
+            price_values = [float(i) for i in data.price_fluctuation if i is not None]
+            if price_values:
+                price_fluctuation_max = max(price_values)
+                price_fluctuation_min = min(price_values)
+                price_fluctuation_median = statistics.median(price_values)
+        except (ValueError, TypeError) as e:
+            # 如果转换失败，记录日志但不中断程序
+            logger.warning(f"价格波动区间数据转换失败: {e}")
+    
     expert_valuations = None
     # 浏览热度分 - 优化数据获取逻辑
     daily_browse_volume = 0  # 默认值
@@ -534,6 +553,10 @@ async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str,
         "weighted_average_price": transaction_data,
         "manual_bids": manual_bids,  # 手动收集的竞价列表 (用户填写)
         "expert_valuations": expert_valuations,  # 专家估值列表 (系统配置)
+        # 月交易额波动区间的三个关键数值
+        "price_fluctuation_max": price_fluctuation_max,  # 最高价
+        "price_fluctuation_min": price_fluctuation_min,  # 最低价
+        "price_fluctuation_median": price_fluctuation_median,  # 中位数
         # 计算热度系数C2
         "daily_browse_volume": daily_browse_volume,  # 近7日日均浏览量 (API获取)
         "collection_count": collection_count,  # 收藏数