diff --git a/sanguo_factor/analyzer.py b/sanguo_factor/analyzer.py
index 48d4144..4601cb8 100644
--- a/sanguo_factor/analyzer.py
+++ b/sanguo_factor/analyzer.py
@@ -1,6 +1,7 @@
 """Factor analysis with alphalens - lazy import to avoid ImportError."""
 import sys
 import os
+import warnings
 _VNPY_SRC = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "vnpy_v4.4.0"))
 if _VNPY_SRC not in sys.path:
     sys.path.insert(0, _VNPY_SRC)
@@ -34,7 +35,7 @@ class FactorReport:
     factor_names: list[str]
     output_dir: str
     ic_summary: dict = field(default_factory=dict)
-    report_path: str | None = None
+    report_paths: dict = field(default_factory=dict)
 
 
 def run_factor_analysis(
@@ -67,7 +68,7 @@ def run_factor_analysis(
             factor_names=factor_names,
             output_dir=output_dir,
             ic_summary={"error": "alphalens not installed"},
-            report_path=None
+            report_paths={}
         )
 
     if AlphaLabSession is None:
@@ -75,7 +76,7 @@ def run_factor_analysis(
             factor_names=factor_names,
             output_dir=output_dir,
             ic_summary={"error": "AlphaLabSession not available"},
-            report_path=None
+            report_paths={}
         )
 
     # Lazy imports for container environment
@@ -90,7 +91,7 @@ def run_factor_analysis(
             factor_names=factor_names,
             output_dir=output_dir,
             ic_summary={"error": f"Required import missing: {e}"},
-            report_path=None
+            report_paths={}
         )
 
     # Create AlphaLab session and load symbols
@@ -112,9 +113,9 @@ def run_factor_analysis(
     # Compute factors using AlphaLabSession
     factor_df = session.compute_factors(factor_names, train_period, valid_period, test_period)
 
-    # Initialize IC summary and report path
+    # Initialize IC summary and report paths
     ic_summary = {}
-    report_path = None
+    report_paths = {}
 
     # Process each factor
     for factor_name in factor_names:
@@ -140,11 +141,14 @@ def run_factor_analysis(
 
             # Build prices DataFrame (datetime × vt_symbol)
             # We need close prices - assume factor_df contains close column or derive it
+            use_cumsum_fallback = False
             if "close" in factor_pd.columns:
                 prices_df = factor_pd.pivot(index="datetime", columns="vt_symbol", values="close")
             else:
                 # If close isn't available, create a simple price structure from the data
                 # This is a simplified approach - in production, you'd re-read bars or cache close prices
+                warnings.warn(f"close 列缺失，因子 {factor_name} 使用 cumsum 兜底价格，tears 结果不可靠", UserWarning)
+                use_cumsum_fallback = True
                 prices_df = factor_pd.pivot(index="datetime", columns="vt_symbol", values=factor_col)
                 # Replace with simple returns-based price approximation
                 prices_df = prices_df.cumsum()  # Simplified: cumulative sum as price proxy
@@ -179,23 +183,25 @@ def run_factor_analysis(
             # Save the tears report
             factor_report_path = os.path.join(output_dir, f"{factor_name}_tears.html")
             plt.savefig(factor_report_path.replace(".html", ".png"))  # Save as PNG
-            report_path = factor_report_path.replace(".png", ".html")  # Mark HTML as report
+            report_paths[factor_name] = factor_report_path.replace(".png", ".html")  # Mark HTML as report
 
             # Store basic IC summary (simplified)
+            status = "warning_unreliable_prices" if use_cumsum_fallback else "success"
             ic_summary[factor_name] = {
-                "status": "success",
+                "status": status,
                 "report": factor_report_path
             }
 
         except Exception as e:
+            err_type = type(e).__name__
             ic_summary[factor_name] = {
                 "status": "error",
-                "error": str(e)
+                "error": f"{err_type}: {e}"
             }
 
     return FactorReport(
         factor_names=factor_names,
         output_dir=output_dir,
         ic_summary=ic_summary,
-        report_path=report_path
+        report_paths=report_paths
     )