diff --git a/qlib/workflow/online/update.py b/qlib/workflow/online/update.py
index 96cbf4d65..e5dbd413e 100644
--- a/qlib/workflow/online/update.py
+++ b/qlib/workflow/online/update.py
@@ -135,10 +135,9 @@ class PredUpdater(RecordUpdater):
         # RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.
         # https://github.com/pytorch/pytorch/issues/16797
 
-        start_time = get_date_by_shift(self.last_end, 1, freq=self.freq)
-        if start_time > self.to_date:
+        if self.last_end >= self.to_date:
             self.logger.info(
-                f"The prediction in {self.record.info['id']} are latest ({start_time}). No need to update to {self.to_date}."
+                f"The prediction in {self.record.info['id']} are latest ({self.last_end}). No need to update to {self.to_date}."
             )
             return
 
diff --git a/qlib/workflow/online/utils.py b/qlib/workflow/online/utils.py
index a7478afb7..86763d5d6 100644
--- a/qlib/workflow/online/utils.py
+++ b/qlib/workflow/online/utils.py
@@ -189,6 +189,12 @@ class OnlineToolR(OnlineTool):
             cls, kwargs = get_cls_kwargs(task["dataset"], default_module="qlib.data.dataset")
             if issubclass(cls, TSDatasetH):
                 hist_ref = kwargs.get("step_len", TSDatasetH.DEFAULT_STEP_LEN)
-            PredUpdater(rec, to_date=to_date, hist_ref=hist_ref).update()
+            try:
+                updater = PredUpdater(rec, to_date=to_date, hist_ref=hist_ref)
+            except OSError:
+                # skip the recorder without pred
+                self.logger.warn(f"Can't find `pred.pkl`, skip it.")
+                continue
+            updater.update()
 
         self.logger.info(f"Finished updating {len(online_models)} online model predictions of {exp_name}.")