diff --git a/qlib/contrib/data/handler.py b/qlib/contrib/data/handler.py
index e97b00c24..6b3de336d 100644
--- a/qlib/contrib/data/handler.py
+++ b/qlib/contrib/data/handler.py
@@ -32,79 +32,6 @@ def check_transform_proc(proc_l, fit_start_time, fit_end_time):
     return new_l
 
 
-class ALPHA360_Denoise(DataHandlerLP):
-    def __init__(self, instruments="csi500", start_time=None, end_time=None, fit_start_time=None, fit_end_time=None):
-        data_loader = {
-            "class": "QlibDataLoader",
-            "kwargs": {
-                "config": {
-                    "feature": self.get_feature_config(),
-                    "label": self.get_label_config(),
-                },
-            },
-        }
-
-        learn_processors = [
-            {"class": "DropnaLabel", "kwargs": {"fields_group": "label"}},
-            {"class": "CSZScoreNorm", "kwargs": {"fields_group": "label"}},
-        ]
-        infer_processors = [
-            {"class": "ProcessInf", "kwargs": {}},
-            {"class": "TanhProcess", "kwargs": {}},
-            {"class": "Fillna", "kwargs": {}},
-        ]
-
-        super().__init__(
-            instruments,
-            start_time,
-            end_time,
-            data_loader=data_loader,
-            learn_processors=learn_processors,
-            infer_processors=infer_processors,
-        )
-
-    def get_label_config(self):
-        return (["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"])
-
-    def get_feature_config(self):
-
-        fields = []
-        names = []
-
-        for i in range(59, 0, -1):
-            fields += ["Ref($close, %d)/$close" % (i)]
-            names += ["CLOSE%d" % (i)]
-        fields += ["$close/$close"]
-        names += ["CLOSE0"]
-        for i in range(59, 0, -1):
-            fields += ["Ref($open, %d)/$close" % (i)]
-            names += ["OPEN%d" % (i)]
-        fields += ["$open/$close"]
-        names += ["OPEN0"]
-        for i in range(59, 0, -1):
-            fields += ["Ref($high, %d)/$close" % (i)]
-            names += ["HIGH%d" % (i)]
-        fields += ["$high/$close"]
-        names += ["HIGH0"]
-        for i in range(59, 0, -1):
-            fields += ["Ref($low, %d)/$close" % (i)]
-            names += ["LOW%d" % (i)]
-        fields += ["$low/$close"]
-        names += ["LOW0"]
-        for i in range(59, 0, -1):
-            fields += ["Ref($vwap, %d)/$close" % (i)]
-            names += ["VWAP%d" % (i)]
-        fields += ["$vwap/$close"]
-        names += ["VWAP0"]
-        for i in range(59, 0, -1):
-            fields += ["Ref($volume, %d)/$volume" % (i)]
-            names += ["VOLUME%d" % (i)]
-        fields += ["$volume/$volume"]
-        names += ["VOLUME0"]
-
-        return fields, names
-
-
 _DEFAULT_LEARN_PROCESSORS = [
     {"class": "DropnaLabel"},
     {"class": "CSZScoreNorm", "kwargs": {"fields_group": "label"}},