diff --git a/qlib/data/ops.py b/qlib/data/ops.py
index d9a2ffbb3e3..f68fd894ece 100644
--- a/qlib/data/ops.py
+++ b/qlib/data/ops.py
@@ -1277,6 +1277,7 @@ def _load_internal(self, instrument, start_index, end_index, *args):
         _series = self.feature.load(instrument, start_index, end_index, *args)
         if self.N == 0:
             series = pd.Series(expanding_rsquare(_series.values), index=_series.index)
+            series.loc[np.isclose(_series.expanding(min_periods=1).std(), 0, atol=2e-05)] = np.nan
         else:
             series = pd.Series(rolling_rsquare(_series.values, self.N), index=_series.index)
             series.loc[np.isclose(_series.rolling(self.N, min_periods=1).std(), 0, atol=2e-05)] = np.nan
diff --git a/tests/ops/test_rolling_operator.py b/tests/ops/test_rolling_operator.py
new file mode 100644
index 00000000000..f950895f2c6
--- /dev/null
+++ b/tests/ops/test_rolling_operator.py
@@ -0,0 +1,28 @@
+import numpy as np
+import pandas as pd
+
+from qlib.data.ops import Rsquare
+
+
+class FeatureStub:
+    def __init__(self, values):
+        self.series = pd.Series(values, dtype=float)
+
+    def load(self, instrument, start_index, end_index, *args):
+        return self.series
+
+
+def test_expanding_rsquare_masks_near_constant_windows():
+    values = [100, 100, 100, 100.000001, 100, 100]
+
+    result = Rsquare(FeatureStub(values), 0)._load_internal(None, None, None)
+
+    assert result.isna().all()
+
+
+def test_expanding_rsquare_keeps_varying_windows():
+    values = [1, 2, 4, 8, 16]
+
+    result = Rsquare(FeatureStub(values), 0)._load_internal(None, None, None)
+
+    assert np.isfinite(result.iloc[1:]).all()