diff --git a/tests/toolkit/test_time_series_preprocessor.py b/tests/toolkit/test_time_series_preprocessor.py
index 9c052fec..5a813c77 100644
--- a/tests/toolkit/test_time_series_preprocessor.py
+++ b/tests/toolkit/test_time_series_preprocessor.py
@@ -212,6 +212,18 @@ def test_create_timestamps():
             2,
             [103.5, 107.0],
         ),
+        (
+            pd.Timestamp(2021, 12, 31),
+            "QE",
+            None,
+            4,
+            [
+                pd.Timestamp(2022, 3, 31),
+                pd.Timestamp(2022, 6, 30),
+                pd.Timestamp(2022, 9, 30),
+                pd.Timestamp(2022, 12, 31),
+            ],
+        ),
     ]
 
     for start, freq, sequence, periods, expected in test_cases:
@@ -220,8 +232,9 @@ def test_create_timestamps():
         assert ts == expected
 
         # test based on provided sequence
-        ts = create_timestamps(start, time_sequence=sequence, periods=periods)
-        assert ts == expected
+        if sequence is not None:
+            ts = create_timestamps(start, time_sequence=sequence, periods=periods)
+            assert ts == expected
 
     # it is an error to provide neither freq or sequence
     with pytest.raises(ValueError):
diff --git a/tsfm_public/toolkit/time_series_preprocessor.py b/tsfm_public/toolkit/time_series_preprocessor.py
index a69db0a6..68bfa5db 100644
--- a/tsfm_public/toolkit/time_series_preprocessor.py
+++ b/tsfm_public/toolkit/time_series_preprocessor.py
@@ -759,14 +759,24 @@ def create_timestamps(
 
     # more complex logic is required to support all edge cases
     if isinstance(freq, (pd.Timedelta, datetime.timedelta, str)):
-        # if isinstance(freq, str):
-        #     freq = pd._libs.tslibs.timedeltas.Timedelta(freq)
-
-        return pd.date_range(
-            last_timestamp,
-            freq=freq,
-            periods=periods + 1,
-        ).tolist()[1:]
+        try:
+            # try date range directly
+            return pd.date_range(
+                last_timestamp,
+                freq=freq,
+                periods=periods + 1,
+            ).tolist()[1:]
+        except ValueError as e:
+            # if it fails, we can try to compute a timedelta from the provided string
+            if isinstance(freq, str):
+                freq = pd._libs.tslibs.timedeltas.Timedelta(freq)
+                return pd.date_range(
+                    last_timestamp,
+                    freq=freq,
+                    periods=periods + 1,
+                ).tolist()[1:]
+            else:
+                raise e
     else:
         # numerical timestamp column
         return [last_timestamp + i * freq for i in range(1, periods + 1)]