diff --git a/CHANGELOG.md b/CHANGELOG.md
index 3683b4d037abe18c16383245252cd3b3d00e24e4..900d0a67b28e0565e976f971ed8e19aff9eb252e 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,12 @@
 # Changelog
 All notable changes to this project will be documented in this file.
 
+## v0.6.9 - 2025-04-04 - fixed bug in trends/moving_block_bootstrap
+
+### technical:
+* when calculating a trend on a timeseries which is not complete, the method
+`moving_block_bootstrap` may throw a `ValueError` based on randomly chosen blocks
+
 ## v0.6.8 - 2025-03-07 - bugfix in time harmonizing
 
 ## v0.6.7 - 2025-02-21 - fixed output format
diff --git a/dist/toarstats-0.6.9-py3-none-any.whl b/dist/toarstats-0.6.9-py3-none-any.whl
new file mode 100644
index 0000000000000000000000000000000000000000..3364d3cf699f596787d59f996ea5449533a59f82
Binary files /dev/null and b/dist/toarstats-0.6.9-py3-none-any.whl differ
diff --git a/setup.cfg b/setup.cfg
index bdd4fbc3f9ff610553a4f00e5dd10c8bf8f0966b..b1e5ccd2c9c0ef40465d7a533899cc6ae9295d37 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,6 +1,6 @@
 [metadata]
 name = toarstats
-version = 0.6.8
+version = 0.6.9
 author = Niklas Selke, Martin Schultz, Max Lensing
 author_email = n.selke@fz-juelich.de, m.schultz@fz-juelich.de, m.lensing@fz-juelich.de
 description = Collection of statistics for the TOAR community
diff --git a/toarstats/trends/utils.py b/toarstats/trends/utils.py
index bd6167aff44a3b6165fe100e0fd850d940328eb1..650cf99d02c60bd8fabb6384a58936fd7ba5700c 100644
--- a/toarstats/trends/utils.py
+++ b/toarstats/trends/utils.py
@@ -63,9 +63,12 @@ def moving_block_bootstrap(method, data, quantile=None, num_samples=1000):
     for _ in range(num_samples):
         bn = rng.choice(len(blocks), nblocks)
         samp_data = data.iloc[blocks[bn].flatten()]
-        if method == "quant":
-            mod = smf.quantreg("value~datetime", samp_data).fit(q=quantile)
-        else:
-            mod = smf.ols("value~datetime", samp_data).fit(method="qr")
+        try:
+            if method == "quant":
+                mod = smf.quantreg("value~datetime", samp_data).fit(q=quantile)
+            else:
+                mod = smf.ols("value~datetime", samp_data).fit(method="qr")
+        except ValueError:
+            continue
         samples.append(mod.params)
     return samples