diff --git a/doc/source/user_guide/computation.rst b/doc/source/user_guide/computation.rst
index 151ef36be7c98..10e27606a1415 100644
--- a/doc/source/user_guide/computation.rst
+++ b/doc/source/user_guide/computation.rst
@@ -229,6 +229,15 @@ see the :ref:`groupby docs <groupby.transform.window_resample>`.
 
    The API for window statistics is quite similar to the way one works with ``GroupBy`` objects, see the documentation :ref:`here <groupby>`.
 
+.. warning::
+
+    When using ``rolling()`` and an associated function the results are calculated with rolling sums. As a consequence
+    when having values differing with magnitude :math:`1/np.finfo(np.double).eps` this results in truncation. It must be
+    noted, that large values may have an impact on windows, which do not include these values. `Kahan summation
+    <https://en.wikipedia.org/wiki/Kahan_summation_algorithm>`__ is used
+    to compute the rolling sums to preserve accuracy as much as possible. The same holds true for ``Rolling.var()`` for
+    values differing with magnitude :math:`(1/np.finfo(np.double).eps)^{0.5}`.
+
 We work with ``rolling``, ``expanding`` and ``exponentially weighted`` data through the corresponding
 objects, :class:`~pandas.core.window.Rolling`, :class:`~pandas.core.window.Expanding` and :class:`~pandas.core.window.ExponentialMovingWindow`.