diff --git a/doc/source/whatsnew/v0.23.3.txt b/doc/source/whatsnew/v0.23.3.txt
index d308cf7a3cfac..266d2ce448fb0 100644
--- a/doc/source/whatsnew/v0.23.3.txt
+++ b/doc/source/whatsnew/v0.23.3.txt
@@ -24,6 +24,11 @@ Fixed Regressions
 Bug Fixes
 ~~~~~~~~~
 
+**Groupby/Resample/Rolling**
+
+- Bug where calling :func:`DataFrameGroupBy.agg` with a list of functions including ``ohlc`` as the non-initial element would raise a ``ValueError`` (:issue:`21716`)
+-
+
 **Conversion**
 
 -
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 08acdcf94094a..a496394547339 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -3549,13 +3549,11 @@ def _aggregate_multiple_funcs(self, arg, _level):
                 obj._selection = name
             results[name] = obj.aggregate(func)
 
-        if isinstance(list(compat.itervalues(results))[0],
-                      DataFrame):
-
+        if any(isinstance(x, DataFrame) for x in compat.itervalues(results)):
             # let higher level handle
             if _level:
                 return results
-            return list(compat.itervalues(results))[0]
+
         return DataFrame(results, columns=columns)
 
     def _wrap_output(self, output, index, names=None):
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index e05f9de5ea7f4..66577d738dd28 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -1674,3 +1674,22 @@ def test_tuple_correct_keyerror():
                                                           [3, 4]]))
     with tm.assert_raises_regex(KeyError, "(7, 8)"):
         df.groupby((7, 8)).mean()
+
+
+def test_groupby_agg_ohlc_non_first():
+    # GH 21716
+    df = pd.DataFrame([[1], [1]], columns=['foo'],
+                      index=pd.date_range('2018-01-01', periods=2, freq='D'))
+
+    expected = pd.DataFrame([
+        [1, 1, 1, 1, 1],
+        [1, 1, 1, 1, 1]
+    ], columns=pd.MultiIndex.from_tuples((
+        ('foo', 'ohlc', 'open'), ('foo', 'ohlc', 'high'),
+        ('foo', 'ohlc', 'low'), ('foo', 'ohlc', 'close'),
+        ('foo', 'sum', 'foo'))), index=pd.date_range(
+            '2018-01-01', periods=2, freq='D'))
+
+    result = df.groupby(pd.Grouper(freq='D')).agg(['sum', 'ohlc'])
+
+    tm.assert_frame_equal(result, expected)