diff --git a/arch/tests/univariate/test_positions_and_alias.py b/arch/tests/univariate/test_positions_and_alias.py
index 94124050ad..e2f7f3fd2d 100644
--- a/arch/tests/univariate/test_positions_and_alias.py
+++ b/arch/tests/univariate/test_positions_and_alias.py
@@ -6,7 +6,8 @@
 in Python.
 """
 
-import matplotlib.pyplot as plt
+from arch.compat.matplotlib import HAS_MATPLOTLIB
+
 import numpy as np
 from numpy.testing import assert_allclose
 import pandas as pd
@@ -29,6 +30,9 @@
 )
 from arch.utility.array import cutoff_to_index, find_index
 
+if HAS_MATPLOTLIB:
+    import matplotlib.pyplot as plt
+
 NOBS = 300
 DATES = pd.date_range("2000-01-03", periods=NOBS, freq="B")
 PARAMS = np.array([0.05, 0.05, 0.1, 0.8])
@@ -183,6 +187,7 @@ def test_forecast_start_below_minus_nobs(result, model):
             model.forecast(result.params, horizon=2, start=start)
 
 
+@pytest.mark.skipif(not HAS_MATPLOTLIB, reason="matplotlib not installed")
 def test_hedgehog_plot_negative_start(result):
     kwargs = {"horizon": 3, "step": 50}
     fig_neg = result.hedgehog_plot(start=-100, **kwargs)
diff --git a/arch/tests/univariate/test_string_options.py b/arch/tests/univariate/test_string_options.py
index 360ccb9544..b008280a78 100644
--- a/arch/tests/univariate/test_string_options.py
+++ b/arch/tests/univariate/test_string_options.py
@@ -1,8 +1,9 @@
 """String options of the univariate models are not case sensitive"""
 
+from arch.compat.matplotlib import HAS_MATPLOTLIB
+
 from functools import partial
 
-import matplotlib.pyplot as plt
 import numpy as np
 from numpy.testing import assert_allclose
 import pandas as pd
@@ -30,6 +31,9 @@
 )
 from arch.univariate.base import ARCHModelForecast, _align_forecast
 
+if HAS_MATPLOTLIB:
+    import matplotlib.pyplot as plt
+
 # A string that is not an option is a ValueError and anything else a TypeError
 BAD_VALUES = [
     pytest.param("bogus", ValueError, id="bogus"),
@@ -242,6 +246,7 @@ def test_forecast_method_invalid(returns, result, bad, exc, use_result):
 
 
 @pytest.mark.parametrize("annualize", ["d", "w", "m"])
+@pytest.mark.skipif(not HAS_MATPLOTLIB, reason="matplotlib not installed")
 def test_plot_annualize_case(result, annualize):
     scale = {"d": 252, "w": 52, "m": 12}[annualize]
     expected = result.conditional_volatility * np.sqrt(scale)
@@ -258,6 +263,7 @@ def test_plot_annualize_case(result, annualize):
 @pytest.mark.parametrize(
     ("bad", "exc"), [("bogus", ValueError), ("Q", ValueError), (1, TypeError)]
 )
+@pytest.mark.skipif(not HAS_MATPLOTLIB, reason="matplotlib not installed")
 def test_plot_annualize_invalid(result, bad, exc):
     with pytest.raises(exc, match=r"annualize must be one of 'd', 'w' or 'm'; got "):
         result.plot(annualize=bad)
@@ -265,6 +271,7 @@ def test_plot_annualize_invalid(result, bad, exc):
 
 
 @pytest.mark.parametrize("plot_type", ["volatility", "mean"])
+@pytest.mark.skipif(not HAS_MATPLOTLIB, reason="matplotlib not installed")
 def test_hedgehog_plot_type_case(result, plot_type, returns):
     try:
         for spelling in (plot_type, plot_type.upper(), plot_type.title()):
@@ -281,6 +288,7 @@ def test_hedgehog_plot_type_case(result, plot_type, returns):
 
 
 @pytest.mark.parametrize(("bad", "exc"), BAD_VALUES)
+@pytest.mark.skipif(not HAS_MATPLOTLIB, reason="matplotlib not installed")
 def test_hedgehog_plot_invalid(result, bad, exc):
     with pytest.raises(exc, match=r"plot_type must be one of 'volatility' or"):
         result.hedgehog_plot(plot_type=bad)
diff --git a/arch/tests/univariate/test_validation_base.py b/arch/tests/univariate/test_validation_base.py
index 0b2f2b9844..7b9c0c84e2 100644
--- a/arch/tests/univariate/test_validation_base.py
+++ b/arch/tests/univariate/test_validation_base.py
@@ -7,12 +7,13 @@
 functions in ``arch.univariate.base`` and of ``arch.univariate.diagnostics``.
 """
 
+from arch.compat.matplotlib import HAS_MATPLOTLIB
+
 from collections.abc import Callable
 from fractions import Fraction
 from types import MappingProxyType
 from typing import Any
 
-import matplotlib.pyplot as plt
 import numpy as np
 from numpy.testing import assert_allclose
 import pandas as pd
@@ -43,6 +44,9 @@
 from arch.univariate.diagnostics import excess_kurtosis, hill_estimator, var_ratio
 from arch.utility.exceptions import StartingValueWarning
 
+if HAS_MATPLOTLIB:
+    import matplotlib.pyplot as plt
+
 NOBS = 250
 INDEX = pd.date_range("2000-01-03", periods=NOBS, freq="B")
 PARAMS = np.array([0.05, 0.05, 0.1, 0.8])
@@ -414,7 +418,8 @@ def call(**kwargs: Any) -> Any:
         try:
             return getattr(fitted(), name)(**kwargs)
         finally:
-            plt.close("all")
+            if HAS_MATPLOTLIB:
+                plt.close("all")
 
     return call
 
@@ -950,6 +955,8 @@ def constraints(**kwargs: Any):
     ),
 )
 def test_validation(row):
+    if not HAS_MATPLOTLIB and row.target in ("plot", "hedgehog"):
+        pytest.skip("matplotlib not installed")
     run_row(row)
 
 
@@ -1002,6 +1009,7 @@ def test_forecast_of_fixed_result_checks_arguments():
     assert fixed.forecast(horizon=np.int64(2)).mean.shape[1] == 2
 
 
+@pytest.mark.skipif(not HAS_MATPLOTLIB, reason="matplotlib not installed")
 def test_plot_error_does_not_leave_a_figure():
     plt.close("all")
     with pytest.raises(ValueError, match=r"^annualize must be"):