diff --git a/arch/tests/univariate/test_base.py b/arch/tests/univariate/test_base.py
new file mode 100644
index 0000000000..1acfbeae01
--- /dev/null
+++ b/arch/tests/univariate/test_base.py
@@ -0,0 +1,10 @@
+from arch.univariate.base import format_float_fixed
+
+
+def test_format_float_fixed():
+    out = format_float_fixed(0.0)
+    assert out == '0.0000'
+    out = format_float_fixed(1.23e-9)
+    assert out == '1.2300e-09'
+    out = format_float_fixed(123456789.0)
+    assert out == '1.2346e+08'
diff --git a/arch/tests/univariate/test_mean.py b/arch/tests/univariate/test_mean.py
index 7fcc8cb225..f83b61e95c 100644
--- a/arch/tests/univariate/test_mean.py
+++ b/arch/tests/univariate/test_mean.py
@@ -364,6 +364,11 @@ def test_ar(self):
         ar = ARX(self.y, lags=1, volatility=GARCH(), distribution=StudentsT())
         res = ar.fit(disp=DISPLAY, update_freq=5, cov_type='mle')
         res.param_cov
+        sims = res.forecast(horizon=5, method='simulation')
+        assert isinstance(sims.simulations.residual_variances, np.ndarray)
+        assert isinstance(sims.simulations.residuals, np.ndarray)
+        assert isinstance(sims.simulations.values, np.ndarray)
+        assert isinstance(sims.simulations.variances, np.ndarray)
 
     @pytest.mark.skipif(not HAS_MATPLOTLIB, reason='matplotlib not installed')
     def test_ar_plot(self):
@@ -381,6 +386,7 @@ def test_ar_plot(self):
         res.hedgehog_plot(start=500, type='mean')
         res.hedgehog_plot(type='volatility')
         res.hedgehog_plot(start=500, method='simulation', simulations=100)
+        res.hedgehog_plot(type='volatility', method='bootstrap')
 
     def test_arch_arx(self):
         self.rng.seed(12345)
diff --git a/arch/univariate/base.py b/arch/univariate/base.py
index e003e9449c..830cf49e71 100644
--- a/arch/univariate/base.py
+++ b/arch/univariate/base.py
@@ -692,7 +692,7 @@ def forecast(self, params, horizon=1, start=None, align='origin', method='analyt
 
         Returns
         -------
-        forecasts : DataFrame
+        forecasts : ARCHModelForecast
             t by h data frame containing the forecasts.  The alignment of the
             forecasts is controlled by `align`.
 
@@ -735,7 +735,7 @@ class _SummaryRepr(object):
     """Base class for returning summary as repr and str"""
 
     def summary(self):
-        return Summary()
+        raise NotImplementedError("Subclasses optionally must provide.")
 
     def __repr__(self):
         out = self.__str__() + '\n'
@@ -1086,7 +1086,7 @@ def forecast(self, params=None, horizon=1, start=None, align='origin', method='a
 
         Returns
         -------
-        forecasts : DataFrame
+        forecasts : ARCHModelForecast
             t by h data frame containing the forecasts.  The alignment of the
             forecasts is controlled by `align`.