diff --git a/.travis.yml b/.travis.yml
index e04c8bd..714ed45 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -4,17 +4,17 @@ sudo: false
 matrix:
   include:
     - python: 2.7
-      env: PANDAS_VERSION=0.18.1 NUMPY_VERSION=1.11.1 SCIPY_VERSION=0.17.1 LIBGFORTRAN_VERSION=3.0
-    - python: 2.7
-      env: PANDAS_VERSION=0.19.2 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
+      env: PANDAS_VERSION=0.24.2 NUMPY_VERSION=1.12.1 SCIPY_VERSION=1.2.1 LIBGFORTRAN_VERSION=3.0
     - python: 2.7
       env: PANDAS_VERSION=0.20.1 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
-    - python: 3.5
-      env: PANDAS_VERSION=0.18.1 NUMPY_VERSION=1.11.1 SCIPY_VERSION=0.17.1 LIBGFORTRAN_VERSION=3.0
-    - python: 3.5
-      env: PANDAS_VERSION=0.19.2 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
+    - python: 3.6
+      env: PANDAS_VERSION=1.0.4 NUMPY_VERSION=1.18.4 SCIPY_VERSION=1.4.1 LIBGFORTRAN_VERSION=3.0
     - python: 3.6
       env: PANDAS_VERSION=0.20.1 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
+    - python: 3.6
+      env: PANDAS_VERSION=1.0.4 NUMPY_VERSION=1.18.4 SCIPY_VERSION=1.4.1 LIBGFORTRAN_VERSION=3.0
+    - python: 3.7
+      env: PANDAS_VERSION=1.0.4  NUMPY_VERSION=1.18.4 SCIPY_VERSION=1.4.1 LIBGFORTRAN_VERSION=3.0
 
 before_install:
   # We do this conditionally because it saves us some downloading if the
diff --git a/empyrical/stats.py b/empyrical/stats.py
index 2713edf..45e7d69 100644
--- a/empyrical/stats.py
+++ b/empyrical/stats.py
@@ -1747,7 +1747,13 @@ def gpd_risk_estimates_aligned(returns, var_p=0.01):
 
         DEFAULT_THRESHOLD = 0.2
         MINIMUM_THRESHOLD = 0.000000001
-        returns_array = pd.Series(returns).as_matrix()
+
+        try:
+            returns_array = pd.Series(returns).to_numpy()
+        except AttributeError:
+            # while zipline requires support for pandas < 0.25
+            returns_array = pd.Series(returns).as_matrix()
+
         flipped_returns = -1 * returns_array
         losses = flipped_returns[flipped_returns > 0]
         threshold = DEFAULT_THRESHOLD