diff --git a/tests/risk/answer_key.py b/tests/risk/answer_key.py
index 8a0449a7..22ddbd55 100644
--- a/tests/risk/answer_key.py
+++ b/tests/risk/answer_key.py
@@ -173,6 +173,13 @@ class AnswerKey(object):
         'year': DataIndex('Sim', 'BE', 34, 34),
     }
 
+    ALGORITHM_PERIOD_COVARIANCE = {
+        'Monthly': DataIndex('Sim', 'AX', 23, 34),
+        '3-Month': DataIndex('Sim', 'AY', 25, 34),
+        '6-month': DataIndex('Sim', 'AZ', 28, 34),
+        'year': DataIndex('Sim', 'BA', 34, 34),
+    }
+
     def __init__(self):
         self.workbook = xlrd.open_workbook(ANSWER_KEY_PATH)
 
diff --git a/tests/risk/test_risk.py b/tests/risk/test_risk.py
index 7f4ad84a..56760447 100644
--- a/tests/risk/test_risk.py
+++ b/tests/risk/test_risk.py
@@ -423,51 +423,36 @@ class TestRisk(unittest.TestCase):
     # just to avoid distraction - it is much closer than covariance
     # and can probably pass with 6 significant digits instead of 7.
     #re-enable variance, alpha, and beta tests once this is resolved
-    def dtest_algorithm_covariance_06(self):
-        metric = self.metrics_06.month_periods[3]
-        print repr(metric)
-        print "----"
-        self.assertEqual([round(x.algorithm_covariance, 7)
+    def test_algorithm_covariance_06(self):
+        answer_key_month_periods = ANSWER_KEY.get_values(
+            AnswerKey.ALGORITHM_PERIOD_COVARIANCE['Monthly'],
+            decimal=7)
+        self.assertEqual([np.round(x.algorithm_covariance, 7)
                           for x in self.metrics_06.month_periods],
-                         [0.0000289,
-                          0.0000222,
-                          -0.0000554,
-                          -0.0000192,
-                          0.0000954,
-                          -0.0000333,
-                          -0.0001111,
-                          0.0000322,
-                          -0.0000349,
-                          -0.0000143,
-                          0.0000108,
-                          -0.0000386])
+                         answer_key_month_periods)
 
-        self.assertEqual([round(x.algorithm_covariance, 7)
+        answer_key_three_month_periods = ANSWER_KEY.get_values(
+            AnswerKey.ALGORITHM_PERIOD_COVARIANCE['3-Month'],
+            decimal=7)
+        self.assertEqual([np.round(x.algorithm_covariance, 7)
                           for x in self.metrics_06.three_month_periods],
-                         [-0.0000026,
-                          -0.0000189,
-                          0.0000049,
-                          0.0000121,
-                          -0.0000158,
-                          -0.000031,
-                          -0.0000336,
-                          -0.0000036,
-                          -0.0000119,
-                          -0.0000122])
+                         answer_key_three_month_periods)
 
-        self.assertEqual([round(x.algorithm_covariance, 7)
-                          for x in self.metrics_06.six_month_periods],
-                         [0.000005,
-                          -0.0000172,
-                          -0.0000142,
-                          -0.0000102,
-                          -0.0000089,
-                          -0.0000207,
-                          -0.0000229])
+        answer_key_six_month_periods = ANSWER_KEY.get_values(
+            AnswerKey.ALGORITHM_PERIOD_COVARIANCE['6-month'],
+            decimal=7)
+        results_six_month_periods = [
+            np.round(x.algorithm_covariance, 7)
+            for x in self.metrics_06.six_month_periods]
+        self.assertEqual(results_six_month_periods,
+                         answer_key_six_month_periods)
 
-        self.assertEqual([round(x.algorithm_covariance, 7)
+        answer_key_year_periods = ANSWER_KEY.get_values(
+            AnswerKey.ALGORITHM_PERIOD_COVARIANCE['year'],
+            decimal=7)
+        self.assertEqual([np.round(x.algorithm_covariance, 7)
                           for x in self.metrics_06.year_periods],
-                         [-8.75273E-06])
+                         answer_key_year_periods)
 
     def test_benchmark_variance_06(self):
         answer_key_month_periods = ANSWER_KEY.get_values(
diff --git a/zipline/finance/risk.py b/zipline/finance/risk.py
index a049c717..fd246704 100644
--- a/zipline/finance/risk.py
+++ b/zipline/finance/risk.py
@@ -482,11 +482,11 @@ class RiskMetricsBase(object):
 
         returns_matrix = np.vstack([self.algorithm_returns,
                                     self.benchmark_returns])
-        C = np.cov(returns_matrix)
+        C = np.cov(returns_matrix, ddof=0)
         eigen_values = la.eigvals(C)
         condition_number = max(eigen_values) / min(eigen_values)
         algorithm_covariance = C[0][1]
-        benchmark_variance = C[1][1]
+        benchmark_variance = np.var(self.benchmark_returns, ddof=1)
         beta = C[0][1] / C[1][1]
 
         return (