diff --git a/tests/modelling/test_modelling_algo.py b/tests/modelling/test_modelling_algo.py
index 01e320bc..1b4e8714 100644
--- a/tests/modelling/test_modelling_algo.py
+++ b/tests/modelling/test_modelling_algo.py
@@ -332,6 +332,7 @@ class FFCAlgorithmTestCase(TestCase):
             raise
 
         cls.dates = cls.raw_data[cls.AAPL].index.tz_localize('UTC')
+        cls.AAPL_split_date = Timestamp("2014-06-09", tz='UTC')
 
     @classmethod
     def tearDownClass(cls):
@@ -386,13 +387,13 @@ class FFCAlgorithmTestCase(TestCase):
     def make_source(self):
         return Panel(self.raw_data).tz_localize('UTC', axis=1)
 
-    def test_handle_adjustment(self):
-        AAPL, MSFT, BRK_A = assets = self.AAPL, self.MSFT, self.BRK_A
+    def compute_expected_vwaps(self, window_lengths):
+        AAPL, MSFT, BRK_A = self.AAPL, self.MSFT, self.BRK_A
 
         # Our view of the data before AAPL's split on June 9, 2014.
         raw = {k: v.copy() for k, v in iteritems(self.raw_data)}
 
-        split_date = Timestamp("2014-06-09", tz='UTC')
+        split_date = self.AAPL_split_date
         split_loc = self.dates.get_loc(split_date)
         split_ratio = 7.0
 
@@ -404,12 +405,9 @@ class FFCAlgorithmTestCase(TestCase):
             adj[AAPL].ix[:split_loc, column] /= split_ratio
         adj[AAPL].ix[:split_loc, 'volume'] *= split_ratio
 
-        window_lengths = [1, 2, 5, 10]
         # length -> asset -> expected vwap
         vwaps = {length: {} for length in window_lengths}
-        vwap_keys = {}
         for length in window_lengths:
-            vwap_keys[length] = "vwap_%d" % length
             for asset in AAPL, MSFT, BRK_A:
                 raw_vwap = rolling_vwap(raw[asset], length)
                 adj_vwap = rolling_vwap(adj[asset], length)
@@ -462,21 +460,32 @@ class FFCAlgorithmTestCase(TestCase):
             decimal=2,
         )
 
+        return vwaps
+
+    def test_handle_adjustment(self):
+        AAPL, MSFT, BRK_A = assets = self.AAPL, self.MSFT, self.BRK_A
+
+        window_lengths = [1, 2, 5, 10]
+        vwaps = self.compute_expected_vwaps(window_lengths)
+
+        def vwap_key(length):
+            return "vwap_%d" % length
+
         def initialize(context):
             pipeline = Pipeline('test')
             context.vwaps = []
-            for length, key in iteritems(vwap_keys):
+            for length in vwaps:
                 context.vwaps.append(VWAP(window_length=length))
-                pipeline.add(context.vwaps[-1], name=key)
+                pipeline.add(context.vwaps[-1], name=vwap_key(length))
 
             attach_pipeline(pipeline)
 
         def handle_data(context, data):
             today = get_datetime()
             results = drain_pipeline('test')
-            for length, key in iteritems(vwap_keys):
+            for length in vwaps:
                 for asset in assets:
-                    computed = results.loc[asset, key]
+                    computed = results.loc[asset, vwap_key(length)]
                     expected = vwaps[length][asset].loc[today]
 
                     # Only having two places of precision here is a bit