TST Moved transaction focused tests to test_txn.py. Added slippage ad…

…justement test.

pyfolio/tests/test_pos.py

@@ -17,7 +17,6 @@
 
 from pyfolio.pos import (get_portfolio_alloc,
                          extract_pos)
-from pyfolio.txn import (get_turnover)
 
 
 class PositionsTestCase(TestCase):
@@ -74,50 +73,3 @@ def test_extract_pos(self):
         expected.columns.name = 'sid'
 
         assert_frame_equal(result, expected)
-
-    def test_get_turnover(self):
-        """
-        Tests turnover using a 20 day period.
-
-        With no transactions the turnover should be 0.
-
-        with 100% of the porfolio value traded each day
-        the daily turnover rate should be 0.5.
-
-        For monthly turnover it should be the sum
-        of the daily turnovers because 20 days < 1 month.
-
-        e.g (20 days) * (0.5 daily turn) = 10x monthly turnover rate.
-        """
-        dates = date_range(start='2015-01-01', freq='D', periods=20)
-
-        positions = DataFrame([[0.0, 10.0]]*len(dates),
-                              columns=[0, 'cash'], index=dates)
-        transactions = DataFrame([[0, 0]]*len(dates),
-                                 columns=['txn_volume', 'txn_shares'],
-                                 index=dates)
-
-        # Test with no transactions
-        expected = Series([0.0]*len(dates), index=dates)
-        result = get_turnover(transactions, positions)
-        assert_series_equal(result, expected)
-
-        # Monthly freq
-        index = date_range('01-01-2015', freq='M', periods=1)
-        expected = Series([0.0], index=index)
-        result = get_turnover(transactions, positions, period='M')
-        assert_series_equal(result, expected)
-
-        # Test with 0.5 daily turnover
-        transactions = DataFrame([[10.0, 0]]*len(dates),
-                                 columns=['txn_volume', 'txn_shares'],
-                                 index=dates)
-
-        expected = Series([0.5]*len(dates), index=dates)
-        result = get_turnover(transactions, positions)
-        assert_series_equal(result, expected)
-
-        # Monthly freq: should be the sum of the daily freq
-        result = get_turnover(transactions, positions, period='M')
-        expected = Series([10.0], index=index)
-        assert_series_equal(result, expected)

pyfolio/tests/test_txn.py

@@ -0,0 +1,81 @@
+from unittest import TestCase
+
+from pandas import (
+    Series,
+    DataFrame,
+    date_range
+)
+from pandas.util.testing import (assert_series_equal)
+
+from pyfolio.txn import (get_turnover,
+                         adjust_returns_for_slippage)
+
+
+class TransactionsTestCase(TestCase):
+
+    def test_get_turnover(self):
+        """
+        Tests turnover using a 20 day period.
+
+        With no transactions the turnover should be 0.
+
+        with 100% of the porfolio value traded each day
+        the daily turnover rate should be 0.5.
+
+        For monthly turnover it should be the sum
+        of the daily turnovers because 20 days < 1 month.
+
+        e.g (20 days) * (0.5 daily turn) = 10x monthly turnover rate.
+        """
+        dates = date_range(start='2015-01-01', freq='D', periods=20)
+
+        positions = DataFrame([[0.0, 10.0]]*len(dates),
+                              columns=[0, 'cash'], index=dates)
+        transactions = DataFrame([[0, 0]]*len(dates),
+                                 columns=['txn_volume', 'txn_shares'],
+                                 index=dates)
+
+        # Test with no transactions
+        expected = Series([0.0]*len(dates), index=dates)
+        result = get_turnover(transactions, positions)
+        assert_series_equal(result, expected)
+
+        # Monthly freq
+        index = date_range('01-01-2015', freq='M', periods=1)
+        expected = Series([0.0], index=index)
+        result = get_turnover(transactions, positions, period='M')
+        assert_series_equal(result, expected)
+
+        # Test with 0.5 daily turnover
+        transactions = DataFrame([[10.0, 0]]*len(dates),
+                                 columns=['txn_volume', 'txn_shares'],
+                                 index=dates)
+
+        expected = Series([0.5]*len(dates), index=dates)
+        result = get_turnover(transactions, positions)
+        assert_series_equal(result, expected)
+
+        # Monthly freq: should be the sum of the daily freq
+        result = get_turnover(transactions, positions, period='M')
+        expected = Series([10.0], index=index)
+        assert_series_equal(result, expected)
+
+    def test_adjust_returns_for_slippage(self):
+        dates = date_range(start='2015-01-01', freq='D', periods=20)
+
+        positions = DataFrame([[0.0, 10.0]]*len(dates),
+                              columns=[0, 'cash'], index=dates)
+
+        # 100% total, 50% average daily turnover
+        transactions = DataFrame([[10.0, 0]]*len(dates),
+                                 columns=['txn_volume', 'txn_shares'],
+                                 index=dates)
+        returns = Series([0.05]*len(dates), index=dates)
+        # 0.001% slippage per dollar traded
+        slippage_bps = 10
+        expected = Series([0.049]*len(dates), index=dates)
+
+        turnover = get_turnover(transactions, positions, average=False)
+        result = adjust_returns_for_slippage(returns, turnover, slippage_bps)
+
+        assert_series_equal(result, expected)