Merge pull request #378 from quantopian/fixed-zero-last-sale-price

BUG: Fixed random dips in returns as shown to user.

tests/test_perf_tracking.py

@@ -760,6 +760,14 @@ class TestPositionPerformance(unittest.TestCase):
         pp = perf.PerformancePeriod(1000.0)
 
         pp.execute_transaction(txn)
+
+        # This verifies that the last sale price is being correctly
+        # set in the positions. If this is not the case then returns can
+        # incorrectly show as sharply dipping if a transaction arrives
+        # before a trade. This is caused by returns being based on holding
+        # stocks with a last sale price of 0.
+        self.assertEqual(pp.positions[1].last_sale_price, 10.0)
+
         for trade in trades:
             pp.update_last_sale(trade)
 
@@ -1487,7 +1495,9 @@ class TestPerformanceTracker(unittest.TestCase):
             self.assertEquals(foo_event_2.dt,
                               msg_2['minute_perf']['period_close'])
 
-            # Ensure that a Sharpe value for cumulative metrics is being
-            # created.
-            self.assertIsNotNone(msg_1['cumulative_risk_metrics']['sharpe'])
+            # In this test event1 transactions arrive on the first bar.
+            # This leads to no returns as the price is constant.
+            # Sharpe ratio cannot be computed and is None.
+            # In the second bar we can start establishing a sharpe ratio.
+            self.assertIsNone(msg_1['cumulative_risk_metrics']['sharpe'])
             self.assertIsNotNone(msg_2['cumulative_risk_metrics']['sharpe'])

zipline/finance/performance/period.py

@@ -303,6 +303,7 @@ class PerformancePeriod(object):
         position.update(txn)
         self.ensure_position_index(txn.sid)
         self._position_amounts[txn.sid] = position.amount
+        self._position_last_sale_prices[txn.sid] = position.last_sale_price
 
         self.period_cash_flow -= txn.price * txn.amount
 

zipline/finance/performance/position.py

@@ -152,6 +152,12 @@ class Position(object):
                 total_cost = prev_cost + txn_cost
                 self.cost_basis = total_cost / total_shares
 
+            # Update the last sale price if txn is
+            # best data we have so far
+            if self.last_sale_date is None or txn.dt > self.last_sale_date:
+                self.last_sale_price = txn.price
+                self.last_sale_date = txn.dt
+
         self.amount = total_shares
 
     def adjust_commission_cost_basis(self, commission):