MAINT: Factor out downside risk calculation.

Move the downside risk calculation into the main risk module;
so that the same calculation can eventually be used by both
the period and cumulative calculations, to prevent implementation
drift.

zipline/finance/risk/cumulative.py

@@ -30,6 +30,7 @@ from . risk import (
     alpha,
     check_entry,
     choose_treasury,
+    downside_risk,
 )
 
 log = logbook.Logger('Risk Cumulative')
@@ -449,10 +450,9 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
         return np.std(daily_returns) * math.sqrt(252)
 
     def calculate_downside_risk(self):
-        rets = self.algorithm_returns
-        mar = self.mean_returns
-        downside_diff = (rets[rets < mar] - mar).valid()
-        return np.std(downside_diff) * math.sqrt(252)
+        return downside_risk(self.algorithm_returns,
+                             self.mean_returns,
+                             252)
 
     def calculate_beta(self):
         """

zipline/finance/risk/risk.py

@@ -56,6 +56,7 @@ Risk Report
 """
 
 import logbook
+import math
 import numpy as np
 
 from zipline.finance import trading
@@ -103,6 +104,13 @@ def sharpe_ratio(algorithm_volatility, algorithm_return, treasury_return):
     return (algorithm_return - treasury_return) / algorithm_volatility
 
 
+def downside_risk(algorithm_returns, mean_returns, normalization_factor):
+    rets = algorithm_returns
+    mar = mean_returns
+    downside_diff = (rets[rets < mar] - mar).valid()
+    return np.std(downside_diff) * math.sqrt(normalization_factor)
+
+
 def sortino_ratio(algorithm_returns, algorithm_period_return, mar):
     """
     http://en.wikipedia.org/wiki/Sortino_ratio