PERF: Send pre-adjusted returns to information_ratio

zipline/finance/risk/cumulative.py

@@ -279,9 +279,11 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
             risk_adj_returns,
             _downside_risk=self.downside_risk[dt_loc]
         )
+        # 0.0 for the second argument allows the passing of already-adjusted
+        # returns for the first argument.
         self.information[dt_loc] = information_ratio(
-            algorithm_returns_series,
-            benchmark_returns_series
+            risk_adj_returns,
+            0.0
         )
         self.max_drawdown = max_drawdown(
             algorithm_returns_series

zipline/finance/risk/period.py

@@ -131,9 +131,11 @@ class RiskMetricsPeriod(object):
             risk_adj_returns,
             _downside_risk=self.downside_risk
         )
+        # 0.0 for the second argument allows the passing of already-adjusted
+        # returns for the first argument.
         self.information = information_ratio(
-            self.algorithm_returns,
-            self.benchmark_returns
+            risk_adj_returns,
+            0.0
         )
         self.beta = beta(
             self.algorithm_returns,