BUG: Fix calculation of cumulative risk stats.

- Use current dt instead of market_close.
- Handle intraday close
- Remove zeroing out of sharpe etc.

zipline/finance/performance.py

@@ -322,9 +322,7 @@ class PerformanceTracker(object):
             perf_period.calculate_performance()
 
     def handle_minute_close(self, dt):
-
-        todays_date = self.market_close.replace(hour=0, minute=0, second=0,
-                                                microsecond=0)
+        todays_date = dt.replace(hour=0, minute=0, second=0, microsecond=0)
 
         minute_returns = self.minute_performance.returns
         self.minute_performance.rollover()
@@ -335,22 +333,20 @@ class PerformanceTracker(object):
         self.intraday_risk_metrics.update(dt,
                                           algo_minute_returns,
                                           bench_minute_returns)
-        # the intraday risk metrics compound the minutely returns of the
-        # benchmark.
-        bench_since_open = self.intraday_risk_metrics.benchmark_returns[-1]
-        benchmark_returns = pd.Series({dt: bench_since_open})
+
+        bench_since_open = \
+            self.intraday_risk_metrics.benchmark_period_returns[-1]
+
+        benchmark_returns = pd.Series({todays_date: bench_since_open})
 
         # if we've reached market close, check on dividends
         if dt == self.market_close:
             for perf_period in self.perf_periods:
                 perf_period.update_dividends(todays_date)
 
-        algorithm_returns = pd.Series({dt: self.todays_performance.returns})
-
-        self.intraday_risk_metrics.update(dt,
-                                          algorithm_returns,
-                                          benchmark_returns)
-
+        algorithm_returns = pd.Series({
+            todays_date: self.todays_performance.returns
+        })
         self.cumulative_risk_metrics.update(todays_date,
                                             algorithm_returns,
                                             benchmark_returns)
@@ -364,6 +360,15 @@ class PerformanceTracker(object):
             )
             self.returns.append(todays_return_obj)
 
+    def handle_intraday_close(self):
+        self.intraday_risk_metrics = \
+            risk.RiskMetricsIterative(self.sim_params)
+        # increment the day counter before we move markers forward.
+        self.day_count += 1.0
+        # move the market day markers forward
+        self.market_open, self.market_close = \
+            trading.environment.next_open_and_close(self.market_open)
+
     def handle_market_close(self):
         # add the return results from today to the list of DailyReturn objects.
         todays_date = self.market_close.replace(hour=0, minute=0, second=0,

zipline/finance/risk.py

@@ -693,16 +693,9 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
             'period_label': period_label
         }
 
-        if self.sim_params.emission_rate == 'daily':
-            # Some risk metrics only make sense in a context of daily
-            # risk calculations.
-            rval['sharpe'] = self.sharpe[-1]
-            rval['sortino'] = self.sortino[-1]
-            rval['information'] = self.information[-1]
-        elif self.sim_params.emission_rate == 'minute':
-            rval['sharpe'] = 0.0
-            rval['sortino'] = 0.0
-            rval['information'] = 0.0
+        rval['sharpe'] = self.sharpe[-1]
+        rval['sortino'] = self.sortino[-1]
+        rval['information'] = self.information[-1]
 
         return {k: None
                 if check_entry(k, v)

zipline/gens/tradesimulation.py

@@ -170,6 +170,7 @@ class AlgorithmSimulator(object):
                             tp.rollover()
                             if mkt_close < self.algo.perf_tracker.last_close:
                                 mkt_close = self.get_next_close(mkt_close)
+                                self.algo.perf_tracker.handle_intraday_close()
 
             risk_message = self.algo.perf_tracker.handle_simulation_end()
             yield risk_message