ENH: Add basis for minute rate emission of performance.

- Create different benchmark containers in performance
  depending on emission rate.
- Add a minute close method which updates algorithm and
  benchmark returns, and calculates the risk metrics
  depending on those methods.
- Provide fake 0.0 values for annualized metrics like
  sharpe, sortino, and information, until we figure out
  how they should be treated in the context of minutely
  calculation.

*NOTE* This does not fully work without the changes to the
simulation loop by @fawce

tests/test_minute_risk.py

@@ -0,0 +1,57 @@
+#
+# Copyright 2013 Quantopian, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import datetime
+import pytz
+
+from zipline.finance.trading import SimulationParameters
+from zipline.finance import risk
+
+
+class TestMinuteRisk(unittest.TestCase):
+
+    def setUp(self):
+
+        start_date = datetime.datetime(
+            year=2006,
+            month=1,
+            day=3,
+            hour=0,
+            minute=0,
+            tzinfo=pytz.utc)
+        end_date = datetime.datetime(
+            year=2006, month=1, day=3, tzinfo=pytz.utc)
+
+        self.sim_params = SimulationParameters(
+            period_start=start_date,
+            period_end=end_date
+        )
+        self.sim_params.emission_rate = 'minute'
+
+    def test_minute_risk(self):
+
+        risk_metrics = risk.RiskMetricsIterative(self.sim_params)
+
+        first_dt = self.sim_params.first_open
+        second_dt = self.sim_params.first_open + datetime.timedelta(minutes=1)
+
+        risk_metrics.update(first_dt, 1.0, 2.0)
+
+        self.assertEquals(1, len(risk_metrics.alpha))
+
+        risk_metrics.update(second_dt, 3.0, 4.0)
+
+        self.assertEquals(2, len(risk_metrics.alpha))

tests/test_perf_tracking.py

@@ -1047,19 +1047,31 @@ class TestPerformanceTracker(unittest.TestCase):
                                   dt=foo_event_1.dt,
                                   price=10.0,
                                   commission=0.50)
+        benchmark_event_1 = Event({
+            'dt': start_dt,
+            'returns': 1.0,
+            'type': DATASOURCE_TYPE.BENCHMARK
+        })
 
         foo_event_2 = factory.create_trade(
             'foo', 11.0, 20, start_dt + datetime.timedelta(minutes=1))
         bar_event_2 = factory.create_trade(
             'bar', 11.0, 20, start_dt + datetime.timedelta(minutes=1))
+        benchmark_event_2 = Event({
+            'dt': start_dt + datetime.timedelta(minutes=1),
+            'returns': 2.0,
+            'type': DATASOURCE_TYPE.BENCHMARK
+        })
 
         events = [
             foo_event_1,
             order_event_1,
+            benchmark_event_1,
             txn_event_1,
             bar_event_1,
             foo_event_2,
-            bar_event_2
+            benchmark_event_2,
+            bar_event_2,
         ]
 
         messages = {date: snapshot[-1].perf_messages[0] for date, snapshot in