updated factory to load from msgpack files, added tests for risk, parameterized treasury and benchmark data.

zipline/finance/risk.py

@@ -4,7 +4,6 @@ import pytz
 import numpy as np
 import numpy.linalg as la
 import zipline.util as qutil
-import zipline.db as db
 import zipline.protocol as zp
 from pymongo import ASCENDING, DESCENDING
 
@@ -13,10 +12,17 @@ class daily_return():
     def __init__(self, date, returns):
         self.date = date
         self.returns = returns
+    
+    def __repr__(self):
+        return str(self.date) + " - " + str(self.returns)
         
 class periodmetrics():
-    def __init__(self, start_date, end_date, returns, benchmark_returns):
-        self.db = db.DbConnection.get()[1]
+    def __init__(self, start_date, end_date, returns, benchmark_returns, treasury_curves, trading_calendar):
+        """
+        :param treasury_curves: {datetime in utc -> {duration label -> interest rate}}
+        """
+        
+        self.treasury_curves = treasury_curves
         self.start_date = start_date
         self.end_date = end_date
         self.trading_calendar = trading_calendar
@@ -134,13 +140,18 @@ class periodmetrics():
         else:
             self.treasury_duration = '30year'
         
-        treasuryQS = self.db.treasury_curves.find(
-                                                            spec={"date" : {"$lte" : self.end_date}},
-                                                            sort=[("date",DESCENDING)],
-                                                            limit=3,
-                                                            slave_ok=True)
-    
-        for curve in treasuryQS:
+        
+        one_day = datetime.timedelta(days=1)
+        
+        curve = None
+        #in case end date is not a trading day, search for the next market day for an interest rate
+        for i in range(7): 
+            if(self.treasury_curves.has_key(self.end_date + i * one_day)):
+                #qutil.LOGGER.info(self.treasury_curves[self.end_date + i * one_day])
+                curve = self.treasury_curves[self.end_date + i * one_day]
+                break
+        
+        if curve:
             self.treasury_curve = curve
             rate = self.treasury_curve[self.treasury_duration]
             #1month note data begins in 8/2001, so we can use 3month instead.
@@ -149,17 +160,18 @@ class periodmetrics():
             if rate != None:
                 return rate * (td.days + 1) / 365
 
-        raise Exception("no rate for end date = {dt} and term = {term}, from {curve}. Using zero.".format(dt=self.end_date, 
-                                                                                                          term=self.treasury_duration, 
-                                                                                                          curve=self.treasury_curve['date']))
+        raise Exception("no rate for end date = {dt} and term = {term}. Using zero.".format(dt=self.end_date, 
+                                                                                                          term=self.treasury_duration))
         
 class riskmetrics():
     
-    def __init__(self, algorithm_returns):
+    def __init__(self, algorithm_returns, benchmark_returns, treasury_curves, trading_calendar):
         """algorithm_returns needs to be a list of daily_return objects sorted in date ascending order"""
-        self.db = db.DbConnection.get()[1]
+        
         self.algorithm_returns = algorithm_returns
         self.bm_returns = [x for x in benchmark_returns if x.date >= self.algorithm_returns[0].date and x.date <= self.algorithm_returns[-1].date]
+        self.treasury_curves = treasury_curves
+        self.trading_calendar = trading_calendar
         
         qutil.LOGGER.debug("#### {start} thru {end} with {count} trading_days of {total} possible".format(start=self.algorithm_returns[0].date, 
                                                                                            end=self.algorithm_returns[-1].date,
@@ -191,23 +203,16 @@ class riskmetrics():
             if(cur_end > the_end):
                 break
             #qutil.LOGGER.debug("start: {start}, end: {end}".format(start=cur_start, end=cur_end))
-            cur_period_metrics = periodmetrics(start_date=cur_start, end_date=cur_end, returns=self.algorithm_returns, benchmark_returns=self.bm_returns)
+            cur_period_metrics = periodmetrics(start_date=cur_start, 
+                                               end_date=cur_end, 
+                                               returns=self.algorithm_returns, 
+                                               benchmark_returns=self.bm_returns, 
+                                               treasury_curves=self.treasury_curves,
+                                               trading_calendar=self.trading_calendar)
             ends.append(cur_period_metrics)
             cur_start = advance_by_months(cur_start, 1)
             
         return ends
-        
-    def store_to_db(self, back_test_run_id):
-        col = self.db.risk_metrics
-        for period in self.month_periods:
-            for metric in ["algorithm_period_returns", "benchmark_period_returns", "excess_return", "trading_days", "benchmark_volatility", "algorithm_volatility", "sharpe", "beta", "alpha", "max_drawdown"]:
-                record = {'back_test_run_id':back_test_run_id}
-                record['ending_on']     = period.end_date
-                record['metric_name']   = metric
-                for dur in ["month", "three_month", "six_month", "year", "three_year", "five_year"]:
-                    record[dur] = self.find_metric_by_end(period.end_date, dur, metric)
-                    #qutil.LOGGER.debug("storing {val} for {metric} and {dur}".format(val=record[dur], metric=metric, dur=dur))
-                col.insert(record, safe=True)
     
     def find_metric_by_end(self, end_date, duration, metric):
         col = getattr(self, duration + "_periods")
@@ -233,9 +238,10 @@ def advance_by_months(dt, jump_in_months):
 
 class TradingCalendar(object):
 
-    def __init__(self, benchmark_returns):
+    def __init__(self, benchmark_returns, treasury_curves):
         self.trading_days = []
         self.trading_day_map = {}
+        self.treasury_curves = treasury_curves
         for bm in benchmark_returns:
             self.trading_days.append(bm.date)
             self.trading_day_map[bm.date] = bm
@@ -253,21 +259,4 @@ class TradingCalendar(object):
             return self.trading_day_map[date].returns
         else:
             return 0.0
-
-       
-def get_benchmark_data():
-    bmQS = db.DbConnection.get()[1].bench_marks.find(
-                                 spec={"symbol" : "GSPC"}, 
-                                 sort=[("date",ASCENDING)],
-                                 slave_ok=True,
-                                 as_class=zp.namedict)
-    bm_returns = []
-    for bm in bmQS:
-        bm_r = daily_return(date=bm.date.replace(tzinfo=pytz.utc), returns=bm.returns)
-        bm_returns.append(bm_r)    
-
-    cal = TradingCalendar(bm_returns)
-    return bm_returns, cal
-
-benchmark_returns, trading_calendar = get_benchmark_data() 
     

zipline/test/factory.py

@@ -1,9 +1,26 @@
 import datetime
 import pytz
+import msgpack
+import random
 import zipline.util as qutil
 import zipline.finance.risk as risk
 import zipline.protocol as zp
 
+def load_market_data():
+    fp_bm = open("./etc/benchmark.msgpack", "rb")
+    bm_map = msgpack.loads(fp_bm.read())
+    bm_returns = []
+    for epoch, returns in bm_map.iteritems():
+        bm_returns.append(risk.daily_return(date=datetime.datetime.fromtimestamp(epoch).replace(hour=0, minute=0, second=0, tzinfo=pytz.utc), returns=returns))
+    bm_returns = sorted(bm_returns, key=lambda(x): x.date) 
+    fp_tr = open("./etc/treasury_curves.msgpack", "rb")
+    tr_map = msgpack.loads(fp_tr.read())
+    tr_curves = {}
+    for epoch, curve in tr_map.iteritems():
+        tr_curves[datetime.datetime.fromtimestamp(epoch).replace(hour=0, minute=0, second=0, tzinfo=pytz.utc)] = curve
+        
+    return bm_returns, tr_curves
+    
 
 def create_trade(sid, price, amount, datetime):
     row = {
@@ -16,14 +33,14 @@ def create_trade(sid, price, amount, datetime):
     }
     return row
 
-def create_trade_history(sid, prices, amounts, start_time, interval):
+def create_trade_history(sid, prices, amounts, start_time, interval, trading_calendar):
     i = 0
     trades = []
     current = start_time.replace(tzinfo = pytz.utc)
 
     for price, amount in zip(prices, amounts):
 
-        if(risk.trading_calendar.is_trading_day(current)):
+        if(trading_calendar.is_trading_day(current)):
             trade = create_trade(sid, price, amount, current)
             trades.append(trade)
 
@@ -38,13 +55,13 @@ def createTxn(sid, price, amount, datetime, btrid=None):
                       price=price, transaction_cost=-1*price*amount)
     return txn
 
-def createTxnHistory(sid, priceList, amtList, startTime, interval):
+def create_transaction_history(sid, priceList, amtList, startTime, interval, trading_calendar):
     txns = []
     current = startTime
 
     for price, amount in zip(priceList, amtList):
 
-        if risk.trading_calendar.is_trading_day(current):
+        if trading_calendar.is_trading_day(current):
             txns.append(createTxn(sid, price, amount, current))
             current = current + interval
 
@@ -52,3 +69,47 @@ def createTxnHistory(sid, priceList, amtList, startTime, interval):
             current = current + datetime.timedelta(days=1)
 
     return txns
+
+
+def create_returns(daycount, start, trading_calendar):
+    i = 0
+    test_range = []
+    current = start.replace(tzinfo=pytz.utc)
+    one_day = datetime.timedelta(days = 1)
+    while i < daycount: 
+        i += 1
+        r = risk.daily_return(current, random.random())
+        test_range.append(r)
+        current = current + one_day
+    return [ x for x in test_range if(trading_calendar.is_trading_day(x.date)) ]
+    
+
+def create_returns_from_range(start, end, trading_calendar):
+    current = start.replace(tzinfo=pytz.utc)
+    end = end.replace(tzinfo=pytz.utc)
+    one_day = datetime.timedelta(days = 1)
+    test_range = []
+    i = 0
+    while current <= end: 
+        current = current + one_day
+        if(not trading_calendar.is_trading_day(current)):
+            continue
+        r = risk.daily_return(current, random.random())
+        i += 1
+        test_range.append(r)
+
+    return test_range
+    
+def create_returns_from_list(returns, start, trading_calendar):
+    current = start.replace(tzinfo=pytz.utc)
+    one_day = datetime.timedelta(days = 1)
+    test_range = []
+    i = 0
+    while len(test_range) < len(returns): 
+        if(trading_calendar.is_trading_day(current)):
+            r = risk.daily_return(current, returns[i])
+            i += 1
+            test_range.append(r)
+        current = current + one_day
+    return sorted(test_range, key=lambda(x):x.date)
+

zipline/test/test_risk.py

@@ -0,0 +1,238 @@
+import unittest
+import copy
+import datetime
+import calendar
+import pytz
+import zipline.finance.risk as risk
+import zipline.test.factory as factory
+import zipline.util as qutil
+
+class Risk(unittest.TestCase):
+    
+    def setUp(self):
+        qutil.configure_logging()
+        self.benchmark_returns, self.treasury_curves = factory.load_market_data()
+        self.trading_calendar = risk.TradingCalendar(self.benchmark_returns, self.treasury_curves)
+        
+        self.onesec = datetime.timedelta(seconds=1)
+        self.oneday = datetime.timedelta(days=1)
+        self.tradingday = datetime.timedelta(hours=6, minutes=30)
+        self.dt = datetime.datetime.utcnow()
+        returns = [0.0093,-0.0193,0.0351,0.0396,0.0338,-0.0211,0.0389,0.0326,-0.0137,-0.0411,-0.0032,0.0149,0.0133,0.0348,0.042,-0.0455,0.0262,-0.0461,0.0021,-0.0273,-0.0429,0.0427,-0.0104,0.0346,-0.0311,0.0003,0.0211,0.0248,-0.0215,0.004,0.0267,0.0029,-0.0369,0.0057,0.0298,-0.0179,-0.0361,-0.0401,-0.0123,-0.005,0.0203,-0.041,0.0011,0.0118,0.0103,-0.0184,-0.0437,0.0411,-0.0242,-0.0054,-0.0039,-0.0273,-0.0075,0.0064,-0.0376,0.0424,0.0399,0.019,0.0236,-0.0284,-0.0341,0.0266,0.05,0.0069,-0.0442,-0.016,0.0173,0.0348,-0.0404,-0.0068,-0.0376,0.0356,0.0043,-0.0481,-0.0134,0.0257,0.0442,0.0234,0.0394,0.0376,-0.0147,-0.0098,0.0474,-0.0102,0.0138,0.0286,0.0347,0.0279,-0.0067,0.0462,-0.0432,0.0247,0.0174,-0.0305,-0.0317,-0.0068,0.0264,-0.0257,-0.0328,0.0092,0.0288,-0.002,0.0288,0.028,-0.0093,0.0178,-0.0365,-0.0086,-0.0133,-0.0309,0.0473,-0.0149,0.0378,-0.0316,-0.0292,-0.0453,-0.0451,0.0093,0.0397,-0.0361,-0.0168,-0.0494,-0.0143,-0.0405,-0.0349,0.0069,0.0378,-0.0233,-0.0492,0.018,-0.0386,0.0339,0.0119,0.0454,0.0118,-0.011,-0.0254,0.0266,-0.0366,-0.0211,0.0399,0.0307,0.035,-0.0402,0.0304,-0.0031,0.0256,0.0134,-0.0019,-0.0235,-0.0058,-0.0117,0.0051,-0.0451,-0.0466,-0.0124,0.0283,-0.0499,0.0318,-0.0028,0.0203,0.005,0.0085,0.0048,0.0277,0.0159,-0.0149,0.035,0.0404,-0.01,0.0377,0.0302,0.0046,-0.0328,-0.0469,0.0071,-0.0382,-0.0214,0.0429,0.0145,-0.0279,-0.0172,0.0423,0.041,-0.0183,0.0137,-0.0412,-0.0348,0.0302,0.0248,0.0051,-0.0298,-0.0103,-0.0333,-0.0399,0.0485,-0.0166,0.0384,0.0259,-0.0163,0.0357,0.0308,-0.0386,0.0481,-0.0446,-0.0282,-0.0037,0.0202,0.0216,0.0113,0.0194,0.0392,0.0016,0.0268,-0.0155,-0.027,0.02,0.0216,-0.0009,0.022,0,0.041,0.0133,-0.0382,0.0495,-0.0221,-0.0329,-0.0033,-0.0089,-0.0129,-0.0252,0.048,-0.0307,-0.0357,0.0033,-0.0412,-0.0407,0.0455,0.0159,-0.0051,-0.0274,-0.0213,0.0361,0.0051,-0.0378,0.0084,0.0066,-0.0103,-0.0037,0.0478,-0.0278]
+        start_date = datetime.datetime(year=2006, month=1, day=1, tzinfo=pytz.utc)
+        self.algo_returns_06 = factory.create_returns_from_list(returns, start_date, self.trading_calendar)
+        end_date = datetime.datetime(year=2006, month=12, day=31, tzinfo=pytz.utc)
+        self.metrics_06 = risk.riskmetrics(self.algo_returns_06, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        
+    def tearDown(self):
+        return
+    
+    def test_factory(self):
+        returns = [0.1] * 100
+        start_date = datetime.datetime(year=2006, month=1, day=1, tzinfo=pytz.utc) 
+        r_objects = factory.create_returns_from_list(returns, start_date, self.trading_calendar)
+        self.assertTrue(r_objects[-1].date <= datetime.datetime(year=2006, month=12, day=31, tzinfo=pytz.utc))
+           
+    def test_drawdown(self):
+        start_date = datetime.datetime(year=2006, month=1, day=1)
+        returns = factory.create_returns_from_list([1.0,-0.5,0.8,.17,1.0,-0.1,-0.45], start_date, self.trading_calendar)
+        #200, 100, 180, 210.6, 421.2, 379.8, 208.494
+        metrics = risk.periodmetrics(returns[0].date, returns[-1].date, returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual(metrics.max_drawdown, 0.505)
+    
+    def test_benchmark_returns_06(self):
+        start_date = datetime.datetime(year=2006, month=1, day=1)
+        end_date = datetime.datetime(year=2006, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([round(x.benchmark_period_returns, 4)  for x in metrics.month_periods],    
+        [0.0255,0.0005,0.0111,0.0122,-0.0309,0.0001,0.0051,0.0213,0.0246,0.0315,0.0165,0.0126])
+        self.assertEqual([round(x.benchmark_period_returns, 4) for x in metrics.three_month_periods],
+        [0.0373,0.0239,-0.0083,-0.0191,-0.0259,0.0266,0.0517,0.0793,0.0743,0.0617])
+        self.assertEqual([round(x.benchmark_period_returns, 4) for x in metrics.six_month_periods],
+        [0.0176,-0.0027,0.0181,0.0316,0.0514,0.1028,0.1166])
+        self.assertEqual([round(x.benchmark_period_returns,4) for x in metrics.year_periods],[0.1362])
+
+    def test_trading_days_06(self):
+        start_date = datetime.datetime(year=2006, month=1, day=1)
+        end_date = datetime.datetime(year=2006, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([x.trading_days for x in metrics.year_periods],[251])
+        self.assertEqual([x.trading_days for x in metrics.month_periods],[20,19,23,19,22,22,20,23,20,22,21,20])
+
+    def test_benchmark_volatility_06(self):
+        start_date = datetime.datetime(year=2006, month=1, day=1)
+        end_date = datetime.datetime(year=2006, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.month_periods],
+        [0.031,0.026,0.024,0.025,0.037,0.047,0.039,0.022,0.023,0.021,0.025,0.019])
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.three_month_periods],
+        [0.047,0.042,0.050,0.064,0.070,0.064,0.049,0.037,0.039,0.037])
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.six_month_periods],
+        [0.079,0.082,0.081,0.081,0.08,0.074,0.061])
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.year_periods],[0.100])
+   
+    def test_algorithm_returns_06(self):
+         self.assertEqual([round(x.algorithm_period_returns, 3) for x in self.metrics_06.month_periods],[0.101,-0.062,-0.041,0.092,0.135,-0.25,0.076,-0.003,-0.024,0.072,0.063,-0.071])
+         self.assertEqual([round(x.algorithm_period_returns, 3) for x in self.metrics_06.three_month_periods],[-0.009,-0.017,0.188,-0.071,-0.085,-0.196,0.047,0.043,0.112,0.058])
+         self.assertEqual([round(x.algorithm_period_returns, 3) for x in self.metrics_06.six_month_periods],[-0.08,-0.101,-0.044,-0.027,-0.045,-0.106,0.108])
+         self.assertEqual([round(x.algorithm_period_returns, 3) for x in self.metrics_06.year_periods],[0.02])
+    
+    def test_algorithm_volatility_06(self):
+        self.assertEqual([round(x.algorithm_volatility, 3) for x in self.metrics_06.month_periods],[0.137,0.12,0.13,0.142,0.128,0.14,0.141,0.118,0.143,0.144,0.117,0.135])
+        self.assertEqual([round(x.algorithm_volatility, 3) for x in self.metrics_06.three_month_periods],[0.222,0.224,0.229,0.243,0.243,0.235,0.23,0.231,0.231,0.227])
+        self.assertEqual([round(x.algorithm_volatility, 3) for x in self.metrics_06.six_month_periods],[0.328,0.329,0.329,0.333,0.334,0.329,0.321])
+        self.assertEqual([round(x.algorithm_volatility, 3) for x in self.metrics_06.year_periods],[0.458])
+    
+    def test_algorithm_sharpe_06(self):
+        self.assertEqual([round(x.sharpe, 3) for x in self.metrics_06.month_periods],[0.711,-0.541,-0.348,0.625,1.017,-1.809,0.508,-0.062,-0.193,0.467,0.502,-0.557])
+        self.assertEqual([round(x.sharpe, 3) for x in self.metrics_06.three_month_periods],[-0.094,-0.129,0.769,-0.342,-0.402,-0.888,0.153,0.131,0.432,0.2])
+        self.assertEqual([round(x.sharpe, 3) for x in self.metrics_06.six_month_periods],[-0.322,-0.383,-0.213,-0.156,-0.213,-0.398,0.257])
+        self.assertEqual([round(x.sharpe, 3) for x in self.metrics_06.year_periods],[-0.066])
+
+    def dtest_algorithm_beta_06(self):
+        self.assertEqual([round(x.beta, 3) for x in self.metrics_06.month_periods],[0.553,0.583,-2.168,-0.548,1.463,-0.322,-1.38,1.473,-1.315,-0.7,0.352,-2.002])
+        self.assertEqual([round(x.beta, 3) for x in self.metrics_06.three_month_periods],[-0.075,-0.637,0.124,0.186,-0.204,-0.497,-0.867,-0.173,-0.499,-0.563])
+        self.assertEqual([round(x.beta, 3) for x in self.metrics_06.six_month_periods],[-0.075,-0.637,0.124,0.186,-0.204,-0.497,-0.867,-0.173,-0.499,-0.563])
+        self.assertEqual([round(x.beta, 3) for x in self.metrics_06.year_periods],[-0.219])
+        
+    def dtest_algorithm_alpha_06(self):
+        self.assertEqual([round(x.alpha, 3) for x in self.metrics_06.month_periods],[0.085,-0.063,-0.03,0.093,0.182,-0.255,0.073,-0.032,0,0.086,0.054,-0.058])
+        self.assertEqual([round(x.alpha, 3) for x in self.metrics_06.three_month_periods],[-0.051,-0.021,0.179,-0.077,-0.106,-0.202,0.069,0.042,0.13,0.073])
+        self.assertEqual([round(x.alpha, 3) for x in self.metrics_06.six_month_periods],[-0.105,-0.135,-0.072,-0.051,-0.066,-0.094,0.152])
+        self.assertEqual([round(x.alpha, 3) for x in self.metrics_06.year_periods],[-0.011])
+
+    #FIXME: Covariance is not matching excel precisely enough to run the test. Month 4 seems to be the problem. Variance is disabled
+    #just to avoid distraction - it is much closer than covariance and can probably pass with 6 significant digits instead of 7.
+    #re-enable variance, alpha, and beta tests once this is resolved
+    def dtest_algorithm_covariance_06(self):
+        metric = self.metrics_06.month_periods[3]
+        print repr(metric)
+        print "----"
+        self.assertEqual([round(x.algorithm_covariance, 7) for x in self.metrics_06.month_periods],[0.0000289,0.0000222,-0.0000554,-0.0000192,0.0000954,-0.0000333,-0.0001111,0.0000322,-0.0000349,-0.0000143,0.0000108,-0.0000386])
+        self.assertEqual([round(x.algorithm_covariance, 7) for x in self.metrics_06.three_month_periods],[-0.0000026,-0.0000189,0.0000049,0.0000121,-0.0000158,-0.000031,-0.0000336,-0.0000036,-0.0000119,-0.0000122])
+        self.assertEqual([round(x.algorithm_covariance, 7) for x in self.metrics_06.six_month_periods],[0.000005,-0.0000172,-0.0000142,-0.0000102,-0.0000089,-0.0000207,-0.0000229])
+        self.assertEqual([round(x.algorithm_covariance, 7) for x in self.metrics_06.year_periods],[-8.75273E-06])
+
+    def dtest_benchmark_variance_06(self):
+        self.assertEqual([round(x.benchmark_variance, 7) for x in self.metrics_06.month_periods],[0.0000496,0.000036,0.0000244,0.0000332,0.0000623,0.0000989,0.0000765,0.0000209,0.0000252,0.0000194,0.0000292,0.0000183])
+        self.assertEqual([round(x.benchmark_variance, 7) for x in self.metrics_06.three_month_periods],[0.0000351,0.0000298,0.0000395,0.0000648,0.0000773,0.0000625,0.0000387,0.0000211,0.0000238,0.0000217])
+        self.assertEqual([round(x.benchmark_variance, 7) for x in self.metrics_06.six_month_periods],[0.0000499,0.0000538,0.0000508,0.0000517,0.0000492,0.0000432,0.00003])
+        self.assertEqual([round(x.benchmark_variance, 7) for x in self.metrics_06.year_periods],[0.0000399])
+
+
+    def test_benchmark_returns_08(self):
+        start_date = datetime.datetime(year=2008, month=1, day=1)
+        end_date = datetime.datetime(year=2008, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([round(x.benchmark_period_returns, 3)  for x in metrics.month_periods],    
+        [-0.061,-0.035,-0.006,0.048,0.011,-0.086,-0.01,0.012,-0.091,-0.169,-0.075,0.008])
+        self.assertEqual([round(x.benchmark_period_returns, 3) for x in metrics.three_month_periods],
+        [-0.099,0.005,0.052,-0.032,-0.085,-0.084,-0.089,-0.236,-0.301,-0.226])
+        self.assertEqual([round(x.benchmark_period_returns, 3) for x in metrics.six_month_periods],
+        [-0.128,-0.081,-0.036,-0.118,-0.301,-0.360,-0.294])
+        self.assertEqual([round(x.benchmark_period_returns,3) for x in metrics.year_periods],[-0.385])
+    
+    def test_trading_days_08(self):
+        start_date = datetime.datetime(year=2008, month=1, day=1)
+        end_date = datetime.datetime(year=2008, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([x.trading_days for x in metrics.year_periods],[253])
+        self.assertEqual([x.trading_days for x in metrics.month_periods],[21,20,20,22,21,21,22,21,21,23,19,22])
+        
+    def test_benchmark_volatility_08(self):
+        start_date = datetime.datetime(year=2008, month=1, day=1)
+        end_date = datetime.datetime(year=2008, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.month_periods],
+        [0.07,0.058,0.082,0.054,0.041,0.057,0.068,0.06,0.157,0.244,0.195,0.145])
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.three_month_periods],
+        [0.120,0.113,0.105,0.09,0.098,0.107,0.179,0.293,0.344,0.340])
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.six_month_periods],
+        [0.15,0.149,0.15,0.2,0.308,0.36,0.383])
+        #TODO: ugly, but I can't get the rounded float to match. maybe we need a different test that checks the difference between the numbers
+        self.assertEqual([round(x.benchmark_volatility, 3) for x in metrics.year_periods],[0.41099999999999998])
+        
+    def test_treasury_returns_06(self):
+        start_date = datetime.datetime(year=2006, month=1, day=1)
+        end_date = datetime.datetime(year=2006, month=12, day=31)
+        returns = factory.create_returns_from_range(start_date, end_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.month_periods],
+        [0.0037,0.0034,0.0039,0.0038,0.0040,0.0037,0.0043,0.0043,0.0038,0.0044,0.0043,0.0041])
+        self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.three_month_periods],
+        [0.0114,0.0118,0.0122,0.0125,0.0129,0.0127,0.0123,0.0128,0.0125,0.0128])
+        self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.six_month_periods],
+        [0.0260,0.0257,0.0258,0.0252,0.0259,0.0256,0.0258])
+        self.assertEqual([round(x.treasury_period_return, 4) for x in metrics.year_periods],
+        [0.0500])
+        
+    def test_benchmarkrange(self):
+        self.check_year_range(datetime.datetime(year=2008,month=1,day=1), 2)
+        
+    def test_partial_month(self):
+        start_date = datetime.datetime(year=1991, month=1, day=1)
+        returns = factory.create_returns(365 * 5 + 2, start_date, self.trading_calendar) #1992 and 1996 were leap years
+        returns = returns[:-10] #truncate the returns series to end mid-month
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        total_months = 60
+        self.check_metrics(metrics, total_months, start_date)
+        
+    def check_year_range(self, start_date, years):
+        if(start_date.month <= 2):
+            ld = calendar.leapdays(start_date.year, start_date.year + years)
+        else:
+            #because we may catch the leap of the last year, and i think this func is [start,end)
+            ld = calendar.leapdays(start_date.year, start_date.year + years + 1) 
+        returns = factory.create_returns(365 * years + ld, start_date, self.trading_calendar)
+        metrics = risk.riskmetrics(returns, self.benchmark_returns, self.treasury_curves, self.trading_calendar)
+        total_months = years * 12
+        self.check_metrics(metrics, total_months, start_date)
+        
+    def check_metrics(self, metrics, total_months, start_date):
+        self.assert_range_length(metrics.month_periods, total_months, 1, start_date)
+        self.assert_range_length(metrics.three_month_periods, total_months, 3, start_date)
+        self.assert_range_length(metrics.six_month_periods, total_months, 6, start_date)
+        self.assert_range_length(metrics.year_periods, total_months, 12, start_date)
+        self.assert_range_length(metrics.three_year_periods, total_months, 36, start_date)
+        self.assert_range_length(metrics.five_year_periods, total_months, 60, start_date)
+        
+    def assert_last_day(self, period_end):
+        #30 days has september, april, june and november
+        if(period_end.month in [9,4,6,11]):
+            self.assertEqual(period_end.day, 30)
+        #all the rest have 31, except for february
+        elif(period_end.month != 2):
+            self.assertEqual(period_end.day, 31)
+        else:
+            if calendar.isleap(period_end.year):
+                self.assertEqual(period_end.day, 29)
+            else:
+                self.assertEqual(period_end.day, 28)
+        
+    def assert_month(self, start_month, actual_end_month):
+        if start_month == 1:
+            expected_end_month =  12
+        else:
+            expected_end_month = start_month - 1
+            
+        self.assertEqual(expected_end_month, actual_end_month)
+        
+    def assert_range_length(self, col, total_months, period_length, start_date):
+        if(period_length > total_months):
+            self.assertEqual(len(col), 0)
+        else:
+            self.assertEqual(len(col), total_months - (period_length - 1), "mismatch for total months - expected:{total_months}/actual:{actual}, period:{period_length}, start:{start_date}, calculated end:{end}".format(
+                                                                            total_months=total_months,
+                                                                            period_length=period_length,
+                                                                            start_date=start_date,
+                                                                            end=col[-1].end_date,
+                                                                            actual=len(col)
+                                                                            ))
+            self.assert_month(start_date.month, col[-1].end_date.month)
+            self.assert_last_day(col[-1].end_date)