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BUG: Fix get_benchmark_returns.

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It should calculate the return off the pervious day's close, instead
of current day's open.
This commit is contained in:
Ben McCann
2013-07-14 15:44:57 -07:00
committed by Eddie Hebert
parent b9bd928862
commit efe50f8494
3 changed files with 129 additions and 121 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+1
View File
@@ -140,6 +140,7 @@ Thank you for all the help so far!
- [Jeremiah Lowin](http://www.lowindata.com) for teaching us the nuances of Sharpe and Sortino Ratios
- Brian Cappello
- @verdverm (Tony Worm), Order types (stop, limit)
- @benmccann for benchmarking contributions
- Quantopian Team
(alert us if we've inadvertantly missed listing you here!)
tests/test_risk.py
+114 -115
View File
@@ -96,41 +96,41 @@ class TestRisk(unittest.TestCase):
self.assertEqual([round(x.benchmark_period_returns, 4)
for x in metrics.month_periods],
[0.0255,
0.0004,
0.0110,
0.0057,
-0.0290,
0.0021,
0.0061,
0.0221,
0.0247,
0.0324,
0.0189,
0.0139])
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],
[0.0372,
0.0171,
-0.0128,
-0.0214,
-0.0211,
0.0305,
0.0537,
0.0813,
0.0780,
0.0666])
[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],
[0.015,
-0.0043,
0.0173,
0.0311,
0.0586,
0.1108,
0.1239])
[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],
[0.1407])
[0.1362])
def test_trading_days_06(self):
returns = factory.create_returns_from_range(self.sim_params)
@@ -153,7 +153,7 @@ class TestRisk(unittest.TestCase):
0.047,
0.039,
0.022,
0.022,
0.023,
0.021,
0.025,
0.019])
@@ -161,7 +161,7 @@ class TestRisk(unittest.TestCase):
self.assertEqual([round(x.benchmark_volatility, 3)
for x in metrics.three_month_periods],
[0.047,
0.043,
0.042,
0.050,
0.064,
0.070,
@@ -177,7 +177,7 @@ class TestRisk(unittest.TestCase):
0.082,
0.081,
0.081,
0.08,
0.080,
0.074,
0.061])
@@ -360,39 +360,39 @@ class TestRisk(unittest.TestCase):
[0.131,
-0.11,
-0.067,
0.144,
0.298,
-0.391,
0.106,
-0.034,
0.136,
0.301,
-0.387,
0.107,
-0.032,
-0.058,
0.068,
0.09,
-0.125])
0.069,
0.095,
-0.123])
self.assertEqual([round(x.information, 3)
for x in self.metrics_06.three_month_periods],
[-0.013,
-0.006,
0.113,
-0.012,
-0.02,
-0.11,
0.01,
-0.005,
0.03,
0.009])
-0.009,
0.111,
-0.014,
-0.017,
-0.108,
0.011,
-0.004,
0.032,
0.011])
self.assertEqual([round(x.information, 3)
for x in self.metrics_06.six_month_periods],
[-0.013,
-0.013,
-0.014,
-0.003,
-0.002,
-0.013,
-0.042,
0.009])
-0.011,
-0.041,
0.011])
self.assertEqual([round(x.information, 3)
for x in self.metrics_06.year_periods],
[-0.002])
[-0.001])
def dtest_algorithm_beta_06(self):
self.assertEqual([round(x.beta, 3)
@@ -578,49 +578,47 @@ class TestRisk(unittest.TestCase):
returns = factory.create_returns_from_range(self.sim_params08)
metrics = risk.RiskReport(returns, self.sim_params08)
monthly = [round(x.benchmark_period_returns, 3)
for x in metrics.month_periods]
self.assertEqual(monthly,
[-0.051,
-0.039,
0.001,
0.043,
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,
-0.007,
0.026,
-0.093,
-0.160,
-0.072,
0.009])
0.008])
self.assertEqual([round(x.benchmark_period_returns, 3)
for x in metrics.three_month_periods],
[-0.087,
0.003,
0.055,
-0.026,
-0.072,
-0.058,
-0.075,
-0.218,
-0.293,
-0.214])
[-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],
[-0.110,
-0.069,
-0.006,
-0.099,
-0.274,
-0.334,
-0.273])
[-0.128,
-0.081,
-0.036,
-0.118,
-0.301,
-0.36,
-0.294])
self.assertEqual([round(x.benchmark_period_returns, 3)
for x in metrics.year_periods],
[-0.353])
[-0.385])
def test_trading_days_08(self):
returns = factory.create_returns_from_range(self.sim_params08)
@@ -634,49 +632,50 @@ class TestRisk(unittest.TestCase):
def test_benchmark_volatility_08(self):
returns = factory.create_returns_from_range(self.sim_params08)
metrics = risk.RiskReport(returns, self.sim_params08)
self.assertEqual([round(x.benchmark_volatility, 3)
for x in metrics.month_periods],
[0.069,
0.056,
0.080,
0.049,
0.040,
0.052,
[0.07,
0.058,
0.082,
0.054,
0.041,
0.057,
0.068,
0.055,
0.150,
0.230,
0.188,
0.137])
0.06,
0.157,
0.244,
0.195,
0.145])
self.assertEqual([round(x.benchmark_volatility, 3)
for x in metrics.three_month_periods],
[0.118,
0.108,
0.101,
0.083,
0.094,
0.102,
0.172,
0.277,
0.328,
0.323])
[0.12,
0.113,
0.105,
0.09,
0.098,
0.107,
0.179,
0.293,
0.344,
0.34])
self.assertEqual([round(x.benchmark_volatility, 3)
for x in metrics.six_month_periods],
[0.144,
0.143,
0.143,
0.190,
0.292,
0.342,
0.364])
[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],
[0.391])
[0.411])
def test_treasury_returns_06(self):
returns = factory.create_returns_from_range(self.sim_params)
zipline/data/benchmarks.py
+14 -6
View File
@@ -104,19 +104,27 @@ def get_benchmark_data(symbol, start_date=None, end_date=None):
def get_benchmark_returns(symbol, start_date=None, end_date=None):
"""
Returns a list of return percentages in chronological order.
"""
if start_date is None:
start_date = datetime(year=1950, month=1, day=3)
if end_date is None:
end_date = datetime.utcnow()
benchmark_returns = []
# Get the benchmark data and convert it to a list in chronological order.
data_points = list(get_benchmark_data(symbol, start_date, end_date))
data_points.reverse()
for data_point in get_benchmark_data(symbol, start_date, end_date):
returns = (data_point['close'] - data_point['open']) / \
data_point['open']
# Calculate the return percentages.
benchmark_returns = []
for i, data_point in enumerate(data_points):
if i == 0:
returns = 0
else:
prev_close = data_points[i-1]['close']
returns = (data_point['close'] - prev_close) / prev_close
daily_return = DailyReturn(date=data_point['date'], returns=returns)
benchmark_returns.append(daily_return)
# Reverse data so we can load it in reverse chron order.
benchmark_returns.reverse()
return benchmark_returns