mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-28 13:00:23 +08:00
fawce
2c7355a0dc
Global state for the financial simulation environment is accessed through the
zipline.finance.trading module, which now contains a module variable:
environment.
Parameters are passed into an algorithm as a keyword argument, sim_params.
SimulationParameters creates a trading day index for the test period that
can be used to find trading days, calculate distance between trading days,
and other common operations. The sim params index is just selected from the
global state.
================
Details:
- adding delorean to the requirements.
- made index symbol a parameter for loading the benchmark data. changed
messagepack storage to be symbol specific.
- ported risk, performance, algorithm, transforms, batch transforms
and associated tests to use simulation parameters and global environment
- factory and sim factory use global state and sim params
- factory method parameter names now reflect the class expected
1097 lines
33 KiB
Python
1097 lines
33 KiB
Python
#
|
|
# Copyright 2012 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 calendar
|
|
import pytz
|
|
import zipline.finance.risk as risk
|
|
from zipline.utils import factory
|
|
|
|
from zipline.finance.trading import SimulationParameters
|
|
|
|
|
|
class Risk(unittest.TestCase):
|
|
|
|
def setUp(self):
|
|
|
|
start_date = datetime.datetime(
|
|
year=2006,
|
|
month=1,
|
|
day=1,
|
|
hour=0,
|
|
minute=0,
|
|
tzinfo=pytz.utc)
|
|
end_date = datetime.datetime(
|
|
year=2006, month=12, day=31, tzinfo=pytz.utc)
|
|
|
|
self.sim_params = SimulationParameters(
|
|
period_start=start_date,
|
|
period_end=end_date
|
|
)
|
|
|
|
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()
|
|
|
|
self.algo_returns_06 = factory.create_returns_from_list(
|
|
RETURNS,
|
|
self.sim_params
|
|
)
|
|
|
|
self.metrics_06 = risk.RiskReport(
|
|
self.algo_returns_06,
|
|
self.sim_params
|
|
)
|
|
|
|
start_08 = datetime.datetime(
|
|
year=2008,
|
|
month=1,
|
|
day=1,
|
|
hour=0,
|
|
minute=0,
|
|
tzinfo=pytz.utc)
|
|
|
|
end_08 = datetime.datetime(
|
|
year=2008,
|
|
month=12,
|
|
day=31,
|
|
tzinfo=pytz.utc
|
|
)
|
|
self.sim_params08 = SimulationParameters(
|
|
period_start=start_08,
|
|
period_end=end_08
|
|
)
|
|
|
|
def tearDown(self):
|
|
return
|
|
|
|
def test_factory(self):
|
|
returns = [0.1] * 100
|
|
r_objects = factory.create_returns_from_list(returns, self.sim_params)
|
|
self.assertTrue(r_objects[-1].date <=
|
|
datetime.datetime(
|
|
year=2006, month=12, day=31, tzinfo=pytz.utc))
|
|
|
|
def test_drawdown(self):
|
|
returns = factory.create_returns_from_list(
|
|
[1.0, -0.5, 0.8, .17, 1.0, -0.1, -0.45], self.sim_params)
|
|
#200, 100, 180, 210.6, 421.2, 379.8, 208.494
|
|
metrics = risk.RiskMetricsBatch(returns[0].date,
|
|
returns[-1].date,
|
|
returns)
|
|
self.assertEqual(metrics.max_drawdown, 0.505)
|
|
|
|
def test_benchmark_returns_06(self):
|
|
returns = factory.create_returns_from_range(self.sim_params)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
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])
|
|
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])
|
|
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])
|
|
self.assertEqual([round(x.benchmark_period_returns, 4)
|
|
for x in metrics.year_periods],
|
|
[0.1407])
|
|
|
|
def test_trading_days_06(self):
|
|
returns = factory.create_returns_from_range(self.sim_params)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
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):
|
|
returns = factory.create_returns_from_range(self.sim_params)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
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,
|
|
0.022,
|
|
0.021,
|
|
0.025,
|
|
0.019])
|
|
|
|
self.assertEqual([round(x.benchmark_volatility, 3)
|
|
for x in metrics.three_month_periods],
|
|
[0.047,
|
|
0.043,
|
|
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 test_algorithm_sortino_06(self):
|
|
self.assertEqual([round(x.sortino, 3)
|
|
for x in self.metrics_06.month_periods],
|
|
[4.491,
|
|
-2.842,
|
|
-2.052,
|
|
3.898,
|
|
7.023,
|
|
-8.532,
|
|
3.079,
|
|
-0.354,
|
|
-1.125,
|
|
3.009,
|
|
3.277,
|
|
-3.122])
|
|
self.assertEqual([round(x.sortino, 3)
|
|
for x in self.metrics_06.three_month_periods],
|
|
[-0.769,
|
|
-1.043,
|
|
6.677,
|
|
-2.77,
|
|
-3.209,
|
|
-6.769,
|
|
1.253,
|
|
1.085,
|
|
3.659,
|
|
1.674])
|
|
self.assertEqual([round(x.sortino, 3)
|
|
for x in self.metrics_06.six_month_periods],
|
|
[-2.728,
|
|
-3.258,
|
|
-1.84,
|
|
-1.366,
|
|
-1.845,
|
|
-3.415,
|
|
2.238])
|
|
self.assertEqual([round(x.sortino, 3)
|
|
for x in self.metrics_06.year_periods],
|
|
[-0.524])
|
|
|
|
def test_algorithm_information_06(self):
|
|
self.assertEqual([round(x.information, 3)
|
|
for x in self.metrics_06.month_periods],
|
|
[0.131,
|
|
-0.11,
|
|
-0.067,
|
|
0.144,
|
|
0.298,
|
|
-0.391,
|
|
0.106,
|
|
-0.034,
|
|
-0.058,
|
|
0.068,
|
|
0.09,
|
|
-0.125])
|
|
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])
|
|
self.assertEqual([round(x.information, 3)
|
|
for x in self.metrics_06.six_month_periods],
|
|
[-0.013,
|
|
-0.013,
|
|
-0.003,
|
|
-0.002,
|
|
-0.013,
|
|
-0.042,
|
|
0.009])
|
|
self.assertEqual([round(x.information, 3)
|
|
for x in self.metrics_06.year_periods],
|
|
[-0.002])
|
|
|
|
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):
|
|
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,
|
|
0.011,
|
|
-0.075,
|
|
-0.007,
|
|
0.026,
|
|
-0.093,
|
|
-0.160,
|
|
-0.072,
|
|
0.009])
|
|
|
|
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])
|
|
|
|
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])
|
|
|
|
self.assertEqual([round(x.benchmark_period_returns, 3)
|
|
for x in metrics.year_periods],
|
|
[-0.353])
|
|
|
|
def test_trading_days_08(self):
|
|
returns = factory.create_returns_from_range(self.sim_params08)
|
|
metrics = risk.RiskReport(returns, self.sim_params08)
|
|
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):
|
|
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,
|
|
0.068,
|
|
0.055,
|
|
0.150,
|
|
0.230,
|
|
0.188,
|
|
0.137])
|
|
|
|
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])
|
|
|
|
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])
|
|
# 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])
|
|
|
|
def test_treasury_returns_06(self):
|
|
returns = factory.create_returns_from_range(self.sim_params)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
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,
|
|
0.004])
|
|
|
|
self.assertEqual([round(x.treasury_period_return, 4)
|
|
for x in metrics.three_month_periods],
|
|
[0.0114,
|
|
0.0116,
|
|
0.0122,
|
|
0.0125,
|
|
0.0129,
|
|
0.0127,
|
|
0.0123,
|
|
0.0128,
|
|
0.0125,
|
|
0.0127])
|
|
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,
|
|
0.0257])
|
|
|
|
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 = datetime.datetime(
|
|
year=1991,
|
|
month=1,
|
|
day=1,
|
|
hour=0,
|
|
minute=0,
|
|
tzinfo=pytz.utc)
|
|
|
|
#1992 and 1996 were leap years
|
|
total_days = 365 * 5 + 2
|
|
end = start + datetime.timedelta(days=total_days)
|
|
sim_params90s = SimulationParameters(
|
|
period_start=start,
|
|
period_end=end
|
|
)
|
|
|
|
returns = factory.create_returns(total_days, sim_params90s)
|
|
returns = returns[:-10] # truncate the returns series to end mid-month
|
|
metrics = risk.RiskReport(returns, sim_params90s)
|
|
total_months = 60
|
|
self.check_metrics(metrics, total_months, start)
|
|
|
|
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, self.sim_params08)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
total_months = years * 12
|
|
self.check_metrics(metrics, total_months, start_date)
|
|
|
|
def check_metrics(self, metrics, total_months, start_date):
|
|
"""
|
|
confirm that the right number of riskmetrics were calculated for each
|
|
window length.
|
|
"""
|
|
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
|
|
)
|
|
|
|
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)
|
|
|
|
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,
|
|
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]
|