def test_trading_environment(self):
benchmark_returns, treasury_curves = \
factory.load_market_data()
env = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=datetime(2008, 1, 1, tzinfo=pytz.utc),
period_end=datetime(2008, 12, 31, tzinfo=pytz.utc),
capital_base=100000,
)
#holidays taken from: http://www.nyse.com/press/1191407641943.html
new_years = datetime(2008, 1, 1, tzinfo=pytz.utc)
mlk_day = datetime(2008, 1, 21, tzinfo=pytz.utc)
presidents = datetime(2008, 2, 18, tzinfo=pytz.utc)
good_friday = datetime(2008, 3, 21, tzinfo=pytz.utc)
memorial_day = datetime(2008, 5, 26, tzinfo=pytz.utc)
july_4th = datetime(2008, 7, 4, tzinfo=pytz.utc)
labor_day = datetime(2008, 9, 1, tzinfo=pytz.utc)
tgiving = datetime(2008, 11, 27, tzinfo=pytz.utc)
christmas = datetime(2008, 5, 25, tzinfo=pytz.utc)
a_saturday = datetime(2008, 8, 2, tzinfo=pytz.utc)
a_sunday = datetime(2008, 10, 12, tzinfo=pytz.utc)
holidays = [
new_years,
mlk_day,
presidents,
good_friday,
memorial_day,
july_4th,
labor_day,
tgiving,
christmas,
a_saturday,
a_sunday
]
for holiday in holidays:
self.assertTrue(not env.is_trading_day(holiday))
first_trading_day = datetime(2008, 1, 2, tzinfo=pytz.utc)
last_trading_day = datetime(2008, 12, 31, tzinfo=pytz.utc)
workdays = [first_trading_day, last_trading_day]
for workday in workdays:
self.assertTrue(env.is_trading_day(workday))
self.assertTrue(env.last_close.month == 12)
self.assertTrue(env.last_close.day == 31)
def test_trading_environment(self):
benchmark_returns, treasury_curves = \
factory.load_market_data()
env = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=datetime(2008, 1, 1, tzinfo=pytz.utc),
period_end=datetime(2008, 12, 31, tzinfo=pytz.utc),
capital_base=100000,
)
#holidays taken from: http://www.nyse.com/press/1191407641943.html
new_years = datetime(2008, 1, 1, tzinfo=pytz.utc)
mlk_day = datetime(2008, 1, 21, tzinfo=pytz.utc)
presidents = datetime(2008, 2, 18, tzinfo=pytz.utc)
good_friday = datetime(2008, 3, 21, tzinfo=pytz.utc)
memorial_day = datetime(2008, 5, 26, tzinfo=pytz.utc)
july_4th = datetime(2008, 7, 4, tzinfo=pytz.utc)
labor_day = datetime(2008, 9, 1, tzinfo=pytz.utc)
tgiving = datetime(2008, 11, 27, tzinfo=pytz.utc)
christmas = datetime(2008, 5, 25, tzinfo=pytz.utc)
a_saturday = datetime(2008, 8, 2, tzinfo=pytz.utc)
a_sunday = datetime(2008, 10, 12, tzinfo=pytz.utc)
holidays = [
new_years, mlk_day, presidents, good_friday, memorial_day,
july_4th, labor_day, tgiving, christmas, a_saturday, a_sunday
]
for holiday in holidays:
self.assertTrue(not env.is_trading_day(holiday))
first_trading_day = datetime(2008, 1, 2, tzinfo=pytz.utc)
last_trading_day = datetime(2008, 12, 31, tzinfo=pytz.utc)
workdays = [first_trading_day, last_trading_day]
for workday in workdays:
self.assertTrue(env.is_trading_day(workday))
self.assertTrue(env.last_close.month == 12)
self.assertTrue(env.last_close.day == 31)
class RiskCompareIterativeToBatch(unittest.TestCase):
"""
Assert that RiskMetricsIterative and RiskMetricsBatch
behave in the same way.
"""
def setUp(self):
self.start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
self.end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=self.start_date,
period_end=self.end_date,
capital_base=1000.0
)
self.oneday = datetime.timedelta(days=1)
def test_risk_metrics_returns(self):
risk_metrics_refactor = risk.RiskMetricsIterative(
self.start_date, self.trading_env)
todays_date = self.start_date
cur_returns = []
for i, ret in enumerate(RETURNS):
todays_return_obj = risk.DailyReturn(
todays_date,
ret
)
cur_returns.append(todays_return_obj)
# Move forward day counter to next trading day
todays_date += self.oneday
while not self.trading_env.is_trading_day(todays_date):
todays_date += self.oneday
try:
risk_metrics_original = risk.RiskMetricsBatch(
start_date=self.start_date,
end_date=todays_date,
returns=cur_returns,
trading_environment=self.trading_env
)
except Exception as e:
#assert that when original raises exception, same
#exception is raised by risk_metrics_refactor
np.testing.assert_raises(
type(e), risk_metrics_refactor.update, todays_date, ret)
continue
risk_metrics_refactor.update(todays_date, ret)
self.assertEqual(
risk_metrics_original.start_date,
risk_metrics_refactor.start_date)
self.assertEqual(
risk_metrics_original.end_date,
risk_metrics_refactor.end_date)
self.assertEqual(
risk_metrics_original.treasury_duration,
risk_metrics_refactor.treasury_duration)
self.assertEqual(
risk_metrics_original.treasury_curve,
risk_metrics_refactor.treasury_curve)
self.assertEqual(
risk_metrics_original.treasury_period_return,
risk_metrics_refactor.treasury_period_return)
self.assertEqual(
risk_metrics_original.benchmark_returns,
risk_metrics_refactor.benchmark_returns)
self.assertEqual(
risk_metrics_original.algorithm_returns,
risk_metrics_refactor.algorithm_returns)
risk_original_dict = risk_metrics_original.to_dict()
risk_refactor_dict = risk_metrics_refactor.to_dict()
self.assertEqual(set(risk_original_dict.keys()),
set(risk_refactor_dict.keys()))
err_msg_format = """\
"In update step {iter}: {measure} should be {truth} but is {returned}!"""
for measure in risk_original_dict.iterkeys():
if measure == 'max_drawdown':
np.testing.assert_almost_equal(
risk_refactor_dict[measure],
risk_original_dict[measure],
err_msg=err_msg_format.format(
iter=i,
measure=measure,
truth=risk_original_dict[measure],
returned=risk_refactor_dict[measure]))
else:
np.testing.assert_equal(
risk_original_dict[measure],
risk_refactor_dict[measure],
err_msg_format.format(
iter=i,
measure=measure,
truth=risk_original_dict[measure],
returned=risk_refactor_dict[measure])
)
class RiskCompareIterativeToBatch(unittest.TestCase):
"""
Assert that RiskMetricsIterative and RiskMetricsBatch
behave in the same way.
"""
def setUp(self):
self.start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
self.end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=self.start_date,
period_end=self.end_date,
capital_base=1000.0
)
self.oneday = datetime.timedelta(days=1)
def test_risk_metrics_returns(self):
risk_metrics_refactor = risk.RiskMetricsIterative(
self.start_date, self.trading_env)
todays_date = self.start_date
cur_returns = []
for i, ret in enumerate(RETURNS):
todays_return_obj = risk.DailyReturn(
todays_date,
ret
)
cur_returns.append(todays_return_obj)
# Move forward day counter to next trading day
todays_date += self.oneday
while not self.trading_env.is_trading_day(todays_date):
todays_date += self.oneday
try:
risk_metrics_original = risk.RiskMetricsBatch(
start_date=self.start_date,
end_date=todays_date,
returns=cur_returns,
trading_environment=self.trading_env
)
except Exception as e:
#assert that when original raises exception, same
#exception is raised by risk_metrics_refactor
np.testing.assert_raises(
type(e), risk_metrics_refactor.update, ret)
continue
risk_metrics_refactor.update(ret)
self.assertEqual(
risk_metrics_original.start_date,
risk_metrics_refactor.start_date)
self.assertEqual(
risk_metrics_original.end_date,
risk_metrics_refactor.end_date)
self.assertEqual(
risk_metrics_original.treasury_duration,
risk_metrics_refactor.treasury_duration)
self.assertEqual(
risk_metrics_original.treasury_curve,
risk_metrics_refactor.treasury_curve)
self.assertEqual(
risk_metrics_original.treasury_period_return,
risk_metrics_refactor.treasury_period_return)
self.assertEqual(
risk_metrics_original.benchmark_returns,
risk_metrics_refactor.benchmark_returns)
self.assertEqual(
risk_metrics_original.algorithm_returns,
risk_metrics_refactor.algorithm_returns)
risk_original_dict = risk_metrics_original.to_dict()
risk_refactor_dict = risk_metrics_refactor.to_dict()
self.assertEqual(set(risk_original_dict.keys()),
set(risk_refactor_dict.keys()))
err_msg_format = """\
"In update step {iter}: {measure} should be {truth} but is {returned}!"""
for measure in risk_original_dict.iterkeys():
if measure == 'max_drawdown':
np.testing.assert_almost_equal(
risk_refactor_dict[measure],
risk_original_dict[measure],
err_msg=err_msg_format.format(
iter=i,
measure=measure,
truth=risk_original_dict[measure],
returned=risk_refactor_dict[measure]))
else:
np.testing.assert_equal(
risk_original_dict[measure],
risk_refactor_dict[measure],
err_msg_format.format(
iter=i,
measure=measure,
truth=risk_original_dict[measure],
returned=risk_refactor_dict[measure])
)
