def test_representation(self):
test_period = RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=self.algo_returns,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
treasury_curves=self.env.treasury_curves,
)
metrics = [
"algorithm_period_returns",
"benchmark_period_returns",
"excess_return",
"num_trading_days",
"benchmark_volatility",
"algorithm_volatility",
"sharpe",
"sortino",
"information",
"beta",
"alpha",
"max_drawdown",
"max_leverage",
"algorithm_returns",
"benchmark_returns",
]
representation = test_period.__repr__()
assert all([metric in representation for metric in metrics])
def test_representation(self):
test_period = RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=self.algo_returns,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
treasury_curves=self.env.treasury_curves,
)
metrics = [
"algorithm_period_returns",
"benchmark_period_returns",
"excess_return",
"num_trading_days",
"benchmark_volatility",
"algorithm_volatility",
"sharpe",
"sortino",
"information",
"beta",
"alpha",
"max_drawdown",
"max_leverage",
"algorithm_returns",
"benchmark_returns",
]
representation = test_period.__repr__()
assert all([metric in representation for metric in metrics])
def test_algorithm_leverages(self):
# Max leverage for an algorithm with 'None' as leverage is 0.
np.testing.assert_equal(
[x.max_leverage for x in self.metrics.month_periods],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])
np.testing.assert_equal(
[x.max_leverage for x in self.metrics.three_month_periods],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])
np.testing.assert_equal(
[x.max_leverage for x in self.metrics.six_month_periods],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])
np.testing.assert_equal(
[x.max_leverage for x in self.metrics.year_periods],
[0.0])
test_period = RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=self.algo_returns,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
algorithm_leverages=[.01, .02, .03],
)
# This return period has a list instead of None for algorithm_leverages
# Confirm that max_leverage is set to the max of those values
assert test_period.max_leverage == .03
def test_sharpe_value_when_null(self):
# Sharpe is displayed as '0.0' instead of np.nan
null_returns = factory.create_returns_from_list([0.0] * 251,
self.sim_params)
test_period = RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=null_returns,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
treasury_curves=self.env.treasury_curves,
)
assert test_period.sharpe == 0.0
def test_returns_beyond_treasury(self):
# The last treasury value is used when return dates go beyond
# treasury curve data
treasury_curves = self.env.treasury_curves
treasury = treasury_curves[treasury_curves.index < self.start_session]
test_period = RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=self.algo_returns,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
treasury_curves=treasury,
algorithm_leverages=[.01, .02, .03])
assert test_period.treasury_curves.equals(treasury[-1:])
# This return period has a list instead of None for algorithm_leverages
# Confirm that max_leverage is set to the max of those values
assert test_period.max_leverage == .03
def test_index_mismatch_exception(self):
# An exception is raised when returns and benchmark returns
# have indexes that do not match
bench_params = SimulationParameters(
start_session=pd.Timestamp("2006-02-01", tz='UTC'),
end_session=pd.Timestamp("2006-02-28", tz='UTC'),
trading_calendar=self.trading_calendar,
)
benchmark = factory.create_returns_from_list([BENCHMARK_BASE] * 19,
bench_params)
with np.testing.assert_raises(Exception):
RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=self.algo_returns,
benchmark_returns=benchmark,
trading_calendar=self.trading_calendar,
treasury_curves=self.env.treasury_curves,
)