def test_log_return_passthrough():
# addresses #343
df = get_data()
for method in {"mean_historical_return", "ema_historical_return", "capm_return"}:
mu1 = expected_returns.return_model(df, method=method, log_returns=False)
mu2 = expected_returns.return_model(df, method=method, log_returns=True)
try:
pd.testing.assert_series_equal(mu1, mu2)
except AssertionError:
return
assert False
def test_risk_matrix_and_returns_data():
# Test the switcher method for simple calls
df = get_data()
for method in {"mean_historical_return", "ema_historical_return", "capm_return"}:
mu = expected_returns.return_model(df, method=method)
assert isinstance(mu, pd.Series)
assert list(mu.index) == list(df.columns)
assert mu.notnull().all()
assert mu.dtype == "float64"
mu2 = expected_returns.return_model(
expected_returns.returns_from_prices(df), method=method, returns_data=True
)
pd.testing.assert_series_equal(mu, mu2)
def test_return_model_additional_kwargs():
df = get_data()
mkt_prices = get_benchmark_data()
mu1 = expected_returns.return_model(
df, method="capm_return", market_prices=mkt_prices, risk_free_rate=0.03
)
mu2 = expected_returns.capm_return(
df, market_prices=mkt_prices, risk_free_rate=0.03
)
pd.testing.assert_series_equal(mu1, mu2)
def test_return_model_not_implemented():
df = get_data()
with pytest.raises(NotImplementedError):
expected_returns.return_model(df, method="fancy_new!")
