def test_stationary(seed, method, axis, trend, n_samples):
coint = CointAnalysis(method=method, axis=axis, trend=trend)
x0 = make_stationary(seed=seed, n_samples=n_samples, n_series=1)
x1 = make_nonstationary(seed=seed, n_samples=n_samples, n_series=1)
X = np.concatenate([x0, x1], axis=1)
assert coint.test(X).pvalue_ is np.nan
def test_fit(seed, method, axis, trend, n_samples, gamma):
coint = CointAnalysis(method=method, axis=axis, trend=trend)
X = make_cointegrated(seed=seed, n_samples=n_samples, gamma=gamma)
coint.fit(X)
assert np.isclose(-coint.coef_[0] / coint.coef_[1], gamma, rtol=1e-1)
assert np.isclose(coint.mean_, 0, atol=abs(coint.coef_[1] * 1e-1))
assert np.isclose(coint.std_, np.abs(coint.coef_[1]), rtol=1e-1)
def test_transform(seed, method, axis, trend, n_samples, gamma, adjust):
coint = CointAnalysis(method=method, axis=axis, trend=trend)
X = make_cointegrated(seed=seed, n_samples=n_samples, gamma=gamma)
spread = coint.fit_transform(X)
if adjust:
assert np.isclose(spread.mean(), 0.0, atol=1e-1)
assert np.isclose(spread.std(), 1.0, atol=1e-1)
else:
assert np.isclose(spread.mean(), coint.mean_, atol=1e-1)
assert np.isclose(spread.std(), coint.std_, atol=1e-1)
def main():
hyg = fetch_etf('HYG')
bkln = fetch_etf('BKLN')
X = np.array([hyg, bkln]).T
coint = CointAnalysis()
# pvalue
pvalue = coint.test(X).pvalue_
print(f'pvalue: {pvalue}')
# fit, transform
spread = pd.Series(coint.fit_transform(X), index=hyg.index)
print(f'coef: {coint.coef_}')
print(f'mean: {coint.mean_}')
print(f'std: {coint.std_}')
# plot
plot_prices(hyg, bkln)
plot_adjust(hyg, bkln, coint)
plot_spread(spread)
def test_coint_test():
X = np.random.randn(100, 2)
with pytest.raises(ValueError):
coint = CointAnalysis(method='hoge')
coint.test(X)
with pytest.raises(ValueError):
coint = CointAnalysis(axis=2)
coint.test(X)
with pytest.raises(ValueError):
coint = CointAnalysis(trend='ct')
coint.test(X)
def test_coint_fit():
X = np.random.randn(100, 2)
with pytest.raises(ValueError):
coint = CointAnalysis(method="hoge")
coint.fit(X)
with pytest.raises(ValueError):
coint = CointAnalysis(axis=2)
coint.fit(X)
with pytest.raises(ValueError):
coint = CointAnalysis(trend="ct")
coint.fit(X)
def test_notcointegrated(seed, method, axis, trend, gamma, n_samples):
coint = CointAnalysis(method=method, axis=axis, trend=trend)
X = make_notcointegrated(seed=seed, n_samples=n_samples, gamma=gamma)
assert coint.test(X).pvalue_ > 0.1