def data():
premia = np.array([.1, .1, .1])
out = generate_data(nportfolio=10,
output='pandas',
alpha=True,
premia=premia)
out['joined'] = concat([out.factors, out.portfolios], 1)
return out
def data():
premia = np.array([0.1, 0.1, 0.1])
out = generate_data(nportfolio=10,
output="pandas",
alpha=True,
premia=premia)
out["joined"] = concat([out.factors, out.portfolios], 1, sort=False)
return out
def data(request):
return generate_data(nportfolio=10, output=request.param)
def test_infeasible(output):
data = generate_data(nfactor=10, nportfolio=20, nobs=10, output=output)
with pytest.raises(ValueError):
LinearFactorModel(data.portfolios, data.factors)
