Data generation

bekk.generate_data.simulate_bekk(param, nobs=1000, distr='normal', degf=10, lam=0)

Simulate data.

Parameters:

param : BEKKParams instance

Attributes of this class hold parameter matrices

nobs : int

Number of observations to generate. Time series length

distr : str

Name of the distribution from which to generate innovations.

Must be

• ‘normal’
• ‘student’
• ‘skewt’

degf : int

Degrees of freedom for Student or SkewStudent distributions

lam : float

Skewness parameter for Student or SkewStudent distributions. Must be between (-1, 1)

Returns:

innov : (nobs, nstocks) array

Multivariate innovation matrix

bekk.generate_data.download_data(tickers=None, nobs=None, start='2002-01-01', end='2015-12-31')

Download stock market data and save it to disk.

Parameters:

tickers : list of str

Tickers to download

nobs : int

Number of observations in the time series

start : str

First observation date

end : str

Last observation date

Returns:

ret : DataFrame

Demeaned returns