View the model
Download the model
Given a series of observations, we want to estimate the data generation process with allowing variance to vary over time following a first order generalized autoregressive conditional heteroscedasticity model (i.e. GARCH(p,q), p=1 & q=1) which the error term, et, is assumed to follow Student's-t distribution.