The GARCH_modelb.xlsx Model

GARCH Model with Student's-t Error Distribution

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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.

Keywords:

Econometrics | Forecasting | Time Series | Maximum Likelihood | Time Varying Parameters | GARCH | Heteroscedasticity | Volatility Modeling |