Flexible and Robust GARCH-X Modelling
Extraction functions for 'garchx' objects
Flexible and Robust GARCH-X Modelling
Estimate a GARCH-X model
Asymptotic Coefficient Covariance
Auxiliary functions
Simulate from a GARCH-X model
Difference a vector or a matrix, with special treatment of zoo objects
Lag a vector or a matrix, with special treatment of zoo objects
Refit a model to new data
Random number generation from the multivariate normal distribution
T-tests and Wald-tests under nullity
Flexible and robust estimation and inference of generalised autoregressive conditional heteroscedasticity (GARCH) models with covariates ('X') based on the results by Francq and Thieu (2018) <doi:10.1017/S0266466617000512>. Coefficients can straightforwardly be set to zero by omission, and quasi maximum likelihood methods ensure estimates are generally consistent and inference valid, even when the standardised innovations are non-normal and/or dependent over time, see <https://journal.r-project.org/archive/2021/RJ-2021-057/RJ-2021-057.pdf> for an overview of the package.