BEKK – modello GARCH in Stata

What is BEKK GARCH?

The VAR-BEKK-GARCH model, a multivariate GARCH model proposed by Engle and Kroner (1995), estimates the conditional mean function and the conditional volatility function of high-dimensional relationships, which we use to test volatility spillovers between multi-markets.

What is a multivariate GARCH used for?

Multivariate GARCH models have also been used to investigate volatility and correlation trans- mission and spillover effects in studies of contagion, see Tse and Tsui (2002) and Bae, Karolyi, and Stulz (2003).

What is a multivariate GARCH model?

MGARCH stands for multivariate GARCH, or multivariate generalized autoregressive conditional heteroskedasticity. MGARCH allows the conditional-on-past-history covariance matrix of the dependent variables to follow a flexible dynamic structure. Stata fits MGARCH models.

What is a DCC GARCH model?

A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations.

What is dynamic conditional correlation?

class of multivariate models called dynamic conditional correlation models is proposed. These have. the flexibility of univariate GARCH models coupled with parsimonious parametric models for the. correlations. They are not linear but can often be estimated very simply with univariate or two-step.