Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/162281 
Year of Publication: 
2017
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 17-015/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
The purpose of the paper is to show that univariate GARCH is not a special case of multivariate GARCH, specifically the Full BEKK model, except under parametric restrictions on the off-diagonal elements of the random coefficient autoregressive coefficient matrix, provides the regularity conditions that arise from the underlying random coefficient autoregressive process, and for which the (quasi-) maximum likelihood estimates have valid asymptotic properties under the appropriate parametric restrictions. The paper provides a discussion of the stochastic processes, regularity conditions, and asymptotic properties of univariate and multivariate GARCH models. It is shown that the Full BEKK model, which in practice is estimated almost exclusively, has no underlying stochastic process, regularity conditions, or asymptotic properties.
Subjects: 
Random coefficient stochastic process
Off-diagonal parametric restrictions
Diagonal and Full BEKK
Regularity conditions
Asymptotic properties
Conditional volatility
Univariate and multivariate models.
JEL: 
C22
C32
C52
C58
Document Type: 
Working Paper

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