Analytical quasi maximum likelihood inference in multivariate volatility models

Christian Hafner and H. Herwartz

No EI 2003-21, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: Quasi maximum likelihood estimation and inference in multivariate volatility models remains a challenging computational task if, for example, the dimension is high. One of the reasons is that typically numerical procedures are used to compute the score and the Hessian, and often they are numerically unstable. We provide analytical formulae for the score and the Hessian and show in a simulation study that they clearly outperform numerical methods. As an example, we use the popular BEKK-GARCH model, for which we derive first and second order derivatives.

Keywords: multivariate GARCH models; quasi maximum likelihood (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Date: 2003-08-06
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Citations: View citations in EconPapers (7)

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Journal Article: Analytical quasi maximum likelihood inference in multivariate volatility models (2008)
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