Department of Economics and Business Economics

Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model

Research output: ResearchWorking paper

Documents

  • rp17_28

    Final published version, 839 KB, PDF-document

  • Annestiina Silvennoinen
    Annestiina SilvennoinenQueensland University of TechnologyAustralia
  • Timo Terasvirta
A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations are deterministically time-varying. Parameters of the model are estimated jointly using maximum likelihood. Consistency and asymptotic normality of maximum likelihood estimators is proved. Numerical aspects of the estimation algorithm are discussed. A bivariate empirical example is provided.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages46
StatePublished - 4 Sep 2017
SeriesCREATES Research Papers
Number2017-28

See relations at Aarhus University Citationformats

Download statistics

No data available

ID: 116687516