Shifts in Individual Parameters of a GARCH Model Articles uri icon

publication date

  • January 2010

start page

  • 122

end page

  • 153

issue

  • 1

volume

  • 8

international standard serial number (ISSN)

  • 1479-8409

electronic international standard serial number (EISSN)

  • 1479-8417

abstract

  • Most asset return series, especially those in high frequency, show high excess kurtosis and persistence in volatility that cannot be adequately described by the generalized conditional heteroscedastic (GARCH) model,
    even with heavy-tailed innovations. Many researchers have argued that
    these characteristics are due to shifts in volatility that may be
    associated with significant economic events such as financial crises.
    Indeed, several authors have investigated the case of pure structural
    changes, in which all of the parameters in the GARCH model are assumed
    to change simultaneously. In this paper, we take an alternative approach
    by studying the case in which changes occur in individual parameters of
    a GARCH model. We investigate the impacts of such changes on the
    underlying return series and its volatility, and propose an iterative
    procedure to detect them. In all cases, the changes affect permanently
    the level of the volatility, but in some cases, the changes also alter
    the dynamic structure of the volatility series. Monte Carlo experiments
    are used to investigate the performance of the proposed procedure in
    finite samples, and real examples are used to demonstrate the impacts of
    detected volatility changes and the efficacy of the proposed procedure.
    Practical implications of the parameter changes in financial
    applications are also discussed.