Cover Image

Testing for an omitted multiplicative long-term component in GARCH models

We consider the problem of testing for an omitted multiplicative long-term component in GARCH-type models. Under the alternative, there is a two-component model with a short-term GARCH component that fluctuates around a smoothly time-varying long-term component which is driven by the dynamics of an...

Full description

Saved in:
Bibliographic Details
Main Authors: Conrad, Christian (Author) , Schienle, Melanie (Author)
Format: Article (Journal)
Language:English
Published: 2020
In: Journal of business & economic statistics
Year: 2020, Volume: 38, Issue: 2, Pages: 229-242
ISSN:1537-2707
DOI:10.1080/07350015.2018.1482759
Subjects:
Aufsatz in Zeitschrift
Online Access:Verlag, lizenzpflichtig: https://www.tandfonline.com/doi/pdf/10.1080/07350015.2018.1482759
Resolving-System, lizenzpflichtig: https://doi.org/10.1080/07350015.2018.1482759
Verlag, Supplemental, lizenzpflichtig: https://www.tandfonline.com/doi/suppl/10.1080/07350015.2018.1482759
Get full text
Author Notes:Christian Conrad, Melanie Schienle
Description
Summary:We consider the problem of testing for an omitted multiplicative long-term component in GARCH-type models. Under the alternative, there is a two-component model with a short-term GARCH component that fluctuates around a smoothly time-varying long-term component which is driven by the dynamics of an explanatory variable. We suggest a Lagrange multiplier statistic for testing the null hypothesis that the variable has no explanatory power. We derive the asymptotic theory for our test statistic and investigate its finite sample properties by Monte Carlo simulation. Our test also covers the mixed-frequency case in which the returns are observed at a higher frequency than the explanatory variable. The usefulness of our procedure is illustrated by empirical applications to S&P 500 return data. Supplementary materials for this article are available online.
Item Description:Published online: 07 Sep 2018
Gesehen am 17.04.2019
Physical Description:Online Resource
ISSN:1537-2707
DOI:10.1080/07350015.2018.1482759

Similar Items