Markov Switching Garch Models: Higher Order Moments, Kurtosis Measures, and Volatility Evaluation in Recessions and Pandemic
Maddalena Cavicchioli
Journal of Business & Economic Statistics, 2022, vol. 40, issue 4, 1772-1783
Abstract:
In this article, we derive neat matrix formulas in closed form for computing higher order moments and kurtosis of univariate Markov switching GARCH models. Then we provide asymptotic theory for sample estimators of higher order moments and kurtosis which can be used for testing normality. We also check our theory statements numerically via Monte Carlo simulations. Finally, we take advantage of our theoretical results to recognize different periods of high volatility stressing the stock markets, such as financial crisis and pandemic.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2021.1974459 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:40:y:2022:i:4:p:1772-1783
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20
DOI: 10.1080/07350015.2021.1974459
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan
More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().