ARCH, GARCH, and Time-Varying Variance

John D. Levendis
Additional contact information
John D. Levendis: Loyola University New Orleans

Chapter Chapter 9 in Time Series Econometrics, 2023, pp 201-262 from Springer

Abstract: Abstract Given that risk (unpredictable ups and downs) and return are fundamental to finance, it is natural that financial econometricians would begin trying to model variance rigorously. Financial markets are notorious for their volatility, with periods of relative stability followed by periods of turbulence. The fact that the variance today depends, in some part, on the variance yesterday implies that variance itself can be modeled as an autoregressive process. The fact that this change can be sudden raises questions of structural change. In this chapter, we take earlier models that focused on the level of a time series, and extend them to model variance.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sptchp:978-3-031-37310-7_9

Ordering information: This item can be ordered from
http://www.springer.com/9783031373107

DOI: 10.1007/978-3-031-37310-7_9

Access Statistics for this chapter

More chapters in Springer Texts in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().