Bayesian Comparison of GARCH Processes with Asymmetric and Heavy Tailed Conditional Distributions

Mateusz Pipień

Chapter 8 in FindEcon Monograph Series: Advances in Financial Market Analysis, 2007, vol. 3, pp 123-140 from University of Lodz

Abstract: The main goal of this chapter is to define a set of competing GARCH specifications, all with asymmetric conditional distributions, which also allow for heavy tails. As an initial specification we consider GARCH model with conditional Student-t distribution with unknown degrees of freedom parameter, proposed by Bollerslev (1987). By introducing skewness, according to the methods mentioned above and by incorporating the resulting family as a conditional distribution, we generate GARCH models which compete in explaining possible asymmetry of the conditional and unconditional distribution of the financial data. We also consider GARCH process with conditional alfa-Stable distribution, which formally, from the definition, also allows for skewness, see Nolan (1996).

Keywords: Bayesian econometrics; GARCH model; Asymmetric and heavy tailed conditional distributions (search for similar items in EconPapers)
JEL-codes: C01 E02 F00 G00 (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.repec.uni.lodz.pl/RePEc/files/findec/2007/2007_No_3_Ch_8.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to www.repec.uni.lodz.pl:443 (No such host is known. )

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:ann:findec:book:y:2007:n:03:ch:08:mon

Access Statistics for this chapter

More chapters in FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making from University of Lodz Contact information at EDIRC.
Bibliographic data for series maintained by Piotr Wdowiński ().