Modelling tail risk with tempered stable distributions: an overview
Hasan Fallahgoul () and
Gregoire Loeper ()
Additional contact information
Hasan Fallahgoul: Monash University
Gregoire Loeper: Monash University
Annals of Operations Research, 2021, vol. 299, issue 1, No 50, 1253-1280
Abstract:
Abstract In this study, we investigate the performance of different parametric models with stable and tempered stable distributions for capturing the tail behaviour of log-returns (financial asset returns). First, we define and discuss the properties of stable and tempered stable random variables. We then show how to estimate their parameters and simulate them based on their characteristic functions. Finally, as an illustration, we conduct an empirical analysis to explore the performance of different models representing the distributions of log-returns for the S&P500 and DAX indexes.
Keywords: Lévy process; Stable distribution; Tail risk; Tempered stable distribution (search for similar items in EconPapers)
JEL-codes: C5 G12 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1007/s10479-019-03204-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:annopr:v:299:y:2021:i:1:d:10.1007_s10479-019-03204-3
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1007/s10479-019-03204-3
Access Statistics for this article
Annals of Operations Research is currently edited by Endre Boros
More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().