Risk Premia and Lévy Jumps: Theory and Evidence*
Hasan Fallahgoul,
Julien Hugonnier and
Loriano Mancini
Journal of Financial Econometrics, 2023, vol. 21, issue 3, 810-851
Abstract:
We develop a novel class of time-changed Lévy models, which are tractable and readily applicable, capture the leverage effect, and exhibit pure jump processes with finite or infinite activity. Our models feature four nested processes reflecting market, volatility and jump risks, and observation error of time changes. To operationalize the models, we use volume-based proxies of the unobservable time changes. To estimate risk premia, we derive the change of measure analytically. An extensive time series and option pricing analysis of sixteen time-changed Lévy models shows that infinite activity processes carry significant jump risk premia, and largely outperform many finite activity processes.
Keywords: Lévy jumps; time changes; tempered stable law; time series; option pricing (search for similar items in EconPapers)
JEL-codes: C5 G12 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1093/jjfinec/nbab020 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Risk Premia and Lévy Jumps: Theory and Evidence (2019) 
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:oup:jfinec:v:21:y:2023:i:3:p:810-851.
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani
More articles in Journal of Financial Econometrics from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().