A Bayesian Analysis of Return Dynamics with Lévy Jumps

Haitao Li, Martin T. Wells and Cindy L. Yu

The Review of Financial Studies, 2008, vol. 21, issue 5, 2345-2378

Abstract: We have developed Bayesian Markov chain Monte Carlo (MCMC) methods for inferences of continuous-time models with stochastic volatility and infinite-activity Lévy jumps using discretely sampled data. Simulation studies show that (i) our methods provide accurate joint identification of diffusion, stochastic volatility, and Lévy jumps, and (ii) the affine jump-diffusion (AJD) models fail to adequately approximate the behavior of infinite-activity jumps. In particular, the AJD models fail to capture the "infinitely many" small Lévy jumps, which are too big for Brownian motion to model and too small for compound Poisson process to capture. Empirical studies show that infinite-activity Lévy jumps are essential for modeling the S&P 500 index returns. The Author 2006. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (59)

Downloads: (external link)
http://hdl.handle.net/10.1093/rfs/hhl036 (application/pdf)
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:oup:rfinst:v:21:y:2008:i:5:p:2345-2378

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

The Review of Financial Studies is currently edited by Itay Goldstein

More articles in The Review of Financial Studies from Society for Financial Studies Oxford University Press, Journals Department, 2001 Evans Road, Cary, NC 27513 USA.. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().