Skip Navigation



RFS Advance Access published online on February 17, 2006
Review of Financial Studies, doi:10.1093/rfs/hhj022
This Article
Right arrow Full Text (Accepted Manuscript)
Right arrow All Versions of this Article:
19/3/909    most recent
hhj022v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Bates, D. S.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 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

Article

Maximum Likelihood Estimation of Latent Affine Processes

David S. Bates 1 *
1 University of Iowa and the National Bureau of Economic Research, Iowa City, IA

* To whom correspondence should be addressed.
David S. Bates, E-mail: david-bates{at}uiowa.edu


  Abstract

This article develops a direct filtration-based maximum likelihood methodology for estimating the parameters and realizations of latent affine processes. Filtration is conducted in the transform space of characteristic functions, using a version of Bayes’ rule for recursively updating the joint characteristic function of latent variables and the data conditional upon past data. An application to daily stock market returns over 1953-96 reveals substantial divergences from EMM-based estimates; in particular, more substantial and time-varying jump risk. The implications for pricing stock index options are examined.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 REV FINANC STUDHome page
N. Garleanu, L. H. Pedersen, and A. M. Poteshman
Demand-Based Option Pricing
Rev. Financ. Stud., October 1, 2009; 22(10): 4259 - 4299.
[Abstract] [Full Text] [PDF]

Home page
 REV FINANC STUDHome page
M. S. Johannes, N. G. Polson, and J. R. Stroud
Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices
Rev. Financ. Stud., July 1, 2009; 22(7): 2759 - 2799.
[Abstract] [Full Text] [PDF]

Home page
 REV FINANC STUDHome page
S. Thompson
Identifying Term Structure Volatility from the LIBOR-Swap Curve
Rev. Financ. Stud., April 1, 2008; 21(2): 819 - 854.
[Abstract] [Full Text] [PDF]

Home page
 JOURNAL OF FINANCIAL ECONOMETRICSHome page
M. R. Fengler, W. K. Hardle, and E. Mammen
A semiparametric factor model for implied volatility surface dynamics
J. Financial Econometrics, April 1, 2007; 5(2): 189 - 218.
[Abstract] [Full Text] [PDF]

Home page
 JOURNAL OF FINANCIAL ECONOMETRICSHome page
G. J. Jiang and R. C. A. Oomen
Estimating Latent Variables and Jump Diffusion Models Using High-Frequency Data
J. Financial Econometrics, January 1, 2007; 5(1): 1 - 30.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.