NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Maximum Likelihood Estimation of Latent Affine Processes

David S. Bates

NBER Working Paper No. 9673
Issued in May 2003
NBER Program(s):   AP

This article develops a direct filtration-based maximum likelihood methodology for estimating the parameters and realizations of latent affine processes. The equivalent of Bayes' rule is derived for recursively updating the joint characteristic function of latent variables and the data conditional upon past data. Likelihood functions can consequently be evaluated directly by Fourier inversion. An application to daily stock returns over 1953-96 reveals substantial divergences from EMM-based estimates: in particular, more substantial and time-varying jump risk.

download in pdf format
   (1046 K)

email paper

This paper is available as PDF (1046 K) or via email.

Machine-readable bibliographic record - MARC, RIS, BibTeX

Document Object Identifier (DOI): 10.3386/w9673

Published: Bates, David S. "Maximum Likelihood Estimation Of Latent Affine Processes," Review of Financial Studies, 2006, v19(3,Fall), 909-965.

Users who downloaded this paper also downloaded these:
Bates w14913 U.S. Stock Market Crash Risk, 1926-2006
Aït-Sahalia and Kimmel w10579 Maximum Likelihood Estimation of Stochastic Volatility Models
 
Publications
Activities
Meetings
Data
People
About

Support
National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138; 617-868-3900; email: info@nber.org

Contact Us