TY  - JOUR
AU  - Bates,David S.
TI  - Maximum Likelihood Estimation of Latent Affine Processes
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 9673
PY  - 2003
Y2  - May 2003
UR  - http://www.nber.org/papers/w9673
L1  - http://www.nber.org/papers/w9673.pdf
N1  - Author contact info:
David S. Bates
Henry B. Tippie College of Business
Department of Finance
University of Iowa
Iowa City, IA 52242-1000
Tel: 319/353-2288
Fax: 319/335-3690
E-Mail: david-bates@uiowa.edu
AB  - 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.
ER  -