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Maximum likelihood estimation of latent affine processes

Author: David S Bates; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, ©2003.
Series: Working paper series (National Bureau of Economic Research), no. 9673.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Abstract: 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  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: David S Bates; National Bureau of Economic Research.
OCLC Number: 52915402
Notes: "May 2003."
Description: 1 online resource (28, [8] pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 9673.
Responsibility: David S. Bates.

Abstract:

Abstract: 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.

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