Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/10147
Title: Likelihood ratio gradient estimation for Meixner distribution and Lévy processes
Authors: Kawai, Reiichiro
First Published: 5-Nov-2011
Publisher: Springer-Verlag
Citation: Computational Statistics, 2012 (in press)
Abstract: We address the problem of gradient estimation with respect to four characterizing parameters of the Meixner distribution and Lévy process. With the help of the explicit marginal probability density function, the likelihood ratio method is directly applicable, while unbiased estimators may contain infinite random series in their score function. We quantify the estimator bias arising when the infinite series is truncated to finite term. We further propose a substantially simple exact simulation method for the Meixner distribution, based on acceptance-rejection sampling and the Esscher density transform. Numerical results are presented in the context of financial Greeks to illustrate the effectiveness of our formulas along with bias estimates.
DOI Link: 10.1007/s00180-011-0288-7
ISSN: 0943-4062
eISSN: 1613-9658
Links: http://www.springer.com/statistics/journal/180
http://hdl.handle.net/2381/10147
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: © Springer-Verlag 2011. Deposited with reference to the journsl's archiving policy available on the journal's website and on the Sherpa/RoMEO website.
Description: The original publication is available at www.springerlink.com
Appears in Collections:Published Articles, Dept. of Mathematics

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