Parameter Estimation of the Extended Vasiček Model

Autor:	Sanae RUJIVAN
Jazyk:	angličtina
Rok vydání:	2011
Předmět:	The extended Vasiček model transition density maximum likelihood estimation Technology (General) T1-995 Science (General) Q1-390
Zdroj:	Walailak Journal of Science and Technology, Vol 7, Iss 1 (2011)
Druh dokumentu:	article
ISSN:	1686-3933 2228-835X
DOI:	10.2004/wjst.v7i1.54
Popis:	In this paper, an estimate of the drift and diffusion parameters of the extended Vasiček model is presented. The estimate is based on the method of maximum likelihood. We derive a closed-form expansion for the transition (probability) density of the extended Vasiček process and use the expansion to construct an approximate log-likelihood function of a discretely sampled data of the process. Approximate maximum likelihood estimators (AMLEs) of the parameters are obtained by maximizing the approximate log-likelihood function. The convergence of the AMLEs to the true maximum likelihood estimators is obtained by increasing the number of terms in the expansions with a small time step size.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/9c95509f1a964276a1906803ec629f35 Zobrazit plný text záznamu View record in DOAJ