On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations*

Stan Hurn (), K. A. Lindsay and Vance Lindsay Martin

Journal of Time Series Analysis, 2003, vol. 24, issue 1, pages 45-63

Abstract: A method for estimating the parameters of stochastic differential equations (SDEs) by simulated maximum likelihood is presented. This method is feasible whenever the underlying SDE is a Markov process. Estimates are compared to those generated by indirect inference, discrete and exact maximum likelihood. The technique is illustrated with reference to a one-factor model of the term structure of interest rates using 3-month US Treasury Bill data. Copyright 2003 Blackwell Publishing Ltd.

Date: 2003
View citations in EconPapers

Downloads: (external link)
http://www.blackwell-synergy.com/servlet/useragent ... &year=2003&part=null link to full text (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:bla:jtsera:v:24:y:2003:i:1:p:45-63

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782

Access Statistics for this article

Journal of Time Series Analysis is edited by M.B. Priestley

More articles in Journal of Time Series Analysis from Blackwell Publishing
Series data maintained by Christopher F. Baum ().