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On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations*
Author(s) -
Hurn A. S.,
Lindsay K. A.,
Martin V. L.
Publication year - 2003
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00292
Subject(s) - mathematics , stochastic differential equation , maximum likelihood , inference , likelihood function , maximum likelihood sequence estimation , markov chain , statistics , mathematical optimization , computer science , artificial intelligence
. 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.