On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations
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.
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Volume (Year): 24 (2003)
Issue (Month): 1 (January)
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