Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations.

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large n...

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Detalles Bibliográficos
Publicado en:Journal of Financial Econometrics Vol. 5; no. 3; pp. 390 - 456
Autores principales: Hurn, A. S., Jeisman, J. I., Lindsay, K. A.
Formato: Artículo
Publicado: Oxford University Press / UK Summer 2007
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox-Ingersoll-Ross and Ornstein-Uhlenbeck equations respectively. Reprinted by permission of the publisher.