A Refinement to Ait-Sahalia's (2002) "Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-Form Approximation Approach"

Gurdip Bakshi and Nengjiu Ju
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Gurdip Bakshi: Smith School of Business, University of Maryland
Nengjiu Ju: School of Business and Management, Hong Kong University of Science and Technology

The Journal of Business, 2005, vol. 78, issue 5, 2037-2052

Abstract: This paper provides a closed-form density approximation when the underlying state variable is a one-dimensional diffusion. Building on Aït-Sahalia (2002), we show that our refinement is applicable under a wide class of drift and diffusion functions. In addition, it facilitates the maximum likelihood estimation of discretely sampled diffusion models of short interest-rate or stock volatility with unknown conditional densities. Our interest-rate examples demonstrate that the analytical approximation is sufficiently accurate.

Date: 2005
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:ucp:jnlbus:v:78:y:2005:i:5:p:2037-2036

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