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Journal of Financial Econometrics Advance Access published online on March 1, 2006
Journal of Financial Econometrics, doi:10.1093/jjfinec/nbj007
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© The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
Received September 23, 2004
Revised December 23, 2005
Accepted January 1, 2006

Article

Empirical Comparisons in Short-Term Interest Rate Models Using Nonparametric Methods

Manuel Arapis 1 and Jiti Gao 2 *
     1 University of Western Australia
2 School of Mathematics and Statistics, University of Western Australia, Crawley, WA 6009, Australia

* To whom correspondence should be addressed.
Jiti Gao, E-mail: jiti.gao{at}uwa.edu.au


  Abstract

This study applies the nonparametric estimation procedure to the diffusion process modeling the dynamics of short-term interest rates. This approach allows us to operate in continuous time, estimating the continuous-time model, despite the use of discrete data. Three methods are proposed. We apply these methods to two important financial data. After selecting an appropriate bandwidth for each dataset, empirical comparisons indicate that the specification of the drift has a considerable impact on the pricing of derivatives through its effect on the diffusion function. In addition, a novel nonparametric test has been proposed for specification of linearity in the drift. Our simulation directs us to reject the null hypothesis of linearity at the 5% significance level for the two financial datasets.

Keywords: diffusion process, drift function, kernel density estimation, stochastic volatility.
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