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Nonparametric Estimation of the Short Rate Diffusion Process from a Panel of Yields

Published online by Cambridge University Press:  01 October 2009

Abdoul G. Sam  and
George J. Jiang
Abdoul G. Sam
Affiliation:
Department of Agricultural, Environmental, and Development Economics, Ohio State University, 2120 Fyffe Rd., Columbus, OH 43210. sam.7@cfaes.osu.edu
George J. Jiang
Affiliation:
Eller College of Management, University of Arizona, PO Box 210108, Tucson, AZ 85721. gjiang@email.arizona.edu
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Abstract

In this paper, we propose a nonparametric estimator of the short rate diffusion process using observations of a panel of yields. The proposed estimator can greatly reduce the bias of the nonparametric estimator proposed in Stanton (1997) that uses a single time series of short rate observations. Simulations confirm that the new method significantly attenuates the spurious nonlinearity of the drift function as documented in Chapman and Pearson (2000). We apply the method to estimate the U.S. short rate process using a panel of six Treasury yields. With 42 years’ daily observations of the panel of yields, the proposed drift function estimator achieves the same efficiency as the Stanton (1997) estimator based on 145 years of daily short rate observations. Finally, we show that the proposed estimator also has significant economic implications on the pricing of bonds and interest rate derivatives.

Type
Research Articles
Information
Journal of Financial and Quantitative Analysis , Volume 44 , Issue 5 , October 2009 , pp. 1197 - 1230
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2009

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