Barkoulas, John and Baum, Christopher F. and Chakraborty, Atreya (2003) Nearest-neighbor forecast of U.S. interest rates. The International Journal of Banking and Finance , 1 (1). pp. 119-140. ISSN 1617-722

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Abstract

We employ a nonlineal: nonparametric method to model the stochastic behavior of changes in several short and long term U.S. interest rates. We apply a nonlinear autoregression to the series using the locally weighted regression (LWR) estimation method, a nearest-neighbor method, and evaluate the forecasting performance with a measure of root mean square error (RMSE). We compare the forecasting performance of the nonparametric fit to the performance of two benchmark linear models: an autoregressive model and a random-walk-with-drift model. The nonparametric model exhibits greater out-of sample forecast accuracy that that of the linear predictors for most US. interest rate series. The improvements in forecast accuracy are statistically significant and robust. This evidence establishes the presence of significant nonlinear mean predictability in U.S. interest rates, as well as the usefulness of the LWR method as as modeling strategy for these benchmark series.

Item Type:	Article
Uncontrolled Keywords:	interest rate, forecasting performance
Subjects:	H Social Sciences > HG Finance
Divisions:	UNSPECIFIED
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	01 Aug 2010 00:21
Last Modified:	01 Aug 2010 00:21
URI:	https://repo.uum.edu.my/id/eprint/334

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