Improved Estimation Strategy in Multi-Factor Vasicek Model

S. Ejaz Ahmed (), Sévérien Nkurunziza () and Shuangzhe Liu ()
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S. Ejaz Ahmed: University of Windsor, Department of Mathematics and Statistics
Sévérien Nkurunziza: University of Windsor, Department of Mathematics and Statistics
Shuangzhe Liu: University of Canberra, Faculty of Information Sciences and Engineering

A chapter in Statistical Inference, Econometric Analysis and Matrix Algebra, 2009, pp 255-270 from Springer

Abstract: Abstract We consider simultaneous estimation of the drift parameters of multivari-ate Ornstein-Uhlebeck process. In this paper, we develop an improved estimation methodology for the drift parameters when homogeneity of several such parameters may hold. However, it is possible that the information regarding the equality of these parameters may not be accurate. In this context, we consider Stein-rule (or shrinkage) estimators to improve upon the performance of the classical maximum likelihood estimator (MLE). The relative dominance picture of the proposed estimators are explored and assessed under an asymptotic distributional quadratic risk criterion. For practical arguments, a simulation study is conducted which illustrates the behavior of the suggested method for small and moderate length of time observation period. More importantly, both analytical and simulation results indicate that estimators based on shrinkage principle not only give an excellent estimation accuracy but outperform the likelihood estimation uniformly.

Keywords: Interest Rate; Maximum Likelihood Estimator; Wiener Process; Term Structure; Process Capability Index (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2121-5_17

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DOI: 10.1007/978-3-7908-2121-5_17

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