Improved Estimation Strategy in Multi-Factor Vasicek Model

S. Ejaz Ahmed, Severien Nkurunziza, Shuangzhe Liu

Research output: A Conference proceeding or a Chapter in BookChapter


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.
Original languageEnglish
Title of host publicationStatistical Inference, Econometric Analysis and Matrix Algebra
EditorsBernhard Schipp, Walter Kraemer
Place of PublicationHeidelberg
PublisherPhysica Verlag
Number of pages16
ISBN (Print)9783790821208
Publication statusPublished - 2009


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