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Activity Number:
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405
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Business and Economics Statistics Section
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| Abstract - #301711 |
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Title:
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Shrinkage Drift Parameters Estimation for Multifactors Ornstein-Uhlenbeck Processes
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Author(s):
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Ejaz S. Ahmed*+ and Severien Nkurunziza
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Companies:
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University of Windsor and University of Windsor
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Address:
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401 Sunset Avenue, Windsor, ON, N9B 3P4, Canada
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Keywords:
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Ornstein-Uhlenbeck process ; Vasicek process ; Gaussian process ; Gaussian process ; shrinkage estimator ; MLE
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Abstract:
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We consider some inference problem concerning the drift parameters of multi-factors Vasicek model (or multivariate Ornstein-Uhlebeck process). For example, it asserts that the term structure of interest rate is not just a single process, but rather a superpositions of several analogous processes. This motivates us to develop an improved estimation theory for the drift parameters when homogeneity of several parameters may hold. However, the information regarding the equality of the theses parameters may be imprecise. In this context, we consider {\it Stein-rule} (or shrinkage) estimators which allow us to improve upon the performance of classical maximum likelihood estimator (MLE). Asymptotic properties of some shrinkage estimators are studied. Under an asymptotic distributional quadratic risk criterion, their relative dominance picture is explored and assessed.
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