Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Levy Processes

Yong Bao, Aman Ullah Author Email:aman.ullah@ucr.edu, Yun Wang Author Email:wyuncolor@gmail.com and Jun Yu
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Aman Ullah Author Email:aman.ullah@ucr.edu: University of California, Riverside
Yun Wang Author Email:wyuncolor@gmail.com: University of International Business and Economics
Authors registered in the RePEc Author Service: Peter C. B. Phillips

Working Papers from Singapore Management University, Sim Kee Boon Institute for Financial Economics

Abstract: This paper develops the approximate nite-sample bias of the ordinary least squares or quasi maximum likelihood estimator of the mean reversion parameter in continuous-time Levy processes. For the special case of Gaussian processes, our results reduce to those of Tang and Chen (2009) (when the long-run mean is unknown) and Yu (2012) (when the long-run mean is known). Simulations show that in general the approximate bias works well in capturing the true bias of the mean reversion estimator under di erence scenarios. However, when the time span is small and the mean reversion parameter is approaching its lower bound, we nd it more dicult to approximate well the nite-sample bias.

Keywords: Date-stamping strategy, Flexible window, Generalized sup ADF test, Multiple bubbles, Rational bubble, Periodically collapsing bubbles; Sup ADF test, (search for similar items in EconPapers)
JEL-codes: C10 C22 (search for similar items in EconPapers)
Pages: 20 Pages
Date: 2013-02
New Economics Papers: this item is included in nep-his, nep-rmg and nep-sea
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Published in SMU-SKBI CoFie Working Paper

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Related works:
Working Paper: Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes (2013)
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