Continuous-time L evy processes have become increasingly popular in the asset pricing literature and estimation of the mean reversion parameter has attracted attention recently. 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 L evy processes. Simulations show that in general the approximate bias works well in capturing the true bias of the mean reversion estimator under difference scenarios. However, when the time span is small and the mean reversion parameter is approaching its lower bound, we find it more difficult to approximate well the nite-sample bias.
Bias, Mean Reversion Parameter, L evy processes
Bao, Yong; Ullah, Aman; Wang, Yun; and YU, Jun.
Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes. (2013). Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1503
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