Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes
Continuous-time Levy 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...
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sg-smu-ink.soe_research-25022019-04-21T15:28:58Z Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes BAO, Yong ULLAH, Aman WANG, Yun YU, Jun Continuous-time Levy 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 Levy 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. 2013-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1503 https://ink.library.smu.edu.sg/context/soe_research/article/2502/viewcontent/02_2013.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Bias Mean Reversion Parameter Levy processes Econometrics |
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Bias Mean Reversion Parameter Levy processes Econometrics BAO, Yong ULLAH, Aman WANG, Yun YU, Jun Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes |
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Continuous-time Levy 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 Levy 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. |
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BAO, Yong ULLAH, Aman WANG, Yun YU, Jun |
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BAO, Yong ULLAH, Aman WANG, Yun YU, Jun |
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BAO, Yong |
title |
Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes |
title_short |
Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes |
title_full |
Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes |
title_fullStr |
Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes |
title_full_unstemmed |
Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes |
title_sort |
bias in the mean reversion estimator in continuous-time gaussian and lévy processes |
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Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/soe_research/1503 https://ink.library.smu.edu.sg/context/soe_research/article/2502/viewcontent/02_2013.pdf |
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