Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Levy Processes
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.
|Date of creation:||Feb 2013|
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|Publication status:||Published in SMU-SKBI CoFie Working Paper|
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- Jun Yu, 2009.
"Bias in the Estimation of the Mean Reversion Parameter in Continuous Time Models,"
16-2009, Singapore Management University, School of Economics.
- Yu, Jun, 2012. "Bias in the estimation of the mean reversion parameter in continuous time models," Journal of Econometrics, Elsevier, vol. 169(1), pages 114-122.
- Jun Yu, 2007. "Bias in the Estimation of the Mean Reversion Parameter in Continuous Time Models," Working Papers CoFie-06-2008, Sim Kee Boon Institute for Financial Economics, revised Oct 2008.
- Jun Yu, 2009. "Bias in the Estimation of the Mean Reversion Parameter in Continuous Time Models," Microeconomics Working Papers 23045, East Asian Bureau of Economic Research.
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