Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes
AbstractThis paper develops the approximate finite-sample bias of the ordinary least squares or quasi max- imum 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 difference scenarios. However, when the time span is small and the mean reversion parameter is approaching its lower bound, we nd it more difficult to approximate well the finite-sample bias.
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Bibliographic InfoPaper provided by Singapore Management University, School of Economics in its series Working Papers with number 02-2013.
Date of creation: Mar 2013
Date of revision:
Publication status: Published in SMU Economics and Statistics Working Paper Series
Find related papers by JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-03-30 (All new papers)
- NEP-ECM-2013-03-30 (Econometrics)
- NEP-ETS-2013-03-30 (Econometric Time Series)
- NEP-SEA-2013-03-30 (South East Asia)
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