Publication Type

Working Paper

Version

publishedVersion

Publication Date

11-2009

Abstract

It is well known that for continuous time models with a linear drift standard estimation methods yield biased estimators for the mean reversion parameter both in nite discrete samples and in large in-…ll samples. In this paper, we obtain two expressions to approximate the bias of the least squares/maximum likelihood estimator of the mean reversion parameter in the Ornstein-Uhlenbeck process with a known long run mean when discretely sampled data are available. The first expression mimics the bias formula of Marriott and Pope (1954) for the discrete time model. Simulations show that this expression does not work satisfactorily when the speed of mean reversion is slow. Slow mean reversion corresponds to the near unit root situation and is empirically realistic for financial time series. An improvement is made in the second expression where a nonlinear correction term is included into the bias formula. It is shown that the nonlinear term is important in the near unit root situation. Simulations indicate that the second expression captures the magnitude, the curvature and the non-monotonicity of the actual bias better than the first expression.

Keywords

Least squares, Maximum likelihood, Discrete sampling, Continuous record, Near unit root.

Discipline

Econometrics

Research Areas

Econometrics

First Page

1

Last Page

27

Publisher

SMU Economics and Statistics Working Paper Series, No. 16-2009

City or Country

Singapore

Copyright Owner and License

Authors

Comments

Published in Journal of Econometrics, 2012, https://doi.org/10.1016/j.jeconom.2012.01.004

Download

Included in

Econometrics Commons

Share

COinS