Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jeconom.2008.11.001
Title: Parameter estimation and bias correction for diffusion processes
Authors: Tang, C.Y. 
Chen, S.X.
Keywords: Bias correction
Bootstrap
Continuous-time models
Diffusion processes
Jackknife
Parameter estimation
Issue Date: Apr-2009
Citation: Tang, C.Y., Chen, S.X. (2009-04). Parameter estimation and bias correction for diffusion processes. Journal of Econometrics 149 (1) : 65-81. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jeconom.2008.11.001
Abstract: This paper considers parameter estimation for continuous-time diffusion processes which are commonly used to model dynamics of financial securities including interest rates. To understand why the drift parameters are more difficult to estimate than the diffusion parameter, as observed in previous studies, we first develop expansions for the bias and variance of parameter estimators for two of the most employed interest rate processes, Vasicek and CIR processes. Then, we study the first order approximate maximum likelihood estimator for linear drift processes. A parametric bootstrap procedure is proposed to correct bias for general diffusion processes with a theoretical justification. Simulation studies confirm the theoretical findings and show that the bootstrap proposal can effectively reduce both the bias and the mean square error of parameter estimates, for both univariate and multivariate processes. The advantages of using more accurate parameter estimators when calculating various option prices in finance are demonstrated by an empirical study. © 2008 Elsevier B.V. All rights reserved.
Source Title: Journal of Econometrics
URI: http://scholarbank.nus.edu.sg/handle/10635/105292
ISSN: 03044076
DOI: 10.1016/j.jeconom.2008.11.001
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