Maximum Likelihood Estimation for the Fractional Vasicek Model

This paper estimates the drift parameters in the fractional Vasicek model from a continuous record of observations via maximum likelihood (ML). The asymptotic theory for the ML estimates (MLE) is established in the stationary case, the explosive case, and the boundary case for the entire range of th...

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Bibliographic Details
Main Authors: Katsuto Tanaka, Weilin Xiao, Jun Yu
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Econometrics
Subjects:
Online Access:https://www.mdpi.com/2225-1146/8/3/32
Description
Summary:This paper estimates the drift parameters in the fractional Vasicek model from a continuous record of observations via maximum likelihood (ML). The asymptotic theory for the ML estimates (MLE) is established in the stationary case, the explosive case, and the boundary case for the entire range of the Hurst parameter, providing a complete treatment of asymptotic analysis. It is shown that changing the sign of the persistence parameter changes the asymptotic theory for the MLE, including the rate of convergence and the limiting distribution. It is also found that the asymptotic theory depends on the value of the Hurst parameter.
ISSN:2225-1146