Maximum likelihood estimation for the fractional Vasicek model

• Main Authors: TANAKA, Katsuto, XIAO, Weilin, Jun YU
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Maximum likelihood estimate; fractional Vasicek model; asymptotic distribution; stationary process; explosive process; boundary process; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/2432; https://ink.library.smu.edu.sg/context/soe_research/article/3431/viewcontent/MLE_FM_econometrics_08_00032_pvoa.pdf
• Institution: Singapore Management University

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.