Maximum Likelihood Estimation for the Fractional Vasicek Model
Katsuto Tanaka (),
Weilin Xiao () and
Jun Yu ()
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Katsuto Tanaka: Faculty of Economics, Gakushuin University, Tokyo 171-8588, Japan
Weilin Xiao: School of Management, Zhejiang University, Hangzhou 310058, China
Econometrics, 2020, vol. 8, issue 3, 1-28
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.
Keywords: maximum likelihood estimate; fractional Vasicek model; asymptotic distribution; stationary process; explosive process; boundary process (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Working Paper: Maximum Likelihood Estimation for the Fractional Vasicek Model (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:8:y:2020:i:3:p:32-:d:397839
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