Comparison of the LS-based estimators and the MLE for the fractional Ornstein–Uhlenbeck process

Katsuto Tanaka ()
Additional contact information
Katsuto Tanaka: Gakushuin University

Statistical Inference for Stochastic Processes, 2020, vol. 23, issue 2, No 8, 415-434

Abstract: Abstract We deal with the fractional Ornstein–Uhlenbeck (fO–U) process driven by the fractional Brownian motion (fBm), where the drift parameter $$\alpha $$ α of the fO–U process is any unknown real number, whereas the Hurst index H of the fBm belongs to (0, 1) and is assumed to be known. Under this setting we consider the least squares (LS)-based estimators and the maximum likelihood estimator (MLE) of $$\alpha $$ α , and examine the efficiencies of the LS-based estimators relative to the MLE, paying attention to the effect of the sign of $$\alpha $$ α and the value of H. It is found that the MLE is more efficient than the LSE when $$\alpha \ne 0$$ α ≠ 0 , but the LSE is more efficient when $$\alpha =0$$ α = 0 .

Keywords: Asymptotic efficiency; Fractional Ornstein–Uhlenbeck process; Least squares estimator; Maximum likelihood estimator; Characteristic function; Numerical integration; Primary 60H05; 60H35; Secondary 62M10 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11203-020-09215-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sistpr:v:23:y:2020:i:2:d:10.1007_s11203-020-09215-3

Ordering information: This journal article can be ordered from
http://www.springer. ... ty/journal/11203/PS2

DOI: 10.1007/s11203-020-09215-3

Access Statistics for this article

Statistical Inference for Stochastic Processes is currently edited by Denis Bosq, Yury A. Kutoyants and Marc Hallin

More articles in Statistical Inference for Stochastic Processes from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().