EconPapers    
Economics at your fingertips  
 

Asymptotically efficient estimation of Ergodic rough fractional Ornstein-Uhlenbeck process under continuous observations

Kohei Chiba () and Tetsuya Takabatake ()
Additional contact information
Kohei Chiba: Osaka University
Tetsuya Takabatake: Hiroshima University

Statistical Inference for Stochastic Processes, 2024, vol. 27, issue 1, No 4, 103-122

Abstract: Abstract We consider the problem of asymptotically efficient estimation of drift parameters of the ergodic fractional Ornstein-Uhlenbeck process under continuous observations when the Hurst parameter $$H

Keywords: Fractional Ornstein-Uhlenbeck process; Estimation of drift parameters; Continuous observations; Local asymptotic normality property; 62M09 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11203-023-09300-3 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:27:y:2024:i:1:d:10.1007_s11203-023-09300-3

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

DOI: 10.1007/s11203-023-09300-3

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 ().

 
Page updated 2025-04-12
Handle: RePEc:spr:sistpr:v:27:y:2024:i:1:d:10.1007_s11203-023-09300-3