Least-squares estimators of drift parameter for discretely observed fractional Ornstein-Uhlenbeck processes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F20%3A43920940" target="_blank" >RIV/60461373:22340/20:43920940 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2227-7390/8/5/716/pdf" target="_blank" >https://www.mdpi.com/2227-7390/8/5/716/pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/MATH8050716" target="_blank" >10.3390/MATH8050716</a>

Result language

angličtina

Original language name

Least-squares estimators of drift parameter for discretely observed fractional Ornstein-Uhlenbeck processes

Original language description

We introduce three new estimators of the drift parameter of a fractional Ornstein-Uhlenbeck process. These estimators are based on modifications of the least-squares procedure utilizing the explicit formula for the process and covariance structure of a fractional Brownian motion. We demonstrate their advantageous properties in the setting of discrete-time observations with fixed mesh size, where they outperform the existing estimators. Numerical experiments by Monte Carlo simulations are conducted to confirm and illustrate theoretical findings. New estimation techniques can improve calibration of models in the form of linear stochastic differential equations driven by a fractional Brownian motion, which are used in diverse fields such as biology, neuroscience, finance and many others. © 2020 by the authors.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/LTAIN19007" target="_blank" >LTAIN19007: Development of Advanced Computational Algorithms for evaluating post-surgery rehabilitation</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Mathematics

ISSN

2227-7390

e-ISSN

—

Volume of the periodical

8

Issue of the periodical within the volume

5

Country of publishing house

CH - SWITZERLAND

Number of pages

20

Pages from-to

—

UT code for WoS article

000542738100018

EID of the result in the Scopus database

2-s2.0-85085530851