Statistical inference for nonergodic weighted fractional Vasicek models

Khalifa Es-Sebaiy, Mishari Al-Foraih, Fares Alazemi

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A problem of drift parameter estimation is studied for a nonergodic weighted fractional Vasicek model defined as dXt = θ(μ+Xt)dt +dBta,b, t ≥ 0, with unknown parameters θ>0, μ ∈ ℝ and α:= θμ, whereas Ba,b:= {Bta,b,t ≥ 0} is a weighted fractional Brownian motion with parameters a>−1, |b| < 1, |b| <a+ 1. Least square-type estimators (˜θT, ˜μT) and (˜θT,˜αT) are provided, respectively, for (θ, μ) and (θ, α) based on a continuous-time observation of {Xt, t ∈[0,T]} as T →∞. The strong consistency and the joint asymptotic distribution of (˜θT, ˜μT) and (˜θT,˜αT) are studied. Moreover, it is obtained that the limit distribution of ˜θT is a Cauchy-type distribution, and ˜μT and ˜αT are asymptotically normal.

Original languageEnglish
Pages (from-to)291-307
Number of pages17
JournalModern Stochastics: Theory and Applications
Volume8
Issue number3
DOIs
StatePublished - Sep 2021

Keywords

  • Joint asymptotic distribution
  • Parameter estimation
  • Strong consistency
  • Weighted fractional Vasicek model
  • Young integral

Funding Agency

  • Kuwait Foundation for the Advancement of Sciences

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