Translator Disclaimer
July 2021 Infinite Variance Stable Gegenbaeur Arfisma Models
Filamory Abraham Michael Keita, Ouagnina Hili, Serge-Hippolyte Arnaud KANGA
Afr. Stat. 16(3): 2789-2808 (July 2021). DOI: 10.16929/as/2021.2789.184

Abstract

This paper develops the theory of the Gegenbauer AutoRegressive Fractionally Integrated Seasonal Moving Average (GARFISMA) process with α-stable innovations. We establish its conditions for causality and invertibility. This is a finite parameter process which exhibits high variability, long memory, cyclical, and seasonality in financial, hydrological data studies, and more. We perform some simulations to illustrate the behavior of our process.

Nous établissons ses conditions de causalité et d'inversibilité. Il s'agit d'un processus de paramètre fini qui présente une grande variabilité, une mémoire longue, un caractère cyclique et saisonnier dans les études de données financières, hydrologiques, etc. Nous effectuons quelques simulations pour illustrer le comportement de notre processus.

Citation

Download Citation

Filamory Abraham Michael Keita. Ouagnina Hili. Serge-Hippolyte Arnaud KANGA. "Infinite Variance Stable Gegenbaeur Arfisma Models." Afr. Stat. 16 (3) 2789 - 2808, July 2021. https://doi.org/10.16929/as/2021.2789.184

Information

Published: July 2021
First available in Project Euclid: 20 January 2022

Digital Object Identifier: 10.16929/as/2021.2789.184

Subjects:
Primary: 60E07
Secondary: 60G32 , 62G32

Keywords: Alpha stable distribution , cyclic time series , Gegenbauer polynomials , long memory , seasonal process

Rights: Copyright © 2021 The Statistics and Probability African Society

JOURNAL ARTICLE
20 PAGES

This article is only available to subscribers.
It is not available for individual sale.
+ SAVE TO MY LIBRARY

SHARE
Vol.16 • No. 3 • July 2021
Back to Top