ARFURIMA models: simulations of their properties and application

• Authors: Sanusi Alhaji Jibrin , Rosmanjawati Abdul Rahman

Abstracts

EN

This article defines the Autoregressive Fractional Unit Root Integrated Moving Average (ARFURIMA) model for modelling ILM time series with fractional difference value in the interval of 1 < d < 2. The performance of the ARFURIMA model is examined through a Monte Carlo simulation. Also, some applications were presented using the energy series, bitcoin exchange rates and some financial data to compare the performance of the ARFURIMA and the Semiparametric Fractional Autoregressive Moving Average (SEMIFARMA) models. Findings showed that the ARFURIMA outperformed the SEMIFARMA model. The study’s conclusion provides another perspective in analysing large time series data for modelling and forecasting, and the findings suggest that the ARFURIMA model should be applied if the studied data show a type of ILM process with a degree of fractional difference in the interval of 1 < d < 2.

Keywords

EN

interminable long memory; autocorrelation; fractional unit root integrated series; fractional unit root differencing; ARFURIMA model

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2022
• Volume: 23
• Issue: 2
• Pages: 69-87

Dates

published

2022

Contributors

author

Sanusi Alhaji Jibrin

• Department of Statistics, Kano University of Science and Technology, Wudil. Nigeria

• https://orcid.org/0000000312767965

author

Rosmanjawati Abdul Rahman

• School of Mathematical Sciences, Universiti Sains Malaysia. Malaysia

• https://orcid.org/0000000253840674

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Identifiers

DOI

10.2478/stattrans-2022-0017

Biblioteka Nauki

2107044