ARFURIMA models: simulations of their properties and application

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Statistics in Transition new series (SiTns) ; ISSN: 2450-0291 ; Volume: 23 ; Year: 2022 ; Issue: 2 ; Pages: 69-87 ; Warsaw: Sciendo

Classification and Topics

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

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Jibrin, Sanusi Alhaji ; Rahman, Rosmanjawati Abdul
• Event: Veröffentlichung
• (who): Sciendo
• (where): Warsaw
• (when): 2022

Further information

• DOI: doi:10.2478/stattrans-2022-0017
• Handle: http://hdl.handle.net/10419/266308
• Last update: 10.03.2025, 11:45 AM CET