ARFURIMA Models: Simulations of Their Properties and Application

• Autorzy: Sanusi Alhaji Jibrin , Rosmanjawati Abdul Rahman
• Języki publikacji: EN

Abstrakty

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. (original abstract)

Słowa kluczowe

EN

Monte Carlo simulation; Statistical models; Estimation

PL

Symulacja Monte Carlo; Modele statystyczne; Estymacja

• Czasopismo: Statistics in Transition
• Rocznik: 2022
• Tom: 23
• Numer: nr 2
• Strony: 69--87

Twórcy

autor

Sanusi Alhaji Jibrin

• Kano University of Science and Technology, Wudil, Kano State, Nigeria

autor

Rosmanjawati Abdul Rahman

• School of Mathematical Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia

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Identyfikatory

DOI

10.2478/stattrans-2022-0017