Modeling and forecasting Tapis crude oil price: A long memory approach

Modeling and forecasting Tapis crude oil price: A long memory approach

This paper proposes a fractional filter and Auto Regressive Fractional Unit Root Integral Moving Average (ARFURIMA) model on daily Malaysian Tapis Crude Oil Price (MTCOP) for the period 4th June 2007 to 29th June 2018. The goodness of fits and dependence tests of each model are discussed. Results in...

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Hauptverfasser: Rahman, Rosmanjawati Abdul, Jibrin, Sanusi Alhaji
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Sprache:eng
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Crude oil
Crude oil prices
Dependence
Forecasting
Integrals
International markets
Mathematical models
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creator Rahman, Rosmanjawati Abdul
Jibrin, Sanusi Alhaji
description This paper proposes a fractional filter and Auto Regressive Fractional Unit Root Integral Moving Average (ARFURIMA) model on daily Malaysian Tapis Crude Oil Price (MTCOP) for the period 4th June 2007 to 29th June 2018. The goodness of fits and dependence tests of each model are discussed. Results indicate that ARFURIMA model is superior to the Auto Regressive Integral Moving Average (ARIMA) and Auto Regressive Fractional Integral Moving Average (ARFIMA) models in modelling and forecasting the Tapis Crude Oil Price.
doi_str_mv 10.1063/1.5136393
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subjects Crude oil
Crude oil prices
Dependence
Forecasting
Integrals
International markets
Mathematical models
title Modeling and forecasting Tapis crude oil price: A long memory approach
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