Fractionally integrated ARMA for crude palm oil prices prediction: case of potentially overdifference

DOI10.1080/02664763.2013.825706OpenAlexW2078651389MaRDI QIDQ5129156

Abdul Aziz Karia, Imbarine Bujang, Ismail Ahmad

Publication date: 26 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.825706

zbMATH Keywords

forecastcrude palm oil pricesfirst-order differencingfractionally integratedoverdifference

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Comparing the performances of symmetric and asymmetric generalized autoregressive conditionally heteroscedasticity models based on long-memory models under different distributions

Cites Work

• An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series
• Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
• Long memory relationships and the aggregation of dynamic models
• Some simulations and applications of forecasting long-memory time-series models
• A permanent-transitory decomposition for ARFIMA processes
• Long memory processes and fractional integration in econometrics
• On the estimation and diagnostic checking of the ARFIMA-HYGARCH model
• Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation
• Testing for a unit root in time series regression
• Fractional differencing
• Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• ESTIMATION OF THE MEMORY PARAMETER FOR NONSTATIONARY OR NONINVERTIBLE FRACTIONALLY INTEGRATED PROCESSES
• Efficient Tests for an Autoregressive Unit Root
• Long memory and regime switching

This page was built for publication: Fractionally integrated ARMA for crude palm oil prices prediction: case of potentially overdifference