Title: Modelling seasonal fractionally integrated process with volatility and structural change

Authors: Lawrence Dhliwayo; Florance Matarise; Charles Chimedza

Addresses: Department of Mathematics and Computational Sciences, University of Zimbabwe, MP 167, Mount Pleasant, Harare, Zimbabwe ' Department of Mathematics and Computational Sciences, University of Zimbabwe, MP 167, Mount Pleasant, Harare, Zimbabwe ' School of Statistics and Actuarial Science, University of the Witwatersrand, South Africa

Abstract: This study investigates fractionally integrated processes, specifically SARFIMA-GARCH models with structural changes. These models encompass four key aspects of time series data: seasonality, fractional integration, volatility, and structural change. The primary focus of this study is to extend the seasonal structural change detection test for both mean and volatility in a given realisation. The parameters for the seasonal structural change (SSC)-SARFIMA and seasonal structural change (SSC)-GARCH models were derived. Additionally, we establish test statistics that are crucial for assessing the statistical significance of seasonal structural change in a SARFIMA-GARCH model. A simulation study was conducted to demonstrate the reliability of the derived detection procedures.

Keywords: time series analysis; seasonality; fractional integration; structural change; SSC-SARFIMA; SSC-GARCH.

DOI: 10.1504/IJCEE.2024.142098

International Journal of Computational Economics and Econometrics, 2024 Vol.14 No.4, pp.468 - 485

Accepted: 20 Jan 2024
Published online: 07 Oct 2024 *

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