A BIBLIOMETRIC ANALYSIS OF THE ARFIMA MODEL DURING 1993 – 2022

Abstract

The Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is the best choice for the long-term memory data series. In this research, we review and evaluate the literature on ARFIMA models. ARFIMA research activity was examined using a bibliometric technique using a sample of 784 papers from the Scopus database that were published between the years 1993 and 2022. Moreover, we identified the primary research areas, categories of published documents, most significant platforms and sources of ARFIMA publications, widely cited studies, productive authors, author's institutions and countries, as well as evaluated the publication's citation pattern. The titles and keywords, including abstracts of the documents, are also included, as well as their terms and occurrences. Microsoft Excel was used for frequency analysis, Harzing's Publish or Perish for citation analysis and metrics, as well as VOS viewer for data visualisation. The results indicate that there is an increment in the publications' number. The network analysis and statistical analysis revealed that the year 2018 had the most papers issued.