Article: A bibliometric analysis of information criteria for forecasting volatility Journal: International Journal of Information and Decision Sciences (IJIDS) 2025 Vol.17 No.4 pp.371 - 400 Abstract: Volatility forecasting model selection is an essential issue when making financial decisions, which increasingly focus on modelling, forecasting, and evaluation. However, this area has not yet undergone a systematic analysis in the relevant literature. This paper takes advantage of the VOSviewer and bibliometric techniques to overview the temporal distribution of articles, the corresponding author's countries, the citation network, the co-occurrence, the thematic evolution, and the top of the journal or authors or articles. Content analysis was done to 60 pieces of literature, including their data characteristics, theoretical basis, and practical application, as well as suggestions for potential research directions. Through bibliometric techniques and content analysis, this study provides a thorough overview of the research done in the field of volatility forecasting model selection. The research findings indicate that scientific productivity on the subject is expanding rapidly. New methodologies, such as neural networks, have been introduced, necessitating a broad perspective by the researcher in the evaluation of empirical results. Inderscience Publishers - linking academia, business and industry through research

Title: A bibliometric analysis of information criteria for forecasting volatility

Authors: Youyuan Wu; Wei Chong Choo; Bolaji Tunde Matemilola; Jen Sim Ho

Addresses: School of Business and Economics, University Putra Malaysia, Serdang, 43400, Malaysia ' School of Business and Economics, University Putra Malaysia, Serdang 43400, Malaysia; Laboratory of Computational Statistics and Operations Research, Institute for Mathematical Research, University Putra Malaysia, Serdang, 43400, Malaysia ' Fac. Econ. and Management, University Putra Malaysia, Serdang, 43400, Malaysia ' School of Business and Economics, University Putra Malaysia, Serdang, 43400, Malaysia

Abstract: Volatility forecasting model selection is an essential issue when making financial decisions, which increasingly focus on modelling, forecasting, and evaluation. However, this area has not yet undergone a systematic analysis in the relevant literature. This paper takes advantage of the VOSviewer and bibliometric techniques to overview the temporal distribution of articles, the corresponding author's countries, the citation network, the co-occurrence, the thematic evolution, and the top of the journal or authors or articles. Content analysis was done to 60 pieces of literature, including their data characteristics, theoretical basis, and practical application, as well as suggestions for potential research directions. Through bibliometric techniques and content analysis, this study provides a thorough overview of the research done in the field of volatility forecasting model selection. The research findings indicate that scientific productivity on the subject is expanding rapidly. New methodologies, such as neural networks, have been introduced, necessitating a broad perspective by the researcher in the evaluation of empirical results.

Keywords: bibliometric analysis; information criteria; volatility forecasting; model selection.

DOI: 10.1504/IJIDS.2025.150100

International Journal of Information and Decision Sciences, 2025 Vol.17 No.4, pp.371 - 400

Received: 23 Jul 2023
Accepted: 31 Jan 2024
Published online: 01 Dec 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: A bibliometric analysis of information criteria for forecasting volatility

Keep up-to-date