Modeling and forecasting interval-valued data in finance: a half-century review

Purpose This paper aims to provide a comprehensive review of the applications and methodologies of interval-valued data in finance, as well as explore more potential application research in the future by the methods of bibliometrics. Design/methodology/approach This paper conducts a bibliometric analysis of 1,051 papers about interval-valued data applications in finance from 1977 to 2023. We use descriptive statistical analysis and literature co-citation network analysis to examine influential journals, institutions, research hotspots and different applications and methods of interval-valued data in finance. Findings First, the descriptive statistical analysis reflects that the Journal of Forecasting and the International Journal of Forecasting and Information Science are listed as the most influential journals, and Chinese Academy of Sciences is one of the most influential institutions. Second, cluster analysis of co-cited articles reveals that the hot research topics cover forecast for interval-valued time series data, decomposition ensemble approach, cross-section interval regression, event analysis, portfolio selection, principal component analysis and cluster of interval-valued data. Third, this paper proposes five future research directions, such as including interval-based financial risk management. Originality/value This paper provides a scientometric and systematic way to review interval-valued data application in financial research. It offers more robust findings by integrating studies from different fields to find the salient problems of interval-valued data application in financial research using cluster analysis of co-cited papers. The descriptive analysis of this study offers helpful guidance for readers to find the respective important journals, authors, and institutions in the research area. This paper also proposes five directions for future research based on the current research hotspots and the future development trends of finance, which can help scholars choose their research topics.