EXPLORING THE RESEARCH TRENDS IN RETURN VOLATILITY AND FORECASTING RISK : BIBLIOMETRIC BIG DATA ANALYSES

Abstract

A brief overview of return volatility and forecasting risk in the literature is lacking, despite the fact that research on these issues has attracted much attention in the last ten years. The objective of this study is to explore paper-level literature metrics relating to return volatility and forecasting risk. To achieve this goal, we have adopted a systematic approach that combines VOSViewer and PRISMA. Our analytical framework is based on an extensive dataset obtained from Scopus covering the period between 2013 and 2023. Utilizing data from 777 return volatility and forecasting risk papers found in the Scopus database, our study uses VOSViewer's Scopus analysis results to present a bibliometric overview of the publication's citation structure as well as the funding sponsors, universities, countries involved in research work on the subject along with the journal authors and keywords associated with them. The findings of this study highlight the growing scholarly attention given to return volatility and risk forecasting. Our results are highly relevant for governance policymakers, as they offer a new perspective on the important role of possible factors in destabilizing return volatility. Based on our results, it can be said that this study provides a comprehensive overview of the disparate literature and suggests avenues for further research along with improved accounting procedures to tackle the problems caused by return volatility. Keywords: Stock M