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Stock market volatility: a systematic review.

Authors :
Dhingra, Barkha
Batra, Shallu
Aggarwal, Vaibhav
Yadav, Mahender
Kumar, Pankaj
Source :
Journal of Modelling in Management; 2024, Vol. 19 Issue 3, p925-952, 28p
Publication Year :
2024

Abstract

Purpose: The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility. Design/methodology/approach: This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area. Findings: The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with "cryptocurrencies" and "bitcoin" during "COVID-19." The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area. Originality/value: This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17465664
Volume :
19
Issue :
3
Database :
Complementary Index
Journal :
Journal of Modelling in Management
Publication Type :
Academic Journal
Accession number :
175993068
Full Text :
https://doi.org/10.1108/JM2-04-2023-0080