A Critical Review of Overconfidence in Investment Decisions: A Bibliometric Analysis

Authors

  • Shalini Ojha Research Scholar, Department of Commerce, Gauhati University, Guwahati, Assam, India
  • Amal Kumar Agarwala Department of Statistics, Arya Vidyapeeth College (Autonomous), Guwahati, Assam, India

DOI:

https://doi.org/10.32479/ijefi.17098

Keywords:

Bibliometric Analysis, Overconfidence, Investment Behaviour, Stock Market, Pandemic

Abstract

The precedence of behavior bias-based studies with respect to investment is quite prevalent. Hence, a bibliometric analysis of available literature may lead to fresh topics in association with overconfidence bias. The literature ranging between 1970 and 2024 were scanned using terms related to overconfidence in finance as keywords to reach the related publications. After screening, 1327 publications related to overconfidence, 728 documents were identified. Martin Weber emerged as the most cited author. SSRN electronic journal, qualitative research in financial matters and review of behavioral finance have published most cited papers in the field of overconfidence and investment decision. The United States have published highest number of papers and citations, while Germany, India and China have also emerged as nations with highest citations. The United States of America has published highest number of papers with citations. Germany, India and China have also emerged as nations with highly citated papers. Considering year on year growth in the publications, more work may be expected from the arena of overconfidence, and authors of the present study have taken the liberty to suggest a few possibilities that can be explored. Studies with risk tolerance, after pandemic impact, experience and financial/tax literacy, loss aversion and availability bias-based studies may be considered by researchers in accordance to overconfidence.

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Published

2024-10-30

How to Cite

Ojha, S., & Agarwala, A. K. (2024). A Critical Review of Overconfidence in Investment Decisions: A Bibliometric Analysis. International Journal of Economics and Financial Issues, 14(6), 104–109. https://doi.org/10.32479/ijefi.17098

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