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Article
Publication date: 30 August 2023

Sneha Badola, Aditya Kumar Sahu and Amit Adlakha

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore…

Abstract

Purpose

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Design/methodology/approach

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

Findings

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

Research limitations/implications

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

Originality/value

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

Details

Qualitative Research in Financial Markets, vol. 16 no. 3
Type: Research Article
ISSN: 1755-4179

Keywords

Article
Publication date: 29 December 2023

Parvathy S. Nair and Atul Shiva

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative…

Abstract

Purpose

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.

Design/methodology/approach

The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.

Findings

The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.

Practical implications

The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.

Originality/value

This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.

Highlights

  1. Overconfidence bias is an important predictor of retail investors' behavior

  2. Formative dimensions of the overconfidence bias index.

  3. Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

  4. Modern portfolio theory and illusion of control theory support this study.

Overconfidence bias is an important predictor of retail investors' behavior

Formative dimensions of the overconfidence bias index.

Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

Modern portfolio theory and illusion of control theory support this study.

Details

Managerial Finance, vol. 50 no. 5
Type: Research Article
ISSN: 0307-4358

Keywords

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