Impact of Cognitive Biases on Trading Frequency, Risk Tolerance, and Diversification: Evidence from Emerging Markets
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose: This paper will discuss the role of cognitive biases in determining trading frequency, portfolio diversification and risk tolerance among retail investors in the emerging markets. It also determines whether demographic variables, like age, and gender can moderate these behavioral relationships. Design/Methodology/Approach: 632 individual investors were surveyed on-line in Southeast Asia and the Middle East to gather primary data. Using validated behavioral finance scales, the research uses partial least square structural equation modeling (PLS-SEM), with the support of bootstrapping, multi-group analysis, and nonlinear sensitivity tests to estimate direct, moderating, and curvilinear influences of cognitive biases on investment behaviors. Findings: Overconfidence has a substantive effect on trading frequency and diversification of the portfolio, and the loss aversion decreases the trading frequency, and risk tolerance. Gender reinforces the overconfidence-trading relationship and age increases the negative impact of loss aversion on diversification. There is amplification of behavioral effects at higher bias levels displayed by nonlinear tests. Implications/Originality/Value: The study has given detailed evidence on the impact of cognitive biases and demographic factors combined to affect the investment decisions in emerging markets. The results highlight the importance of regulators, policy makers and fintech platforms integrating behavioral insights into the way they educate investors, provide advisory technology and in their digital trading interfaces to encourage more consistent and welfare-enhancing investment behaviors. To the extent possible, the authors have guaranteed that the content is accurate, current, and contains no plagiarism. To the best of their ability, the authors have ensured that the content is correct, up-to-date, and free of plagiarism. 4.0
Author: Emmanuel Imuede Oyasor
Institution: Walter Sisulu University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7128676199