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Deciphering risk and behavioural biases in investment decision-making

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  • Anushree Ganguly

Abstract

Behaviour distinctly shapes individuals' risk tolerance and these biases influence perceptions of risk and drive decision-making in financial contexts. In this study, we investigate the impact of behavioural biases on risk tolerance, focusing on selective cognitive and emotional biases such as overconfidence, regret aversion, representativeness, anchoring and adjustment, herding, loss aversion, and mental accounting. The research aims to develop a comprehensive model that captures the complex relationships between prominent biases and risk tolerance with respect to investment decisions, accounting for the interdependencies and interactions among these variables. The research design is descriptive and exploratory, aiming to understand risk patterns driven by biases. Data was collected through structured questionnaire from 365 individuals, and a structural equation was used to analyse the relationship between biases and risk tolerance. Confirmatory factor analysis (CFA) was used to validate measurement models of behavioural biases and risk tolerance, while structural equation modelling (SEM) was used to analyse the relationship between behavioural biases and risk tolerance.

Suggested Citation

  • Anushree Ganguly, 2026. "Deciphering risk and behavioural biases in investment decision-making," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 16(4), pages 511-528.
    • Handle: RePEc:ids:afasfa:v:16:y:2026:i:4:p:511-528
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