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Bihari, Anshita, Dash, Manoranjan, Muduli, Kamalakanta, Kumar, Anil, Mulat-Weldemeskel, Eyob and Luthra, Sunil (2023) Does cognitive biased knowledge influence investor decisions? An empirical investigation using machine learning and artificial neural network. VINE Journal of Information and Knowledge Management Systems. ISSN 2059-5891
Purpose:
Current research in the field of behavioural finance has attempted to discover behavioural biases and their characteristics in individual investors' irrational decision-making. The goal of this research is to find out how biases in information based on knowledge affect decisions about investments.
Design/methodology/approach:
In step one, through existing research and consultation with specialists, thirteen relevant items covering major aspects of bias were determined. In the second step, multiple linear regression (MLR) and artificial neural network (ANN) were used to analyse the data of 337 retail investors.
Findings:
The investment choice was heavily impacted by regret aversion, followed by loss aversion, overconfidence, and the Barnum effect. It was observed that the Barnum effect has a statistically significant negative link with investing choices. The research also found that investors' fear of making mistakes and their tendency to be too sure of themselves were the most significant factors in their decisions about where to put their money.
Practical implications:
This research contributes to the expansion of the knowledge base in behavioural finance theory by highlighting the significance of cognitive psychological traits in how leading investors end up making irrational decisions. Portfolio managers, financial institutions, and investors in developing markets may all significantly benefit from the information offered.
Originality/value:
This research is a one-of-a-kind study since it analyses the emotional biases along with the cognitive biases of investor decision-making. Investor decisions generally consider the shadowy side of knowledge management.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.
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