HOW COGNITIVE TRAPS SHAPE INVESTOR CHOICES: A CASE STUDY FROM THE PAKISTAN STOCK EXCHANGE INVESTORS.

Abstract

Classical financial theories deal with investor rationality, but over time it has become clear that investors are not always rational and make decisions based on behavior, which can lead to financial losses. Therefore, in this study, we have investigated the impact of different behavioral biases, such as overconfidence, herding, loss aversion, and risk perception, on individual investors who invest in the stock exchange of Pakistan. For this purpose, convenience and snowball sampling techniques have been used to collect data from stock exchange investors via structured, adapted questionnaires. On this basis, we have collected data from 370 stock investors and investigated the influence of behavioral biases on the investment decision-making of individual stock exchange investors in Pakistan using a multiple linear regression model in SPSS, in which we have found that these behavioral biases (overconfidence, herding, loss aversion, and risk perception) have a significant influence on the investment decision-making of individual stock exchange investors in Pakistan. Further, it has given directions to new researchers to investigate new biases in investment decision-making with hierarchical or second-order models.