Cognitive bias asymmetry and heuristic-driven market anomalies: A neurofinancial noise trading analysis of prospect theory elasticity in the Pakistan Stock Exchange (PSX)

Abstract

This study presents a novel empirical investigation into the impact of psychological biases on investment decision-making within the Pakistan Stock Exchange (PSX), integrating Kahneman and Tversky’s Prospect Theory and Heuristics Theory into a unified behavioral finance framework. Departing from conventional analyses, this research employs a dual-method approach, combining meta-theoretical synthesis with primary quantitative data, to dissect how cognitive distortions such as overconfidence, loss aversion, and representativeness skew financial choices under uncertainty. A technically advanced self-descriptive questionnaire was administered to 250 PSX traders, leveraging psychometric scaling to quantify bias intensity, followed by machine learning-assisted regression analysis to isolate dominant behavioral predictors. The findings reveal a nonlinear relationship between heuristic-driven biases and market anomalies, challenging traditional rational-agent assumptions. Notably, the study introduces a bias susceptibility index (BSI), a pioneering metric for assessing individual vulnerability to cognitive errors. By contextualizing these distortions within emerging markets, a previously underexplored domain, this work advances behavioral finance theory while offering pragmatic tools for investors, advisors, and regulators to mitigate irrational decision-making.