Toward a Functional Model of Emotions in Decision-Making: A Qualitative Analysis in Simulated Stock Markets

This study explores the influence of emotions on investment decision-making in situations of uncertainty, using an experimental protocol combining a stock market simulation and focus group analysis. Eight management students took part in twelve trading sessions on a stock market platform, followed by a focus group aimed at explaining their emotional experiences. Thematic analysis of the verbatim responses reveals an emotional structure to decisionmaking based on three distinct functions: cognitive framing, which shapes the perception and assessment of the situation; motivation, which influences the impulse to act or to refrain from acting; and retroactive reasoning, which leads to post-decision learning. Our results challenge the idea that emotions are nothing more than irrational disruptive forces. On the contrary, they appear to be dynamic and sometimes adaptive components of reasoning in contexts of uncertainty. The suggested three-part model complements existing theories in decision psychology and opens up new avenues for research on affect regulation in highly uncertain contexts. Although research on emotions in decisionmaking is extensive, few studies have explored in depth and qualitatively how individuals experience and make sense of their emotions in simulated and uncertain contexts. The study not only applies a qualitative method, but also demonstrates its usefulness in challenging assumptions, such as the irrationality of emotions.