Modeling the Effects of Behavioral Biases and Personality Traits of Investor Types on Their Decision-Making under Capital Market Uncertainty

Abstract Objectives : This study aims to model the impact of behavioral biases and personality traits of individual and institutional investors on their decision-making under conditions of uncertainty in the capital markt. Methodology/Design/Approach : The present study adopts a mixed-method approach. In the qualitative section, opinions of 17 experts (faculty members and market participants) were collected and analyzed through Interpretive Structural Modeling (ISM). In the quantitative section, data from 384 investors were gathered using a questionnaire in 2024 and analyzed via Structural Equation Modeling(SEM). Findings : In the qualitative phase, Delphi technique, ISM, and MICMAC software were used to identify and classify the dimensions and components. Results indicated that cognitive and emotional biases, cultural dimensions, personal characteristics, personality types, and demographic features significantly influenced investor decision-making. Cognitive biases, personal traits, personality types, and demographic features were identified as key foundational factors. In the quantitative phase, SEM analysis confirmed the significant positive impact of behavioral biases and personality traits on the decision-making of both individual and institutional investors under market uncertainty. Conclusion : The results reveal a complex and multifaceted set of psychological, cognitive, emotional, demographic, cultural, and behavioral factors that hierarchically influence investor behavior. Innovation : By presenting a structured framework of factors affecting investor decisions, this study enriches the behavioral finance literature and provides practical guidelines to improve investment behavior under uncertainty.