Impact of CEO Testosterone Levels on Financial Decision-Making and Risk-Taking: A Neuro-Financial Approach Using Frog Leaping Algorithm
Abstract
This study investigates the influence of CEO testosterone levels on financial decision-making and risk-taking behavior, leveraging a neuro-financial perspective to bridge biological, psychological, and financial domains. The research focuses on firms listed in the BIST 30 and BIST 100 indices of the Borsa Istanbul (BIST) to explore the dynamic interplay between executive physiology and corporate financial strategies. Testosterone, a critical physiological marker, has been linked to varying decision-making styles, where elevated levels often correlate with higher aggression, bold strategies, and increased risk appetite, while reduced levels promote cautious and risk-averse behaviors.The Frog Leaping Algorithm (FLA), a computational optimization model inspired by the leaping behavior of frogs, is employed to analyze and simulate decision-making patterns shaped by testosterone variations among CEOs. This algorithmic approach enables the identification of behavioral trends, strategic tendencies, and their financial implications across companies with different market capitalizations (large-cap, mid-cap, and small-cap). By incorporating FLA into the neuro-financial framework, the study provides a novel computational lens to interpret physiological impacts on corporate governance and strategic outcomes.The findings aim to offer practical insights for investors, corporate analysts, and scholars by highlighting how biological factors, such as testosterone, interact with financial modeling and market dynamics. Furthermore, this research enriches the emerging field of neuro-finance, particularly within the context of emerging markets like Turkey, by presenting an interdisciplinary methodology that integrates computational algorithms, behavioral science, and corporate strategy.
Keywords: CEO Testosterone Levels, Financial Decision-Making, Risk-Taking Behavior, Neuro-Finance, Frog Leaping Algorithm, Corporate Governance.
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