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This study examines how board structure influences market sensitivity, measured by Beta, in software companies listed on the NASDAQ Global Select Market. Focusing on governance metrics such as board size, meeting frequency, and executive compensation, the research analyzes their impact on Beta from 2014 to 2023. Machine learning models, including Decision Trees and Bagging Classifiers, evaluate this relationship, using accuracy, precision, recall, and F1 scores. Findings suggest that governance factors significantly affect market sensitivity, offering valuable insights for corporate leaders and investors managing firm risk in volatile sectors like software.
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Ahmet Akusta (2025) studied this question.
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