Personality Traits: The link between women on upper echelon and financial performance

Automatic recognition of personality traits

Abstract

This paper has explored how the personality traits of women in upper echelon impact the financial performance of FTSE 350 companies in the United Kingdom leveraging new insight from computational social scientist who adopted machine learning to extract personality traits scores from transcript of earnings call of women Chief Executive Officers and Chief Financial Officers with the analysts. The personality traits of these top executives will be automatically recognised from the transcript of their spoken communications during the earnings call. The Open Language Chief Executive Tool will be executed on Phyton to produce output of their personality scores. Subsequently, the impact of these top executives on company’s financial performance will be established using ordinary least square regression analysis to examine the relationship between the personality scores and financial performance using Statistical Package for the Social Science.