Advancements and Challenges in Asset Pricing: Revisit on CEOs’ Characteristic and Firm Digitalization

บทคัดย่อ

          Over the last decade, asset pricing research has significantly expanded beyond traditional risk-based paradigms to incorporate insights from behavioral finance, machine learning applications, and firm-specific factors. This paper examines how CEO characteristics—specifically age, international experience, hometown identity, duality, and gender—together with firm digitalization (including digital transformation levels, IT investments, and AI adoption), shape corporate risk profiles and valuation. Recent advances in extended factor models, such as Fama–French extensions and mispricing factors, have enhanced our ability to explain return anomalies, while machine learning techniques help address the “factor zoo” problem by identifying previously overlooked predictors. Empirical evidence suggests that CEO demographics and backgrounds can influence strategic decision-making, thereby affecting asset pricing outcomes. Meanwhile, digital transformation has emerged as a crucial driver of intangible assets and operational efficiency; however, standard valuation approaches often struggle to fully capture these intangible benefits. Challenges remain in measuring and integrating CEO and digitalization variables into asset pricing models, due to issues related to data availability, endogeneity, and the transient nature of technological advantages. Future research should refine measurement strategies, develop dynamic modeling frameworks, and explore interactions among leadership attributes, digital capabilities, and traditional risk factors to better capture the complexity of modern asset pricing