An Empirical Study on the Determinants of Capital Structure Decisions Among Multinational Corporations

Posted: Apr 04, 2015

• Theodore Baker
• Theodore Moore
• Theodore Rodriguez

Abstract

The capital structure decisions of multinational corporations represent one of the most complex and consequential challenges in corporate finance, with implications spanning risk management, cost of capital optimization, and strategic positioning in global markets. Traditional theoretical frameworks, including the trade-off theory, pecking order theory, and agency theory, have provided valuable insights into financing decisions but often fail to capture the multidimensional nature of multinational corporate finance. The existing literature has predominantly relied on linear regression models and static theoretical constructs that inadequately account for the dynamic interplay between macroeconomic conditions, regulatory environments, cultural factors, and firm-specific characteristics across diverse geographic contexts. This research addresses critical gaps in the current understanding by developing and validating a novel computational intelligence framework that integrates machine learning algorithms with financial theory to analyze capital structure determinants. The study introduces several methodological innovations, including a dynamic variable weighting system that adapts to changing economic conditions, a regulatory heterogeneity quantification mechanism, and a cultural dimension integration protocol. These innovations enable a more nuanced analysis of how multinational corporations navigate the complex trade-offs between debt and equity financing across different national contexts.