Presenting an Optimal Model for Explaining Capital Structure Management with a Market Value Creation Approach

Abstract

Objective: The aim of this study is to present an optimal model for capital structure management with a market value creation approach. Methodology: This study utilized data from companies listed on the Tehran Stock Exchange over a six-year period (2017-2022). A regression model was first used to analyze the impact of various variables on capital structure. Subsequently, a decision tree algorithm and the Root Mean Square Error (RMSE) criterion were employed to provide an optimal model for capital structure management. The primary variables studied include economic value added (EVA), growth rate of shareholders' equity, earnings per share (EPS) growth, company size, financial leverage, and free cash flow.  Findings: The results indicated that economic value added, growth rate of shareholders' equity, and earnings per share growth had the most substantial impact on market value added. In contrast, variables such as company size, book-to-market ratio, financial leverage, and free cash flow did not establish a significant relationship with market value added. Additionally, it was found that capital structure alone is not the primary driver of market value creation.  Conclusion: This study demonstrates that in capital structure management, companies should focus on variables such as economic value added and earnings growth rather than solely on optimizing the debt-equity mix. These variables can significantly contribute to increasing market value and improving financial performance.