profitability function Approximation using capital structure variables in Iranian industries

Achieving the optimal capital structure in order to gain maximum profitability and value while having minimum cost of capital is one of the important topics studied by financial professionals. In the field of the relationship between financing decisions and corporate profitability, there exists four major theories of Miller and Modigliani, agency theory, static balance theory (all observing the positive relationship between debt ratio and profitability) and hierarchical theory (negative relationship between debt ratio and Profitability). In this study, using data from 161 companies listed on the Tehran Stock Exchange in five industries (including ceramic tiles, cement, metals, oil and gas, and pharmaceuticals) between 2010 and 2017, the problem of estimating the profitability function by the capital structure has been addressed. In order to estimate the mentioned function, regression analysis as well as a combination of wavelet neural network algorithm and the Imperialistic Competition Algorithm have been used. The results indicate a negative relationship between debt ratios and return on asset (confirmation of hierarchical theory) in ceramic tile, cement, metals, and pharmaceutical companies. However, in the oil and gas industry, no significant relationship has been found between these variables. In addition, the performance of the wavelet neural network optimized by the imperialistic competition algorithm has shown to be more desirable than simple linear regression for all the investigated industries.