The impact of accounting-based information on the financial beta: Case for cement industry in Turkey

Abstract

In financial theory, the cost of equity is defined as a return that stockholders require for a company. It has a vital importance for corporations in evaluation of investment opportunities. There are several methods to calculate the cost of equity including Capital Asset Pricing Model (CAPM). The CAPM is a commonly used method but it has a major restriction. It can be used only for publicly traded corporations not for non-public corporations because it requires stock return data to estimate Financial Beta. When the stock price is not available for a firm, finance literature suggests that Accounting Beta can be used as a proxy of financial beta to estimate the cost of equity. Most of researchers have aimed to find a relationship between financial beta and accounting variables. However, they used correlation or regression based approaches. The purpose of this study is to evaluate the impact of accounting-based information on the financial Beta through a non-linear approach, namely Support Vector Machines (SVM). Most of the studies in finance literature focus on the linear relationship between Betas and accounting variables and the results reveal that the explanatory powers of linear models are limited. To avoid this problem, this study applies SVM as an alternative method to analyze the size of impact of accounting variables on the financial Betas rather than estimating a linear model. Based on Statistical Learning Theory and Structural Risk Minimization Principle, the SVM algorithms are able to solve regression problems without getting stuck in local minima. They achieve the global solution by transforming the regression problem into a quadratic programming (QP) problem and then solving it by any QP solver. Recently, SVM-based algorithms have been developed very rapidly and have been applied to many areas. Finding global solution and having higher generalization potential constitute the major advantages of the SVM algorithms over other regression techniques.In this study, the accounting information is represented by current ratio, quick ratio, net profit margin, assent turnover, return on assets, return on equity, financial leverage and logarithmic total assets over 2005-2014 period. In addition to that, financial betas of cement firms traded in Borsa Istanbul (BIST) are calculated for each year. The result of the study illustrates that financial leverage, the size and asset turnover have the highest impact on financial beta, respectively.