Enterprise Multiple and Future Returns of the Brazilian Stock Market

Rafael Igrejas,Antonio Carlos Figueiredo Pinto,Raphael Braga Da Silva,Marcelo Cabus Klotzle,Paulo Vitor Jordão Da Gama Silva

doi:10.7213/rebrae.10.003.ao06

Abstract

The estimation of cross-section returns for defining investment strategies based on financial multiples has been proven to be relevant following Fama and French’s (1992) research. One of the challenges for such studies is to identify the main variables that are suitable for explaining the returns in a particular context because the variables that are widely used in developed markets behave differently in emerging countries. In this study, we analyze the predictive power of the EV/EBITDA multiple in the context of the Brazilian stock market. The results show that the analyzed multiple has a strong relationship with the future returns of companies listed on the BM&F BOVESPA index between 2005 and 2013. For the period under review, the investment strategy of purchasing stocks when EV/EBITDA was low and selling stocks when EV/EBITDA was high showed abnormal returns of 15.94% per year, even after controlling for risk factors.

Highlights

The estimation of cross-section returns for defining investment strategies based on enterprise multiples is greatly needed to assess stock markets in emerging countries
This study evaluates the robustness of the enterprise multiple (EM) variable with regard to cross-sectional regressions when the following factors are included: the small minus big (SMB) factor, which is calculated as the difference between the returns of the smallest and largest companies in terms of market value; the high minus low (HML) factor, i.e., the difference in returns between the companies with the 30% highest and those with the 30% lowest book-to-market values; and the up minus down (UMD) factor, which is known as momentum factor and is calculated by subtracting the equal weighted returns of higher performing companies from the equal weighted returns of lower performing companies
The independent variables are size, book-to-market, time, and enterprise value (EV)/EBITDA as of December in year t - 1

Summary

Introduction

The estimation of cross-section returns for defining investment strategies based on enterprise multiples is greatly needed to assess stock markets in emerging countries. In this context, the enterprise value (EV)/earnings before interest, taxes, depreciation, and amortization (EBITDA) multiple (the EV/EBITDA multiple) may prove efficient and is recognized to be a relevant pricing tool. Claessens, Dasgupta and Glen (1995) showed that the portfolio returns in these markets generally do not display normal behavior, using non-significant beta to explain the returns They observed the size effect to be non-significant and reported strong evidence of the significance of the book-to-market variable. In a recent study in Brazil, Silva et al (2012) identified low statistical significance for the size and book-to-market variables when estimating stock returns using cross-sectional regressions. Fama and French (1993) and the four-factor model proposed by Carhart (1997) in cross-sectional monthly regressions

Methodology

Results

Coef t-stat

Weighted Method