Reaction of the market to the operational leverage: an empirical study in Brazil

• Autor(a) principal: Dantas, José Alves
• Data de Publicação: 2006
• Outros Autores: Medeiros, Otávio Ribeiro de, Lustosa, Paulo Roberto B
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista Contabilidade & Finanças (Online)
• Texto Completo: https://www.revistas.usp.br/rcf/article/view/34187
• topic: Alavancagem Operacional; Retorno das Ações; Relação Lucro-Retorno; Utilidade da Informação Contábil; Operating Leverage; Stock Returns; Earnings-Return; Accounting Information Value Relevance

Studies evaluating the impact of financial reporting information on capital market variables have gained great importance in the accounting literature and became a tool for assessing the usefulness of accounting information. The present study follows the l path of earnings-return research, measuring operating leverage as a substitute for net income shown in the financial statements. It is based on data between the second quarter of 2001 and the third quarter of 2004 referring to firms listed on Bovespa (São Paulo Stock Exchange) and relating to the following sectors: petroleum and gas, basic materials, industrial goods, construction and transportation, non-cyclical consumption, and cyclical consumption. The hypothesis of the study is that since operating leverage, besides being related to earnings (operating earnings), is one of the factors determining the systematic risk of stocks, and since there is a relationship between risk and stock returns, it is possible to infer a positive relationship between the degree of operating leverage and stock returns. Empirical tests carried out using panel data methods suggest that the operating leverage is statistically relevant in explaining the behavior of stock returns and that this relationship is positive, as predicted by theory. The results also demonstrate that statistical relevance increases when stricter parameters are employed for analyzing the data and that the conclusions are not determined by outlier behavior. Unit root tests on the data series as well as autocorrelation and heteroskedasticity tests on the residuals ensure the robustness of the results obtained.