Using industry -adjusted DuPont analysis to predict future profitability and returns.

Abstract

Industry peer groups serve as both a theoretical and an intuitive benchmark in financial statement analysis. However, the practice of industry-adjusting financial ratios is sparse in existing financial statement analysis research. This paper investigates whether using industry-adjusted DuPont analysis is a useful tool in predicting future changes in return-on-net-operating assets (<italic>RNOA</italic>). DuPont analysis decomposes <italic>RNOA</italic> into two multiplicative components: profit margin and asset turnover, both of which are largely driven by industry membership. In contrast to prior research, which finds that these components are not useful in forecasting when compared with economy-wide means, I find that these two industry-adjusted components exhibit different mean reversion patterns and that using this information helps predict future changes in <italic>RNOA</italic>. This explanatory power remains significant in out-of-sample forecasts of five-year-ahead <italic> RNOA</italic>. Finally, I examine whether market participants understand these future profitability implications. I create a trading strategy that employs the information contained in these components and find that, although market participants understand the mean reversion of abnormal <italic>RNOA</italic> as a whole, a trading strategy that exploits the information in industry-adjusted asset turnover earns positive abnormal returns.