The Incremental Effect of earnings Components’ Volatility and their Persistence on Earnings Predictability

Abstract

The result of prior research shows that if the volatility of earnings increases and their persistence decreases, past earnings aren’t good predictors of future earnings. Relative to aggregate earnings, earnings components will be more informative for firms whose earnings components have different persistence and volatility. We examine whether these earnings components have incremental information content relative to aggregate earnings, and then we construct a model to describe the effect of components’ volatility and their persistence on earnings predictability. In this study, the analyses are based on a sample of 33 firms listed in Tehran Stock Exchange. Data needed are derived from financial statements of companies listed in TSE. To test our hypotheses, we use data for years from 2002 to 2016. The results of study show that higher persistence and lower volatility of components will increase earnings predictability. Among the main components used in the research, sales, cost of goods sold, employee expenses, depreciation, other general, administrative and selling expenses, and interest expenses improve earnings predictability.

Keywords

• earnings components
• predictability
• persistence and volatility