Disaggregated earnings and the prediction of ROE and stock prices: a case of the banking industry

Abstract

Purpose This paper seeks to investigate whether disaggregated bank earnings better predict next period earnings than contemporaneous aggregated earnings. Design/methodology/approach Fairfield et al.'s (1996) regression approach is used for predicting next period's return of equity (ROE) and stock prices using disaggregated earnings data. Findings The results show that the mean adjusted R‐square significantly increases with the progressive disaggregation of earnings. The results also demonstrate that disaggregated components are better able to predict next period earnings and stock prices than aggregated earnings. Research limitations/implications The findings support the US Financial Accounting Standard Board's contention that disaggregated information may be more useful than aggregated information for investment, credit, and financing decisions. Practical implications Investors and analysts should use disaggregated income statement information in predicting next period earnings and stock prices for the banking industry. Originality/value The main contribution of this paper is to demonstrate how fully disaggregated earnings explain ROE, stock prices, and analysts forecast error in the banking industry.

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