Analyst forecasts: sales and profit margins

Autor: C.S. Agnes Cheng, James A. Ohlson, K.C. Kenneth Chu
Rok vydání: 2020
Předmět:
Zdroj: Review of Accounting Studies. 25:54-83
ISSN: 1573-7136
1380-6653
Popis: Sales and profit margins are two popular earnings components discussed in the media. We study properties of one-year-ahead analyst forecasts of these two components. As sales are in dollar amounts and profit margin is a ratio, we propose robust statistical methods to assess and contrast their forecast properties. We find that four performance properties associated with earnings forecasts—optimism, relative accuracy with respect to benchmark model forecasts, forecast suboptimality, and serial correlation of forecast errors—apply to both sales and profit margins. Sales forecasts, in general, perform better than profit margin forecasts. Further evidence also shows that sales forecasts perform better than profit margin forecasts in terms of how their forecast errors explain earnings forecast errors and how realized surprises affect adjustments of the respective forecasts. We also find that a better information environment, surrogated by size, improves sales forecasts more than profit margin forecasts. All of these findings suggest that forecasting profit margins is inherently more difficult than forecasting sales.
Databáze: OpenAIRE
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