Determinants of analysts’ revenue forecast accuracy

Tanja Lorenz () and Carsten Homburg
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Tanja Lorenz: University of Cologne
Carsten Homburg: University of Cologne

Review of Quantitative Finance and Accounting, 2018, vol. 51, issue 2, No 5, 389-431

Abstract: Abstract This study investigates financial analysts’ revenue forecasts and identifies determinants of the forecasts’ accuracy. We find that revenue forecast accuracy is determined by forecast and analyst characteristics similar to those of earnings forecast accuracy—namely, forecast horizon, days elapsed since the last forecast, analysts’ forecasting experience, forecast frequency, forecast portfolio, reputation, earnings forecast issuance, forecast boldness, and analysts’ prior performance in forecasting revenues and earnings. We develop a model that predicts the usefulness of revenue forecasts. Thereby, our study helps to ex ante identify more accurate revenue forecasts. Furthermore, we find that analysts concern themselves with their revenue forecasting performance. Analysts with poor revenue forecasting performance are more likely to stop forecasting revenues than analysts with better performance. Their decision is reasonable because revenue forecast accuracy affects analysts’ career prospects in terms of being promoted or terminated. Our study helps investors and academic researchers to understand determinants of revenue forecasts. This understanding is also beneficial for evaluating earnings forecasts because revenue forecasts reveal whether changes in earnings forecasts are due to anticipated changes in revenues or expenses.

Keywords: Financial analysts; Revenue forecasts; Earnings forecasts; Forecast accuracy; Disaggregated forecasts (search for similar items in EconPapers)
JEL-codes: G24 G29 M41 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11156-017-0675-4

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