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Australian evidence on the accuracy of analysts' expectations

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  • Xiaomeng Chen

Abstract

Purpose - This paper aims to use Australian analysts' forecast data to compare the relative accuracy of consensus and the most recent forecast in the month before the earnings announcement. Design/methodology/approach - Cross‐sectional regression is used on a sample of 4,358 company‐year observations of annual analyst forecasts to examine whether the number of analysts following and the timeliness of an individual analyst's forecast is more strongly associated with the superior forecast measure. Findings - The results suggest that whilst in the late 1980s the most recent forecast was more accurate than the consensus, since the early 1990s the accuracy of the consensus forecast has outperformed the most recent forecast in 15 out of 17 years, and the differences are significant for nine out of 15 years. The forecasting superiority of the consensus can be attributed to the aggregating value of the consensus outweighing the small timing advantage of the most recent forecast over the short forecast horizon examined in this paper. Research limitations/implications - Given the consistent use of analysts' forecasts as proxies for expected earnings in Australian research, this paper provides insights to what extent the expected level of forecast accuracy is realised and the reasons for the greater accuracy in the superior forecast measure. Practical implications - The findings confirm market practitioners' views that the consensus forecast is a better measure of the market's earnings expectations. Originality/value - This paper provides direct evidence of the accuracy of alternative forecast measures and the importance of diversifying idiosyncratic individual error across analyst forecasts.

Suggested Citation

  • Xiaomeng Chen, 2010. "Australian evidence on the accuracy of analysts' expectations," Accounting Research Journal, Emerald Group Publishing Limited, vol. 23(1), pages 94-116, July.
    • Handle: RePEc:eme:arjpps:v:23:y:2010:i:1:p:94-116
    DOI: 10.1108/10309611011060542
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    Cited by:

    1. Xiaomeng Chen & Sue Wright & Hai Wu, 2018. "Exploration intensity, analysts’ private information development and their forecast performance," Accounting and Business Research, Taylor & Francis Journals, vol. 48(1), pages 77-107, January.

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