Estimating analyst's forecast accuracy using behavioural measures (Herding) in the United Kingdom

• Published in: Managerial finance Vol. 36; no. 3; pp. 234 - 256
• Main Authors: Salamouris, Ioannis S, Gulnur Muradoglu, Yaz
• Format: Journal Article
• Language: English
• Published: Patrington Emerald Group Publishing Limited 23-02-2010
• Subjects: Accuracy; Behavior; Decision making; Earnings; Earnings forecasting; Financial analysis; Peers; Reputations; Studies; United Kingdom > UK; United Kingdom; Accuracy; Financial forecasting; Behaviour; Financial analysis
• ISSN: 0307-4358; 1758-7743
• DOI: 10.1108/03074351011019564

Purpose - The purpose of this paper is to identify herding behaviour on financial markets and measure the herding behaviour impact on the accuracy of analysts' earnings forecasts.Design methodology approach - Two alternative measures of herding behaviour, on analysts' earnings forecasts are proposed. The first measure identifies herding as the tendency of analysts to forecast near the consensus. The second measure identifies herding as the tendency of analysts to follow the most accurate forecaster. This paper employs the method of The Generalised Method of Moments in order to relax any possible biases.Findings - In both measures employed, a positive and significant relation is found between the accuracy of analysts' earnings forecasts and herding behaviour. According to the first measure analysts exhibit herding behaviour by forecasting close to the consensus estimates. According the second herding measure, it is found that analysts tend to herd towards the best forecaster at the time. Finally, it is concluded that the accuracy of analysts' forecasts increases as herding increases.Research limitations implications - The present study triggers concerns for further research in the modelling of analysts' forecasting behaviour.Originality value - This paper proposes that a measure based on human biases is the best way to estimate and predict the analysts' earnings forecast future accuracy.