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Are analysts' loss functions asymmetric?

Clatworthy, Mark A., Peel, David A. and Pope, Peter (2012) Are analysts' loss functions asymmetric? Journal of Forecasting, 31 (8). pp. 736-756. ISSN 0277-6693

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Identification Number: 10.1002/for.1253

Abstract

Despite displaying a statistically significant optimism bias, analysts' earnings forecasts are an important input to investors’ valuation models. Understanding the possible reasons for any bias is important if information is to be extracted from earnings forecasts and used optimally by investors. Extant research into the shape of analysts' loss functions explains optimism bias as resulting from analysts minimizing the mean absolute forecast error under symmetric, linear loss functions. When the distribution of earnings outcomes is skewed, optimalforecasts can appear biased. In contrast, research into analysts' economic incentives suggests that positive and negative earnings forecast errors made by analysts are not penalized or rewarded symmetrically, suggesting that asymmetric loss functions are an appropriate characterization. To reconcile these findings, we exploit results from economic theory relating to the Linex loss function to discriminate between the symmetric linear loss and the asymmetric loss explanations of analyst forecast bias. Under asymmetric loss functions optimal forecasts will appear biased even if earnings outcomes are symmetric. Our empirical results support the asymmetric loss function explanation. Further analysis also reveals that forecast bias varies systematically across firm characteristics that capture systematic variation in the earnings forecast error distribution.

Item Type: Article
Official URL: http://onlinelibrary.wiley.com/journal/10.1002/(IS...
Additional Information: © 2011 John Wiley & Sons, Ltd
Divisions: Accounting
Subjects: H Social Sciences > HG Finance
JEL classification: M - Business Administration and Business Economics; Marketing; Accounting > M4 - Accounting and Auditing > M41 - Accounting
Sets: Departments > Accounting
Date Deposited: 23 Oct 2013 08:06
Last Modified: 30 Jan 2019 18:58
URI: http://eprints.lse.ac.uk/id/eprint/53731

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