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Are analysts' loss functions asymmetric?

Research output: Contribution to journalJournal article

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Are analysts' loss functions asymmetric? / Peel, David; Pope, Peter F.; Clatworthy, Mark.

In: Journal of Forecasting, Vol. 31, No. 8, 12.2012, p. 736-756.

Research output: Contribution to journalJournal article

Harvard

Peel, D, Pope, PF & Clatworthy, M 2012, 'Are analysts' loss functions asymmetric?', Journal of Forecasting, vol. 31, no. 8, pp. 736-756. https://doi.org/10.1002/for.1253

APA

Peel, D., Pope, P. F., & Clatworthy, M. (2012). Are analysts' loss functions asymmetric? Journal of Forecasting, 31(8), 736-756. https://doi.org/10.1002/for.1253

Vancouver

Peel D, Pope PF, Clatworthy M. Are analysts' loss functions asymmetric? Journal of Forecasting. 2012 Dec;31(8):736-756. https://doi.org/10.1002/for.1253

Author

Peel, David ; Pope, Peter F. ; Clatworthy, Mark. / Are analysts' loss functions asymmetric?. In: Journal of Forecasting. 2012 ; Vol. 31, No. 8. pp. 736-756.

Bibtex

@article{e2ca59d4f97e4fcfa79144acbb80e659,
title = "Are analysts' loss functions asymmetric?",
abstract = "Despite displaying a statistically significant optimism bias, analysts' earnings forecasts are an important input to investors{\textquoteright} 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.",
author = "David Peel and Pope, {Peter F.} and Mark Clatworthy",
year = "2012",
month = dec,
doi = "10.1002/for.1253",
language = "English",
volume = "31",
pages = "736--756",
journal = "Journal of Forecasting",
issn = "0277-6693",
publisher = "John Wiley and Sons Ltd",
number = "8",

}

RIS

TY - JOUR

T1 - Are analysts' loss functions asymmetric?

AU - Peel, David

AU - Pope, Peter F.

AU - Clatworthy, Mark

PY - 2012/12

Y1 - 2012/12

N2 - 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.

AB - 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.

U2 - 10.1002/for.1253

DO - 10.1002/for.1253

M3 - Journal article

VL - 31

SP - 736

EP - 756

JO - Journal of Forecasting

JF - Journal of Forecasting

SN - 0277-6693

IS - 8

ER -