Home > Research > Publications & Outputs > Are analysts’ loss functions asymmetric?

Electronic data

View graph of relations

Are analysts’ loss functions asymmetric?

Research output: Working paper

Published

Standard

Are analysts’ loss functions asymmetric? / Clatworthy, M A; Peel, D; Pope, P F.

Lancaster University : The Department of Economics, 2006. (Economics Working Paper Series).

Research output: Working paper

Harvard

Clatworthy, MA, Peel, D & Pope, PF 2006 'Are analysts’ loss functions asymmetric?' Economics Working Paper Series, The Department of Economics, Lancaster University.

APA

Clatworthy, M. A., Peel, D., & Pope, P. F. (2006). Are analysts’ loss functions asymmetric? (Economics Working Paper Series). The Department of Economics.

Vancouver

Clatworthy MA, Peel D, Pope PF. Are analysts’ loss functions asymmetric? Lancaster University: The Department of Economics. 2006. (Economics Working Paper Series).

Author

Clatworthy, M A ; Peel, D ; Pope, P F. / Are analysts’ loss functions asymmetric?. Lancaster University : The Department of Economics, 2006. (Economics Working Paper Series).

Bibtex

@techreport{d70c7aab0cb84695a55873bd84bf2587,
title = "Are analysts{\textquoteright} loss functions asymmetric?",
abstract = "Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts{\textquoteright} earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is skewed. An alternative explanation for forecast bias is that analysts have asymmetric loss functions. We test this alternative explanation. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on forecast error skewness. Our results confirm that the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on forecast error skewness is opposite to that found in prior research. Our results are consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across style portfolios formed on book-to-price and market capitalization. These firm characteristics capture systematic variation in forecast error variance and skewness. Within style portfolios, forecast error variance continues to play a dominant role in explaining forecast error.",
author = "Clatworthy, {M A} and D Peel and Pope, {P F}",
year = "2006",
language = "English",
series = "Economics Working Paper Series",
publisher = "The Department of Economics",
type = "WorkingPaper",
institution = "The Department of Economics",

}

RIS

TY - UNPB

T1 - Are analysts’ loss functions asymmetric?

AU - Clatworthy, M A

AU - Peel, D

AU - Pope, P F

PY - 2006

Y1 - 2006

N2 - Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts’ earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is skewed. An alternative explanation for forecast bias is that analysts have asymmetric loss functions. We test this alternative explanation. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on forecast error skewness. Our results confirm that the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on forecast error skewness is opposite to that found in prior research. Our results are consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across style portfolios formed on book-to-price and market capitalization. These firm characteristics capture systematic variation in forecast error variance and skewness. Within style portfolios, forecast error variance continues to play a dominant role in explaining forecast error.

AB - Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts’ earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is skewed. An alternative explanation for forecast bias is that analysts have asymmetric loss functions. We test this alternative explanation. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on forecast error skewness. Our results confirm that the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on forecast error skewness is opposite to that found in prior research. Our results are consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across style portfolios formed on book-to-price and market capitalization. These firm characteristics capture systematic variation in forecast error variance and skewness. Within style portfolios, forecast error variance continues to play a dominant role in explaining forecast error.

M3 - Working paper

T3 - Economics Working Paper Series

BT - Are analysts’ loss functions asymmetric?

PB - The Department of Economics

CY - Lancaster University

ER -