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Dynamic forecasting behavior by analysts: Theory and evidence


  • Clarke, Jonathan
  • Subramanian, Ajay


We examine the dynamic forecasting behavior of security analysts in response to their prior performance relative to their peers within a continuous time/multi-period framework. Our model predicts a U-shaped relationship between the boldness of an analyst's forecast, that is, the deviation of her forecast from the consensus and her prior relative performance. In other words, analysts who significantly out perform or under perform their peers issue bolder forecasts than intermediate performers. We then test these predictions of our model on observed analyst forecast data. Consistent with our theoretical predictions, we document an approximately U-shaped relationship between analysts' prior relative performance and the deviation of their forecasts from the consensus. Our theory examines the impact of both explicit incentives in the form of compensation structures and implicit incentives in the form of career concerns, on the dynamic forecasting behavior of analysts. Consistent with existing empirical evidence, our results imply that analysts who face greater employment risk (that is, the risk of being fired for poor performance) have greater incentives to herd, that is, issue forecasts that deviate less from the consensus. Our multi-period model allows us to examine the dynamic forecasting behavior of analysts in contrast with the extant two-period models that are static in nature. Moreover, the model also differs significantly from existing theoretical models in that it does not rely on any specific assumptions regarding the existence of asymmetric information and/or differential analyst abilities.
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  • Clarke, Jonathan & Subramanian, Ajay, 2006. "Dynamic forecasting behavior by analysts: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 80(1), pages 81-113, April.
  • Handle: RePEc:eee:jfinec:v:80:y:2006:i:1:p:81-113

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    References listed on IDEAS

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    2. Choi, Hyung Suk & Clarke, Jonathan & Ferris, Stephen P. & Jayaraman, Narayanan, 2009. "The effects of regulation on industry structure and trade generation in the US securities industry," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1434-1445, August.
    3. Régis Breton & Sébastien Galanti & Christophe Hurlin & Anne-Gaël Vaubourg, 2013. "Does the firm-analyst relationship matter in explaining analysts' earnings forecast errors?," Working Papers hal-00862996, HAL.
    4. Rocco Ciciretti & Gerald P. Dwyer & Iftekhar Hasan, 2009. "Investment analysts' forecasts of earnings," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 545-568.
    5. Hilary, Gilles & Hsu, Charles, 2011. "Endogenous overconfidence in managerial forecasts," Journal of Accounting and Economics, Elsevier, vol. 51(3), pages 300-313, April.
    6. Kempf, Alexander & Ruenzi, Stefan & Thiele, Tanja, 2009. "Employment risk, compensation incentives, and managerial risk taking: Evidence from the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 92(1), pages 92-108, April.
    7. Papastamos, Dimitrios & Matysiak, George & Stevenson, Simon, 2015. "Assessing the accuracy and dispersion of real estate investment forecasts," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 141-152.
    8. Nikolaos Theriou & George Mlekanis & Dimitrios Maditinos, 2011. "Herding the Mutual Fund Managers in the Athens Stock Exchange," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 131-154.
    9. Ramnath, Sundaresh & Rock, Steve & Shane, Philip, 2008. "The financial analyst forecasting literature: A taxonomy with suggestions for further research," International Journal of Forecasting, Elsevier, vol. 24(1), pages 34-75.
    10. Anne-Gael Vaubourg & Valdete Berisha-Krasniqui & Sébastien Galanti & Christophe Hurlin & Régis Breton, 2013. "We study whether financial analysts' concern for preserving good relationships with firms' managers motivates them to issue pessimistic or optimistic forecasts. Based on a dataset of one-yearahead EPS," Larefi Working Papers 1304, Larefi, Université Bordeaux 4.
    11. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188,
    12. Jerry, Sun, 2011. "The Effect of Analyst Coverage on the Informativeness of Income Smoothing," The International Journal of Accounting, Elsevier, vol. 46(3), pages 333-349, September.
    13. Dimitrios Papastamos & George Matysiak & Simon Stevenson, 2014. "A Comparative Analysis of the Accuracy and Uncertainty in Real Estate and Macroeconomic Forecasts," Real Estate & Planning Working Papers rep-wp2014-06, Henley Business School, Reading University.
    14. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," Center for European, Governance and Economic Development Research Discussion Papers 195, University of Goettingen, Department of Economics.
    15. Bosquet, K. & de Goeij, P. C. & Smedts, K., 2009. "Coexistence and Dynamics of Overconfidence and Strategic Incentives," Discussion Paper 2009-81, Tilburg University, Center for Economic Research.
    16. Derann Hsu & Cheng-Huei Chiao, 2011. "Relative accuracy of analysts’ earnings forecasts over time: a Markov chain analysis," Review of Quantitative Finance and Accounting, Springer, vol. 37(4), pages 477-507, November.
    17. Marinovic, Iván & Ottaviani, Marco & Sorensen, Peter, 2013. "Forecasters’ Objectives and Strategies," Handbook of Economic Forecasting, Elsevier.

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    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage


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