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Financial markets forecasts revisited: are they rational, herding or bold?

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Listed:
  • Ippei Fujiwara
  • Hibiki Ichiue
  • Yoshiyuki Nakazono
  • Yosuke Shigemi

Abstract

We test whether professional forecasters forecast rationally or behaviorally using a unique database, QSS Database, which is the monthly panel of forecasts on Japanese stock prices and bond yields. The estimation results show that (i) professional forecasts are behavioral, namely, significantly influenced by past forecasts, (ii) there exists a stock-bond dissonance: while forecasting behavior in the stock market seems to be herding, that in the bond market seems to be bold in the sense that their current forecasts tend to be negatively related to past forecasts, and (iii) the dissonance is due, at least partially, to the individual forecasters' behavior that is influenced by their own past forecasts rather than others. Even in the same country, forecasting behavior is quite different by market.

Suggested Citation

  • Ippei Fujiwara & Hibiki Ichiue & Yoshiyuki Nakazono & Yosuke Shigemi, 2012. "Financial markets forecasts revisited: are they rational, herding or bold?," Globalization Institute Working Papers 106, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddgw:106
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    References listed on IDEAS

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    Cited by:

    1. Meub, Lukas & Proeger, Till, 2016. "Are groups 'less behavioral'? The case of anchoring," University of Göttingen Working Papers in Economics 188 [rev.], University of Goettingen, Department of Economics.
    2. Meub, Lukas & Proeger, Till, 2016. "Can anchoring explain biased forecasts? Experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 12(C), pages 1-13.
    3. Meub, Lukas & Proeger, Till & Bizer, Kilian, 2013. "Anchoring: A valid explanation for biased forecasts when rational predictions are easily accessible and well incentivized?," University of Göttingen Working Papers in Economics 166, University of Goettingen, Department of Economics.
    4. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena & Mauro Gallegati, 2020. "Long-run expectations in a learning-to-forecast experiment: a simulation approach," Journal of Evolutionary Economics, Springer, vol. 30(1), pages 75-116, January.
    5. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 491-520, September.
    6. Francesca Pancotto & Filippo Maria Pericoli & Marco Pistagnesi, 2013. "Inefficiency in Survey Exchange Rates Forecasts," Working Papers 1/13, Sapienza University of Rome, DISS.
    7. Tzu-Pu CHANG, Ray Yeutien CHOU & Ray Yeutien CHOU, 2018. "Anchoring Effect on Macroeconomic Forecasts : A Heterogeneity Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 134-147, December.
    8. Nakazono, Yoshiyuki, 2013. "Strategic behavior of Federal Open Market Committee board members: Evidence from members’ forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 62-70.
    9. Ibrahim Filiz & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2021. "Sticky Stock Market Analysts," JRFM, MDPI, vol. 14(12), pages 1-27, December.
    10. Meub, Lukas & Proeger, Till, 2014. "Are groups 'less behavioral'? The case of anchoring," University of Göttingen Working Papers in Economics 188, University of Goettingen, Department of Economics.
    11. Meub, Lukas & Proeger, Till, 2014. "An experimental study on social anchoring," University of Göttingen Working Papers in Economics 196, University of Goettingen, Department of Economics.

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    More about this item

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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