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Effects of different ways of incentivizing price forecasts on market dynamics and individual decisions in asset market experiments

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  • Nobuyuki Hanaki

    () (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis - UCA - Université Côte d'Azur - CNRS - Centre National de la Recherche Scientifique)

  • Eizo Akiyama

    () (University of Tsukuba)

  • Ryuichiro Ishikawa

    () (Waseda University)

Abstract

In this study, we investigate (a) whether eliciting future price forecasts influences market outcomes and (b) whether differences in the way in which subjects are incentivized to submit " accurate " price forecasts influence market outcomes as well as the forecasts in an experimental asset market. We consider four treatments: one without forecast elicitation and three with forecast elicitation. In two of the treatments with forecast elicitation, subjects are paid based on their performance in both forecasting and trading, while in the other treatment with forecast elicitations, they are paid based on only one of those factors, which is chosen randomly at the end of the experiment. We found no significant effect of forecast elicitation on market outcomes in the latter case. Thus, to avoid influencing the behavior of subjects and market outcomes by eliciting price forecasts, paying subjects based on either forecasting or trading performance chosen randomly at the end of the experiment is better than paying them based on both. In addition, we consider forecast-only experiments: one in which subjects are rewarded based on the number of accurate forecasts and the other in which they are rewarded based on a quadratic scoring rule. We found no significant difference in terms of forecasting performance between the two.

Suggested Citation

  • Nobuyuki Hanaki & Eizo Akiyama & Ryuichiro Ishikawa, 2018. "Effects of different ways of incentivizing price forecasts on market dynamics and individual decisions in asset market experiments ," Post-Print hal-01712305, HAL.
  • Handle: RePEc:hal:journl:hal-01712305
    DOI: 10.1016/j.jedc.2018.01.018
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-01712305
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    References listed on IDEAS

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    1. Sonnemans, Joep & Tuinstra, Jan, 2010. "Positive expectations feedback experiments and number guessing games as models of financial markets," Journal of Economic Psychology, Elsevier, vol. 31(6), pages 964-984, December.
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    3. Akiyama, Eizo & Hanaki, Nobuyuki & Ishikawa, Ryuichiro, 2014. "How do experienced traders respond to inflows of inexperienced traders? An experimental analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 1-18.
    4. John Beshears & James J. Choi & Andreas Fuster & David Laibson & Brigitte C. Madrian, 2013. "What Goes Up Must Come Down? Experimental Evidence on Intuitive Forecasting," American Economic Review, American Economic Association, vol. 103(3), pages 570-574, May.
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    7. Marimon Ramon & Spear Stephen E. & Sunder Shyam, 1993. "Expectationally Driven Market Volatility: An Experimental Study," Journal of Economic Theory, Elsevier, vol. 61(1), pages 74-103, October.
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    10. Heemeijer, Peter & Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan, 2009. "Price stability and volatility in markets with positive and negative expectations feedback: An experimental investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1052-1072, May.
    11. Bao, T. & Hommes, C.H. & Makarewicz, T.A., 2014. "Bubble Formation and (In)efficient Markets in Learning-to-Forecast and -Optimize Experiments," CeNDEF Working Papers 14-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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