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Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments

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  • Anufriev, M.

    (University of Technology, Sydney)

  • Hommes, C.H.

    (University of Amsterdam)

  • Makarewicz, T.A.

    (University of Amsterdam)

Abstract

We study a model in which individual agents use simple linear first order price forecasting rules, adapting them to the complex evolving market environment with a smart Genetic Algorithm optimization procedure. The novelties are: (1) a parsimonious experimental foundation of individual forecasting behaviour; (2) an explanation of individual and aggregate behavior in four different experimental settings, (3) improved one-period and 50-period ahead forecasting of lab experiments, and (4) a characterization of the mean, median and empirical distribution of forecasting heuristics. The median of the distribution of GA forecasting heuristics can be used in designing or validating simple Heuristic Switching Model.

Suggested Citation

  • Anufriev, M. & Hommes, C.H. & Makarewicz, T.A., 2015. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," CeNDEF Working Papers 15-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    • Handle: RePEc:ams:ndfwpp:15-07
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    Cited by:

    1. Nobuyuki Hanaki & Eizo Akiyama & Ryuichiro Ishikawa, 2017. "Effects of eliciting long-run price forecasts on market dynamics in asset market experiments," Working Papers halshs-01263661, HAL.
    2. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    3. Anufriev, Mikhail & Chernulich, Aleksei & Tuinstra, Jan, 2022. "Asset price volatility and investment horizons: An experimental investigation," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 19-48.
    4. Makarewicz, Tomasz, 2021. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 626-673.
    5. Jasmina Arifovic & Isabelle Salle & Hung Truong, 2023. "History-Dependent Monetary Regimes: A Lab Experiment and a Henk Model," Tinbergen Institute Discussion Papers 23-028/VI, Tinbergen Institute.
    6. Thorp, S. & Bateman, H. & Dobrescu, L.I. & Newell, B.R. & Ortmann, A., 2020. "Flicking the switch: Simplifying disclosure to improve retirement plan choices," Journal of Banking & Finance, Elsevier, vol. 121(C).
    7. Cars Hommes & Tomasz Makarewicz & Domenico Massaro & Tom Smits, 2017. "Genetic algorithm learning in a New Keynesian macroeconomic setup," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1133-1155, November.
    8. Mikhail Anufriev & John Duffy & Valentyn Panchenko, "undated". "Planar Beauty Contests," Discussion Papers 2019-06, School of Economics, The University of New South Wales.
    9. Cars Hommes & Anita Kopányi-Peuker & Joep Sonnemans, 2021. "Bubbles, crashes and information contagion in large-group asset market experiments," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 414-433, June.
    10. Hanaki, Nobuyuki & Akiyama, Eizo & Ishikawa, Ryuichiro, 2018. "Effects of different ways of incentivizing price forecasts on market dynamics and individual decisions in asset market experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 88(C), pages 51-69.
    11. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    12. Leonid Serkov & Sergey Krasnykh, 2023. "The Specific Behavior of Economic Agents with Heterogeneous Expectations in the New Keynesian Model with Rigid Prices and Wages," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    13. Makarewicz, Tomasz, 2019. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series 141, Bamberg University, Bamberg Economic Research Group.
    14. Chernulich, Aleksei, 2021. "Modelling reference dependence for repeated choices: A horse race between models of normalisation," Journal of Economic Psychology, Elsevier, vol. 87(C).
    15. Annicchiarico, Barbara & Surricchio, Silvia & Waldmann, Robert J., 2019. "A behavioral model of the credit cycle," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 53-83.
    16. Mauersberger, Felix, 2021. "Monetary policy rules in a non-rational world: A macroeconomic experiment," Journal of Economic Theory, Elsevier, vol. 197(C).
    17. Deborah Noguera & Gabriel Montes-Rojas, 2023. "Minskyan model with credit rationing in a network economy," SN Business & Economics, Springer, vol. 3(3), pages 1-26, March.
    18. Hommes, Cars & Makarewicz, Tomasz, 2021. "Price level versus inflation targeting under heterogeneous expectations: a laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 39-82.
    19. Hommes, Cars, 2018. "Behavioral & experimental macroeconomics and policy analysis: a complex systems approach," Working Paper Series 2201, European Central Bank.
    20. Anufriev, Mikhail & Arifovic, Jasmina & Ledyard, John & Panchenko, Valentyn, 2022. "The role of information in a continuous double auction: An experiment and learning model," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).
    21. Domenico Colucci & Matteo Vigna & Vincenzo Valori, 2022. "Large and uncertain heterogeneity of expectations: stability of equilibrium from a policy maker standpoint," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 319-348, January.
    22. Bao, Te & Füllbrunn, Sascha & Pei, Jiaoying & Zong, Jichuan, 2024. "Reading the market? Expectation coordination and theory of mind," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 510-527.
    23. Noussair, Charles N. & Popescu, Andreea Victoria, 2021. "Comovement and return predictability in asset markets: An experiment with two Lucas trees," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 671-687.
    24. Tomasz Makarewicz, 2017. "Contrarian Behavior, Information Networks and Heterogeneous Expectations in an Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 231-279, August.

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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