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Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: A comparison

Author

Listed:
  • Annarita Colasante

    () (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)

  • Simone Alfarano

    () (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)

  • Eva Camacho-Cuena

    () (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain)

Abstract

We compare the performance of two learning algorithms in replicating individual short and long-run expectations: the Exploration-Explotation Algorithm (EEA) and the Heuristic Switching Model (HSM). Individual expectations are elicited in a series of Learning-to-Forecast Experiments (LtFEs) with different feedback mechanisms between expectations and market price: positive and negative feedback markets. We implement the EEA proposed by Colasante et al. (2018c). Moreover, we modify the existing version of the HSM in order to incorporate the long-run predictions. Although the two algorithms provide a fairly good description of marker prices in the short- run, the EEA outperforms the HSM in replicating the main characteristics of individual expectation in the long-run, both in terms of coordination of individual expectations and convergence of expectations to the fundamental value.

Suggested Citation

  • Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: A comparison," Working Papers 2019/02, Economics Department, Universitat Jaume I, Castellón (Spain).
  • Handle: RePEc:jau:wpaper:2019/02
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    References listed on IDEAS

    as
    1. Lucas, Robert E, Jr & Prescott, Edward C, 1971. "Investment Under Uncertainty," Econometrica, Econometric Society, vol. 39(5), pages 659-681, September.
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    3. Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan & van de Velden, Henk, 2005. "A strategy experiment in dynamic asset pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 823-843, April.
    4. Annarita Colasante & Simone Alfarano & Eva Camacho & Mauro Gallegati, 2018. "Long-run expectations in a learning-to-forecast experiment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 681-687, June.
    5. Assenza, T. & Heemeijer, P. & Hommes, C.H. & Massaro, D., 2011. "Individual Expectations and Aggregate Macro Behavior," CeNDEF Working Papers 11-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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    15. Colasante, Annarita & Alfarano, Simone & Camacho-Cuena, Eva, 2018. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," MPRA Paper 84835, University Library of Munich, Germany.
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    More about this item

    Keywords

    Expectations; Experiment; Evolutionary Learning;

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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