IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2404.08908.html
   My bibliography  Save this paper

Reference Model Based Learning in Expectation Formation: Experimental Evidence

Author

Listed:
  • Jiaoying Pei

Abstract

How do people form expectations about future prices in financial markets? One of the dominant learning rules that explains the forecasting behavior is the Adaptive Expectation Rule (ADA), which suggests that people adjust their predictions by adapting to the most recent prediction error at a constant weight. However, this rule also implies that they will continually learn and adapt until the prediction error is zero, which contradicts recent experimental evidence showing that people usually stop learning long before reaching zero prediction error. A more recent learning rule, Reference Model Based Learning (RMBL), extends and generalizes ADA, hypothesizing that: i) People apply ADA but dynamically adjust the adaptive coefficient with regards to the auto-correlation of the prediction error in the most recent two periods; ii) Meanwhile, they also utilize a satisficing rule so that people would only adjust their adaptive coefficient when the prediction error is higher than their anticipation. This paper utilizes a rich set of experimental data with observations of 41,490 predictions from 801 subjects from the Learning-to-Forecast Experiments (LtFEs), i.e., the experiment that has been used to study expectation formation. Our results concludes that RMBL fits better than ADA in all the experiments.

Suggested Citation

  • Jiaoying Pei, 2024. "Reference Model Based Learning in Expectation Formation: Experimental Evidence," Papers 2404.08908, arXiv.org, revised May 2024.
  • Handle: RePEc:arx:papers:2404.08908
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2404.08908
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    2. Mikhail Anufriev & Cars Hommes, 2012. "Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(4), pages 35-64, November.
    3. Marimon, Ramon & Sunder, Shyam, 1993. "Indeterminacy of Equilibria in a Hyperinflationary World: Experimental Evidence," Econometrica, Econometric Society, vol. 61(5), pages 1073-1107, September.
    4. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    5. Bao, Te & Duffy, John & Hommes, Cars, 2013. "Learning, forecasting and optimizing: An experimental study," European Economic Review, Elsevier, vol. 61(C), pages 186-204.
    6. Tony Berrada & Peter Bossaerts & Giuseppe Ugazio, 2024. "Investments and Asset Pricing in a World of Satisficing Agents," Swiss Finance Institute Research Paper Series 24-05, Swiss Finance Institute.
    7. 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).
    8. Bao, Te & Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan, 2012. "Individual expectations, limited rationality and aggregate outcomes," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1101-1120.
    9. George W. Evans, 2001. "Expectations in Macroeconomics. Adaptive versus Eductive Learning," Revue Économique, Programme National Persée, vol. 52(3), pages 573-582.
    10. Te Bao & Cars Hommes & Tomasz Makarewicz, 2017. "Bubble Formation and (In)Efficient Markets in Learning‐to‐forecast and optimise Experiments," Economic Journal, Royal Economic Society, vol. 127(605), pages 581-609, October.
    11. Hommes, Cars & Sorger, Gerhard, 1998. "Consistent Expectations Equilibria," Macroeconomic Dynamics, Cambridge University Press, vol. 2(3), pages 287-321, September.
    12. Sonnemans, Joep & Hommes, Cars & Tuinstra, Jan & van de Velden, Henk, 2004. "The instability of a heterogeneous cobweb economy: a strategy experiment on expectation formation," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 453-481, August.
    13. Te Bao & Cars Hommes & Tomasz Makarewicz, 2017. "Bubble Formation and (In)Efficient Markets in Learning‐to‐forecast and optimise Experiments," Economic Journal, Royal Economic Society, vol. 127(605), pages 581-609, October.
    14. Bao, Te & Hommes, Cars, 2019. "When speculators meet suppliers: Positive versus negative feedback in experimental housing markets," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Hommes, Cars, 2018. "Behavioral & experimental macroeconomics and policy analysis: a complex systems approach," Working Paper Series 2201, European Central Bank.
    3. Tiziana Assenza & Te Bao & Cars Hommes & Domenico Massaro, 2014. "Experiments on Expectations in Macroeconomics and Finance," Research in Experimental Economics, in: Experiments in Macroeconomics, volume 17, pages 11-70, Emerald Group Publishing Limited.
    4. Arifovic, Jasmina & Hommes, Cars & Salle, Isabelle, 2019. "Learning to believe in simple equilibria in a complex OLG economy - evidence from the lab," Journal of Economic Theory, Elsevier, vol. 183(C), pages 106-182.
    5. Zhu, Jiahua & Bao, Te & Chia, Wai Mun, 2021. "Evolutionary selection of forecasting and quantity decision rules in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 363-404.
    6. Dávid Kopányi & Jean Paul Rabanal & Olga A. Rud & Jan Tuinstra, 2019. "Can successful forecasters help stabilize asset prices in a learning to forecast experiment?," Working Papers 140, Peruvian Economic Association.
    7. Kopányi, Dávid & Rabanal, Jean Paul & Rud, Olga A. & Tuinstra, Jan, 2019. "Can competition between forecasters stabilize asset prices in learning to forecast experiments?," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    8. Bao, Te & Hennequin, Myrna & Hommes, Cars & Massaro, Domenico, 2020. "Coordination on bubbles in large-group asset pricing experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    9. 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.
    10. Zhou Lu & Te Bao & Xiaohua Yu, 2021. "Gender and Bubbles in Experimental Markets with Positive and Negative Expectation Feedback," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1307-1326, April.
    11. Giamattei, Marcus & Huber, Jürgen & Lambsdorff, Johann Graf & Nicklisch, Andreas & Palan, Stefan, 2020. "Who inflates the bubble? Forecasters and traders in experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    12. 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.
    13. Fatemeh Mokhtarzadeh & Luba Petersen, 2021. "Coordinating expectations through central bank projections," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 883-918, September.
    14. 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.
    15. 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.
    16. Colasante, Annarita & Palestrini, Antonio & Russo, Alberto & Gallegati, Mauro, 2017. "Adaptive expectations versus rational expectations: Evidence from the lab," International Journal of Forecasting, Elsevier, vol. 33(4), pages 988-1006.
    17. Hommes, Cars H., 2014. "Behaviorally Rational Expectations and Almost Self-Fulfilling Equilibria," Review of Behavioral Economics, now publishers, vol. 1(1-2), pages 75-97, January.
    18. Bao, Te & Duffy, John, 2016. "Adaptive versus eductive learning: Theory and evidence," European Economic Review, Elsevier, vol. 83(C), pages 64-89.
    19. Nobuyuki Hanaki & Cars Hommes & Dávid Kopányi & Anita Kopányi-Peuker & Jan Tuinstra, 2023. "Forecasting returns instead of prices exacerbates financial bubbles," Experimental Economics, Springer;Economic Science Association, vol. 26(5), pages 1185-1213, November.
    20. 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.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2404.08908. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.