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Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics

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  • Makarewicz, Tomasz

Abstract

Behavioral and experimental literature on financial instability focuses on either subjective price expectations (Learning-to-Forecast experiments) or individual trading (Learning-to-Optimize experiments). Bao et al. (2017) have shown that subjects have problems with both tasks. In this paper, I explore these experimental results by investigating a model in which financial traders individually learn how to use forecasting and/or trading anchor-and-adjustment heuristics by updating them with Genetic Algorithms. The model replicates the main outcomes of these two threads of the experimental finance literature. It shows that both forecasters and traders coordinate on chasing asset price trends, which in turn causes substantial and self-fulfilling price oscillations, albeit larger and faster in the case of trading markets. When agents have to learn both tasks, financial instability becomes more persistent.

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  • 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.
  • Handle: RePEc:zbw:bamber:141
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    1. Anufriev, Mikhail & Kopányi, Dávid & Tuinstra, Jan, 2013. "Learning cycles in Bertrand competition with differentiated commodities and competing learning rules," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2562-2581.
    2. Rutström, E. Elisabet & Wilcox, Nathaniel T., 2009. "Stated beliefs versus inferred beliefs: A methodological inquiry and experimental test," Games and Economic Behavior, Elsevier, vol. 67(2), pages 616-632, November.
    3. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
    4. Hommes, Cars & Lux, Thomas, 2013. "Individual Expectations And Aggregate Behavior In Learning-To-Forecast Experiments," Macroeconomic Dynamics, Cambridge University Press, vol. 17(2), pages 373-401, March.
    5. 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.
    6. Lei, Vivian & Noussair, Charles N & Plott, Charles R, 2001. "Nonspeculative Bubbles in Experimental Asset Markets: Lack of Common Knowledge of Rationality vs. Actual Irrationality," Econometrica, Econometric Society, vol. 69(4), pages 831-859, July.
    7. Matthias Weber & John Duffy & Arthur Schram, 2018. "An Experimental Study of Bond Market Pricing," Journal of Finance, American Finance Association, vol. 73(4), pages 1857-1892, August.
    8. Dieci, Roberto & Schmitt, Noemi & Westerhoff, Frank, 2018. "Interactions between stock, bond and housing markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 43-70.
    9. Martin Dufwenberg & Tobias Lindqvist & Evan Moore, 2005. "Bubbles and Experience: An Experiment," American Economic Review, American Economic Association, vol. 95(5), pages 1731-1737, December.
    10. Miguel A. Costa-Gomes & Georg Weizsäcker, 2008. "Stated Beliefs and Play in Normal-Form Games," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(3), pages 729-762.
    11. Charles N. Noussair & Steven Tucker, 2013. "Experimental Research On Asset Pricing," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 554-569, July.
    12. Frijns, Bart & Lehnert, Thorsten & Zwinkels, Remco C.J., 2010. "Behavioral heterogeneity in the option market," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2273-2287, November.
    13. Mikhail Anufriev & Cars Hommes & Raoul Philipse, 2013. "Evolutionary selection of expectations in positive and negative feedback markets," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 663-688, July.
    14. 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.
    15. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    16. Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan & Van De Velden, Henk, 2007. "Learning In Cobweb Experiments," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 8-33, November.
    17. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    18. Hommes,Cars, 2015. "Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems," Cambridge Books, Cambridge University Press, number 9781107564978.
    19. Mikhail Anufriev & Cars Hommes & Tomasz Makarewicz, 2019. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," Journal of the European Economic Association, European Economic Association, vol. 17(5), pages 1538-1584.
    20. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    21. John Duffy & Margit Tavits, 2008. "Beliefs and Voting Decisions: A Test of the Pivotal Voter Model," American Journal of Political Science, John Wiley & Sons, vol. 52(3), pages 603-618, July.
    22. 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.
    23. John Duffy & M. Ünver, 2006. "Asset price bubbles and crashes with near-zero-intelligence traders," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 27(3), pages 537-563, April.
    24. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    25. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    26. Cars Hommes, 2013. "Reflexivity, expectations feedback and almost self-fulfilling equilibria: economic theory, empirical evidence and laboratory experiments," Journal of Economic Methodology, Taylor & Francis Journals, vol. 20(4), pages 406-419, December.
    27. Cars Hommes & Joep Sonnemans & Jan Tuinstra & Henk van de Velden, 2005. "Coordination of Expectations in Asset Pricing Experiments," Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 955-980.
    28. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
    29. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
    30. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
    31. Ernan Haruvy & Yaron Lahav & Charles N. Noussair, 2007. "Traders' Expectations in Asset Markets: Experimental Evidence," American Economic Review, American Economic Association, vol. 97(5), pages 1901-1920, December.
    32. Vincent P. Crawford & Miguel A. Costa-Gomes & Nagore Iriberri, 2013. "Structural Models of Nonequilibrium Strategic Thinking: Theory, Evidence, and Applications," Journal of Economic Literature, American Economic Association, vol. 51(1), pages 5-62, March.
    33. 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.
    34. Smith, Vernon L & Suchanek, Gerry L & Williams, Arlington W, 1988. "Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets," Econometrica, Econometric Society, vol. 56(5), pages 1119-1151, September.
    35. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    36. 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.
    37. 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.
    38. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    39. Breaban, Adriana & Noussair, Charles N., 2015. "Trader characteristics and fundamental value trajectories in an asset market experiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 8(C), pages 1-17.
    40. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
    41. Dieci, Roberto & Westerhoff, Frank, 2010. "Heterogeneous speculators, endogenous fluctuations and interacting markets: A model of stock prices and exchange rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 743-764, April.
    42. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-541, June.
    43. Roberto Dieci & Frank Westerhoff, 2012. "A simple model of a speculative housing market," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 303-329, April.
    44. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.
    45. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    46. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    47. Michael Kirchler & Jurgen Huber & Thomas Stockl, 2012. "Thar She Bursts: Reducing Confusion Reduces Bubbles," American Economic Review, American Economic Association, vol. 102(2), pages 865-883, April.
    48. Stefan Palan, 2013. "A Review Of Bubbles And Crashes In Experimental Asset Markets," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 570-588, July.
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    More about this item

    Keywords

    Financial Instability; Learning-to-Forecast and Learning-to-Optimize Experiments; Genetic Algorithm Model of Individual Learning;
    All these keywords.

    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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