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Fuzzy inductive reasoning, expectation formation and the behavior of security prices

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  • Tay, Nicholas S. P.
  • Linn, Scott C.

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  • Tay, Nicholas S. P. & Linn, Scott C., 2001. "Fuzzy inductive reasoning, expectation formation and the behavior of security prices," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 321-361, March.
    • Handle: RePEc:eee:dyncon:v:25:y:2001:i:3-4:p:321-361
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    19. J. Bradford De Long & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1989. "The Size and Incidence of the Losses from Noise Trading," Journal of Finance, American Finance Association, vol. 44(3), pages 681-696, July.
    20. W. Brian Arthur, 1992. "On Learning and Adaptation in the Economy," Working Paper 854, Economics Department, Queen's University.
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    24. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    1. Jaqueson K. Galimberti & Sergio da Silva, 2012. "An empirical case against the use of genetic-based learning classifier systems as forecasting devices," Economics Bulletin, AccessEcon, vol. 32(1), pages 354-369.
    2. Gradojevic, Nikola, 2007. "Non-linear, hybrid exchange rate modeling and trading profitability in the foreign exchange market," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 557-574, February.
    3. Tesfatsion, Leigh, 2001. "Introduction to the special issue on agent-based computational economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 281-293, March.
    4. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    5. Ryuichi YAMAMOTO, 2005. "Evolution with Individual and Social Learning in an Agent-Based Stock Market," Computing in Economics and Finance 2005 228, Society for Computational Economics.
    6. Witte, Björn-Christopher, 2011. "Removing systematic patterns in returns in a financial market model by artificially intelligent traders," BERG Working Paper Series 82, Bamberg University, Bamberg Economic Research Group.
    7. Brandouy, O., 2005. "Stock markets as Minority Games: cognitive heterogeneity and equilibrium emergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(1), pages 302-328.
    8. Bekiros, Stelios D., 2010. "Heterogeneous trading strategies with adaptive fuzzy Actor-Critic reinforcement learning: A behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1153-1170, June.
    9. Haijun Yang & Shuheng Chen, 2018. "A heterogeneous artificial stock market model can benefit people against another financial crisis," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-25, June.
    10. Aleksandras Vytautas Rutkauskas & Tomas Ramanauskas, 2009. "Building an artificial stock market populated by reinforcement‐learning agents," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(4), pages 329-341, September.
    11. Steinbacher, Matjaz, 2008. "Stochastic Processes in Finance and Behavioral Finance," MPRA Paper 13603, University Library of Munich, Germany.
    12. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.
    13. 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.
    14. Scott C. Linn & Nicholas S. P. Tay, 2007. "Complexity and the Character of Stock Returns: Empirical Evidence and a Model of Asset Prices Based on Complex Investor Learning," Management Science, INFORMS, vol. 53(7), pages 1165-1180, July.
    15. Gradojevic, Nikola & Gençay, Ramazan, 2013. "Fuzzy logic, trading uncertainty and technical trading," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 578-586.
    16. Haijun Yang & Harry Wang & Gui Sun & Li Wang, 2015. "A comparison of U.S and Chinese financial market microstructure: heterogeneous agent-based multi-asset artificial stock markets approach," Journal of Evolutionary Economics, Springer, vol. 25(5), pages 901-924, November.
    17. Adão, Luiz F.S. & Silveira, Douglas & Ely, Regis A. & Cajueiro, Daniel O., 2022. "The impacts of interest rates on banks’ loan portfolio risk-taking," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    18. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    19. Smith, Peter, 2004. "Reworking the Standard Model of Competitive Markets: The Role of Fuzzy Logic and Genetic Algorithms in Modelling Complex Non-Linear Economic System," General Discussion Papers 30569, University of Manchester, Institute for Development Policy and Management (IDPM).

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