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Statistical properties of genetic learning in a model of exchange rate

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  • Arifovic, Jasmina
  • Gencay, Ramazan

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  • Arifovic, Jasmina & Gencay, Ramazan, 2000. "Statistical properties of genetic learning in a model of exchange rate," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 981-1005, June.
    • Handle: RePEc:eee:dyncon:v:24:y:2000:i:5-7:p:981-1005
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    1. King, Robert G. & Wallace, Neil & Weber, Warren E., 1992. "Nonfundamental uncertainty and exchange rates," Journal of International Economics, Elsevier, vol. 32(1-2), pages 83-108, February.
    2. Arifovic, Jasmina, 1998. "Stability Of Equilibria Under Genetic-Algorithm Adaptation: An Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 1-21, March.
    3. Bullard, James & Duffy, John, 1998. "Learning And The Stability Of Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 22-48, March.
    4. John Kareken & Neil Wallace, 1981. "On the Indeterminacy of Equilibrium Exchange Rates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 96(2), pages 207-222.
    5. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    6. Bullard, James & Duffy, John, 1998. "A model of learning and emulation with artificial adaptive agents," Journal of Economic Dynamics and Control, Elsevier, vol. 22(2), pages 179-207, February.
    7. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    8. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
    9. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    10. Dechert, W D & Gencay, R, 1992. "Lyapunov Exponents as a Nonparametric Diagnostic for Stability Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 41-60, Suppl. De.
    11. 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.
    12. Arifovic, Jasmina & Bullard, James & Duffy, John, 1997. "The Transition from Stagnation to Growth: An Adaptive Learning Approach," Journal of Economic Growth, Springer, vol. 2(2), pages 185-209, July.
    13. Marimon, Ramon & McGrattan, Ellen & Sargent, Thomas J., 1990. "Money as a medium of exchange in an economy with artificially intelligent agents," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 329-373, May.
    14. 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.
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    Cited by:

    1. Alina Barbulescu & Cristian Stefan Dumitriu, 2021. "Artificial Intelligence Models for Financial Time Series," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 685-690, August.
    2. Gagnon, Gregory, 2004. "Exchange rate fluctuations in an economy with noise traders," Journal of Macroeconomics, Elsevier, vol. 26(1), pages 45-63, March.
    3. Simone Alfarano & Thomas Lux, 2007. "A Minimal Noise Trader Model with Realistic Time Series Properties," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 345-361, Springer.
    4. Andrea Morone, 2008. "Financial markets in the laboratory: an experimental analysis of some stylized facts," Quantitative Finance, Taylor & Francis Journals, vol. 8(5), pages 513-532.
    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. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
    8. Nuzzo, Simone & Morone, Andrea, 2017. "Asset markets in the lab: A literature review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 42-50.
    9. Al Shugaa, Ameen & Masih, Mansur, 2014. "Uncertainty and Volatility in MENA Stock Markets During the Arab Spring," MPRA Paper 58867, University Library of Munich, Germany.
    10. 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.
    11. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
    12. Siddiqi, Hammad, 2007. "Rational Interacting Agents and Volatility Clustering: A New Approach," MPRA Paper 2984, University Library of Munich, Germany.
    13. Thorsten Hens & Terje Lensberg & Klaus Reiner Schenk‐Hoppé, 2018. "Front‐Running and Market Quality: An Evolutionary Perspective on High Frequency Trading," International Review of Finance, International Review of Finance Ltd., vol. 18(4), pages 727-741, December.
    14. Andrea Gaunersdorfer & Cars Hommes, 2007. "A Nonlinear Structural Model for Volatility Clustering," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288, Springer.
    15. Georges, Christophre, 2006. "Learning with misspecification in an artificial currency market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(1), pages 70-84, May.
    16. Andrea Morone, 2002. "Financial Market in the Laboratory," Computing in Economics and Finance 2002 151, Society for Computational Economics.
    17. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.
    18. 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.
    19. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    20. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    21. Rui Carvalho, 2001. "The Dynamics of the Linear Random Farmer Model," Papers cond-mat/0107150, arXiv.org.
    22. Saeed Rasekhi, 2011. "Fundamental Modeling Exchange Rate using Genetic Algorithm: A Case Study of European Countries," Journal of Economics and Behavioral Studies, AMH International, vol. 3(6), pages 352-359.
    23. Goeree, Jacob K. & Hommes, Cars H., 2000. "Heterogeneous beliefs and the non-linear cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 761-798, June.
    24. 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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