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How helpful is a long memory on financial markets?

Author

Listed:
  • Sandra GØth

    (Department of Economics, University of Bielefeld, P.O. Box 100 131, 33501 Bielefeld, GERMANY)

  • Sven Ludwig

    (Department of Economics, University of Bielefeld, P.O. Box 100 131, 33501 Bielefeld, GERMANY)

Abstract

How should portfolio decisions depend on the past? In a simple model with boundedly rational agents we show that there is no universal answer to this question. Both, long and short memory, can be optimal in the appropriate environment. In most cases there is an equilibrium where both dispositions are equally successful. We characterize such equilibria for the case of two assets and two states. For dynamics based on average payoff, equilibria are global attractors whereas discrete choice dynamics in general do not converge to the equilibrium.

Suggested Citation

  • Sandra GØth & Sven Ludwig, 2000. "How helpful is a long memory on financial markets?," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 16(1), pages 107-134.
    • Handle: RePEc:spr:joecth:v:16:y:2000:i:1:p:107-134
    Note: Received: August 31, 1998; revised version: November 15, 1999
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    References listed on IDEAS

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    1. Schlag, Karl H., 1999. "Which one should I imitate?," Journal of Mathematical Economics, Elsevier, vol. 31(4), pages 493-522, May.
    2. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    3. 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.
    4. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
    5. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
    6. 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.
    7. James Dow, 1991. "Search Decisions with Limited Memory," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(1), pages 1-14.
    8. Hans Föllmer & Martin Schweizer, 1993. "A Microeconomic Approach to Diffusion Models For Stock Prices," Mathematical Finance, Wiley Blackwell, vol. 3(1), pages 1-23, January.
    9. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    10. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
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    Cited by:

    1. Michele Anelli & Michele Patanè & Stefano Zedda, 2022. "Are Banks Still a Risk Source for Stock Market? Some Empirical Evidences," JRFM, MDPI, vol. 15(7), pages 1-13, July.
    2. Daniel Monte & Maher Said, 2014. "The value of (bounded) memory in a changing world," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 56(1), pages 59-82, May.

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    More about this item

    Keywords

    Financial markets; Limited memory; Bounded rationality; Discrete choice.;
    All these keywords.

    JEL classification:

    • D89 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Other
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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