IDEAS home Printed from https://ideas.repec.org/a/spr/joecth/v16y2000i1p107-134.html

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
    as

    Download full text from publisher

    File URL: http://link.springer.de/link/service/journals/00199/papers/0016001/00160107.pdf
    Download Restriction: Access to the full text of the articles in this series is restricted
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Schlag, Karl H., 1999. "Which one should I imitate?," Journal of Mathematical Economics, Elsevier, vol. 31(4), pages 493-522, May.
    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. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    6. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    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. Hommes, C.H., 2005. "Heterogeneous Agent Models in Economics and Finance, In: Handbook of Computational Economics II: Agent-Based Computational Economics, edited by Leigh Tesfatsion and Ken Judd , Elsevier, Amsterdam 2006, pp.1109-1186," CeNDEF Working Papers 05-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    2. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    3. Qi Nan Zhai, 2015. "Asset Pricing Under Ambiguity and Heterogeneity," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 16, July-Dece.
    4. Westerhoff, Frank H. & Dieci, Roberto, 2006. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 293-322, February.
    5. Xue-Zhong He, 2003. "Asset Pricing, Volatility and Market Behaviour: A Market Fraction Approach," Research Paper Series 95, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Alessio Emanuele Biondo, 2018. "Order book microstructure and policies for financial stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 35(1), pages 196-218, March.
    7. Hommes, Cars & Huang, Hai & Wang, Duo, 2005. "A robust rational route to randomness in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 29(6), pages 1043-1072, June.
    8. Youwei Li & Xue-Zhong He, 2005. "Long Memory, Heterogeneity, and Trend Chasing," Computing in Economics and Finance 2005 113, Society for Computational Economics.
    9. Karlis, Alexandros & Galanis, Girogos & Terovitis, Spyridon & Turner, Matthew, "undated". "Heterogeneity and Clustering of Defaults," Economic Research Papers 270011, University of Warwick - Department of Economics.
    10. Christian Peretti, 2007. "Long Memory and Hysteresis," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 363-389, Springer.
    11. Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2000. "Bifurcation Routes to Volatility Clustering," CeNDEF Working Papers 00-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    12. Dieci, Roberto & Foroni, Ilaria & Gardini, Laura & He, Xue-Zhong, 2006. "Market mood, adaptive beliefs and asset price dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 29(3), pages 520-534.
    13. C. Chiarella & P. Khomin, 1999. "Adaptively evolving expectations in models of monetarydynamics‐ The fundamentalists forward looking," Annals of Operations Research, Springer, vol. 89(0), pages 21-34, January.
    14. He, Xue-Zhong & Li, Youwei, 2007. "Power-law behaviour, heterogeneity, and trend chasing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3396-3426, October.
    15. Jörn Dermietzel, 2008. "The Heterogeneous Agents Approach to Financial Markets – Development and Milestones," International Handbooks on Information Systems, in: Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), Handbook on Information Technology in Finance, chapter 19, pages 443-464, Springer.
    16. 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.
    17. Youwei Li & Xue-Zhong (Tony) He, 2005. "Heterogeneity, Profitability and Autocorrelations," Computing in Economics and Finance 2005 244, Society for Computational Economics.
    18. Tamotsu Onozaki, 2018. "Nonlinearity, Bounded Rationality, and Heterogeneity," Springer Books, Springer, number 978-4-431-54971-0, January.
    19. Di Guilmi, Corrado & He, Xue-Zhong & Li, Kai, 2014. "Herding, trend chasing and market volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 349-373.
    20. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2011. "The dynamic behaviour of asset prices in disequilibrium: a survey," International Journal of Behavioural Accounting and Finance, Inderscience Enterprises Ltd, vol. 2(2), pages 101-139.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

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

    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:spr:joecth:v:16:y:2000:i:1:p:107-134. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.