[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v57y2007i2p213-218.html
   My bibliography  Save this article

Stylized facts from a threshold-based heterogeneous agent model

Author

Listed:
  • R. Cross
  • M. Grinfeld
  • H. Lamba
  • T. Seaman
Abstract
A class of heterogeneous agent models is investigated where investors switch trading position whenever their motivation to do so exceeds some critical threshold. These motivations can be psychological in nature or reflect behaviour suggested by the efficient market hypothesis (EMH). By introducing different propensities into a baseline model that displays EMH behaviour, one can attempt to isolate their effects upon the market dynamics. The simulation results indicate that the introduction of a herding propensity results in excess kurtosis and power-law decay consistent with those observed in actual return distributions, but not in significant long-term volatility correlations. Possible alternatives for introducing such long-term volatility correlations are then identified and discussed. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

Suggested Citation

  • R. Cross & M. Grinfeld & H. Lamba & T. Seaman, 2007. "Stylized facts from a threshold-based heterogeneous agent model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 213-218, May.
    • Handle: RePEc:spr:eurphb:v:57:y:2007:i:2:p:213-218
    DOI: 10.1140/epjb/e2007-00108-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1140/epjb/e2007-00108-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1140/epjb/e2007-00108-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521530927, January.
    2. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521824019, 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. 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.
    2. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    3. Cristescu, C.P. & Stan, C. & Scarlat, E.I., 2009. "The dynamics of exchange rate time series and the chaos game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4845-4855.
    4. Lamba, H. & Seaman, T., 2008. "Rational expectations, psychology and inductive learning via moving thresholds," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3904-3909.
    5. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2018. "Simulation of Stylized Facts in Agent-Based Computational Economic Market Models," Papers 1812.02726, arXiv.org, revised Nov 2019.
    6. Torsten Trimborn & Martin Frank & Stephan Martin, 2017. "Mean Field Limit of a Behavioral Financial Market Model," Papers 1711.02573, arXiv.org.
    7. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2020. "Robust Mathematical Formulation And Probabilistic Description Of Agent-Based Computational Economic Market Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(06), pages 1-41, September.
    8. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    9. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2019. "Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models," Papers 1904.04951, arXiv.org, revised Mar 2021.
    10. Trimborn, Torsten & Frank, Martin & Martin, Stephan, 2018. "Mean field limit of a behavioral financial market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 613-631.
    11. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.

    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. Boğaçhan Çelen & Kyle Hyndman, 2012. "An experiment of social learning with endogenous timing," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 251-268, September.
    2. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    3. repec:ebl:ecbull:v:7:y:2006:i:7:p:1-12 is not listed on IDEAS
    4. Gill, David & Sgroi, Daniel, 2008. "The Optimal Choice of Pre-launch Reviewer : How Best to Transmit Information using Tests and Conditional Pricing," The Warwick Economics Research Paper Series (TWERPS) 877, University of Warwick, Department of Economics.
    5. Andreas Blume & April Mitchell Franco & Paul Heidhues, 2021. "Dynamic coordination via organizational routines," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(4), pages 1001-1047, November.
    6. Jonathan E. Alevy & Michael S. Haigh & John List, 2006. "Information Cascades: Evidence from An Experiment with Financial Market Professionals," NBER Working Papers 12767, National Bureau of Economic Research, Inc.
    7. Marco Cipriani & Antonio Guarino, 2009. "Herd Behavior in Financial Markets: An Experiment with Financial Market Professionals," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 206-233, March.
    8. Schlegel, Friederike & Hakenes, Hendrik, 2014. "Tapping the Financial Wisdom of the Crowd - Crowdfunding as a Tool to Aggregate Vague Information," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100563, Verein für Socialpolitik / German Economic Association.
    9. Nimark, Kristoffer, 2008. "Dynamic pricing and imperfect common knowledge," Journal of Monetary Economics, Elsevier, vol. 55(2), pages 365-382, March.
    10. Park, Andreas & Sgroi, Daniel, 2012. "Herding, contrarianism and delay in financial market trading," European Economic Review, Elsevier, vol. 56(6), pages 1020-1037.
    11. Adhvaryu, Achyuta, 2011. "Learning, Misallocation, and Technology Adoption: Evidence from New Malaria Therapy in Tanzania," Working Papers 92, Yale University, Department of Economics.
    12. Drehmann, Mathias & Oechssler, Jorg & Roider, Andreas, 2007. "Herding with and without payoff externalities -- an internet experiment," International Journal of Industrial Organization, Elsevier, vol. 25(2), pages 391-415, April.
    13. Gill, David & Sgroi, Daniel, 2012. "The optimal choice of pre-launch reviewer," Journal of Economic Theory, Elsevier, vol. 147(3), pages 1247-1260.
    14. Gill, David & Sgroi, Daniel, 2008. "Sequential decisions with tests," Games and Economic Behavior, Elsevier, vol. 63(2), pages 663-678, July.
    15. Michal Grajek, 2003. "Estimating Network Effects and Compatibility in Mobile Telecommunications," CIG Working Papers SP II 2003-26, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
    16. Syngjoo Choi, 2012. "A cognitive hierarchy model of learning in networks," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 215-250, September.
    17. Tatsuhiro SHICHIJO & Yuji NAKAYAMA, 2004. "A Way To Sell Goods With Network Externalities," Econometric Society 2004 Far Eastern Meetings 711, Econometric Society.
    18. Antonio Guarino & Steffen Huck & Heike Harmgart, 2008. "When half the truth is better than the truth: A Theory of aggregate information cascades," WEF Working Papers 0046, ESRC World Economy and Finance Research Programme, Birkbeck, University of London.
    19. Diemo Urbig, 2006. "Base rate neglect for the wealth of populations," Computing in Economics and Finance 2006 266, Society for Computational Economics.
    20. Roger Guesnerie & Pedro Jara-Moroni, 2011. "Expectational coordination in simple economic contexts," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 205-246, June.
    21. Duffie, Darrell & Malamud, Semyon & Manso, Gustavo, 2014. "Information percolation in segmented markets," Journal of Economic Theory, Elsevier, vol. 153(C), pages 1-32.

    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:eurphb:v:57:y:2007:i:2:p:213-218. 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.