IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v357y2005i3p534-542.html
   My bibliography  Save this article

Agent-based model with heterogeneous fundamental prices

Author

Listed:
  • Ferreira, Fernando F.
  • de Oliveira, Viviane M.
  • Crepaldi, Antônio F.
  • Campos, Paulo R.A.

Abstract

In this paper, we investigate the properties of the return time series generated by a multi-agent-based model for financial markets. Our model is a variant of the grand canonical minority game model where the agents behave as producers and a fraction of them is allowed to shift their strategy in order to act opportunistically as fundamentalists. Our model assumes the existence of speculators with heterogeneous beliefs about the fundamental price. Our simulation results are robust to reproduce stylized facts as volatility clustering, fat tail, uncorrelated return and slowing decay on the absolute return.

Suggested Citation

  • Ferreira, Fernando F. & de Oliveira, Viviane M. & Crepaldi, Antônio F. & Campos, Paulo R.A., 2005. "Agent-based model with heterogeneous fundamental prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 357(3), pages 534-542.
    • Handle: RePEc:eee:phsmap:v:357:y:2005:i:3:p:534-542
    DOI: 10.1016/j.physa.2005.03.048
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437105003638
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2005.03.048?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Johnson, Neil F. & Jefferies, Paul & Hui, Pak Ming, 2003. "Financial Market Complexity," OUP Catalogue, Oxford University Press, number 9780198526650.
    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. Ling-Yun He, 2010. "Is Price Behavior Scaling and Multiscaling in a Dealer Market? Perspectives from Multi-Agent Based Experiments," Computational Economics, Springer;Society for Computational Economics, vol. 36(3), pages 263-282, October.
    2. Kiniwa, Jun & Koide, Takeshi & Sandoh, Hiroaki, 2009. "Analysis of price behavior in lazy $-game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3879-3891.
    3. Naimzada, Ahmad K. & Ricchiuti, Giorgio, 2009. "Dynamic effects of increasing heterogeneity in financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1764-1772.
    4. He, Ling-Yun & Fan, Ying & Wei, Yi-Ming, 2009. "Impact of speculator's expectations of returns and time scales of investment on crude oil price behaviors," Energy Economics, Elsevier, vol. 31(1), pages 77-84, January.
    5. Ahmad Naimzada & Giorgio Ricchiuti, 2006. "Heterogeneous Fundamentalists and Imitative Processes," Working Papers 104, University of Milano-Bicocca, Department of Economics, revised Nov 2006.
    6. Lustosa, Bernardo C. & Cajueiro, Daniel O., 2010. "Constrained information minority game: How was the night at El Farol?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1230-1238.
    7. Tilles, Paulo F.C. & Ferreira, Fernando F. & Francisco, Gerson & Pereira, Carlos de B. & Sarti, Flavia M., 2011. "A Markovian model market—Akerlof’s lemons and the asymmetry of information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2562-2570.
    8. Minh Tran & Thanh Duong & Duc Pham-Hi & Marc Bui, 2020. "Detecting the Proportion of Traders in the Stock Market: An Agent-Based Approach," Mathematics, MDPI, vol. 8(2), pages 1-14, February.
    9. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    10. Elena Green & Daniel M. Heffernan, 2019. "An Agent-Based Model to Explain the Emergence of Stylised Facts in Log Returns," Papers 1901.05053, arXiv.org.
    11. Mello, Bernardo A. & Cajueiro, Daniel O., 2008. "Minority games, diversity, cooperativity and the concept of intelligence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 557-566.

    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. Tobias Galla & David Sherrington, 2005. "Stationary states of a spherical Minority Game with ergodicity breaking," Papers cond-mat/0508413, arXiv.org, revised Aug 2005.
    2. Lim, Gyuchang & Kim, SooYong & Kim, Junghwan & Kim, Pyungsoo & Kang, Yoonjong & Park, Sanghoon & Park, Inho & Park, Sang-Bum & Kim, Kyungsik, 2009. "Structure of a financial cross-correlation matrix under attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3851-3858.
    3. V. Alfi & L. Pietronero & A. Zaccaria, 2008. "Minimal Agent Based Model For The Origin And Self-Organization Of Stylized Facts In Financial Markets," Papers 0807.1888, arXiv.org.
    4. Gou, Chengling & Guo, Xiaoqian & Chen, Fang, 2008. "Study on system dynamics of evolutionary mix-game models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6353-6359.
    5. Pištěk, Miroslav & Slanina, František, 2011. "Diversity of scales makes an advantage: The case of the Minority Game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2549-2561.
    6. Li, Da-Ye & Nishimura, Yusaku & Men, Ming, 2014. "Fractal markets: Liquidity and investors on different time horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 144-151.
    7. Moews, Ben & Ibikunle, Gbenga, 2020. "Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    8. Oldham, Matthew, 2020. "Quantifying the concerns of Dimon and Buffett with data and computation," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    9. Ted Theodosopoulos, 2004. "Uncertainty relations in models of market microstructure," Papers math/0409076, arXiv.org, revised Feb 2005.
    10. A. Garcia-Bernabeu & J. V. Salcedo & A. Hilario & D. Pla-Santamaria & Juan M. Herrero, 2019. "Computing the Mean-Variance-Sustainability Nondominated Surface by ev-MOGA," Complexity, Hindawi, vol. 2019, pages 1-12, December.
    11. Kostanjcar, Zvonko & Jeren, Branko & Juretic, Zeljan, 2012. "Impact of uncertainty in expected return estimation on stock price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5563-5571.
    12. Ni, Y.C. & Xu, C. & Hui, P.M. & Johnson, N.F., 2009. "Cooperative behavior in evolutionary snowdrift game with bounded rationality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4856-4862.
    13. Niu, Hongli & Wang, Jun, 2017. "Return volatility duration analysis of NYMEX energy futures and spot," Energy, Elsevier, vol. 140(P1), pages 837-849.
    14. Strozzi, Fernanda & Zaldívar, José-Manuel & Zbilut, Joseph P., 2007. "Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 487-499.
    15. Strozzi, F. & Zaldívar, J.M., 2005. "Non-linear forecasting in high-frequency financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 463-479.
    16. Indranil Mukherjee & Amitava Sarkar, 2011. "Complexity, Financial Markets and their Scaling Laws," DEGIT Conference Papers c016_008, DEGIT, Dynamics, Economic Growth, and International Trade.
    17. Moonis Shakeel & Bhavana Srivastava, 2021. "Stylized Facts of High-frequency Financial Time Series Data," Global Business Review, International Management Institute, vol. 22(2), pages 550-564, April.
    18. Jørgen Vitting Andersen, 2014. "From Minority Games to $-Games," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00971373, HAL.
    19. J. Doyne Farmer & John Geanakoplos, 2008. "The virtues and vices of equilibrium and the future of financial economics," Papers 0803.2996, arXiv.org.
    20. Xu, C. & Gu, G.-Q. & Hui, P.M., 2024. "Impacts of an expert’s opinion on the collective performance of a competing population for limited resources," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).

    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:eee:phsmap:v:357:y:2005:i:3:p:534-542. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.