IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1408.1352.html
   My bibliography  Save this paper

A simple model of local prices and associated risk evaluation

Author

Listed:
  • Krzysztof Urbanowicz
  • Peter Richmond
  • Janusz A. Ho{l}yst

Abstract

A simple spin system is constructed to simulate dynamics of asset prices and studied numerically. The outcome for the distribution of prices is shown to depend both on the dimension of the system and the introduction of price into the link measure. For dimensions below 2, the associated risk is high and the price distribution is bimodal. For higher dimensions, the price distribution is Gaussian and the associated risk is much lower. It is suggested that the results are relevant to rare assets or situations where few players are involved in the deal making process.

Suggested Citation

  • Krzysztof Urbanowicz & Peter Richmond & Janusz A. Ho{l}yst, 2014. "A simple model of local prices and associated risk evaluation," Papers 1408.1352, arXiv.org.
    • Handle: RePEc:arx:papers:1408.1352
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1408.1352
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lorenzo Sabatelli & Peter Richmond, 2003. "Phase Transitions, Memory And Frustration In A Sznajd-Like Model With Synchronous Updating," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(09), pages 1223-1229.
    2. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    3. Sabatelli, Lorenzo & Richmond, Peter, 2004. "Non-monotonic spontaneous magnetization in a Sznajd-like consensus model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 274-280.
    Full references (including those not matched with items on IDEAS)

    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. Sabatelli, Lorenzo & Richmond, Peter, 2004. "A consensus-based dynamics for market volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 62-66.
    2. Gündüç, Semra & Eryiğit, Recep, 2015. "The role of persuasion power on the consensus formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 16-24.
    3. Sznajd-Weron, Katarzyna & Sznajd, Józef & Weron, Tomasz, 2021. "A review on the Sznajd model — 20 years after," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    4. Sabatelli, Lorenzo & Richmond, Peter, 2004. "Non-monotonic spontaneous magnetization in a Sznajd-like consensus model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 274-280.
    5. Grabowski, A. & Kosiński, R.A., 2006. "Ising-based model of opinion formation in a complex network of interpersonal interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(2), pages 651-664.
    6. Kaye-Blake, William & Li, Frank Y. & Martin, A. McLeish & McDermott, Alan & Neil, Hayley & Rains, Scott, 2009. "A review of Multi-Agent Simulation Models in Agriculture," 2009 Conference, August 27-28, 2009, Nelson, New Zealand 97165, New Zealand Agricultural and Resource Economics Society.
    7. Lu, Xi & Mo, Hongming & Deng, Yong, 2015. "An evidential opinion dynamics model based on heterogeneous social influential power," Chaos, Solitons & Fractals, Elsevier, vol. 73(C), pages 98-107.
    8. Célestin Coquidé & José Lages & Dima Shepelyansky, 2024. "Opinion Formation in the World Trade Network," Post-Print hal-04461784, HAL.
    9. Xiaolan Qian & Wenchen Han & Junzhong Yang, 2024. "From the DeGroot Model to the DeGroot-Non-Consensus Model: The Jump States and the Frozen Fragment States," Mathematics, MDPI, vol. 12(2), pages 1-13, January.
    10. Dimitris Tsintsaris & Milan Tsompanoglou & Evangelos Ioannidis, 2024. "Dynamics of Social Influence and Knowledge in Networks: Sociophysics Models and Applications in Social Trading, Behavioral Finance and Business," Mathematics, MDPI, vol. 12(8), pages 1-27, April.
    11. Hang-Hyun Jo & Jeoung-Yoo Kim, 2012. "Competitive Targeted Marketing," ISER Discussion Paper 0834, Institute of Social and Economic Research, The University of Osaka.
    12. Ricardo Almeida & Agnieszka B. Malinowska & Tatiana Odzijewicz, 2019. "Optimal Leader–Follower Control for the Fractional Opinion Formation Model," Journal of Optimization Theory and Applications, Springer, vol. 182(3), pages 1171-1185, September.
    13. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    14. Guzmán-Vargas, L. & Hernández-Pérez, R., 2006. "Small-world topology and memory effects on decision time in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(2), pages 326-332.
    15. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    16. Simões, Tiago S.A.N. & Coniglio, Antonio & Herrmann, Hans J. & de Arcangelis, Lucilla, 2024. "Modeling public opinion control by a charismatic leader," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    17. Katarzyna Ostasiewicz & Michal H. Tyc & Piotr Goliczewski & Piotr Magnuszewski & Andrzej Radosz & Jan Sendzimir, 2006. "Integrating economic and psychological insights in binary choice models with social interactions," Papers physics/0609170, arXiv.org.
    18. Si, Xia-Meng & Wang, Wen-Dong & Ma, Yan, 2016. "Role of propagation thresholds in sentiment-based model of opinion evolution with information diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 549-559.
    19. Karataieva, Tatiana & Koshmanenko, Volodymyr & Krawczyk, Małgorzata J. & Kułakowski, Krzysztof, 2019. "Mean field model of a game for power," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 535-547.
    20. repec:plo:pone00:0126090 is not listed on IDEAS
    21. AskariSichani, Omid & Jalili, Mahdi, 2015. "Influence maximization of informed agents in social networks," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 229-239.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1408.1352. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.