IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v152y2021ics0960077921007438.html
   My bibliography  Save this article

Liquidity externality in a market of buying adjustable agents

Author

Listed:
  • Aal, P.K.
  • Sousa, K.R. de A.
  • Salles, L.S.A. de Campos
  • Koehler, M.

Abstract

The market dynamics produced by simple interactions among rational investors can generate complex phenomena such as bubbles, crashes, and business cycles. One powerful tool to understand those phenomena might be the use of Cellular Automata (CA) models. In this contribution we investigate spatial aggregations effects associated to the propagation of information contagion waves across a network of non-equivalent adjustable agents. The contagion dynamics is modeled by an inhomogeneous cellular automaton (InCA) as proposed by Weisbuch and Stauffer[Physica A, 1(323), 651-662 (2003)]. In this system, a tatonnement process emerges as the individual agents try to adjust their reservation price to follow the externality produced by the state of the neighborhood. Using rescale range analysis we show that the periodic oscillations of InCA average state (that resembles business cycles) have long memory effects (for a determined interval of time). The presence of long memory effects is a usual feature present in many real markets. Our results are obtained after the development of an efficient algorithm to count the cluster of agents with the same state. The application of this algorithm revealed that the number and the size of the agent's cluster increase as adjustment amplitude (the parameter that controls the velocity of the tatonnement process) increases. We then show that there is a value of this amplitude that maximizes the system's tendency to form large and synchronized clusters. By associating this adjustment parameter with the liquidity, we demonstrate that the dynamics of the inhomogeneous cellular automata can mimic liquidity externalities found in real markets.

Suggested Citation

  • Aal, P.K. & Sousa, K.R. de A. & Salles, L.S.A. de Campos & Koehler, M., 2021. "Liquidity externality in a market of buying adjustable agents," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007438
    DOI: 10.1016/j.chaos.2021.111389
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921007438
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2021.111389?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. Johannes A. Skjeltorp & Elvira Sojli & Wing Wah Tham, 2012. "Identifying cross-sided liquidity externalities," Working Paper 2012/20, Norges Bank.
    2. Naimzada, Ahmad & Pireddu, Marina, 2015. "Real and financial interacting markets: A behavioral macro-model," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 111-131.
    3. Rajagopal, 2015. "Chaos in Markets," Palgrave Macmillan Books, in: The Butterfly Effect in Competitive Markets, chapter 1, pages 3-29, Palgrave Macmillan.
    4. Randi Næs & Johannes A. Skjeltorp & Bernt Arne Ødegaard, 2011. "Stock Market Liquidity and the Business Cycle," Journal of Finance, American Finance Association, vol. 66(1), pages 139-176, February.
    5. Weisbuch, Gérard & Stauffer, Dietrich, 2003. "Adjustment and social choice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 651-662.
    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. Serena Sordi & Marwil J. Dávila-Fernández, 2020. "Investment behaviour and “bull & bear” dynamics: modelling real and stock market interactions," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(4), pages 867-897, October.
    2. F. Cavalli & A. Naimzada & N. Pecora, 2022. "A stylized macro-model with interacting real, monetary and stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 225-257, January.
    3. Bao, B.C. & Wu, P.Y. & Bao, H. & Xu, Q. & Chen, M., 2018. "Numerical and experimental confirmations of quasi-periodic behavior and chaotic bursting in third-order autonomous memristive oscillator," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 161-170.
    4. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2021. "(Ir)rational explorers in the financial jungle," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1157-1188, September.
    5. Liu, Xiaoyong & Fu, Hui, 2016. "Volatility forecasting for interbank offered rate using grey extreme learning machine: The case of China," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 249-254.
    6. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2020. "(Ir)rational explorers in the financial jungle: modelling Minsky with heterogeneous agents," Department of Economics University of Siena 819, Department of Economics, University of Siena.
    7. Ping‐Wen Sun & Yifan Shen & Meifen Qian & Wu Yan, 2021. "Risk of holding stocks with liquidity sensitive to market uncertainty: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 1993-2029, April.
    8. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    9. Marios Panayides & Barbara Rindi & Ingrid M.Werner, 2017. "Trading Fees and Intermarket Competition," BAFFI CAREFIN Working Papers 1751, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    10. Strobl, Günter, 2022. "A theory of procyclical market liquidity," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    11. James Brugler & Minsoo Kim & Zhuo Zhong, 2024. "Liquidity shocks and pension fund performance: Evidence from early access," Australian Journal of Management, Australian School of Business, vol. 49(2), pages 170-191, May.
    12. Skjeltorp, Johannes A & Odegaard, Bernt Arne, 2010. "Why do firms pay for liquidity provision in limit order markets?," UiS Working Papers in Economics and Finance 2010/3, University of Stavanger.
    13. Chen, Jiun-Lin & Jia, Z. Tingting & Sun, Ping-Wen, 2016. "Real option component of cash holdings, business cycle, and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 97-106.
    14. François-Éric Racicot & Raymond Théoret, 2022. "Tracking market and non-traditional sources of risks in procyclical and countercyclical hedge fund strategies under extreme scenarios: a nonlinear VAR approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    15. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    16. Denis Phan, 2006. "Discrete Choices under Social Influence:Generic Properties," Post-Print halshs-00105857, HAL.
    17. Jiang, Lei, 2014. "Stock liquidity and the Taylor rule," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 202-214.
    18. Chae, Jiwon & Jang, Bong-Gyu & Kim, Taeyoon, 2024. "The effect of regime-switching transaction costs and cash dividends on liquidity premia," International Review of Financial Analysis, Elsevier, vol. 93(C).
    19. Wang, Fengrong & Mbanyele, William & Muchenje, Linda, 2022. "Economic policy uncertainty and stock liquidity: The mitigating effect of information disclosure," Research in International Business and Finance, Elsevier, vol. 59(C).
    20. Theologos Dergiades & Costas Milas & Theodore Panagiotidis, 2015. "Tweets, Google trends, and sovereign spreads in the GIIPS," Oxford Economic Papers, Oxford University Press, vol. 67(2), pages 406-432.

    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:chsofr:v:152:y:2021:i:c:s0960077921007438. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.