IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/99129.html
   My bibliography  Save this paper

Centralized vs decentralized markets in the laboratory: The role of connectivity

Author

Listed:
  • Alfarano, Simone
  • Banal-Estanol, Albert
  • Camacho-Cuena, Eva
  • Iori, Giulia
  • Kapar, Burcu

Abstract

This paper compares the performance of centralized and decentralized markets experimentally. We constrain trading exchanges to happen on an exogenously predetermined network, representing the trading relationships in markets with differing levels of connectivity. Our experimental results show that, despite having lower trading volumes, decentralized markets are not necessarily less efficient. Although information can propagate quicker through highly connected markets, we show that higher connectivity also induces informed traders to trade faster and exploit further their information advantages before the information becomes fully incorporated into prices. This not only reduces market efficiency, but it also increases wealth inequality. We show that, in more connected markets, informed traders trade not only relatively quicker, but also more, in the right direction, despite not doing it at better prices.

Suggested Citation

  • Alfarano, Simone & Banal-Estanol, Albert & Camacho-Cuena, Eva & Iori, Giulia & Kapar, Burcu, 2020. "Centralized vs decentralized markets in the laboratory: The role of connectivity," MPRA Paper 99129, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:99129
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/99129/1/MPRA_paper_99129.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schnitzlein, Charles R, 1996. "Call and Continuous Trading Mechanisms under Asymmetric Information: An Experimental Investigation," Journal of Finance, American Finance Association, vol. 51(2), pages 613-636, June.
    2. Paolo Colla & Antonio Mele, 2010. "Information Linkages and Correlated Trading," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 203-246, January.
    3. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.
    4. Edward Halim & Yohanes E. Riyanto & Nilanjan Roy, 2019. "Costly Information Acquisition, Social Networks, and Asset Prices: Experimental Evidence," Journal of Finance, American Finance Association, vol. 74(4), pages 1975-2010, August.
    5. Attanasi, Giuseppe & Centorrino, Samuele & Moscati, Ivan, 2016. "Over-the-counter markets vs. double auctions: A comparative experimental study," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 22-35.
    6. Helena Veiga & Marc Vorsatz, 2010. "Information aggregation in experimental asset markets in the presence of a manipulator," Experimental Economics, Springer;Economic Science Association, vol. 13(4), pages 379-398, December.
    7. Brice Corgnet & Mark DeSantis & David Porter, 2015. "Revisiting Information Aggregation in Asset Markets: Reflective Learning & Market Efficiency," Working Papers 15-15, Chapman University, Economic Science Institute.
    8. Morone, Andrea & Nuzzo, Simone, 2015. "Market Efficiency, Trading Institutions and Information Mirages: evidence from an experimental asset market," MPRA Paper 67448, University Library of Munich, Germany.
    9. Theissen, Erik, 2000. "Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets," Journal of Financial Markets, Elsevier, vol. 3(4), pages 333-363, November.
    10. Hanson, Robin & Oprea, Ryan & Porter, David, 2006. "Information aggregation and manipulation in an experimental market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(4), pages 449-459, August.
    11. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    12. Bruno Biais & Denis Hilton & Karine Mazurier & Sébastien Pouget, 2005. "Judgemental Overconfidence, Self-Monitoring, and Trading Performance in an Experimental Financial Market," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 287-312.
    13. Topol, Richard, 1991. "Bubbles and Volatility of Stock Prices: Effect of Mimetic Contagion," Economic Journal, Royal Economic Society, vol. 101(407), pages 786-800, July.
    14. Cason, Timothy N. & Friedman, Daniel, 1996. "Price formation in double auction markets," Journal of Economic Dynamics and Control, Elsevier, vol. 20(8), pages 1307-1337, August.
    15. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
    16. Semyon Malamud & Marzena Rostek, 2017. "Decentralized Exchange," American Economic Review, American Economic Association, vol. 107(11), pages 3320-3362, November.
    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. Alba Ruiz-Buforn & Simone Alfarano & Eva Camacho-Cuena & Andrea Morone, 2022. "Single vs. multiple disclosures in an experimental asset market with information acquisition," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1513-1539, October.

    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. Simone Alfarano & Albert Banal-Estañol & Eva Camacho & Giulia Iori & Burcu Kapar & Rohit Rahi, 2024. "Centralized vs decentralized markets: The role of connectivity," Economics Working Papers 1877, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    3. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    4. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    5. Corgnet, Brice & DeSantis, Mark & Porter, David, 2021. "Information aggregation and the cognitive make-up of market participants," European Economic Review, Elsevier, vol. 133(C).
    6. Corgnet, Brice & Deck, Cary & DeSantis, Mark & Porter, David, 2018. "Information (non)aggregation in markets with costly signal acquisition," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 286-320.
    7. Eric M. Aldrich & Kristian López Vargas, 2020. "Experiments in high-frequency trading: comparing two market institutions," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 322-352, June.
    8. Brice Corgnet & Mark DeSantis & David Porter, 2020. "Information Aggregation and the Cognitive Make-up of Traders," Working Papers 20-18, Chapman University, Economic Science Institute.
    9. Brice Corgnet & Cary Deck & Mark Desantis & Kyle Hampton & Erik O Kimbrough, 2019. "Reconsidering Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Working Papers halshs-02146611, HAL.
    10. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2019. "Information aggregation in Arrow–Debreu markets: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 22(3), pages 625-652, September.
    11. Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2023. "When Do Security Markets Aggregate Dispersed Information?," Management Science, INFORMS, vol. 69(6), pages 3697-3729, June.
    12. Morone, Andrea & Nuzzo, Simone, 2016. "Do markets (institutions) drive out lemmings - or vice versa?," Kiel Working Papers 2061, Kiel Institute for the World Economy (IfW Kiel).
    13. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2022. "Manipulation and (Mis)trust in Prediction Markets," Management Science, INFORMS, vol. 68(9), pages 6716-6732, September.
    14. Rocco Caferra & Gabriele Tedeschi & Andrea Morone, 2023. "Agents interaction and price dynamics: evidence from the laboratory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 251-274, April.
    15. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    16. Robert Merl, 2021. "Literature Review of Experimental Asset Markets with Insiders," Working Paper Series, Social and Economic Sciences 2021-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    17. Morone, Andrea & Nuzzo, Simone, 2015. "Market Efficiency, Trading Institutions and Information Mirages: evidence from an experimental asset market," MPRA Paper 67448, University Library of Munich, Germany.
    18. Caferra, Rocco & Morone, Andrea & Nuzzo, Simone, 2019. "The Impact of a Pre-Opening Session on Subsequent Trading: an Experimental Analysis," MPRA Paper 92853, University Library of Munich, Germany.
    19. Brice Corgnet & Mark DeSantis & David Porter, 2015. "Revisiting Information Aggregation in Asset Markets: Reflective Learning & Market Efficiency," Working Papers 15-15, Chapman University, Economic Science Institute.
    20. Zonna, Davide, 2016. "Sprechi di cibo e tentativi di riduzione. Un caso sperimentale [Avoiding food waste. A field experiment]," MPRA Paper 76097, University Library of Munich, Germany.

    More about this item

    Keywords

    Experiments; financial markets; diffusion of information; decentralized trading.;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:pra:mprapa:99129. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.