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Marketmaking in the Laboratory: Does Competition Matter?

Author

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  • Jan Pieter Krahnen

  • Martin Weber

Abstract

This paper is the first experimental study of the effects of competition and adverse selection on the performance of market maker (MM-) markets. Information distribution may is either symmetric or heterogeneous. MM-markets are either monopolistic (the specialist markets), or competitive (the multi MM-market). Welfare comparisons are with respect to a continuous double auction (DA-) market. Informed subjects receive an imperfect signal of the true state of the world. We find three main results. First, competition among market makers significantly reduces the bid-ask spread, and increases transaction volume. Second, competition among market makers induces competitive undercutting, yielding net trading losses for market makers as a group in most periods. Third, from the perspective of uninformed traders, a competing MM-regime is optimal, since it minimizes their expected trading losses.

Suggested Citation

  • Jan Pieter Krahnen & Martin Weber, 2001. "Marketmaking in the Laboratory: Does Competition Matter?," Working Paper Series: Finance and Accounting 4, Department of Finance, Goethe University Frankfurt am Main.
    • Handle: RePEc:fra:franaf:4
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    2. Mirowski, Philip, 2007. "Markets come to bits: Evolution, computation and markomata in economic science," Journal of Economic Behavior & Organization, Elsevier, vol. 63(2), pages 209-242, June.
    3. J. P. Krahnen & C. Rieck & E. Theissen, 1999. "Insider trading and portfolio structure in experimental asset markets with a long-lived asset," The European Journal of Finance, Taylor & Francis Journals, vol. 5(1), pages 29-50.
    4. 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.
    5. 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).
    6. 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.
    7. Steven Kachelmeier & Kristy Towry, 2005. "The Limitations of Experimental Design: A Case Study Involving Monetary Incentive Effects in Laboratory Markets," Experimental Economics, Springer;Economic Science Association, vol. 8(1), pages 21-33, April.
    8. Zhang, Wei & Huang, Ke & Feng, Xu & Zhang, Yongjie, 2017. "Market maker competition and price efficiency: Evidence from China," Economic Modelling, Elsevier, vol. 66(C), pages 121-131.
    9. Lamoureux, Christopher G. & Schnitzlein, Charles R., 2004. "Microstructure with multiple assets: an experimental investigation into direct and indirect dealer competition," Journal of Financial Markets, Elsevier, vol. 7(2), pages 117-143, February.
    10. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).
    11. 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.
    12. Charles N. Noussair & Steven Tucker, 2013. "Experimental Research On Asset Pricing," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 554-569, July.

    More about this item

    Keywords

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    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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