IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2010.08992.html
   My bibliography  Save this paper

Analysis of the impact of maker-taker fees on the stock market using agent-based simulation

Author

Listed:
  • Isao Yagi
  • Mahiro Hoshino
  • Takanobu Mizuta

Abstract

Recently, most stock exchanges in the U.S. employ maker-taker fees, in which an exchange pays rebates to traders placing orders in the order book and charges fees to traders taking orders from the order book. Maker-taker fees encourage traders to place many orders that provide market liquidity to the exchange. However, it is not clear how maker-taker fees affect the total cost of a taking order, including all the charged fees and the market impact. In this study, we investigated the effect of maker-taker fees on the total cost of a taking order with our artificial market model, which is an agent-based model for financial markets. We found that maker-taker fees encourage market efficiency but increase the total costs of taking orders.

Suggested Citation

  • Isao Yagi & Mahiro Hoshino & Takanobu Mizuta, 2020. "Analysis of the impact of maker-taker fees on the stock market using agent-based simulation," Papers 2010.08992, arXiv.org.
  • Handle: RePEc:arx:papers:2010.08992
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2010.08992
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chiarella, Carl & Iori, Giulia, 2009. "The impact of heterogeneous trading rules on the limit order book and order flows," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 525-537.
    2. Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
    3. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2013. "Liquidity Cycles and Make/Take Fees in Electronic Markets," Journal of Finance, American Finance Association, vol. 68(1), pages 299-341, February.
    4. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    5. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    6. T. Verheyden & L. De Moor & F. Van Den Bossche, 2013. "A Tale of Market Efficiency," Review of Business and Economic Literature, Intersentia, vol. 58(2), pages 140-158, June.
    7. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    8. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    9. Robert Battalio & Shane A. Corwin & Robert Jennings, 2016. "Can Brokers Have It All? On the Relation between Make-Take Fees and Limit Order Execution Quality," Journal of Finance, American Finance Association, vol. 71(5), pages 2193-2238, October.
    10. Justin Cox & Bonnie Van Ness & Robert Van Ness, 2019. "Increasing the Tick: Examining the Impact of the Tick Size Change on Maker‐Taker and Taker‐Maker Market Models," The Financial Review, Eastern Finance Association, vol. 54(3), pages 417-449, August.
    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. Andrea Coletta & Matteo Prata & Michele Conti & Emanuele Mercanti & Novella Bartolini & Aymeric Moulin & Svitlana Vyetrenko & Tucker Balch, 2021. "Towards Realistic Market Simulations: a Generative Adversarial Networks Approach," Papers 2110.13287, arXiv.org.
    2. Mahiro Hoshino & Takanobu Mizuta & Yasuhiro Sudo & Isao Yagi, 2022. "Impact of maker-taker fees on stock exchange competition from an agent-based simulation," Journal of Computational Social Science, Springer, vol. 5(2), pages 1323-1342, November.

    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. Mahiro Hoshino & Takanobu Mizuta & Yasuhiro Sudo & Isao Yagi, 2022. "Impact of maker-taker fees on stock exchange competition from an agent-based simulation," Journal of Computational Social Science, Springer, vol. 5(2), pages 1323-1342, November.
    2. Alexandru Mandes, 2014. "Order Placement in a Continuous Double Auction Agent Based Model," MAGKS Papers on Economics 201443, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Baosheng Yuan & Kan Chen, 2006. "Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(2), pages 189-214, November.
    4. Brian Tivnan & Matthew Koehler & Matthew McMahon & Matthew Olson & Neal Rothleder & Rajani Shenoy, 2011. "Adding to the Regulator's Toolbox: Integration and Extension of Two Leading Market Models," Papers 1105.5439, arXiv.org.
    5. Iris Lucas & Michel Cotsaftis & Cyrille Bertelle, 2017. "Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems," Post-Print hal-02114933, HAL.
    6. Jiahua Wang & Hongliang Zhu & Dongxin Li, 2018. "Price Dynamics in an Order-Driven Market with Bayesian Learning," Complexity, Hindawi, vol. 2018, pages 1-15, November.
    7. Alexandru Mandes & Peter Winker, 2017. "Complexity and model comparison in agent based modeling of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 469-506, October.
    8. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    9. Isao Yagi & Yuji Masuda & Takanobu Mizuta, 2020. "Analysis of the Impact of High-Frequency Trading on Artificial Market Liquidity," Papers 2010.13038, arXiv.org.
    10. Oliver Hein & Michael Schwind & Markus Spiwoks, 2008. "Frankfurt Artificial Stock Market: a microscopic stock market model with heterogeneous interacting agents in small-world communication networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 59-71, June.
    11. Isao Yagi & Atsushi Nozaki & Takanobu Mizuta, 2017. "Investigation of the rule for investment diversification at the time of a market crash using an artificial market simulation," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 451-465, December.
    12. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    13. Brock, William A. & Hommes, Cars H. & Wagener, Florian O. O., 2005. "Evolutionary dynamics in markets with many trader types," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 7-42, February.
    14. Yamamoto, Ryuichi & Hirata, Hideaki, 2013. "Strategy switching in the Japanese stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 37(10), pages 2010-2022.
    15. Baosheng Yuan & Kan Chen, 2005. "Impact of Investor's Varying Risk Aversion on the Dynamics of Asset Price Fluctuations," Papers physics/0506224, arXiv.org.
    16. Omurtag, Ahmet & Sirovich, Lawrence, 2006. "Modeling a large population of traders: Mimesis and stability," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 562-576, December.
    17. Marco Raberto & Silvano Cincotti & Sergio Focardi & Michele Marchesi, 2003. "Traders' Long-Run Wealth in an Artificial Financial Market," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 255-272, October.
    18. Anufriev, Mikhail & Panchenko, Valentyn, 2009. "Asset prices, traders' behavior and market design," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1073-1090, May.
    19. Andrea Gaunersdorfer & Cars Hommes, 2007. "A Nonlinear Structural Model for Volatility Clustering," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288, Springer.
    20. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.

    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:2010.08992. 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.