IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v55y2020i2d10.1007_s10614-019-09891-1.html
   My bibliography  Save this article

Impact of Electronic Liquidity Providers Within a High-Frequency Agent-Based Modeling Framework

Author

Listed:
  • Alexandru Mandes

    (University of Giessen)

Abstract

The current contribution addresses the impact of high-frequency electronic liquidity provision strategies on the intraday dynamics of financial markets, by means of an artificial stock market. As novel design feature, an event-based intraday time implementation is proposed, allowing for the generation of time-stamped intraday events, which make possible both the aggregation of time series at various time frequencies, as well as the correct simulation of trading strategies that follow different temporal frequencies, e.g., low- and high-frequency. We provide new insights with respect to the determinants of extreme events, such as flash crashes. Finally, we compare the causal chains and the effectiveness of two potential regulatory policies under the same market circumstances, i.e., minimum resting time and financial-transaction taxes, not only with respect to their flash crash prevention power, but also regarding their impact on market participants and market quality, shedding new light on the policy trade-offs.

Suggested Citation

  • Alexandru Mandes, 2020. "Impact of Electronic Liquidity Providers Within a High-Frequency Agent-Based Modeling Framework," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 407-450, February.
  • Handle: RePEc:kap:compec:v:55:y:2020:i:2:d:10.1007_s10614-019-09891-1
    DOI: 10.1007/s10614-019-09891-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-019-09891-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10614-019-09891-1?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. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2004. "Fluctuations and response in financial markets: the subtle nature of 'random' price changes," Quantitative Finance, Taylor & Francis Journals, vol. 4(2), pages 176-190.
    2. 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.
    3. Harris, Larry, 2002. "Trading and Exchanges: Market Microstructure for Practitioners," OUP Catalogue, Oxford University Press, number 9780195144703.
    4. Carl Chiarella & Giulia Iori, 2002. "A simulation analysis of the microstructure of double auction markets," Quantitative Finance, Taylor & Francis Journals, vol. 2(5), pages 346-353.
    5. repec:bla:jecsur:v:22:y:2008:i:4:p:711-751 is not listed on IDEAS
    6. Marco Avellaneda & Sasha Stoikov, 2008. "High-frequency trading in a limit order book," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 217-224.
    7. Christophe Deissenberg & Sander van Der Hoog & Herbert Dawid, 2008. "EURACE: A Massively Parallel Agent-Based Model of the European Economy," Working Papers halshs-00339756, HAL.
    8. Didier SORNETTE & Susanne VON DER BECKE, 2011. "Crashes and High Frequency Trading," Swiss Finance Institute Research Paper Series 11-64, Swiss Finance Institute.
    9. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    10. Gsell, Markus, 2008. "Assessing the impact of algorithmic trading on markets: A simulation approach," CFS Working Paper Series 2008/49, Center for Financial Studies (CFS).
    11. Herbert Dawid & Michael Neugart, 2011. "Agent-based Models for Economic Policy Design," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 44-50.
    12. Herbert Dawid & Simon Gemkow & Philipp Harting & Michael Neugart, 2013. "Labor Market Integration Policies and The Convergence of Regions: The Role of Skills and Technology Diffusion," Economic Complexity and Evolution, in: Guido Buenstorf & Uwe Cantner & Horst Hanusch & Michael Hutter & Hans-Walter Lorenz & Fritz Rahmeyer (ed.), The Two Sides of Innovation, edition 127, pages 167-186, Springer.
    13. Didier SORNETTE & Susanne VON DER BECKE, 2011. "Crashes and High Frequency Trading," Swiss Finance Institute Research Paper Series 11-63, Swiss Finance Institute.
    14. 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.
    15. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    16. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    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. Alexandru Mandes, 2015. "Impact of inventory-based electronic liquidity providers within a high-frequency event- and agent-based modeling framework," MAGKS Papers on Economics 201515, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    3. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
    4. repec:spo:wpmain:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
    5. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    6. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    7. Chiarella, Carl & Ladley, Daniel, 2016. "Chasing trends at the micro-level: The effect of technical trading on order book dynamics," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 119-131.
    8. Ricetti, Luca & Russo, Alberto & Gallegati, Mauro, 2013. "Unemployment benefits and financial leverage in an agent based macroeconomic model," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-44.
    9. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    10. Virgilio, Gianluca, 2017. "Is high-frequency trading tiering the financial markets?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 158-171.
    11. Roberto Mota Navarro & Hern'an Larralde Ridaura, 2016. "A detailed heterogeneous agent model for a single asset financial market with trading via an order book," Papers 1601.00229, arXiv.org, revised Jul 2016.
    12. Matthias Lengnick & Hans-Werner Wohltmann, 2013. "Agent-based financial markets and New Keynesian macroeconomics: a synthesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 1-32, April.
    13. Wladimir Ostrovsky, 2023. "Dealer Strategies in Agent-Based Models," Papers 2312.05943, arXiv.org.
    14. Gianluca Piero Maria Virgilio, 2019. "High-frequency trading: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 183-208, June.
    15. Gao-Feng Gu & Xiong Xiong & Hai-Chuan Xu & Wei Zhang & Yongjie Zhang & Wei Chen & Wei-Xing Zhou, 2021. "An empirical behavioral order-driven model with price limit rules," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    16. Daniel Fricke & Thomas Lux, 2015. "The effects of a financial transaction tax in an artificial financial market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 119-150, April.
    17. Olivier Guéant, 2016. "The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making," Post-Print hal-01393136, HAL.
    18. Christopher M Wray & Steven R Bishop, 2016. "A Financial Market Model Incorporating Herd Behaviour," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-28, March.
    19. Chia-Hsuan Yeh & Chun-Yi Yang, 2013. "Do price limits hurt the market?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 125-153, April.
    20. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).
    21. Iwao Maeda & David deGraw & Michiharu Kitano & Hiroyasu Matsushima & Kiyoshi Izumi & Hiroki Sakaji & Atsuo Kato, 2020. "Latent Segmentation of Stock Trading Strategies Using Multi-Modal Imitation Learning," JRFM, MDPI, vol. 13(11), pages 1-12, October.
    22. Steffen, Viktoria, 2023. "A literature review on extreme price movements with reversal," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).

    More about this item

    Keywords

    Agent-based modeling; High-frequency trading; Electronic liquidity provision; Market quality; Flash crash; Regulatory policy;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:kap:compec:v:55:y:2020:i:2:d:10.1007_s10614-019-09891-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.