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Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High-Frequency Trading

Author

Listed:
  • Sandrine Jacob Leal

    (ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine)

  • Mauro Napoletano

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

Abstract

We investigate the effects of a set of regulatory policies directed towards high-frequency trading (HFT) through an agent-based model of a limit order book able to generate flash crashes as the result of the interactions between low- and high-frequency traders. In particular, we study the impact of the imposition of minimum resting times, of circuit breakers, of cancellation fees and of transaction taxes on asset price volatility and on the occurrence and the duration of flash crashes. Monte-Carlo simulations reveal that HFT-targeted policies imply a trade-off between market stability and resilience. Indeed, we find that policies able to tackle volatility and flash crashes also hinder the market from quickly recovering after a crash. This result is mainly due to the dual role of HFT, as both a cause of flash crashes and a key player in the post-crash recovery.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Sandrine Jacob Leal & Mauro Napoletano, 2016. "Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High-Frequency Trading," Working Papers hal-01512781, HAL.
    • Handle: RePEc:hal:wpaper:hal-01512781
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    Cited by:

    1. Shen, Dehua & Shi, Guiqiang, 2025. "The role of whale investors in the bitcoin market," Research in International Business and Finance, Elsevier, vol. 78(C).
    2. Xing Gao & Daniel Ladley, 2022. "Noise trading and market stability," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1283-1301, October.
    3. Takanobu Mizuta & Sadayuki Horie, 2019. "Mechanism by which active funds make market efficient investigated with agent-based model," Evolutionary and Institutional Economics Review, Springer, vol. 16(1), pages 43-63, June.
    4. Xintong Wang & Christopher Hoang & Yevgeniy Vorobeychik & Michael P. Wellman, 2021. "Spoofing the Limit Order Book: A Strategic Agent-Based Analysis," Games, MDPI, vol. 12(2), pages 1-43, May.
    5. Xinyue He & Teresa Serra & Philip Garcia, 2021. "Resilience in “Flash Events” in the Corn and Lean Hog Futures Markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 743-764, March.
    6. Wang, Liming & Sun, Xuchu & Zhu, Hongliang & Li, Tangrong, 2025. "Exploring the dynamic impact of transaction taxes on market quality in HFT and non-HFT environments: An agent-based modeling approach," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
    7. Mignot Sarah & Pellizzari Paolo & Westerhoff Frank, 2024. "Fake News and Asset Price Dynamics," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 244(4), pages 351-379.
    8. Albert Sanghoon Park, 2024. "Understanding resilience in sustainable development: Rallying call or siren song?," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(1), pages 260-274, February.
    9. Sarah Mignot & Fabio Tramontana & Frank Westerhoff, 2021. "Speculative asset price dynamics and wealth taxes," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 641-667, December.
    10. Tianlin Hu & Yang Ming, 2025. "When Do Circuit Breakers Stabilize Markets? Evidence and Theory," Annals of Economics and Finance, Society for AEF, vol. 26(2), pages 573-613, November.
    11. Xiaotao Zhang & Jing Ping & Tao Zhu & Yuelei Li & Xiong Xiong, 2016. "Are Price Limits Effective? An Examination of an Artificial Stock Market," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-21, August.
    12. Svitlana Vyetrenko & David Byrd & Nick Petosa & Mahmoud Mahfouz & Danial Dervovic & Manuela Veloso & Tucker Hybinette Balch, 2019. "Get Real: Realism Metrics for Robust Limit Order Book Market Simulations," Papers 1912.04941, arXiv.org.
    13. Benjamin Clapham & Martin Haferkorn & Kai Zimmermann, 2020. "Does Speed Matter? The Role Of High‐Frequency Trading For Order Book Resiliency," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(4), pages 933-964, December.
    14. Bernardo A. Furtado & Miguel A. Fuentes & Claudio J. Tessone, 2019. "Policy Modeling and Applications: State-of-the-Art and Perspectives," Complexity, Hindawi, vol. 2019, pages 1-11, February.
    15. Noemi Schmitt & Ivonne Schwartz & Frank Westerhoff, 2022. "Heterogeneous speculators and stock market dynamics: a simple agent-based computational model," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1263-1282, October.

    More about this item

    Keywords

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G01 - Financial Economics - - General - - - Financial Crises
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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