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High frequency trading strategies, market fragility and price spikes: an agent based model perspective

Citations

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Cited by:

  1. Peter Fratrič & Giovanni Sileno & Sander Klous & Tom Engers, 2022. "Manipulation of the Bitcoin market: an agent-based study," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
  2. Pankaj Kumar, 2021. "Deep Hawkes Process for High-Frequency Market Making," Papers 2109.15110, arXiv.org.
  3. Zetao Zheng & Guoan Li & Deqiang Ouyang & Decui Liang & Jie Shao, 2024. "Limit Order Book Event Stream Prediction with Diffusion Model," Papers 2412.09631, arXiv.org.
  4. 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).
  5. Kirill Mansurov & Alexander Semenov & Dmitry Grigoriev & Andrei Radionov & Rustam Ibragimov, 2024. "Cryptocurrency Exchange Simulation," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2585-2603, November.
  6. Taiga Saito & Shivam Gupta, 2025. "Big data applications with theoretical models and social media in financial management," Annals of Operations Research, Springer, vol. 348(3), pages 1489-1511, May.
  7. Kang Gao & Perukrishnen Vytelingum & Stephen Weston & Wayne Luk & Ce Guo, 2022. "Understanding intra-day price formation process by agent-based financial market simulation: calibrating the extended chiarella model," Papers 2208.14207, arXiv.org.
  8. Taiga Saito & Shivam Gupta, 2022. "Big Data Applications with Theoretical Models and Social Media in Financial Management," CIRJE F-Series CIRJE-F-1205, CIRJE, Faculty of Economics, University of Tokyo.
  9. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  10. Erdinc Akyildirim & Aurelio F. Bariviera & Duc Khuong Nguyen & Ahmet Sensoy, 2022. "Forecasting high-frequency stock returns: a comparison of alternative methods," Annals of Operations Research, Springer, vol. 313(2), pages 639-690, June.
  11. Zijian Shi & John Cartlidge, 2024. "Neural stochastic agent‐based limit order book simulation with neural point process and diffusion probabilistic model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
  12. Henry Hanifan & Ben Watson & John Cartlidge & Dave Cliff, 2021. "Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated Traders," Papers 2103.00600, arXiv.org.
  13. Alexander Musaev & Andrey Makshanov & Dmitry Grigoriev, 2022. "Numerical Studies of Channel Management Strategies for Nonstationary Immersion Environments: EURUSD Case Study," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
  14. Xianfeng Jiao & Zizhong Li & Chang Xu & Yang Liu & Weiqing Liu & Jiang Bian, 2023. "Microstructure-Empowered Stock Factor Extraction and Utilization," Papers 2308.08135, arXiv.org.
  15. Qixuan Luo & Shijia Song & Handong Li, 2023. "Research on the Effects of Liquidation Strategies in the Multi-asset Artificial Market," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1721-1750, December.
  16. Christopher J. Cho & Timothy J. Norman & Manuel Nunes, 2023. "PRIME: A Price-Reverting Impact Model of a cryptocurrency Exchange," Papers 2305.07559, arXiv.org.
  17. Henry Hanifan & John Cartlidge, 2019. "Fools Rush In: Competitive Effects of Reaction Time in Automated Trading," Papers 1912.02775, arXiv.org, revised Nov 2020.
  18. Gianluca P. M. Virgilio & Manuel Ernesto Paz López, 2024. "Revisiting noise—Fischer Black’s noise at the time of high-frequency trading," Risk Management, Palgrave Macmillan, vol. 26(4), pages 1-22, December.
  19. Zijian Shi & John Cartlidge, 2021. "The Limit Order Book Recreation Model (LOBRM): An Extended Analysis," Papers 2107.00534, arXiv.org.
  20. Victor Dragotă & Camelia Delcea, 2019. "How Long Does It Last to Systematically Make Bad Decisions? An Agent-Based Application for Dividend Policy," JRFM, MDPI, vol. 12(4), pages 1-34, November.
  21. Zijian Shi & John Cartlidge, 2023. "Neural Stochastic Agent-Based Limit Order Book Simulation: A Hybrid Methodology," Papers 2303.00080, arXiv.org.
  22. Kang Gao & Perukrishnen Vytelingum & Stephen Weston & Wayne Luk & Ce Guo, 2024. "High-Frequency Financial Market Simulation and Flash Crash Scenarios Analysis: An Agent-Based Modelling Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 27(2), pages 1-8.
  23. Perukrishnen Vytelingum & Rory Baggott & Namid Stillman & Jianfei Zhang & Dingqiu Zhu & Tao Chen & Justin Lyon, 2025. "Agent-based Liquidity Risk Modelling for Financial Markets," Papers 2505.15296, arXiv.org.
  24. Hu, Shicheng & Zhang, Weijie & Li, Danping & Wu, Bing, 2023. "Incorporating improved directional change and regime change detection to formulate trading strategies in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
  25. Kang Gao & Perukrishnen Vytelingum & Stephen Weston & Wayne Luk & Ce Guo, 2022. "High-frequency financial market simulation and flash crash scenarios analysis: an agent-based modelling approach," Papers 2208.13654, arXiv.org.
  26. Nicolas Cofre & Magdalena Mosionek-Schweda, 2023. "A simulated electronic market with speculative behaviour and bubble formation," Papers 2311.12247, arXiv.org.
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