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A NASDAQ Market Simulation:Insights on a Major Market from the Science of Complex Adaptive Systems

Author

Listed:
  • Vince Darley

    (President & CEO of Eurobios, UK)

  • Alexander V Outkin

    (Los Alamos National Laboratory, USA)

Abstract

This pioneering book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the NASDAQ Stock Market's decimalization that was implemented in 2001.

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Vince Darley & Alexander V Outkin, 2007. "A NASDAQ Market Simulation:Insights on a Major Market from the Science of Complex Adaptive Systems," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6217.
    • Handle: RePEc:wsi:wsbook:6217
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    Citations

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    Cited by:

    1. Richard Bookstaber, 2012. "Using Agent-Based Models for Analyzing Threats to Financial Stability," Working Papers 12-03, Office of Financial Research, US Department of the Treasury.
    2. Mark Paddrik & Roy Hayes & William Scherer & Peter Beling, 2017. "Effects of limit order book information level on market stability metrics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 221-247, July.
    3. Gelman, Sergey & Lushchikov, Roman, 2015. "Stock liquidity in forefront of anticipated announcements," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113176, Verein für Socialpolitik / German Economic Association.
    4. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    5. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    6. Xinhui Yang & Jie Zhang & Qing Ye, 2020. "Tick size and market quality: Simulations based on agent‐based artificial stock markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 125-141, July.
    7. Liudmila G. Egorova, 2014. "The Effectiveness Of Different Trading Strategies For Price-Takers," HSE Working papers WP BRP 29/FE/2014, National Research University Higher School of Economics.
    8. Takanobu Mizuta, 2019. "An agent-based model for designing a financial market that works well," Papers 1906.06000, arXiv.org.
    9. Victor Storchan & Svitlana Vyetrenko & Tucker Balch, 2021. "Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators," Papers 2108.00664, arXiv.org.
    10. Colin M. Van Oort & Ethan Ratliff-Crain & Brian F. Tivnan & Safwan Wshah, 2023. "Adaptive Agents and Data Quality in Agent-Based Financial Markets," Papers 2311.15974, arXiv.org.
    11. Saki Kawakubo & Kiyoshi Izumi & Shinobu Yoshimura, 2014. "Analysis Of An Option Market Dynamics Based On A Heterogeneous Agent Model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(2), pages 105-128, April.
    12. Georges, Christophre, 2008. "Staggered updating in an artificial financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2809-2825, September.
    13. 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.
    14. 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.
    15. Richard Bookstaber & Mark Paddrik, 2015. "An Agent-Based Model of Liquidity," Working Papers 15-18, Office of Financial Research, US Department of the Treasury.
    16. Andjelka Kelic & Zachary A. Collier & Christopher Brown & Walter E. Beyeler & Alexander V. Outkin & Vanessa N. Vargas & Mark A. Ehlen & Christopher Judson & Ali Zaidi & Billy Leung & Igor Linkov, 2013. "Decision framework for evaluating the macroeconomic risks and policy impacts of cyber attacks," Environment Systems and Decisions, Springer, vol. 33(4), pages 544-560, December.
    17. Georges, Christophre & Wallace, John C., 2009. "Learning Dynamics And Nonlinear Misspecification In An Artificial Financial Market," Macroeconomic Dynamics, Cambridge University Press, vol. 13(5), pages 625-655, November.

    Book Chapters

    The following chapters of this book are listed in IDEAS

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