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Stylized algorithmic trading: satisfying the predictive near-term demand of liquidity

Author

Listed:
  • Edward W. Sun

    (KEDGE Business School)

  • Timm Kruse

    (InfoTech)

  • Yi-Ting Chen

    (College of Computer Science, National Chiao Tung University)

Abstract

Regulatory reform enacted (e.g., the Dodd-Frank Act enforced in the U.S.) requires the financial service industry to consider the “reasonably expected near term demand” (i.e., RENTD) in trading. To manage the price impact and transaction cost associated with orders submitted to an order driven market, market makers or specialists must determine their trading styles (aggressive, neutral, or passive) based on the market liquidity in response to RENTD, particularly for trading a large quantity of some financial instrument. In this article we introduce a model considering different trading styles to satisfy the predictive near-term customer demand of market liquidity in order to find an optimal order submission strategy based on different market situations. We show some analytical properties and numerical performances of our model in search of optimal solutions. We evaluate the performances of our model with simulations run over a set of experiments in comparison with two alternative strategies. Our results suggest that the proposed model illustrates superiority in performance.

Suggested Citation

  • Edward W. Sun & Timm Kruse & Yi-Ting Chen, 2019. "Stylized algorithmic trading: satisfying the predictive near-term demand of liquidity," Annals of Operations Research, Springer, vol. 281(1), pages 315-347, October.
    • Handle: RePEc:spr:annopr:v:281:y:2019:i:1:d:10.1007_s10479-019-03150-0
    DOI: 10.1007/s10479-019-03150-0
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    References listed on IDEAS

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    1. Alexander Schied & Torsten Schöneborn, 2009. "Risk aversion and the dynamics of optimal liquidation strategies in illiquid markets," Finance and Stochastics, Springer, vol. 13(2), pages 181-204, April.
    2. Edward Sun & Timm Kruse & Min-Teh Yu, 2015. "Financial Transaction Tax: Policy Analytics Based on Optimal Trading," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 103-141, June.
    3. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    4. Foucault, Thierry & Pagano, Marco & Roell, Ailsa, 2013. "Market Liquidity: Theory, Evidence, and Policy," OUP Catalogue, Oxford University Press, number 9780199936243, Decembrie.
    5. Bessembinder, Hendrik & Carrion, Allen & Tuttle, Laura & Venkataraman, Kumar, 2016. "Liquidity, resiliency and market quality around predictable trades: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 121(1), pages 142-166.
    6. Edward Sun & Timm Kruse & Min-Teh Yu, 2014. "High frequency trading, liquidity, and execution cost," Annals of Operations Research, Springer, vol. 223(1), pages 403-432, December.
    7. Michael A. Goldstein & Paul Irvine & Eugene Kandel & Zvi Wiener, 2009. "Brokerage Commissions and Institutional Trading Patterns," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5175-5212, December.
    8. Albert S. Kyle & Anna A. Obizhaeva, 2016. "Market Microstructure Invariance: Empirical Hypotheses," Econometrica, Econometric Society, vol. 84, pages 1345-1404, July.
    9. Aur'elien Alfonsi & Antje Fruth & Alexander Schied, 2007. "Optimal execution strategies in limit order books with general shape functions," Papers 0708.1756, arXiv.org, revised Feb 2010.
    10. Ting, Christopher & Warachka, Mitch & Zhao, Yonggan, 2007. "Optimal liquidation strategies and their implications," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1431-1450, April.
    11. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
    12. Albert S. Kyle & Anna A. Obizhaeva, 2016. "Market Microstructure Invariance: Empirical Hypotheses," Econometrica, Econometric Society, vol. 84(4), pages 1345-1404, July.
    13. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "The Impact of Trades on Daily Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1241-1277.
    14. Aurelien Alfonsi & Antje Fruth & Alexander Schied, 2010. "Optimal execution strategies in limit order books with general shape functions," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 143-157.
    15. Werner, Ingrid M., 2003. "NYSE order flow, spreads, and information," Journal of Financial Markets, Elsevier, vol. 6(3), pages 309-335, May.
    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.
    17. Edward M. H. Lin & Edward W. Sun & Min-Teh Yu, 2018. "Systemic risk, financial markets, and performance of financial institutions," Annals of Operations Research, Springer, vol. 262(2), pages 579-603, March.
    18. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    19. Robert Almgren, 2003. "Optimal execution with nonlinear impact functions and trading-enhanced risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(1), pages 1-18.
    20. George C. Chacko & Jakub W. Jurek & Erik Stafford, 2008. "The Price of Immediacy," Journal of Finance, American Finance Association, vol. 63(3), pages 1253-1290, June.
    21. Anne Jones Dorn & Daniel Dorn & Paul Sengmueller, 2015. "Trading as Gambling," Management Science, INFORMS, vol. 61(10), pages 2376-2393, October.
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    Cited by:

    1. Giacomo Morelli, 2021. "Liquidity drops," Annals of Operations Research, Springer, vol. 299(1), pages 711-719, April.
    2. Barbara Będowska-Sójka, 2021. "Is liquidity wasted? The zero-returns on the Warsaw Stock Exchange," Annals of Operations Research, Springer, vol. 297(1), pages 37-51, February.

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    More about this item

    Keywords

    Artificial intelligence; Algorithmic trading; Decision analytics; Discrete optimization; FinTech; Liquidity;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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