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Research on the Effects of Liquidation Strategies in the Multi-asset Artificial Market

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  • Qixuan Luo

    (Beijing Normal University)

  • Shijia Song

    (Beijing Normal University)

  • Handong Li

    (Beijing Normal University)

Abstract

The widespread application of algorithmic trading (AT) will have a lasting and profound effect on the financial market. This paper uses the multi-agent model to construct a multi-asset artificial stock market that can trade multiple assets simultaneously. The simulation results show that the multi-asset market can reproduce the stylized facts of the actual stock market. Then, the effects of an institutional trader using the four different AT strategies on the market containing the three risky assets are studied. The results are as follows: (1) The two types of implementation shortfall (IS) strategies can help the institutional trader achieve the smaller total liquidation costs; (2) the liquidation behavior of the institutional trader using the different strategies has significant negative impacts on the most market indicators of the liquidity, the volatility, the price discovery efficiency and the long memory of absolute returns on the whole, while the individual market indicators are improved in a few cases; (3) compared with the other three strategies, the portfolio IS strategy considering both the optimal liquidation time and the correlation of the stocks is better in terms of the execution effects and the impacts on the market.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:62:y:2023:i:4:d:10.1007_s10614-022-10316-9
    DOI: 10.1007/s10614-022-10316-9
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    1. Erhan Bayraktar & Michael Ludkovski, 2014. "Liquidation In Limit Order Books With Controlled Intensity," Mathematical Finance, Wiley Blackwell, vol. 24(4), pages 627-650, October.
    2. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Alex Frino & Michael Garcia & Zeyang Zhou, 2020. "Impact of algorithmic trading on speed of adjustment to new information: Evidence from interest rate derivatives," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 749-760, May.
    4. Paulwin Graewe & Ulrich Horst, 2016. "Optimal Trade Execution with Instantaneous Price Impact and Stochastic Resilience," Papers 1611.03435, arXiv.org, revised Jul 2017.
    5. Richard Bookstaber & Mark Paddrik & Brian Tivnan, 2018. "An agent-based model for financial vulnerability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 433-466, July.
    6. David K. Ding & Sie Ting Lau, 2001. "An Analysis of Transactions Data for the Stock Exchange of Singapore: Patterns, Absolute Price Change, Trade Size and Number of Transactions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(1‐2), pages 151-174, January.
    7. He, Hua & Mamaysky, Harry, 2005. "Dynamic trading policies with price impact," Journal of Economic Dynamics and Control, Elsevier, vol. 29(5), pages 891-930, May.
    8. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    9. Scholtus, Martin & van Dijk, Dick & Frijns, Bart, 2014. "Speed, algorithmic trading, and market quality around macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 89-105.
    10. Forsyth, P.A. & Kennedy, J.S. & Tse, S.T. & Windcliff, H., 2012. "Optimal trade execution: A mean quadratic variation approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1971-1991.
    11. Frank McGroarty & Ash Booth & Enrico Gerding & V. L. Raju Chinthalapati, 2019. "High frequency trading strategies, market fragility and price spikes: an agent based model perspective," Annals of Operations Research, Springer, vol. 282(1), pages 217-244, November.
    12. Frédéric Abergel & Côme Huré & Huyên Pham, 2020. "Algorithmic trading in a microstructural limit order book model," Post-Print hal-01514987, HAL.
    13. Xue Cheng & Marina Di Giacinto & Tai-Ho Wang, 2017. "Optimal execution with uncertain order fills in Almgren–Chriss framework," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 55-69, January.
    14. Brogaard, Jonathan & Garriott, Corey, 2019. "High-Frequency Trading Competition," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(4), pages 1469-1497, August.
    15. 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).
    16. David K. Ding & Sie Ting Lau, 2001. "An Analysis of Transactions Data for the Stock Exchange of Singapore: Patterns, Absolute Price Change, Trade Size and Number of Transactions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(1-2), pages 151-174.
    17. Jim Gatheral & Alexander Schied, 2011. "Optimal Trade Execution Under Geometric Brownian Motion In The Almgren And Chriss Framework," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 353-368.
    18. Olivier Guéant & Charles-Albert Lehalle, 2015. "General Intensity Shapes In Optimal Liquidation," Mathematical Finance, Wiley Blackwell, vol. 25(3), pages 457-495, July.
    19. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
    20. Qixuan Luo & Yu Shi & Xuan Zhou & Handong Li, 2021. "Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1025-1049, December.
    21. Chiarella, Carl & He, Xue-Zhong & Pellizzari, Paolo, 2012. "A Dynamic Analysis Of The Microstructure Of Moving Average Rules In A Double Auction Market," Macroeconomic Dynamics, Cambridge University Press, vol. 16(4), pages 556-575, September.
    22. Farjam, Mike & Kirchkamp, Oliver, 2018. "Bubbles in hybrid markets: How expectations about algorithmic trading affect human trading," Journal of Economic Behavior & Organization, Elsevier, vol. 146(C), pages 248-269.
    23. René Carmona & Kevin Webster, 2019. "The self-financing equation in limit order book markets," Finance and Stochastics, Springer, vol. 23(3), pages 729-759, July.
    24. Frédéric Abergel & Côme Huré & Huyên Pham, 2020. "Algorithmic trading in a microstructural limit order book model," Quantitative Finance, Taylor & Francis Journals, vol. 20(8), pages 1263-1283, August.
    25. Bernales, Alejandro, 2019. "Make-take decisions under high-frequency trading competition," Journal of Financial Markets, Elsevier, vol. 45(C), pages 1-18.
    26. 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.
    27. Olivier Guéant & Charles-Albert Lehalle, 2015. "General Intensity Shapes In Optimal Liquidation," Mathematical Finance, Wiley Blackwell, vol. 25(3), pages 457-495, July.
    28. Fr'ed'eric Abergel & C^ome Hur'e & Huy^en Pham, 2017. "Algorithmic trading in a microstructural limit order book model," Papers 1705.01446, arXiv.org, revised Feb 2020.
    29. Glosten, Lawrence R. & Harris, Lawrence E., 1988. "Estimating the components of the bid/ask spread," Journal of Financial Economics, Elsevier, vol. 21(1), pages 123-142, May.
    30. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    31. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    32. Yasong Jin, 2017. "Optimal execution strategy and liquidity adjusted value-at-risk," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1147-1157, August.
    33. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    34. 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.
    35. Noemi Schmitt & Frank Westerhoff, 2017. "Herding behaviour and volatility clustering in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1187-1203, August.
    36. Alexis Bismuth & Olivier Gu'eant & Jiang Pu, 2016. "Portfolio choice, portfolio liquidation, and portfolio transition under drift uncertainty," Papers 1611.07843, arXiv.org, revised Mar 2019.
    37. 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.
    38. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    39. Weston Barger & Matthew Lorig, 2019. "Optimal Liquidation Under Stochastic Price Impact," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 1-28, March.
    40. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    41. 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.
    42. Qixuan Luo & Yu Shi & Handong Li, 2021. "Research on Portfolio Liquidation Strategy under Discrete Times," Papers 2103.15400, arXiv.org.
    43. Pankaj K. Jain, 2005. "Financial Market Design and the Equity Premium: Electronic versus Floor Trading," Journal of Finance, American Finance Association, vol. 60(6), pages 2955-2985, December.
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