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

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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.

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Authors and Affiliations

  1. Faculty of Education, Beijing Normal University, Beijing, 100875, China

    Qixuan Luo

  2. School of Systems Science, Beijing Normal University, Beijing, 100875, China

    Shijia Song & Handong Li

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  1. Qixuan Luo
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Appendices

Appendix

See Tables 13, 14, 15 and 16

Table 13 Descriptive statistical results of the return of the 40 constituent stocks in the SSE 50 in 2019
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Table 14 Results of the indicators of Stock 1 under different conditions
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Table 15 Results of the indicators of Stock 2 under different conditions
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Table 16 Results of the indicators of Stock 3 under different conditions
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Luo, Q., Song, S. & Li, H. Research on the Effects of Liquidation Strategies in the Multi-asset Artificial Market. Comput Econ 62, 1721–1750 (2023). https://doi.org/10.1007/s10614-022-10316-9

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