Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model

Qixuan Luo (), Yu Shi (), Xuan Zhou () and Handong Li ()
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Qixuan Luo: Beijing Normal University
Yu Shi: Beijing Normal University
Xuan Zhou: Beijing Normal University
Handong Li: Beijing Normal University

Computational Economics, 2021, vol. 58, issue 4, No 4, 1025-1049

Abstract: Abstract Based on the multi-agent model, an artificial stock market with four types of traders is constructed. On this basis, this paper focuses on comparing the effects of liquidation behavior on market liquidity, volatility, price discovery efficiency and long memory of absolute returns when the institutional trader adopts equal-order strategy, Volume Weighted Average Price (VWAP) strategy and Implementation Shortfall (IS) strategy respectively. The results show the following: (1) the artificial stock market based on multi-agent model can reproduce the stylized facts of real stock market well; (2) among these three algorithmic trading strategies, IS strategy causes the longest liquidation time and the lowest liquidation cost; (3) the liquidation behavior of institutional trader will significantly reduce market liquidity, price discovery efficiency and long memory of absolute returns, and increase market volatility; (4) in comparison, IS strategy has the least impact on market liquidity, volatility and price discovery efficiency, while VWAP strategy has the least impact on long memory of absolute returns.

Keywords: Multi-agent model; Artificial stock market; Effects of liquidation strategies; Algorithmic trading; Equal-order strategy; VWAP strategy; IS strategy (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10614-020-09987-z

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