Impact of arbitrage trading between an ETF and its underlying assets on market liquidity of their markets using an agent-based simulation

Xin Guan (), Takanobu Mizuta () and Isao Yagi ()
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Xin Guan: Kogakuin University Graduate School
Takanobu Mizuta: SPARX Asset Management Co. Ltd.
Isao Yagi: Kogakuin University

Journal of Computational Social Science, 2024, vol. 7, issue 3, No 20, 2839-2870

Abstract: Abstract Exchange-traded funds (ETFs) are mutual funds that invest in a diversified portfolio of many financial assets. They are listed on stock exchanges and traded as financial instruments. As some ETFs are exchangeable with all the underlying assets held by the ETFs, when the ETF’s price and the total value of the underlying assets held by the ETF differ, some investors buy the cheaper one and sell the more expensive one to make a profit from the price difference (i.e., arbitrage trading). In this study, we constructed an artificial market consisting of two underlying assets and an ETF and then conducted simulations of arbitrage trading between the underlying asset markets and the ETF market, comparing scenarios with and without arbitrage trading. From the results, we evaluated the essential impact of arbitrage trading on the liquidity of each market from the perspective of representative liquidity indicators (Volume, Depth, and Tightness). In addition, we also checked how liquidity differs when the orders that are submitted are unevenly distributed across markets. The results revealed that there is a tendency for liquidity to differ between Volume, which is highly valued by financial practitioners, and other indicators (Depth and Tightness). Volume represents trading activity, whereas the other indicators represent the current condition of the market. Therefore, it is important for prospective traders to consider liquidity beyond Volume alone when making investment decisions.

Keywords: Agent-based simulation; Artificial market; Arbitrage trading; ETF (exchange-traded funds); Financial market; Market liquidity (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s42001-024-00324-0

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