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Stability effects of arbitrage in exchange traded funds: an agent-based model

Authors:

Tucker Hybinette Balch,

Michael P. WellmanAuthors Info & Claims

ICAIF '21: Proceedings of the Second ACM International Conference on AI in Finance

Article No.: 49, Pages 1 - 9

https://doi.org/10.1145/3490354.3494414

Published: 04 May 2022 Publication History

Abstract

An index-based exchange traded fund (ETF) with underlying securities that trade on the same market creates potential opportunities for arbitrage between price deviations in the ETF and the corresponding index. We examine whether ETF arbitrage transmits small volatility events, termed mini flash crashes, from one of its underlying symbols to another. We address this question in an agent-based, simulated market where agents can trade an ETF and its two underlying symbols. We explore multiple market configurations with active and inactive ETF arbitrageurs. Through empirical game-theoretic analysis, we find that when arbitrageurs actively trade, background traders' surplus increases because of the increased liquidity. Arbitrage helps the ETF more accurately track the index. We also observe that when one symbol experiences a mini flash crash, arbitrage transmits a price change in the opposite direction to the other symbol. The size of the mini flash crash depends more on the market configuration than the arbitrageurs, but the recovery of the mini flash crash is faster when arbitrageurs are present.

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Cited By

Yagi IGuan XMizuta T(2024)Investigation of market impacts of arbitrage trading between an ETF and its underlying assets using an agent-based simulationFinance Research Letters10.1016/j.frl.2024.10586267(105862)Online publication date: Sep-2024
https://doi.org/10.1016/j.frl.2024.105862
Guan XMizuta TYagi I(2024)Impact of arbitrage trading between an ETF and its underlying assets on market liquidity of their markets using an agent-based simulationJournal of Computational Social Science10.1007/s42001-024-00324-07:3(2839-2870)Online publication date: 18-Sep-2024
https://doi.org/10.1007/s42001-024-00324-0
Shearer MRauterberg GWellman M(2023)Learning to Manipulate a Financial BenchmarkProceedings of the Fourth ACM International Conference on AI in Finance10.1145/3604237.3626847(592-600)Online publication date: 27-Nov-2023
https://dl.acm.org/doi/10.1145/3604237.3626847

Stability effects of arbitrage in exchange traded funds: an agent-based model
1. Applied computing
  1. Law, social and behavioral sciences

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cover image ACM Conferences

ICAIF '21: Proceedings of the Second ACM International Conference on AI in Finance

November 2021

450 pages

ISBN:9781450391481

DOI:10.1145/3490354

General Chairs:
Anisoara Calinescu
University of Oxford, UK
,
Lukasz Szpruch
The Alan Turing Institute and University of Edinburgh, UK

Copyright © 2021 ACM.

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Published: 04 May 2022

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Cited By

Yagi IGuan XMizuta T(2024)Investigation of market impacts of arbitrage trading between an ETF and its underlying assets using an agent-based simulationFinance Research Letters10.1016/j.frl.2024.10586267(105862)Online publication date: Sep-2024
https://doi.org/10.1016/j.frl.2024.105862
Guan XMizuta TYagi I(2024)Impact of arbitrage trading between an ETF and its underlying assets on market liquidity of their markets using an agent-based simulationJournal of Computational Social Science10.1007/s42001-024-00324-07:3(2839-2870)Online publication date: 18-Sep-2024
https://doi.org/10.1007/s42001-024-00324-0
Shearer MRauterberg GWellman M(2023)Learning to Manipulate a Financial BenchmarkProceedings of the Fourth ACM International Conference on AI in Finance10.1145/3604237.3626847(592-600)Online publication date: 27-Nov-2023
https://dl.acm.org/doi/10.1145/3604237.3626847

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