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Active Trading in ETFs: The Role of High-Frequency Algorithmic Trading

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  • Archana Jain
  • Chinmay Jain
  • Christine X. Jiang

Abstract

In the study reported here, we explored high-frequency algorithmic trading and its effect on exchange-traded funds (ETFs). Using the cancel rate, the trade-to-order ratio, percentage odd-lot volume, and trade size as proxies for algorithmic trading, we found that more algorithmic trading in ETFs results in smaller and less persistent deviations of fund prices from their net asset values (NAVs). Arbitrage strategies adopted by algorithmic traders directly help reduce the magnitude and persistence of ETF price deviations from NAVs. Also, algorithmic trading improves ETF liquidity by lowering spreads and facilitates arbitrage.Disclosure: The authors report no conflicts of interest. Editor’s note: Submitted 6 July 2020Accepted 10 December 2020 by Stephen J. BrownThis article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. Marius Zoican and one anonymous reviewer were the reviewers for this article.

Suggested Citation

  • Archana Jain & Chinmay Jain & Christine X. Jiang, 2021. "Active Trading in ETFs: The Role of High-Frequency Algorithmic Trading," Financial Analysts Journal, Taylor & Francis Journals, vol. 77(2), pages 66-82, April.
    • Handle: RePEc:taf:ufajxx:v:77:y:2021:i:2:p:66-82
    DOI: 10.1080/0015198X.2020.1865694
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