IDEAS home Printed from https://ideas.repec.org/p/cer/papers/wp738.html
   My bibliography  Save this paper

Effect of Exchange-Traded Funds Arbitrage Transactions on their Underlying Holdings

Author

Listed:
  • Gregory Boadu-Sebbe

Abstract

A critical aspect of trading Exchange-Traded Funds (ETFs) is the arbitrage trading strategy taken by authorized participants (APs) to keep ETF prices in line with their net asset values (NAVs). ETF arbitrage trading is a strategy that exploits the discrepancies between an ETF price and the value of the ETF’s underlying assets. In this study, I quantitatively examine the effect of ETF arbitrage on the underlying assets of an ETF. I develop a dynamic state-space model that jointly estimates the price dynamics of an ETF and its underlying assets by explicitly incorporating the ETF arbitrage. The model is estimated individually for the Dow Jones Industrial Average ETF (DIA) and the VanEck Vectors Semiconductor ETF (SMH). The empirical results show that ETF liquidity shocks propagate to the underlying assets via the ETF arbitrage mechanism. These ETF liquidity shocks add a permanent layer of transitory volatility to the underlying asset prices. I find that a unit of liquidity shock to DIA brings a range of 0.1% to 0.93% of extra volatility to the underlying assets of DIA. Similarly, a unit of liquidity shock to SMH adds a range of 0.33% to 0.95% of additional volatility to the underlying assets. In addition, I show that it takes APs longer to correct deviations between the ETF price and its NAV. It takes approximately 4 and 10 minutes for APs to perform the ETF arbitrage for DIA and SMH, respectively. Finally, the findings suggest that an ETF arbitrage transaction speeds up the price discovery process in the ETF markets. There are approximately 74% and 67% variations in the premiums of DIA and SMH due to price discovery, respectively.

Suggested Citation

  • Gregory Boadu-Sebbe, 2022. "Effect of Exchange-Traded Funds Arbitrage Transactions on their Underlying Holdings," CERGE-EI Working Papers wp738, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  • Handle: RePEc:cer:papers:wp738
    as

    Download full text from publisher

    File URL: http://www.cerge-ei.cz/pdf/wp/Wp738.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Menkveld, Albert J. & Koopman, Siem Jan & Lucas, Andre, 2007. "Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 213-225, April.
    2. Markus S. Broman & Pauline Shum, 2018. "Relative Liquidity, Fund Flows and Short†Term Demand: Evidence from Exchange†Traded Funds," The Financial Review, Eastern Finance Association, vol. 53(1), pages 87-115, February.
    3. Dannhauser, Caitlin D., 2017. "The impact of innovation: Evidence from corporate bond exchange-traded funds (ETFs)," Journal of Financial Economics, Elsevier, vol. 125(3), pages 537-560.
    4. Dong Lou, 2012. "A Flow-Based Explanation for Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3457-3489.
    5. Roberto Pascual & David Veredas, 2010. "Does the Open Limit Order Book Matter in Explaining Informational Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 57-87, Winter.
    6. Doron Israeli & Charles M. C. Lee & Suhas A. Sridharan, 2017. "Is there a dark side to exchange traded funds? An information perspective," Review of Accounting Studies, Springer, vol. 22(3), pages 1048-1083, September.
    7. Itzhak Ben‐David & Francesco Franzoni & Rabih Moussawi, 2018. "Do ETFs Increase Volatility?," Journal of Finance, American Finance Association, vol. 73(6), pages 2471-2535, December.
    8. Marcelo Perlin & Alfonso Dufour & Chris Brooks, 2014. "The determinants of a cross market arbitrage opportunity: theory and evidence for the European bond market," Annals of Finance, Springer, vol. 10(3), pages 457-480, August.
    9. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    10. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    11. Hilliard, Jitka, 2014. "Premiums and discounts in ETFs: An analysis of the arbitrage mechanism in domestic and international funds," Global Finance Journal, Elsevier, vol. 25(2), pages 90-107.
    12. Jeffrey Pontiff, 1996. "Costly Arbitrage: Evidence from Closed-End Funds," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(4), pages 1135-1151.
    13. Roberto Pascual & David Veredas, 2009. "What pieces of limit order book information matter in explaining order choice by patient and impatient traders?," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 527-545.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Atanasova, Christina & Weisskopf, Jean-Philippe, 2020. "The price of international equity ETFs: The role of relative liquidity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    2. Luca J. Liebi, 2020. "The effect of ETFs on financial markets: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 165-178, June.
    3. Bae, Kyounghun & Kim, Daejin, 2020. "Liquidity risk and exchange-traded fund returns, variances, and tracking errors," Journal of Financial Economics, Elsevier, vol. 138(1), pages 222-253.
    4. Joey W. Yang & Lewis May & John Gould, 2023. "Exchange‐traded fund ownership and underlying stock mispricing," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(S1), pages 1417-1445, April.
    5. Agarwal, Vikas & Hanouna, Paul & Moussawi, Rabih & Stahel, Christof W., 2021. "Do ETFs increase the commonality in liquidity of underlying stocks?," CFR Working Papers 21-04, University of Cologne, Centre for Financial Research (CFR).
    6. Broman, Markus S., 2020. "Local demand shocks, excess comovement and return predictability," Journal of Banking & Finance, Elsevier, vol. 119(C).
    7. Hautsch, Nikolaus & Hess, Dieter & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2733-2746, October.
    8. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    9. Xu, Liao & Yin, Xiangkang & Zhao, Jing, 2019. "The sidedness and informativeness of ETF trading and the market efficiency of their underlying indexes," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    10. Yuan, Ying & Huang, Yizhao & Chen, Haoran, 2021. "Monthly-rebalanced leveraged exchange-traded products: Performance and mandatory rebalancing needs," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    11. Piotr Fryzlewicz & Thorsten Rheinlander & Marcela Valenzuela & Ilknur Zer, 2014. "Relative Liquidity and Future Volatility," Finance and Economics Discussion Series 2014-45, Board of Governors of the Federal Reserve System (U.S.).
    12. Saæglam, Mehmet & Tuzun, Tugkan & Wermers, Russ, 2021. "Do ETFs increase liquidity?," CFR Working Papers 21-03, University of Cologne, Centre for Financial Research (CFR).
    13. Jang, In Ji & Kang, Namho & Yezegel, Ari, 2022. "Common ownership, price informativeness, and corporate investment," Journal of Banking & Finance, Elsevier, vol. 135(C).
    14. Rhodes, Meredith E. & Mason, Joseph R., 2023. "ETF ownership and firm-specific information in corporate bond returns," Journal of Financial Markets, Elsevier, vol. 63(C).
    15. Nathan Converse & Eduardo Levy-Yeyati & Tomas Williams & Itay Goldstein, 2023. "How ETFs Amplify the Global Financial Cycle in Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 36(9), pages 3423-3462.
    16. Box, Travis & Davis, Ryan & Evans, Richard & Lynch, Andrew, 2021. "Intraday arbitrage between ETFs and their underlying portfolios," Journal of Financial Economics, Elsevier, vol. 141(3), pages 1078-1095.
    17. Thomas Marta & Fabrice Riva, 2022. "Do ETFs increase the comovements of their underlying assets? Evidence from a switch in ETF replication technique," Post-Print hal-03969602, HAL.
    18. Marta Khomyn, 2020. "Essays on Modern Market Structure," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2020, January-A.
    19. Chen, Guanhua & Liu, Xiangli & Liu, Xiao & Zhao, Zhihua, 2024. "ETF ownership and stock pricing efficiency: The role of ETF arbitrage," Finance Research Letters, Elsevier, vol. 62(PA).
    20. David E. Rappoport & Tugkan Tuzun, 2020. "Arbitrage and Liquidity: Evidence from a Panel of Exchange Traded Funds," Finance and Economics Discussion Series 2020-097, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    Exchange-Traded Funds; Underlying assets; ETF arbitrage mechanism; Liquidity shocks; Net asset value (NAV); Price discovery process;
    All these keywords.

    JEL classification:

    • B26 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Financial Economics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cer:papers:wp738. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lucie Vasiljevova (email available below). General contact details of provider: https://edirc.repec.org/data/eiacacz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.