IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2110.07138.html
   My bibliography  Save this paper

ETF Risk Models

Author

Listed:
  • Zura Kakushadze
  • Willie Yu

Abstract

We discuss how to build ETF risk models. Our approach anchors on i) first building a multilevel (non-)binary classification/taxonomy for ETFs, which is utilized in order to define the risk factors, and ii) then building the risk models based on these risk factors by utilizing the heterotic risk model construction of https://ssrn.com/abstract=2600798 (for binary classifications) or general risk model construction of https://ssrn.com/abstract=2722093 (for non-binary classifications). We discuss how to build an ETF taxonomy using ETF constituent data. A multilevel ETF taxonomy can also be constructed by appropriately augmenting and expanding well-built and granular third-party single-level ETF groupings.

Suggested Citation

  • Zura Kakushadze & Willie Yu, 2021. "ETF Risk Models," Papers 2110.07138, arXiv.org.
  • Handle: RePEc:arx:papers:2110.07138
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2110.07138
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zura Kakushadze & Willie Yu, 2016. "Statistical Industry Classification," Journal of Risk & Control, Risk Market Journals, vol. 3(1), pages 17-65.
    2. 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.
    3. Agapova, Anna, 2011. "Conventional mutual index funds versus exchange-traded funds," Journal of Financial Markets, Elsevier, vol. 14(2), pages 323-343, May.
    4. Zura Kakushadze, 2016. "Shrinkage=factor model," Journal of Asset Management, Palgrave Macmillan, vol. 17(2), pages 69-72, March.
    5. Zura Kakushadze & Willie Yu, 2019. "Machine Learning Risk Models," Papers 1903.06334, arXiv.org, revised Apr 2019.
    6. Timothy Krause & Sina Ehsani & Donald Lien, 2014. "Exchange-traded funds, liquidity and volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 24(24), pages 1617-1630, December.
    7. Jeff Madura & Thanh Ngo, 2008. "Impact of ETF inception on the valuation and trading of component stocks," Applied Financial Economics, Taylor & Francis Journals, vol. 18(12), pages 995-1007.
    8. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    9. Zura Kakushadze & Willie Yu, 2016. "Statistical Risk Models," Papers 1602.08070, arXiv.org, revised Jan 2017.
    10. Zura Kakushadze, 2014. "4-Factor Model for Overnight Returns," Papers 1410.5513, arXiv.org, revised Jun 2015.
    11. Zura Kakushadze & Willie Yu, 2019. "Machine Learning Risk Models," Journal of Risk & Control, Risk Market Journals, vol. 6(1), pages 37-64.
    12. Zura Kakushadze & Willie Yu, 2016. "Multifactor Risk Models and Heterotic CAPM," Papers 1602.04902, arXiv.org, revised Mar 2016.
    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. Zura Kakushadze & Willie Yu, 2022. "ETF Risk Models," Bulletin of Applied Economics, Risk Market Journals, vol. 9(1), pages 1-17.
    2. Zura Kakushadze, 2020. "Quant Bust 2020," Papers 2006.05632, arXiv.org.
    3. Zura Kakushadze & Willie Yu, 2019. "Machine Learning Risk Models," Papers 1903.06334, arXiv.org, revised Apr 2019.
    4. 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.
    5. Zura Kakushadze & Willie Yu, 2018. "Betas, Benchmarks and Beating the Market," Papers 1807.09919, arXiv.org.
    6. Kim, Jinhwan & Cho, Hoon & Seok, Sangik, 2023. "Liquidity risk, return performance, and tracking error: Synthetic vs. Physical ETFs," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    7. Lawrence Glosten & Suresh Nallareddy & Yuan Zou, 2021. "ETF Activity and Informational Efficiency of Underlying Securities," Management Science, INFORMS, vol. 67(1), pages 22-47, January.
    8. Zura Kakushadze & Willie Yu, 2017. "Notes on Fano Ratio and Portfolio Optimization," Papers 1711.10640, arXiv.org, revised Apr 2018.
    9. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 1-65.
    10. Zura Kakushadze & Willie Yu, 2016. "Statistical Risk Models," Papers 1602.08070, arXiv.org, revised Jan 2017.
    11. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Papers 2003.05095, arXiv.org.
    12. Kiran Paudel & Atsuyuki Naka, 2023. "Effects of size on the exchange-traded funds performance," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 474-484, October.
    13. 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.
    14. Zura Kakushadze & Willie Yu, 2017. "Dead Alphas as Risk Factors," Papers 1709.06641, arXiv.org.
    15. Damien Kunjal & Faeezah Peerbhai & Paul-Francois Muzindutsi, 2021. "The performance of South African exchange traded funds under changing market conditions," Journal of Asset Management, Palgrave Macmillan, vol. 22(5), pages 350-359, September.
    16. Zura Kakushadze & Willie Yu, 2016. "Multifactor Risk Models and Heterotic CAPM," Papers 1602.04902, arXiv.org, revised Mar 2016.
    17. Timothy Krause & Sina Ehsani & Donald Lien, 2014. "Exchange-traded funds, liquidity and volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 24(24), pages 1617-1630, December.
    18. Zura Kakushadze & Willie Yu, 2018. "Decoding stock market with quant alphas," Journal of Asset Management, Palgrave Macmillan, vol. 19(1), pages 38-48, January.
    19. Kakushadze, Zura & Yu, Willie, 2016. "Factor models for cancer signatures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 527-559.
    20. Zura Kakushadze & Willie Yu, 2017. "Decoding Stock Market with Quant Alphas," Papers 1708.02984, arXiv.org.

    More about this item

    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:arx:papers:2110.07138. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.