IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2403.01088.html
   My bibliography  Save this paper

Justifying the Volatility of S&P 500 Daily Returns

Author

Listed:
  • Hayden Brown

Abstract

Over the past 60 years, there has been a gradual increase in the volatility of daily returns for the S&P 500 Index. Hypothetically, suppose that market forces determine daily volatility such that a daily leveraged S&P 500 fund cannot outperform a standard S&P 500 fund in the long run. Then this hypothetical volatility happens to support the increase in volatility seen in the S&P 500 index. On this basis, it appears that the classic argument of the market portfolio being unbeatable in the long run is determining the volatility of S&P 500 daily returns. Moreover, it follows that the long-term volatility of the daily returns for the S&P 500 Index should continue to increase until passing a particular threshold. If, on the other hand, this hypothesis about market forces increasing volatility is invalid, then there is room for daily leveraged S&P 500 funds to outperform their unleveraged counterparts in the long run.

Suggested Citation

  • Hayden Brown, 2024. "Justifying the Volatility of S&P 500 Daily Returns," Papers 2403.01088, arXiv.org.
    • Handle: RePEc:arx:papers:2403.01088
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2403.01088
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    3. Perron, Pierre & Qu, Zhongjun, 2010. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 275-290.
    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. 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.
    2. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
    3. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    4. Sibbertsen, Philipp & Leschinski, Christian & Busch, Marie, 2018. "A multivariate test against spurious long memory," Journal of Econometrics, Elsevier, vol. 203(1), pages 33-49.
    5. Xu, Liao & Xu, Lu & Zhao, Jing & Zhao, Yang, 2020. "Information-based trading and information propagation: Evidence from the exchange traded fund market," International Review of Financial Analysis, Elsevier, vol. 70(C).
    6. Vassilios Babalos & Elie Bouri & Rangan Gupta, 2024. "Does the Introduction of US Spot Bitcoin ETFs Affect Spot Returns and Volatility of Major Cryptocurrencies?," Working Papers 202416, University of Pretoria, Department of Economics.
    7. Nonejad, Nima, 2022. "An interesting finding about the ability of geopolitical risk to forecast aggregate equity return volatility out-of-sample," Finance Research Letters, Elsevier, vol. 47(PB).
    8. 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).
    9. Ewing, Bradley T. & Malik, Farooq, 2016. "Volatility spillovers between oil prices and the stock market under structural breaks," Global Finance Journal, Elsevier, vol. 29(C), pages 12-23.
    10. Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
    11. Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
    12. Shi, Yanlin & Ho, Kin-Yip, 2015. "Long memory and regime switching: A simulation study on the Markov regime-switching ARFIMA model," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 189-204.
    13. Xu, Liao & Pu, Wenyan, 2022. "ETFs, arbitrage activity, and stock market efficiency: Evidence from Chinese CSI 300 ETFs," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 1-9.
    14. Hu, Gang & Jo, Koren M. & Wang, Yi Alex & Xie, Jing, 2018. "Institutional trading and Abel Noser data," Journal of Corporate Finance, Elsevier, vol. 52(C), pages 143-167.
    15. Damien Kunjal, 2022. "Evaluating the Liquidity Response of South African Exchange-Traded Funds to Country Risk Effects," Economies, MDPI, vol. 10(6), pages 1-20, June.
    16. Mohitosh Kejriwal & Xuewen Yu & Pierre Perron, 2020. "Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 676-690, September.
    17. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    18. 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.
    19. 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.
    20. Todea, Alexandru, 2016. "Cross-correlations between volatility, volatility persistence and stock market integration: the case of emergent stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 208-215.

    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:2403.01088. 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.