IDEAS home Printed from https://ideas.repec.org/a/eee/empfin/v58y2020icp121-138.html
   My bibliography  Save this article

The economic value of VIX ETPs

Author

Listed:
  • Christensen, Kim
  • Christiansen, Charlotte
  • Posselt, Anders M.

Abstract

The fairly new VIX ETPs have been promoted for providing effective and easily accessible diversification, while at the same time having large negative returns. We examine the economic value of using VIX ETPs for diversification of stock–bond portfolios. Our analysis begins in 2009, when the first VIX ETPs are introduced, and therefore only considers the period after the recent financial crisis. For investors with a constant allocation strategy, the diversification benefits of the VIX ETPs do not offset their negative returns. This implies negative economic value of a constant allocation. For a dynamic allocation strategy, including short VIX ETPs in the investment opportunity set can have substantial positive economic value.

Suggested Citation

  • Christensen, Kim & Christiansen, Charlotte & Posselt, Anders M., 2020. "The economic value of VIX ETPs," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 121-138.
  • Handle: RePEc:eee:empfin:v:58:y:2020:i:c:p:121-138
    DOI: 10.1016/j.jempfin.2020.05.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927539820300311
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jempfin.2020.05.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:hal:journl:peer-00815564 is not listed on IDEAS
    2. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    3. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    5. Barndorff-Nielsen, Ole E. & Hansen, Peter Reinhard & Lunde, Asger & Shephard, Neil, 2011. "Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Journal of Econometrics, Elsevier, vol. 162(2), pages 149-169, June.
    6. Christoffer Bordonado & Peter Molnár & Sven R. Samdal, 2017. "VIX Exchange Traded Products: Price Discovery, Hedging, and Trading Strategy," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(2), pages 164-183, February.
    7. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, February.
    8. Zhang, Lan, 2011. "Estimating covariation: Epps effect, microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 33-47, January.
    9. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    10. Ing-Haw Cheng, 2019. "The VIX Premium," The Review of Financial Studies, Society for Financial Studies, vol. 32(1), pages 180-227.
    11. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    12. Marie Briere & Alexandre Burgues & Ombretta Signori, 2008. "Volatility Exposure for Strategic Asset Allocation," Working Papers CEB 08-034.RS, ULB -- Universite Libre de Bruxelles.
    13. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    14. 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.
    15. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    16. Nicolas P.B. Bollen & Michael J. O'Neill & Robert E. Whaley, 2017. "Tail Wags Dog: Intraday Price Discovery in VIX Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(5), pages 431-451, May.
    17. Oh, Dong Hwan & Patton, Andrew J., 2016. "High-dimensional copula-based distributions with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 349-366.
    18. Eraker, Bjørn & Wu, Yue, 2017. "Explaining the negative returns to volatility claims: An equilibrium approach," Journal of Financial Economics, Elsevier, vol. 125(1), pages 72-98.
    19. repec:dau:papers:123456789/7739 is not listed on IDEAS
    20. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
    21. Elvira Caloiero & Massimo Guidolin, 2017. "Volatility as an Alternative asset Class: Does It Improve Portfolio Performance?," BAFFI CAREFIN Working Papers 1763, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    22. Alexander, Carol & Korovilas, Dimitris & Kapraun, Julia, 2016. "Diversification with volatility products," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 213-235.
    23. Johnson, Travis L., 2017. "Risk Premia and the VIX Term Structure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(6), pages 2461-2490, December.
    24. Chen, Hsuan-Chi & Chung, San-Lin & Ho, Keng-Yu, 2011. "The diversification effects of volatility-related assets," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1179-1189, May.
    25. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Yu-Lun & Yang, J. Jimmy, 2021. "Trader positions in VIX futures," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 1-17.
    2. Qadan, Mahmoud & Nisani, Doron & Eichel, Ron, 2022. "Irregularities in forward-looking volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 489-501.
    3. Wei‐Han Liu & Jow‐Ran Chang, 2022. "What can inverse VIX contribute to an investment portfolio?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3791-3798, July.
    4. Ole Linnemann Nielsen & Anders Merrild Posselt, 2022. "Betting on mean reversion in the VIX? Evidence from ETP flows," CREATES Research Papers 2022-06, Department of Economics and Business Economics, Aarhus University.

    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. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    2. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    3. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    4. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    5. Yu‐Sheng Lai, 2019. "Flexible covariance dynamics, high‐frequency data, and optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1529-1548, December.
    6. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    7. Asai, Manabu & McAleer, Michael, 2015. "Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance," Journal of Econometrics, Elsevier, vol. 189(2), pages 251-262.
    8. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
    9. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    10. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    11. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    12. Elena Ivona Dumitrescu & Georgiana-Denisa Banulescu, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," Post-Print hal-03331122, HAL.
    13. repec:hum:wpaper:sfb649dp2012-034 is not listed on IDEAS
    14. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    15. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    16. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    17. Fengler, Matthias & Okhrin, Ostap, 2012. "Realized Copula," Economics Working Paper Series 1214, University of St. Gallen, School of Economics and Political Science.
    18. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
    19. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    20. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    21. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.

    More about this item

    Keywords

    VIX; VIX ETPs; VIX premium; Economic value; Portfolio diversification;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    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:eee:empfin:v:58:y:2020:i:c:p:121-138. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jempfin .

    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.