IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v13y2007i7p621-644.html
   My bibliography  Save this article

Volatility as an Asset Class: European Evidence

Author

Listed:
  • Reinhold Hafner
  • Martin Wallmeier

Abstract

Volatility movements are known to be negatively correlated with stock index returns. Hence, investing in volatility appears to be attractive for investors seeking risk diversification. The most common instruments for investing in pure volatility are variance swaps, which now enjoy an active over-the-counter (OTC) market. This paper investigates the risk-return tradeoff of variance swaps on the Deutscher Aktienindex and Euro STOXX 50 index over the time period from 1995 to 2004. We synthetically derive variance swap rates from the smile in option prices. Using quotes from two large investment banks over two months, we validate that the synthetic values are close to OTC market prices. We find that variance swap returns exhibit an option-like profile compared to returns of the underlying index. Given this pattern, it is crucial to account for the non-normality of returns in measuring the performance of variance swap investments. As in the US, the average returns of selling variance swaps are found to be strongly positive and too large to be compatible with standard equilibrium models. The magnitude of the estimated risk premium is related to variance uncertainty and past index returns. This indicates that the variance swap rate does not seem to incorporate all past information relevant for forecasting future realized variance.

Suggested Citation

  • Reinhold Hafner & Martin Wallmeier, 2007. "Volatility as an Asset Class: European Evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 13(7), pages 621-644.
    • Handle: RePEc:taf:eurjfi:v:13:y:2007:i:7:p:621-644
    DOI: 10.1080/13518470701380142
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/13518470701380142
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13518470701380142?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    2. Santa-Clara, Pedro & Yan, Shu, 2004. "Jump and Volatility Risk and Risk Premia: A New Model and Lessons from S&P 500 Options," University of California at Los Angeles, Anderson Graduate School of Management qt5dv8v999, Anderson Graduate School of Management, UCLA.
    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. Wallmeier,, 2016. "Entwicklungslinien in der Portfoliotheorie und im Asset Management," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 70(4), pages 407-422.
    2. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2021. "A Markov-Switching VSTOXX Trading Algorithm for Enhancing EUR Stock Portfolio Performance," Mathematics, MDPI, vol. 9(9), pages 1-28, May.
    3. Jonathan Batten & Brian Lucey & Frank McGroarty & Maurice Peat & Andrew Urquhart, 2017. "Stylized facts of intraday precious metals," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-21, April.
    4. Detering, Nils & Zhou, Qixiang & Wystup, Uwe, 2012. "Volatilität als Investment: Diversifikationseigenschaften von Volatilitätsstrategien," CPQF Working Paper Series 30, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    5. Marie Briere & Alexandre Burgues & Ombretta Signori, 2008. "Volatility Exposure for Strategic Asset Allocation," Working Papers CEB 08-034.RS, ULB -- Universite Libre de Bruxelles.
    6. Martin Wallmeier, 2011. "Beyond payoff diagrams: how to present risk and return characteristics of structured products," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 313-338, September.
    7. Stavros Degiannakis & Christos Floros & Enrique Salvador & Dimitrios Vougas, 2022. "On the stationarity of futures hedge ratios," Operational Research, Springer, vol. 22(3), pages 2281-2303, July.
    8. 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.
    9. Hayette Gatfaoui, 2010. "Investigating the dependence structure between credit default swap spreads and the U.S. financial market," Annals of Finance, Springer, vol. 6(4), pages 511-535, October.
    10. Dörries, Julian & Korn, Olaf & Power, Gabriel J., 2023. "How should the long-term investor harvest variance risk premiums?," CFR Working Papers 23-06, University of Cologne, Centre for Financial Research (CFR).
    11. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    12. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    13. Sebastiano Vitali & Miloš Kopa & Gabriele Giana, 2023. "Implied volatility smoothing at COVID-19 times," Computational Management Science, Springer, vol. 20(1), pages 1-42, December.

    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. León, Angel & Nave, Juan & Rubio Irigoyen, Gonzalo, 2005. "The Relationship between Risk and Expected Return in Europe," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    2. Boes, M.J., 2006. "Index options : Pricing, implied densities and returns," Other publications TiSEM e9ed8a9f-2472-430a-b666-9, Tilburg University, School of Economics and Management.
    3. Geert Bekaert & Eric Engstrom, 2017. "Asset Return Dynamics under Habits and Bad Environment-Good Environment Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 713-760.
    4. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    5. Turan G. Bali & Hao Zhou, 2011. "Risk, uncertainty, and expected returns," Finance and Economics Discussion Series 2011-45, Board of Governors of the Federal Reserve System (U.S.).
    6. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    7. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    8. Payzan-LeNestour, Elise & Pradier, Lionnel & Putniņš, Tālis J., 2023. "Biased risk perceptions: Evidence from the laboratory and financial markets," Journal of Banking & Finance, Elsevier, vol. 154(C).
    9. Ian W. R. Martin & Dimitris Papadimitriou, 2022. "Sentiment and Speculation in a Market with Heterogeneous Beliefs," American Economic Review, American Economic Association, vol. 112(8), pages 2465-2517, August.
    10. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    11. Masato Ubukata & Toshiaki Watanabe, 2011. "Market Variance Risk Premiums in Japan as Predictor Variables and Indicators of Risk Aversion," Global COE Hi-Stat Discussion Paper Series gd11-214, Institute of Economic Research, Hitotsubashi University.
    12. Wang, Hao & Zhou, Hao & Zhou, Yi, 2013. "Credit default swap spreads and variance risk premia," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3733-3746.
    13. George Halkos & Argyro Zisiadou, 2020. "Is Investors’ Psychology Affected Due to a Potential Unexpected Environmental Disaster?," JRFM, MDPI, vol. 13(7), pages 1-24, July.
    14. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je & Gau, Yin-Feng, 2022. "Risk-return trade-off in the Australian Securities Exchange: Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 384-401.
    15. Sonali Jain & Jayanth R. Varma & Sobhesh Kumar Agarwalla, 2019. "Indian equity options: Smile, risk premiums, and efficiency," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 150-163, February.
    16. Tai‐Yong Roh & Alireza Tourani‐Rad & Yahua Xu & Yang Zhao, 2021. "Volatility‐of‐volatility risk in the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 245-265, February.
    17. Juan M. Londono & Mary Tian, 2014. "Bank Interventions and Options-based Systemic Risk: Evidence from the Global and Euro-area Crisis," International Finance Discussion Papers 1117, Board of Governors of the Federal Reserve System (U.S.).
    18. Tim Bollerslev & Natalia Sizova & George Tauchen, 2011. "Volatility in Equilibrium: Asymmetries and Dynamic Dependencies," Review of Finance, European Finance Association, vol. 16(1), pages 31-80.
    19. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    20. Isao Ishida & Michael McAleer & Kosuke Oya, 2011. "Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S&P 500 and VIX," Documentos de Trabajo del ICAE 2011-17, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    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:taf:eurjfi:v:13:y:2007:i:7:p:621-644. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/REJF20 .

    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.