IDEAS home Printed from https://ideas.repec.org/a/taf/apfiec/v17y2007i5p357-368.html
   My bibliography  Save this article

Is volatility risk priced after all? Some disconfirming evidence

Author

Listed:
  • Geoffrey Loudon
  • Alan Rai

Abstract

Recent theory and evidence from US studies suggest that aggregate market volatility risk is a strong candidate for inclusion in the list of risk factors that earn a risk premium in equilibrium. We re-examine the sensitivity of stock returns to volatility risk using delta-neutral index option straddles to proxy for innovations in aggregate volatility. Contrary to existing US evidence, our analysis finds little evidence that volatility risk is priced in Australian equities. This finding is robust across a variety of methods for characterizing the underlying volatility factor.

Suggested Citation

  • Geoffrey Loudon & Alan Rai, 2007. "Is volatility risk priced after all? Some disconfirming evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 357-368.
  • Handle: RePEc:taf:apfiec:v:17:y:2007:i:5:p:357-368
    DOI: 10.1080/09603100600675516
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/09603100600675516
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/09603100600675516?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. Perry Sadorsky, 2005. "Stochastic volatility forecasting and risk management," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 121-135.
    2. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    3. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    5. Breeden, Douglas T., 1979. "An intertemporal asset pricing model with stochastic consumption and investment opportunities," Journal of Financial Economics, Elsevier, vol. 7(3), pages 265-296, September.
    6. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    7. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    8. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    9. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    10. Campbell, John Y, 1996. "Understanding Risk and Return," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 298-345, April.
    11. Manolis Kavussanos & Stelios Marcoulis & Angelos Arkoulis, 2002. "Macroeconomic factors and international industry returns," Applied Financial Economics, Taylor & Francis Journals, vol. 12(12), pages 923-931.
    12. Joshua D. Coval & Tyler Shumway, 2001. "Expected Option Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 983-1009, June.
    13. Hossein Asgharian & Bjorn Hansson, 2005. "A critical investigation of the explanatory role of factor mimicking portfolios in multifactor asset pricing models," Applied Financial Economics, Taylor & Francis Journals, vol. 15(12), pages 835-847.
    14. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    15. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, 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. Jian Chen & Xiaoquan Liu, 2010. "The model-free measures and the volatility spread," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1829-1833.
    2. Mai, Van Anh (Vivian) & Ang, Tze Chuan ‘Chewie’ & Fang, Victor, 2016. "Aggregate volatility risk and the cross-section of stock returns: Australian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 134-149.

    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. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    2. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    3. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
    4. Malamud, Semyon & Vilkov, Grigory, 2018. "Non-myopic betas," Journal of Financial Economics, Elsevier, vol. 129(2), pages 357-381.
    5. Tyler Muir & Erkko Etula & Tobias Adrian, 2011. "Broker-Dealer Leverage and the Cross-Section of Stock Returns," 2011 Meeting Papers 1448, Society for Economic Dynamics.
    6. John H. Cochrane, 1999. "New facts in finance," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 36-58.
    7. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2010. "Macroeconomic risks and characteristic-based factor models," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1383-1399, June.
    8. Cochrane, John H., 2005. "Financial Markets and the Real Economy," Foundations and Trends(R) in Finance, now publishers, vol. 1(1), pages 1-101, July.
    9. Zura Kakushadze, 2014. "4-Factor Model for Overnight Returns," Papers 1410.5513, arXiv.org, revised Jun 2015.
    10. Cowan, Adrian M. & Joutz, Frederick L., 2006. "An unobserved component model of asset pricing across financial markets," International Review of Financial Analysis, Elsevier, vol. 15(1), pages 86-107.
    11. Tobias Adrian & Erkko Etula, 2010. "Funding liquidity risk and the cross-section of stock returns," Staff Reports 464, Federal Reserve Bank of New York.
    12. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    13. Qi Shi & Bin Li & Adrian (Wai Kong) Cheung & Richard Chung, 2017. "Augmenting the intertemporal CAPM with inflation: Further evidence from alternative models," Australian Journal of Management, Australian School of Business, vol. 42(4), pages 653-672, November.
    14. Elyasiani, Elyas & Gambarelli, Luca & Muzzioli, Silvia, 2020. "Moment risk premia and the cross-section of stock returns in the European stock market," Journal of Banking & Finance, Elsevier, vol. 111(C).
    15. Lu Zhang, 2017. "The Investment CAPM," European Financial Management, European Financial Management Association, vol. 23(4), pages 545-603, September.
    16. Hitz, Lukas & Mustafi, Ismail H. & Zimmermann, Heinz, 2022. "The pricing of volatility risk in the US equity market," International Review of Financial Analysis, Elsevier, vol. 79(C).
    17. Zura Kakushadze, 2014. "Russian-Doll Risk Models," Papers 1412.4342, arXiv.org, revised Nov 2017.
    18. Andrew Detzel, 2017. "Monetary Policy Surprises, Investment Opportunities, And Asset Prices," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 40(3), pages 315-348, September.
    19. Hsu, Po-Hsuan & Huang, Dayong, 2010. "Technology prospects and the cross-section of stock returns," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 39-53, January.
    20. Zura Kakushadze & Willie Yu, 2016. "Multifactor Risk Models and Heterotic CAPM," Papers 1602.04902, arXiv.org, revised Mar 2016.

    More about this item

    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:taf:apfiec:v:17:y:2007:i:5:p:357-368. 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/RAFE20 .

    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.