IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v79y2022ics1057521921002702.html
   My bibliography  Save this article

The pricing of volatility risk in the US equity market

Author

Listed:
  • Hitz, Lukas
  • Mustafi, Ismail H.
  • Zimmermann, Heinz

Abstract

We analyze whether the pricing of volatility risk depends on the asset pricing framework applied in the tests, the specified volatility proxies, and the portfolio sorts used for spanning the asset universe. For this purpose, we compare the results using a macroeconomic and fundamental based asset pricing model using three proxies of volatility and uncertainty, using size/value sorted and industry sector portfolios. Our results reveal that the marginal pricing effect of the VIX volatility factor is strong and statistically significant throughout the models and specifications, while the effect of an EGARCH-based volatility factor is mixed, mostly smaller but with the correct sign. In most cases, the EGARCH factor does not impair the pricing effect of the VIX. The portfolio sorts have a substantial impact on the volatility premiums in both model frameworks. The size of the volatility risk premium is more uniform across the models if the industry sector portfolio sort is used. Finally, the size/value portfolio sort generates larger volatility risk premiums for both models.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:finana:v:79:y:2022:i:c:s1057521921002702
    DOI: 10.1016/j.irfa.2021.101951
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521921002702
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2021.101951?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. Ferson, Wayne E., 2006. "Note from the Editor, Wayne E. Ferson on Shanken, Jay and Mark I. Weinstein, Economic Forces and the Stock Market Revisited, Journal of Empirical Finance 13, Issue 2, 2006, 129-144," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 389-391, June.
    2. Lewellen, Jonathan, 2015. "The Cross-section of Expected Stock Returns," Critical Finance Review, now publishers, vol. 4(1), pages 1-44, June.
    3. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    4. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short‐Run and Long‐Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    5. Bali, Turan G. & Cakici, Nusret, 2008. "Idiosyncratic Volatility and the Cross Section of Expected Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(1), pages 29-58, March.
    6. Gurdip Bakshi & Nikunj Kapadia, 2003. "Delta-Hedged Gains and the Negative Market Volatility Risk Premium," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 527-566.
    7. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
    8. Bollerslev, Tim & Russell, Jeffrey & Watson, Mark (ed.), 2010. "Volatility and Time Series Econometrics: Essays in Honor of Robert Engle," OUP Catalogue, Oxford University Press, number 9780199549498.
    9. Tim A. Kroencke, 2017. "Asset Pricing without Garbage," Journal of Finance, American Finance Association, vol. 72(1), pages 47-98, February.
    10. Roberto Rigobon & Brian Sack, 2003. "Measuring The Reaction of Monetary Policy to the Stock Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(2), pages 639-669.
    11. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An intertemporal CAPM with stochastic volatility," Journal of Financial Economics, Elsevier, vol. 128(2), pages 207-233.
    12. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    13. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    14. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    15. Jonathan Brogaard & Andrew Detzel, 2015. "The Asset-Pricing Implications of Government Economic Policy Uncertainty," Management Science, INFORMS, vol. 61(1), pages 3-18, January.
    16. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    17. Shanken, Jay & Weinstein, Mark I., 2006. "Economic forces and the stock market revisited," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 129-144, March.
    18. J. Ernstberger & H. Haupt & O. Vogler, 2011. "The role of sorting portfolios in asset-pricing models," Applied Financial Economics, Taylor & Francis Journals, vol. 21(18), pages 1381-1396.
    19. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    20. 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.
    21. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2021. "Stock market volatility and jumps in times of uncertainty," Journal of International Money and Finance, Elsevier, vol. 113(C).
    22. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    23. 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.
    24. 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.
    25. Miffre, Joëlle & Brooks, Chris & Li, Xiafei, 2013. "Idiosyncratic volatility and the pricing of poorly-diversified portfolios," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 78-85.
    26. Jordi Galí & Luca Gambetti, 2015. "The Effects of Monetary Policy on Stock Market Bubbles: Some Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 233-257, January.
    27. Ferson, Wayne E. & Sarkissian, Sergei & Simin, Timothy, 1999. "The alpha factor asset pricing model: A parable," Journal of Financial Markets, Elsevier, vol. 2(1), pages 49-68, February.
    28. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    29. Campbell, John Y, 1996. "Understanding Risk and Return," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 298-345, April.
    30. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    31. Fama, Eugene F. & Gibbons, Michael R., 1984. "A comparison of inflation forecasts," Journal of Monetary Economics, Elsevier, vol. 13(3), pages 327-348, May.
    32. Campbell, John Y, 1993. "Intertemporal Asset Pricing without Consumption Data," American Economic Review, American Economic Association, vol. 83(3), pages 487-512, June.
    33. 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.
    34. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    35. Jordan, Bradford D. & Riley, Timothy B., 2015. "Volatility and mutual fund manager skill," Journal of Financial Economics, Elsevier, vol. 118(2), pages 289-298.
    36. 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.
    37. Martijn Cremers & Michael Halling & David Weinbaum, 2015. "Aggregate Jump and Volatility Risk in the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 70(2), pages 577-614, April.
    38. Chris Brooks & Xiafei Li & Joelle Miffre, 2009. "Time Varying Volatility and the Cross-Section of Equity Returns Â," ICMA Centre Discussion Papers in Finance icma-dp2009-01, Henley Business School, University of Reading.
    39. González-Urteaga, Ana & Rubio, Gonzalo, 2017. "The joint cross-sectional variation of equity returns and volatilities," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 17-34.
    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. Bales, Stephan & Burghartz, Kaspar & Burghof, Hans-Peter & Hitz, Lukas, 2023. "Does the source of uncertainty matter? The impact of financial, newspaper and Twitter-based measures on U.S. banks," Research in International Business and Finance, Elsevier, vol. 65(C).

    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. 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).
    2. Peterburgsky, Stanley, 2021. "Aggregate volatility risk: International evidence," Global Finance Journal, Elsevier, vol. 47(C).
    3. Barroso, Pedro & Boons, Martijn & Karehnke, Paul, 2021. "Time-varying state variable risk premia in the ICAPM," Journal of Financial Economics, Elsevier, vol. 139(2), pages 428-451.
    4. Tobias Adrian & Erkko Etula, 2010. "Funding liquidity risk and the cross-section of stock returns," Staff Reports 464, Federal Reserve Bank of New York.
    5. Bai, Jennie & Bali, Turan G. & Wen, Quan, 2021. "Is there a risk-return tradeoff in the corporate bond market? Time-series and cross-sectional evidence," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1017-1037.
    6. 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.
    7. Bali, Turan G. & Brown, Stephen J. & Tang, Yi, 2017. "Is economic uncertainty priced in the cross-section of stock returns?," Journal of Financial Economics, Elsevier, vol. 126(3), pages 471-489.
    8. 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.
    9. Jennie Bai & Turan G. Bali & Quan Wen, 2019. "Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence," NBER Working Papers 25995, National Bureau of Economic Research, Inc.
    10. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    11. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
    12. Labidi, Chiraz & Yaakoubi, Soumaya, 2016. "Investor sentiment and aggregate volatility pricing," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 53-63.
    13. Ali, Sara & Badshah, Ihsan & Demirer, Riza & Hegde, Prasad, 2022. "Economic policy uncertainty and institutional investment returns: The case of New Zealand," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    14. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    15. Lee, Kiryoung & Joen, Yoontae & Kim, Minki, 2022. "Which uncertainty measures matter for the cross-section of stock returns?#," Finance Research Letters, Elsevier, vol. 46(PB).
    16. Bali, Turan G., 2008. "The intertemporal relation between expected returns and risk," Journal of Financial Economics, Elsevier, vol. 87(1), pages 101-131, January.
    17. Efdal Ulas Misirli, 2018. "Productivity Risk and Industry Momentum," Financial Management, Financial Management Association International, vol. 47(3), pages 739-774, September.
    18. Malamud, Semyon & Vilkov, Grigory, 2018. "Non-myopic betas," Journal of Financial Economics, Elsevier, vol. 129(2), pages 357-381.
    19. Maio, Paulo & Philip, Dennis, 2018. "Economic activity and momentum profits: Further evidence," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 466-482.
    20. Esther Eiling, 2013. "Industry-Specific Human Capital, Idiosyncratic Risk, and the Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 68(1), pages 43-84, February.

    More about this item

    Keywords

    Pricing of volatility risk; Cross sectional asset pricing; Macroeconomic vs. fundamental risk factors; Evaluation of portfolio sort technique;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    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:finana:v:79:y:2022:i:c:s1057521921002702. 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/inca/620166 .

    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.