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Is there information in the volatility skew?

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  • James S. Doran
  • David R. Peterson
  • Brian C. Tarrant

Abstract

Since the 1987 crash, option prices have exhibited a strong negative skew, implying higher implied volatility for out‐of‐the‐money puts than at‐ and in‐the‐money puts. This has resulted in incorporating multiple jumps and stochastic volatility within the data generating process to improve the Black–Scholes model in an attempt to capture negative skewness and a highly leptokurtic distribution. The general conclusion is that there is a large jump premium in the short term, which best explains the significant negative skew for short maturity options. Alternative explanations for the negative skew are related to market liquidity driven by demand shocks and supply shortages. Regardless of the explanation for the negative skew, we assess the information content in the shape of the skew to infer if the option market can accurately forecast stock market crashes and/or spikes upward. We demonstrate, using all options on the S&P 100 from 1984–2006, that the shape of the skew can reveal with significant probability when the market will crash or spike. However, we find the magnitude of the spike prediction is not economically significant. Our findings are strongest for the short‐term out‐of‐the money puts, consistent with the notion of investors' aversion to large negative movements. We also find that the power of the crash/spike prediction decreases with an increase in the time to option maturity. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:921–959, 2007

Suggested Citation

  • James S. Doran & David R. Peterson & Brian C. Tarrant, 2007. "Is there information in the volatility skew?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(10), pages 921-959, October.
  • Handle: RePEc:wly:jfutmk:v:27:y:2007:i:10:p:921-959
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    Cited by:

    1. Byun, Suk Joon & Kim, Jun Sik, 2013. "The information content of risk-neutral skewness for volatility forecasting," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 142-161.
    2. Diavatopoulos, Dean & Doran, James S. & Fodor, Andy & Peterson, David R., 2012. "The information content of implied skewness and kurtosis changes prior to earnings announcements for stock and option returns," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 786-802.
    3. 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.
    4. José Afonso Faias & Tiago Castel-Branco, 2018. "Out-Of-Sample Stock Return Prediction Using Higher-Order Moments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(06), pages 1-27, September.
    5. Chen, Chen & Lee, Hsiu-Chuan & Liao, Tzu-Hsiang, 2016. "Risk-neutral skewness and market returns: The role of institutional investor sentiment in the futures market," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 203-225.
    6. Seo, Sung Won & Kim, Jun Sik, 2015. "The information content of option-implied information for volatility forecasting with investor sentiment," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 106-120.
    7. Rolf Poulsen & Klaus Reiner Schenk-Hoppe & Christian-Oliver Ewald, 2009. "Risk minimization in stochastic volatility models: model risk and empirical performance," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 693-704.
    8. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    9. Doran, James S. & Ronn, Ehud I., 2008. "Computing the market price of volatility risk in the energy commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2541-2552, December.
    10. Vilkovz, Grigory & Xiaox, Yan, 2013. "Option-implied information and predictability of extreme returns," SAFE Working Paper Series 5, Leibniz Institute for Financial Research SAFE.
    11. Jungmu Kim & Yuen Jung Park, 2020. "Predictability of OTC Option Volatility for Future Stock Volatility," Sustainability, MDPI, vol. 12(12), pages 1-23, June.
    12. Wong, Alfred, 2019. "Currency jumps, Euribor-OIS spreads and the volatility skew: A study on the dollar-euro crash risk of 2007–2015," Finance Research Letters, Elsevier, vol. 29(C), pages 7-16.
    13. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    14. Wen Jin & Joshua Livnat & Yuan Zhang, 2012. "Option Prices Leading Equity Prices: Do Option Traders Have an Information Advantage?," Journal of Accounting Research, Wiley Blackwell, vol. 50(2), pages 401-432, May.
    15. Luiz Félix & Roman Kräussl & Philip Stork, 2020. "Implied volatility sentiment: a tale of two tails," Quantitative Finance, Taylor & Francis Journals, vol. 20(5), pages 823-849, May.

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