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Modeling the Dynamics of Correlations among Implied Volatilities

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  • Robert Engle
  • Stephen Figlewski

Abstract

Implied volatility (IV) reflects both expected empirical volatility and also risk premia. Stochastic variation in either creates unhedged risk in a delta hedged options position. We develop EGARCH/DCC models for the dynamics of volatilities and correlations among daily IVs from options on twenty-eight large cap stocks. The data strongly support a general correlation structure and also a one-factor model with the VIX index as the common factor. Using IVs from stocks that are either highly correlated with the target stock’s IV or in the same industry together with the VIX can significantly improve hedging of individual IV changes.

Suggested Citation

  • Robert Engle & Stephen Figlewski, 2015. "Modeling the Dynamics of Correlations among Implied Volatilities," Review of Finance, European Finance Association, vol. 19(3), pages 991-1018.
    • Handle: RePEc:oup:revfin:v:19:y:2015:i:3:p:991-1018.
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    File URL: http://hdl.handle.net/10.1093/rof/rfu024
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    Cited by:

    1. Chang, Chia-Lin & McAleer, Michael, 2017. "The correct regularity condition and interpretation of asymmetry in EGARCH," Economics Letters, Elsevier, vol. 161(C), pages 52-55.
    2. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    3. Adjemian, Michael K. & Bruno, Valentina & Robe, Michel A. & Wallen, Jonathan, 2017. "What Drives Volatility Expectations in Grain and Oilseed Markets?," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258452, Agricultural and Applied Economics Association.
    4. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
    5. Ahmad, Wasim & Hernandez, Jose Arreola & Saini, Seema & Mishra, Ritesh Kumar, 2021. "The US equity sectors, implied volatilities, and COVID-19: What does the spillover analysis reveal?," Resources Policy, Elsevier, vol. 72(C).
    6. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2020. "Firm Volatility in Granular Networks," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4097-4162.
    7. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    8. Guglielmo Maria Caporale & Stavroula Yfanti & Menelaos Karanasos & Jiaying Wu, 2023. "Financial Integration and European Tourism Stocks," CESifo Working Paper Series 10269, CESifo.
    9. Fabian Woebbeking, 2021. "Cryptocurrency volatility markets," Digital Finance, Springer, vol. 3(3), pages 273-298, December.
    10. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.
    11. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.
    12. Jarno Talponen, 2018. "Matching distributions: Recovery of implied physical densities from option prices," Papers 1803.03996, arXiv.org.
    13. Psaradellis, Ioannis & Sermpinis, Georgios, 2016. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1268-1283.
    14. Carr, Peter & Wu, Liuren, 2016. "Analyzing volatility risk and risk premium in option contracts: A new theory," Journal of Financial Economics, Elsevier, vol. 120(1), pages 1-20.

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