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Smile in Motion: An Intraday Analysis of Asymmetric Implied Volatility

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  • Wallmeier, Martin

Abstract

We present a new method to measure the intraday relationship between movements of implied volatility smiles and stock returns. It is based on an enhanced smile regression model which captures patterns in the intraday data which have not yet been reported in the literature. Using transaction data for exchange-traded EuroStoxx 50 options from 2000 to 2011 and DAX options from 1995 to 2011, we show that, on average, about 99% of the intraday variation of implied volatility can be explained by moneyness and changes in the index level. Compared to the typical smile regression with moneyness alone, about 50% of the remaining errors can be attributed to movements in the underlying index. We find that the intraday evolution of volatility smiles is generally not consistent with traders' rules of thumb such as the sticky strike or sticky delta rule. On average, the impact of index return on implied volatility is 1.3 to 1.5 times stronger than the sticky strike rule predicts. The main factor driving variations of this adjustment factor is the index return. Our results have implications for option valuation, hedging and the understanding of the leverage effect.

Suggested Citation

  • Wallmeier, Martin, 2012. "Smile in Motion: An Intraday Analysis of Asymmetric Implied Volatility," FSES Working Papers 427, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  • Handle: RePEc:fri:fribow:fribow00427
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    References listed on IDEAS

    as
    1. Rama Cont & Jose da Fonseca, 2002. "Dynamics of implied volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 45-60.
    2. Matthias R. Fengler & Wolfgang K. Härdle & Enno Mammen, 0. "A semiparametric factor model for implied volatility surface dynamics," Journal of Financial Econometrics, Oxford University Press, vol. 5(2), pages 189-218.
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    4. Matthias Fengler & Wolfgang Härdle & Christophe Villa, 2003. "The Dynamics of Implied Volatilities: A Common Principal Components Approach," Review of Derivatives Research, Springer, vol. 6(3), pages 179-202, October.
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    6. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Peter Christoffersen & Steven Heston & Kris Jacobs, 2009. "The Shape and Term Structure of the Index Option Smirk: Why Multifactor Stochastic Volatility Models Work So Well," Management Science, INFORMS, vol. 55(12), pages 1914-1932, December.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    volatility smile; implied volatility; leverage effect; index options; highfrequency data;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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