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The Optimal Corridor for Implied Volatility: from Calm to Turmoil Periods

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  • Silvia Muzzioli

Abstract

Corridor implied volatility is obtained from model-free implied volatility by truncating the integration domain between two barriers. Empirical evidence on volatility forecasting, in various markets, points to the utility of trimming the risk-neutral distribution of the underlying stock price, in order to obtain unbiased measures of future realised volatility (see e.g. [9], [3]). The aim of the paper is to investigate, both in a statistical and in an economic setting, the optimal corridor of strike prices to use for volatility forecasting in the Italian market, by analysing a data set which covers the years 2005-2010 and span both a relatively tranquil and a turmoil period

Suggested Citation

  • Silvia Muzzioli, 2013. "The Optimal Corridor for Implied Volatility: from Calm to Turmoil Periods," Department of Economics (DEMB) 0029, University of Modena and Reggio Emilia, Department of Economics "Marco Biagi".
    • Handle: RePEc:mod:dembwp:0029
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    1. Mark Britten‐Jones & Anthony Neuberger, 2000. "Option Prices, Implied Price Processes, and Stochastic Volatility," Journal of Finance, American Finance Association, vol. 55(2), pages 839-866, April.
    2. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    3. Moriggia, V. & Muzzioli, S. & Torricelli, C., 2009. "On the no-arbitrage condition in option implied trees," European Journal of Operational Research, Elsevier, vol. 193(1), pages 212-221, February.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    6. Torben G. Andersen & Oleg Bondarenko, 2007. "Construction and Interpretation of Model-Free Implied Volatility," NBER Working Papers 13449, National Bureau of Economic Research, Inc.
    7. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    8. S. Muzzioli, 2010. "Option-based forecasts of volatility: an empirical study in the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 16(6), pages 561-586.
    9. Joshua D. Coval & Tyler Shumway, 2001. "Expected Option Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 983-1009, June.
    10. Silvia Muzzioli, 2013. "The Forecasting Performance of Corridor Implied Volatility in the Italian Market," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 359-386, March.
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    Cited by:

    1. Elyas Elyasani & Luca Gambarelli & Silvia Muzzioli, 2016. "The risk asymmetry index," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0061, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    2. Luca Gambarelli & Silvia Muzzioli, 2019. "Risk-asymmetry indices in Europe," Department of Economics 0157, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    3. Elyas Elyasiani & Luca Gambarelli & Silvia Muzzioli, 2018. "The Risk-Asymmetry Index as a new Measure of Risk," Multinational Finance Journal, Multinational Finance Journal, vol. 22(3-4), pages 173-210, September.
    4. Elyas Elyasiani & Luca Gambarelli & Silvia Muzzioli, 2015. "Towards a skewness index for the Italian stock market," Department of Economics 0064, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    5. Elyas Elyasani & Luca Gambarelli & Silvia Muzzioli, 2016. "The risk asymmetry index," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 16212, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    6. Elyas Elyasiani & Luca Gambarelli & Silvia Muzzioli, 2018. "The use of option prices in order to evaluate the skewness risk premium," Department of Economics 0132, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".

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    More about this item

    Keywords

    corridor implied volatility; model-free implied volatility; volatility forecasting; financial turmoil;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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