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Option trading strategies based on semi-parametric implied volatility surface prediction

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  • Francesco Audrino

    ()

  • Dominik Colangelo

    ()

Abstract

We propose constructing a set of trading strategies using predicted option returns for a relatively small forecasting period of ten trading days to form profitable hold-to-expiration, equally weighted, zero-cost portfolios based on 1-month at-the-money call and put options. We use a statistical machine learning procedure based on regression trees to accurately predict future implied volatility surfaces. Such accurate forecasts are needed to obtain reliable option returns used as trading signals in our strategies. We test the performance of the proposed strategies on options on the S&P 100 and on its constituents for the time period between 2002 and 2006: positive annualized returns of up to more than 50% are achieved.

Suggested Citation

  • Francesco Audrino & Dominik Colangelo, 2009. "Option trading strategies based on semi-parametric implied volatility surface prediction," University of St. Gallen Department of Economics working paper series 2009 2009-24, Department of Economics, University of St. Gallen.
  • Handle: RePEc:usg:dp2009:2009-24
    as

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    File URL: http://ux-tauri.unisg.ch/RePEc/usg/dp2009/DP-0924-Au.pdf
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    References listed on IDEAS

    as
    1. Chris Brooks & M. Currim Oozeer, 2002. "Modelling the Implied Volatility of Options on Long Gilt Futures," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(1&2), pages 111-137.
    2. Rama Cont & Jose da Fonseca, 2002. "Dynamics of implied volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 45-60.
    3. Matthias R. Fengler & Wolfgang K. Härdle & Enno Mammen, 0. "A semiparametric factor model for implied volatility surface dynamics," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(2), pages 189-218.
    4. Matthias Fengler & Wolfgang Härdle & Christophe Villa, 2003. "The Dynamics of Implied Volatilities: A Common Principal Components Approach," Review of Derivatives Research, Springer, pages 179-202.
    5. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    6. P. Gagliardini & C. Gourieroux & E. Renault, 2011. "Efficient Derivative Pricing by the Extended Method of Moments," Econometrica, Econometric Society, vol. 79(4), pages 1181-1232, July.
    7. Goyal, Amit & Saretto, Alessio, 2009. "Cross-section of option returns and volatility," Journal of Financial Economics, Elsevier, vol. 94(2), pages 310-326, November.
    8. George Skiadopoulos & Stewart Hodges & Les Clewlow, 2000. "The Dynamics of the S&P 500 Implied Volatility Surface," Review of Derivatives Research, Springer, vol. 3(3), pages 263-282, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Option Trading Strategies; Implied Volatility Surface; Option Pricing; Forecasting; Boosting; Regression Trees;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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