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A semiparametric factor model for implied volatility surface dynamics

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  • Matthias R. Fengler
  • Wolfgang K. Härdle
  • Enno Mammen

Abstract

We propose a semiparametric factor model, which approximates the implied volatility surface (IVS) in a finite dimensional function space. Unlike standard principal component approaches typically used to reduce complexity, our approach is tailored to the degenerated design of IVS data. In particular, we only fit in the local neighborhood of the design points by exploiting the expiry effect present in option data. Using DAX index option data, we estimate the nonparametric components and a low-dimensional time series of latent factors. The modeling approach is completed by studying vector autoregressive models fitted to the latent factors. Copyright , Oxford University Press.

Suggested Citation

  • 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.
  • Handle: RePEc:oup:jfinec:v:5:y::i:2:p:189-218
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbm005
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    Citations

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    Cited by:

    1. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    2. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    3. 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.
    4. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2016. "Dynamic Factor Models for the Volatility Surface," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 127-174 Emerald Publishing Ltd.
    5. Francesco Audrino & Dominik Colagelo, 2007. "Forecasting Implied Volatility Surfaces," University of St. Gallen Department of Economics working paper series 2007 2007-42, Department of Economics, University of St. Gallen.
    6. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    7. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    8. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Georgios Chalamandaris & Andrianos Tsekrekos, 2013. "Explanatory Factors and Causality in the Dynamics of Volatility Surfaces Implied from OTC Asian–Pacific Currency Options," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 327-358, March.

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