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Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?

Author

Listed:
  • Juliusz Jabłecki

    (Faculty of Economic Sciences, University of Warsaw)

  • Ryszard Kokoszczyński

    (Faculty of Economic Sciences, University of Warsaw)

  • Paweł Sakowski

    (Faculty of Economic Sciences, University of Warsaw)

  • Robert Ślepaczuk

    (Faculty of Economic Sciences, University of Warsaw)

  • Piotr Wójcik

    (Faculty of Economic Sciences, University of Warsaw)

Abstract

We suggest that the term structure of volatility futures (e.g. VIX futures) shows a clear pattern of dependence on the current level of VIX index. At the low level of VIX (below 20) the term structure is highly upward sloping; at the high VIX level (over 30) it is strongly downward sloping. We use those features to better predict future volatility and index futures. We begin by introducing some quantitative measures of volatility term structure (VTS) and volatility risk premium (VRP). We use them further to estimate the distance between the actual value and the fair (model) value of the VTS. We find that this distance has significant predictive power for volatility futures and index futures and we use this feature to design a simple strategy to invest in VIX index futures and S&P500.

Suggested Citation

  • Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2014-18
    as

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    File URL: http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP135.pdf
    File Function: First version, 2014
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    References listed on IDEAS

    as
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    Cited by:

    1. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.

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    More about this item

    Keywords

    volatility term structure; volatility risk premium; volatility and index futures; realized volatility; implied volatility; investment strategies; returns forecasting; efficient risk and return measures;
    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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