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Investing in VIX futures based on rolling GARCH models forecasts

Author

Listed:
  • Oleh Bilyk
  • Paweł Sakowski

    (Quantitative Finance Research Group, Faculty of Economic Sciences, University of Warsaw)

  • Robert Ślepaczuk

    (Quantitative Finance Research Group, Faculty of Economic Sciences, University of Warsaw)

Abstract

The aim of this work is to compare the performance of VIX futures trading strategies built across different GARCH model volatility forecasting techniques. Long and short signals for VIX futures are produced by comparing one-day ahead volatility forecasts with current historical volatility. We found out that using the daily data over the seven-year period (2013-2019), strategy based on the fGARCH-TGARCH and GJR-GARCH specifications outperformed those of the GARCH and EGARCH models, and performed slightly below the “buy-and-hold” S&P 500 strategy. For the base GARCH(1,1) model, the training window size and the type gave stable results, whereas the performance across refit frequency, conditional distribution of returns, and historical volatility estimators varies significantly. Despite non-robustness of some investment strategies and some space for improvements, the presented strategies show their potential in competing with the equity and volatility benchmarks.

Suggested Citation

  • Oleh Bilyk & Paweł Sakowski & Robert Ślepaczuk, 2020. "Investing in VIX futures based on rolling GARCH models forecasts," Working Papers 2020-10, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2020-10
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    File URL: https://www.wne.uw.edu.pl/index.php/download_file/5603/
    File Function: First version, 2020
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    More about this item

    Keywords

    GARCH; VIX index; volatility futures; rolling forecasting; volatility; investment strategies; volatility exposure;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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