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Trading Signals in VIX Futures

Author

Listed:
  • Marco Avellaneda
  • Thomas Nanfeng Li
  • Andrew Papanicolaou
  • Gaozhan Wang

Abstract

We propose a new approach for trading VIX futures. We assume that the term structure of VIX futures follows a Markov model. Our trading strategy selects a position in VIX futures by maximizing the expected utility for a day-ahead horizon given the current shape and level of the term structure. Computationally, we model the functional dependence between the VIX futures curve, the VIX futures positions, and the expected utility as a deep neural network with five hidden layers. Out-of-sample backtests of the VIX futures trading strategy suggest that this approach gives rise to reasonable portfolio performance, and to positions in which the investor will be either long or short VIX futures contracts depending on the market environment.

Suggested Citation

  • Marco Avellaneda & Thomas Nanfeng Li & Andrew Papanicolaou & Gaozhan Wang, 2021. "Trading Signals in VIX Futures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 28(3), pages 275-298, May.
    • Handle: RePEc:taf:apmtfi:v:28:y:2021:i:3:p:275-298
    DOI: 10.1080/1350486X.2021.2010584
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    Cited by:

    1. Rama Cont, 2023. "In memoriam: Marco Avellaneda (1955–2022)," Mathematical Finance, Wiley Blackwell, vol. 33(1), pages 3-15, January.
    2. Björn Uhl, 2024. "Sharpe-optimal volatility futures carry," Journal of Asset Management, Palgrave Macmillan, vol. 25(3), pages 288-302, May.

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