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How Does the Market Variance Risk Premium Vary over Time? Evidence from S&P 500 Variance Swap Investment Returns

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  • Eirini Konstantinidi

    (University of Manchester)

  • George Skiadopoulos

    (Queen Mary University of London University of Piraeus)

Abstract

We explore whether the market variance risk premium (VRP) can be predicted. First, we propose a novel approach to measure VRP which distinguishes the investment horizon from the variance swap's maturity. We extract VRP from actual rather than synthetic S&P 500 variance swap quotes, thus avoiding biases in VRP measurement. Next, we find that a deterioration of the economy and of the trading activity, increases VRP. These relations hold both in- and out-of-sample for various maturities and investment horizons and they are economically significant. Volatility trading strategies which condition on the detected relations outperform popular buy-and-hold strategies even after transaction costs are considered.

Suggested Citation

  • Eirini Konstantinidi & George Skiadopoulos, 2014. "How Does the Market Variance Risk Premium Vary over Time? Evidence from S&P 500 Variance Swap Investment Returns," Working Papers 732, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:732
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    4. López, Raquel, 2018. "The behaviour of energy-related volatility indices around scheduled news announcements: Implications for variance swap investments," Energy Economics, Elsevier, vol. 72(C), pages 356-364.
    5. José Da Fonseca & Yahua Xu, 2019. "Variance and skew risk premiums for the volatility market: The VIX evidence," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(3), pages 302-321, March.
    6. Huang, Hong-Gia & Tsai, Wei-Che & Weng, Pei-Shih & Yang, J. Jimmy, 2023. "Intraday momentum in the VIX futures market," Journal of Banking & Finance, Elsevier, vol. 148(C).
    7. López, Raquel & Esparcia, Carlos, 2021. "Analysis of the performance of volatility-based trading strategies on scheduled news announcement days: An international equity market perspective," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 32-54.
    8. Wei Guo & Xinfeng Ruan & Sebastian A. Gehricke & Jin E. Zhang, 2023. "Term spreads of implied volatility smirk and variance risk premium," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(7), pages 829-857, July.
    9. Cui, Zhenyu & Kirkby, J. Lars & Nguyen, Duy, 2021. "Efficient simulation of generalized SABR and stochastic local volatility models based on Markov chain approximations," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1046-1062.
    10. Johannes Rauch & Carol Alexander, 2016. "Tail Risk Premia for Long-Term Equity Investors," Papers 1602.00865, arXiv.org.
    11. Stamatis Leontsinis & Carol Alexander, 2017. "Arithmetic variance swaps," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 551-569, April.
    12. Sakshi Saini & Sanjay Sehgal & Florent Deisting, 2020. "Monetary Policy, Risk Aversion and Uncertainty in an International Context," Multinational Finance Journal, Multinational Finance Journal, vol. 24(3-4), pages 211-266, September.
    13. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    14. Carol Alexander & Johannes Rauch, 2017. "The Aggregation Property and its Applications to Realised Higher Moments," Papers 1709.08188, arXiv.org.
    15. Fassas, Athanasios P. & Papadamou, Stephanos, 2018. "Variance risk premium and equity returns," Research in International Business and Finance, Elsevier, vol. 46(C), pages 462-470.
    16. Carol Alexander & Johannes Rauch, 2016. "Model-Free Discretisation-Invariant Swap Contracts," Papers 1602.00235, arXiv.org, revised Apr 2016.
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    More about this item

    Keywords

    Economic conditions; Predictability; Trading activity; Variance swaps; Variance risk premium; Volatility trading;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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