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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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  • Konstantinidi, Eirini
  • Skiadopoulos, George

Abstract

We explore whether the market variance risk premium (VRP) can be predicted. We measure VRP by distinguishing the investment horizon from the variance swap’s maturity. We extract VRP from actual S&P 500 variance swap quotes and we test four classes of predictive models. We find that the best performing model is the one that conditions on trading activity. This relation is also economically significant. Volatility trading strategies which condition on trading activity outperform popular benchmark strategies, even once we consider transaction costs. Our finding implies that broker dealers command a greater VRP to continue holding short positions in index options in the case where trading conditions deteriorate.

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  • Konstantinidi, Eirini & Skiadopoulos, George, 2016. "How does the market variance risk premium vary over time? Evidence from S&P 500 variance swap investment returns," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 62-75.
  • Handle: RePEc:eee:jbfina:v:62:y:2016:i:c:p:62-75
    DOI: 10.1016/j.jbankfin.2015.10.006
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    4. 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.
    5. Carol Alexander & Johannes Rauch, 2017. "The Aggregation Property and its Applications to Realised Higher Moments," Papers 1709.08188, arXiv.org.
    6. 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.
    7. 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.
    8. Carol Alexander & Johannes Rauch, 2016. "Model-Free Discretisation-Invariant Swap Contracts," Papers 1602.00235, arXiv.org, revised Apr 2016.
    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. 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.
    12. Stamatis Leontsinis & Carol Alexander, 2017. "Arithmetic variance swaps," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 551-569, April.
    13. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
    14. Jonathan Dark & Xin Gao & Thijs van der Heijden & Federico Nardari, 2022. "Forecasting variance swap payoffs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2135-2164, December.
    15. 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.
    16. Cui, Zhenyu & Lars Kirkby, J. & Nguyen, Duy, 2017. "A general framework for discretely sampled realized variance derivatives in stochastic volatility models with jumps," European Journal of Operational Research, Elsevier, vol. 262(1), pages 381-400.
    17. 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).

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    More about this item

    Keywords

    Funding illiquidity; Predictability; 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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