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VIX derivatives: Valuation models and empirical evidence

Author

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  • Lo, Chien-Ling
  • Shih, Pai-Ta
  • Wang, Yaw-Huei
  • Yu, Min-Teh

Abstract

This study proposes an efficient approach for the pricing of VIX derivatives under the affine framework and investigates the respective value of two variance components and variance jumps in the pricing of VIX derivatives. Our numerical results show that our approach significantly reduce the computational burden. Our empirical findings provide support for the use of two-variance component models as the means of capturing the fickle term structure of VIX derivatives, and the use of variance jumps is vital when included in the long-run variance component.

Suggested Citation

  • Lo, Chien-Ling & Shih, Pai-Ta & Wang, Yaw-Huei & Yu, Min-Teh, 2019. "VIX derivatives: Valuation models and empirical evidence," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 1-21.
    • Handle: RePEc:eee:pacfin:v:53:y:2019:i:c:p:1-21
    DOI: 10.1016/j.pacfin.2018.09.004
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    Cited by:

    1. Cheng, Hung-Wen & Chang, Li-Han & Lo, Chien-Ling & Tsai, Jeffrey Tzuhao, 2023. "Empirical performance of component GARCH models in pricing VIX term structure and VIX futures," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 122-142.
    2. Zhao, Yang & Yu, Min-Teh, 2019. "Measuring the liquidity impact on catastrophe bond spreads," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 197-210.
    3. Lin, Chung-Gee & Chang, Chia-Chang, 2020. "Approximate analytic solution for Asian options with stochastic volatility," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    4. Hong, Hui & Bian, Zhicun & Chen, Naiwei, 2020. "Leverage effect on stochastic volatility for option pricing in Hong Kong: A simulation and empirical study," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Daniel Guterding, 2020. "Inventory effects on the price dynamics of VSTOXX futures quantified via machine learning," Papers 2002.08207, arXiv.org.
    6. Lo, Chien-Ling & Chang, Carolyn W. & Lee, Jin-Ping & Yu, Min-Teh, 2021. "Pricing catastrophe swaps with default risk and stochastic interest rates," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    7. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    8. Bo Jing & Shenghong Li & Yong Ma, 2020. "Pricing VIX options with volatility clustering," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 928-944, June.
    9. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    10. Xingguo Luo & Jin E. Zhang & Wenjun Zhang, 2019. "Instantaneous squared VIX and VIX derivatives," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(10), pages 1193-1213, October.

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    More about this item

    Keywords

    VIX derivatives; Variance components; Variance jump; Affine model;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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