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Not all VIXs are (Informationally) equal: Evidence from affine GARCH option pricing models

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  • Escobar-Anel, Marcos
  • Stentoft, Lars
  • Ye, Xize

Abstract

This paper examines which VIX maturity to use in affine GARCH model estimation, when the objective is to do option pricing. Utilizing the Model Confidence Set approach repeatedly, we rank the best VIXs across different dynamic models. Our results highlight the importance of estimating with VIXs and show that with the appropriate VIX a reduction of up to 38% in option pricing errors can be obtained. Our results also show that the 1-year VIX is the worst to use, that the 1-month VIX is an overall favourite, and that the choice of VIX maturity matters mostly for more flexible models.

Suggested Citation

  • Escobar-Anel, Marcos & Stentoft, Lars & Ye, Xize, 2024. "Not all VIXs are (Informationally) equal: Evidence from affine GARCH option pricing models," Finance Research Letters, Elsevier, vol. 69(PA).
    • Handle: RePEc:eee:finlet:v:69:y:2024:i:pa:s1544612324010833
    DOI: 10.1016/j.frl.2024.106053
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    References listed on IDEAS

    as
    1. Wu, Xinyu & Zhao, An & Liu, Li, 2023. "Forecasting VIX using two-component realized EGARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
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    More about this item

    Keywords

    Affine GARCH model estimation; Model confidence set; Option pricing; VIX maturity;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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