IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v69y2024ipas1544612324010833.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324010833
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2024.106053?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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).
    2. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    3. Cummins, Mark & Dowling, Michael & Esposito, Francesco, 2017. "Determining risk model confidence sets," Finance Research Letters, Elsevier, vol. 22(C), pages 169-174.
    4. Jinji Hao & Jin E. Zhang, 2013. "GARCH Option Pricing Models, the CBOE VIX, and Variance Risk Premium," Journal of Financial Econometrics, Oxford University Press, vol. 11(3), pages 556-580, June.
    5. Christophe Chorro & Rahantamialisoa H Fanirisoa, 2022. "Discriminating Between GARCH Models for Option Pricing by Their Ability to Compute Accurate VIX Measures [Option Valuation with Volatility Components, Fat Tails, and Non-Monotonic Pricing Kernels]," Journal of Financial Econometrics, Oxford University Press, vol. 20(5), pages 902-941.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Qiao, Gaoxiu & Yang, Jiyu & Li, Weiping, 2020. "VIX forecasting based on GARCH-type model with observable dynamic jumps: A new perspective," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    8. Liu, Zhichao & Liu, Jing & Zeng, Qing & Wu, Lan, 2022. "VIX and stock market volatility predictability: A new approach," Finance Research Letters, Elsevier, vol. 48(C).
    9. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    10. Kanniainen, Juho & Lin, Binghuan & Yang, Hanxue, 2014. "Estimating and using GARCH models with VIX data for option valuation," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 200-211.
    11. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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).
    2. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Gongyue Jiang & Gaoxiu Qiao & Lu Wang & Feng Ma, 2024. "Hybrid forecasting of crude oil volatility index: The cross‐market effects of stock market jumps," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2378-2398, September.
    4. Wenjun Zhang & Jin E. Zhang, 2020. "GARCH Option Pricing Models and the Variance Risk Premium," JRFM, MDPI, vol. 13(3), pages 1-21, March.
    5. Xinglin Yang & Peng Wang, 2018. "VIX futures pricing with conditional skewness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1126-1151, September.
    6. Qi Wang & Zerong Wang, 2021. "VIX futures and its closed‐form pricing through an affine GARCH model with realized variance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 135-156, January.
    7. Gaoxiu Qiao & Gongyue Jiang, 2023. "VIX futures pricing based on high‐frequency VIX: A hybrid approach combining SVR with parametric models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1238-1260, September.
    8. Zhuo Huang & Chen Tong & Tianyi Wang, 2019. "VIX term structure and VIX futures pricing with realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 72-93, January.
    9. Alfaro, Rodrigo & Inzunza, Alejandra, 2023. "Modeling S&P500 returns with GARCH models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(3).
    10. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2023. "Covariance dependent kernels, a Q-affine GARCH for multi-asset option pricing," International Review of Financial Analysis, Elsevier, vol. 87(C).
    11. Ying Wang & Hoi Ying Wong, 2017. "VIX Forecast Under Different Volatility Specifications," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(2), pages 131-148, June.
    12. Qiao, Gaoxiu & Ma, Xuekun & Jiang, Gongyue & Wang, Lu, 2024. "Crude oil volatility index forecasting: New evidence based on positive and negative jumps from Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 415-437.
    13. Papantonis, Ioannis, 2016. "Volatility risk premium implications of GARCH option pricing models," Economic Modelling, Elsevier, vol. 58(C), pages 104-115.
    14. Badescu, Alexandru & Cui, Zhenyu & Ortega, Juan-Pablo, 2016. "A note on the Wang transform for stochastic volatility pricing models," Finance Research Letters, Elsevier, vol. 19(C), pages 189-196.
    15. Gongyue Jiang & Gaoxiu Qiao & Feng Ma & Lu Wang, 2022. "Directly pricing VIX futures with observable dynamic jumps based on high‐frequency VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1518-1548, August.
    16. Lin, Shin-Hung & Huang, Hung-Hsi & Li, Sheng-Han, 2015. "Option pricing under truncated Gram–Charlier expansion," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 77-97.
    17. Junting Liu & Qi Wang & Yuanyuan Zhang, 2024. "VIX option pricing through nonaffine GARCH dynamics and semianalytical formula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1189-1223, July.
    18. Qiao, Gaoxiu & Yang, Jiyu & Li, Weiping, 2020. "VIX forecasting based on GARCH-type model with observable dynamic jumps: A new perspective," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    19. Wang, Qi & Wang, Zerong, 2020. "VIX valuation and its futures pricing through a generalized affine realized volatility model with hidden components and jump," Journal of Banking & Finance, Elsevier, vol. 116(C).
    20. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Aug 2024.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:69:y:2024:i:pa:s1544612324010833. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.