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S&P volatility, VIX, and asymptotic volatility estimates

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  • Bonaparte, Yosef
  • Chatrath, Arjun
  • Christie-David, Rohan

Abstract

We examine the efficacy of the VIX as a predictor of 30-day forward S&P 500 volatility. We find that its accuracy hovers between 20% and 25%, depending on sampling period. An alternative framework, built on asymptotic distribution theory (AVE), predicts this volatility with an accuracy between 90% to 95%. The adjusted R-square adjudicates for accuracy. Other goodness-of-fit measures corroborate this evidence. We suggest that this outcome is underpinned by the fact that (a) options price behaviors do not adequately reflect stock market volatility patterns, and (b) our methodology accounts more comprehensively for idiosyncratic risk.

Suggested Citation

  • Bonaparte, Yosef & Chatrath, Arjun & Christie-David, Rohan, 2023. "S&P volatility, VIX, and asymptotic volatility estimates," Finance Research Letters, Elsevier, vol. 51(C).
    • Handle: RePEc:eee:finlet:v:51:y:2023:i:c:s1544612322005694
    DOI: 10.1016/j.frl.2022.103392
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    Cited by:

    1. Bonaparte, Yosef, 2023. "Introducing the Cryptocurrency VIX: CVIX✰," Finance Research Letters, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    VIX; Realized volatility; Asymptotic distribution theory;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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