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Modeling S&P500 returns with GARCH models

Author

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  • Alfaro, Rodrigo
  • Inzunza, Alejandra

Abstract

This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an external validation of the model using an option-based index reported by the Federal Reserve of Minneapolis, we are able to propose a calibrate model to track the tail-risk of this stock index.

Suggested Citation

  • Alfaro, Rodrigo & Inzunza, Alejandra, 2023. "Modeling S&P500 returns with GARCH models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(3).
    • Handle: RePEc:eee:lajcba:v:4:y:2023:i:3:s2666143823000170
    DOI: 10.1016/j.latcb.2023.100096
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    References listed on IDEAS

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    More about this item

    Keywords

    GARCH option pricing models; VIX; Tail-risk statistics;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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