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High-Frequency Tail Risk Premium and Stock Return Predictability

Author

Listed:
  • Caio Almeida

    (Princeton University)

  • Kim Ardison

    (SPX Capital, Rio De Janeiro, Brazil)

  • Gustavo Freire

    (Erasmus University Rotterdam)

  • René Garcia

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, UdeM - Université de Montréal)

  • Piotr Orlowski

    (UdeM - Université de Montréal)

Abstract

We propose a novel measure of the market return tail risk premium based on minimum- distance state price densities recovered from high-frequency data. The tail risk premium extracted from intra-day S&P 500 returns predicts the market equity and variance risk premiums and expected excess returns on a cross section of characteristics-sorted portfolios. Additionally, we describe the differential role of the quantity of tail risk, and of the tail premium, in shaping the future distribution of index returns. Our results are robust to controlling for established measures of variance and tail risk, and of risk premiums, in the predictive models.

Suggested Citation

  • Caio Almeida & Kim Ardison & Gustavo Freire & René Garcia & Piotr Orlowski, 2024. "High-Frequency Tail Risk Premium and Stock Return Predictability," Post-Print hal-04927211, HAL.
    • Handle: RePEc:hal:journl:hal-04927211
    DOI: 10.1017/S0022109023001199
    Note: View the original document on HAL open archive server: https://hal.science/hal-04927211v1
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    References listed on IDEAS

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