High-Frequency Tail Risk Premium and Stock Return Predictability

Caio Almeida, Kim Ardison, Gustavo Freire, René Garcia and Piotr Orlowski
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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 - UT - Université 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

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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.

Date: 2024-12
New Economics Papers: this item is included in nep-mst, nep-rmg and nep-upt
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Published in Journal of Financial and Quantitative Analysis, 2024, 59 (8), pp.3633-3670. ⟨10.1017/S0022109023001199⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04927211

DOI: 10.1017/S0022109023001199

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