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- W4287180596 abstract "This paper develops a generalization of the Hansen-Jagannathan bound that incorporates information beyond the mean and variance of returns. The resulting bound compares the physical and risk neutral distribution for every $tau$-quantile, where $tau in (0,1)$. An empirical application with S&P500 return data shows that the new bound is stronger than the Hansen-Jagannathan bound for small values of $tau$. The long run risk model cannot reconcile this feature of the data, due to the absence of disaster risk. I extend this finding using conditioning information and document that disaster risk is time-varying, using a semiparametric approach. I also propose a new measure of quantile forecastability and show that many stylized facts about the equity premium carry over to the quantile setting." @default.
- W4287180596 created "2022-07-25" @default.
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- W4287180596 date "2021-05-17" @default.
- W4287180596 modified "2023-09-26" @default.
- W4287180596 title "A Quantile Approach to Asset Pricing Models" @default.
- W4287180596 hasPublicationYear "2021" @default.
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