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Do Stock Markets Price Skewness? New Evidence from Quantile Regression Skewness Forecasts

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Date
2017
Publisher city
Paris
Publisher
Université Paris-Dauphine
Notes
Revise and Resubmit. Journal of Financial and Quantitative Analysis.
Collection title
Cahier de recherche DRM
Link to item file
http://dx.doi.org/10.2139/ssrn.2494291
Sujet
Asset pricing, ex-ante physical skew, realized skewness, quantile regression models; G11; G12; G15
JEL code
G.G1.G15; G.G1.G12; G.G1.G11
URI
https://basepub.dauphine.fr/handle/123456789/16340
Collections
  • DRM : Publications
Metadata
Show full item record
Author
Aretz, Kevin
Arisoy, Eser
Type
Document de travail / Working paper
Abstract (EN)
We use density forecasts derived from recursively estimated quantile regressions to calculate a forecast of the physical skewness of an asset's future return distribution. The forecast is unbiased and efficient, and it can easily be adapted to forecast the skewness of returns calculated over any conceivable return interval. Using Neuberger's (2012) realized physical skewness, we show that our quantile regression skewness forecast outperforms other variables proposed in the literature. Despite this, it does not condition the cross-section of future stock returns, neither independently nor when combined with other forecasts. Overall, we cast doubt on whether stock markets price expected stock skewness.

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SCD Paris Dauphine - Place du Maréchal de Lattre de Tassigny 75775 Paris Cedex 16

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