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- W3023492034 abstract "Almeida et al. (2016) suggest to use the excess expected shortfall as a tail-risk measure: ... ... Almeida et al. (2016) obtain a measure of aggregate tail risk by averaging tail-risk measure (1) across a set of benchmark returns. As their estimation approach relies on the nonparametric estimation of a pricing probability consistent with the joint distribution of benchmark returns, they propose for parsimony to summarize the information in the cross-section of individual stock returns using five principal components of size and book-to-market returns. Their measure or aggregate tail risk is the average expected shortfall of the first five principal components of size and book-to-market returns: ... Almeida et al. (2016) apply predictive regression methods based on standard asymptotics and find that TRMt,h is a powerful predictor for market returns and a set of important macro variables. The tail risk proxy (3) is different from the aggregate market excess expected shortfall: ..." @default.
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- W3023492034 date "2017-01-01" @default.
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- W3023492034 title "Comment on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy" @default.
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