Comparer des méthodes

	Valeur à risque conditionnelle (Expected Shortfall)	Régression quantile
Domaine	Finance	Économétrie
Famille	Regression model	Regression model
Année d'origine	2000	1978
Auteur d'origine	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Koenker & Bassett
Type	Coherent tail-risk measure	Conditional quantile regression
Source fondatrice	Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	CVaR, expected shortfall, average value-at-risk, tail VaR	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	5	5
Résumé	Conditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it has replaced VaR as the regulatory standard under Basel III/IV.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.