Compară metode

	Valoare la Risc Condiționată (Expected Shortfall)	Regresia cuantilică
Domeniu	Finanțe	Econometrie
Familie	Regression model	Regression model
Anul apariției	2000	1978
Autorul original	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Koenker & Bassett
Tip	Coherent tail-risk measure	Conditional quantile regression
Sursa seminală	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.
Denumiri alternative	CVaR, expected shortfall, average value-at-risk, tail VaR	conditional quantile regression, regression quantiles, Kantil Regresyon
Înrudite	5	5
Rezumat	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.