Salīdzināt metodes

	Nosacītais riska apmērs (paredzamais deficīts)	Kvantīļu regresija
Nozare	Finanses	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	2000	1978
Autors	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Koenker & Bassett
Tips	Coherent tail-risk measure	Conditional quantile regression
Pirmavots	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.
Citi nosaukumi	CVaR, expected shortfall, average value-at-risk, tail VaR	conditional quantile regression, regression quantiles, Kantil Regresyon
Saistītās	5	5
Kopsavilkums	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.