Bandingkan kaedah

	Nilai-Risiko Bersyarat (Expected Shortfall)	Regresi Kuantil
Bidang	Kewangan	Ekonometrik
Keluarga	Regression model	Regression model
Tahun asal	2000	1978
Pengasas	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Koenker & Bassett
Jenis	Coherent tail-risk measure	Conditional quantile regression
Sumber perintis	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
Berkaitan	5	5
Ringkasan	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.