手法を比較

	条件付きバリュー・アット・リスク（期待ショートフォール）	分位点回帰
分野	ファイナンス	計量経済学
系統	Regression model	Regression model
提唱年	2000	1978
提唱者	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Koenker & Bassett
種類	Coherent tail-risk measure	Conditional quantile regression
原典	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.
別名	CVaR, expected shortfall, average value-at-risk, tail VaR	conditional quantile regression, regression quantiles, Kantil Regresyon
関連	5	5
概要	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.