ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Betinget Value-at-Risk (Forventet Underskud)×Kvantilregression×
FagområdeFinansieringØkonometri
FamilieRegression modelRegression model
Oprindelsesår20001978
OphavspersonRockafellar & Uryasev (2000); Acerbi & Tasche (2002)Koenker & Bassett
TypeCoherent tail-risk measureConditional quantile regression
Oprindelig kildeRockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasserCVaR, expected shortfall, average value-at-risk, tail VaRconditional quantile regression, regression quantiles, Kantil Regresyon
Relaterede55
ResuméConditional 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.
ScholarGateDatasæt
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Conditional Value-at-Risk · Quantile Regression. Hentet 2026-06-15 fra https://scholargate.app/da/compare