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| Value-at-Risk Condizionale (Expected Shortfall)× | Regressione quantilica× | |
|---|---|---|
| Campo≠ | Finanza | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2000 | 1978 |
| Ideatore≠ | Rockafellar & Uryasev (2000); Acerbi & Tasche (2002) | Koenker & Bassett |
| Tipo≠ | Coherent tail-risk measure | Conditional quantile regression |
| Fonte seminale≠ | Rockafellar, 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 ↗ |
| Alias≠ | CVaR, expected shortfall, average value-at-risk, tail VaR | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Correlati | 5 | 5 |
| Sintesi≠ | 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. |
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