方法对比
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| 尾部风险度量（预期短缺、谱系、期望分位数）× | 分位数回归× | |
|---|---|---|
| 领域≠ | 金融学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1999 | 1978 |
| 提出者≠ | Artzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall) | Koenker & Bassett |
| 类型≠ | Coherent tail risk measure | Conditional quantile regression |
| 开创性文献≠ | Artzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| 别名≠ | expected shortfall, conditional value at risk, CVaR, spectral risk measure | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 相关 | 5 | 5 |
| 摘要≠ | Tail risk measures quantify the loss distribution beyond Value-at-Risk (VaR). Expected Shortfall — the expected loss given that VaR is exceeded — is the leading coherent risk measure, formalised by Artzner, Delbaen, Eber and Heath (1999) and shown to be coherent by Acerbi and Tasche (2002). Spectral and expectile-based measures generalise it. | 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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