方法对比

	尾部风险度量（预期短缺、谱系、期望分位数）	GARCH 模型（波动率预测）
领域	金融学	计量经济学
方法族	Regression model	Regression model
起源年份	1999	1986
提出者	Artzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)	Tim Bollerslev
类型	Coherent tail risk measure	Conditional volatility model
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.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
别名	expected shortfall, conditional value at risk, CVaR, spectral risk measure	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
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.	The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.