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VaR回测×GARCH 模型(波动率预测)×
领域金融学计量经济学
方法族Regression modelRegression model
起源年份19981986
提出者Kupiec (1995); Christoffersen (1998); Engle & Manganelli (DQ test)Tim Bollerslev
类型Statistical hypothesis tests on VaR violation sequencesConditional volatility model
开创性文献Kupiec, P. H. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The Journal of Derivatives, 3(2), 73-84. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
别名VaR backtest, Kupiec test, Christoffersen test, Dynamic Quantile testGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
相关35
摘要VaR backtesting is a family of statistical tests that validate a risk model by comparing its Value-at-Risk forecasts against realised losses. It builds on Kupiec's (1995) unconditional coverage test, Christoffersen's (1998) conditional coverage test, and the Engle-Manganelli Dynamic Quantile (DQ) test.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.
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ScholarGate方法对比: VaR Backtesting · GARCH Model. 于 2026-06-15 检索自 https://scholargate.app/zh/compare