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Retro-validació del Valor en Risc (VaR)×Model GARCH (Previsió de la Volatilitat)×
CampFinancesEconometria
FamíliaRegression modelRegression model
Any d'origen19981986
Autor originalKupiec (1995); Christoffersen (1998); Engle & Manganelli (DQ test)Tim Bollerslev
TipusStatistical hypothesis tests on VaR violation sequencesConditional volatility model
Font seminalKupiec, 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 ↗
ÀliesVaR backtest, Kupiec test, Christoffersen test, Dynamic Quantile testGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relacionats35
ResumVaR 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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ScholarGateCompara mètodes: VaR Backtesting · GARCH Model. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare