Methoden vergleichen

	Value-at-Risk (VaR) Backtesting	GARCH-Modell (Volatilitätsvorhersage)
Fachgebiet	Finanzwirtschaft	Ökonometrie
Familie	Regression model	Regression model
Entstehungsjahr	1998	1986
Urheber	Kupiec (1995); Christoffersen (1998); Engle & Manganelli (DQ test)	Tim Bollerslev
Typ	Statistical hypothesis tests on VaR violation sequences	Conditional volatility model
Wegweisende Quelle	Kupiec, P. H. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The Journal of Derivatives, 3(2), 73-84.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Aliasnamen	VaR backtest, Kupiec test, Christoffersen test, Dynamic Quantile test	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Verwandt	3	5
Zusammenfassung	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.