Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Tilbakeprøving av Value-at-Risk (VaR)× | GARCH-modell (volatilitetsprognoser)× | |
|---|---|---|
| Fagfelt≠ | Finans | Økonometri |
| Familie | Regression model | Regression model |
| Opprinnelsesår≠ | 1998 | 1986 |
| Opphavsperson≠ | Kupiec (1995); Christoffersen (1998); Engle & Manganelli (DQ test) | Tim Bollerslev |
| Type≠ | Statistical hypothesis tests on VaR violation sequences | Conditional volatility model |
| Opprinnelig kilde≠ | 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 ↗ |
| Alias≠ | VaR backtest, Kupiec test, Christoffersen test, Dynamic Quantile test | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Relaterte≠ | 3 | 5 |
| Sammendrag≠ | 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. |
| ScholarGateDatasett ↗ |
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