Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Risikotermer for halerisiko (Expected Shortfall, Spektral, Expectile)× | GARCH-modell (volatilitetsprognoser)× | |
|---|---|---|
| Fagfelt≠ | Finans | Økonometri |
| Familie | Regression model | Regression model |
| Opprinnelsesår≠ | 1999 | 1986 |
| Opphavsperson≠ | Artzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall) | Tim Bollerslev |
| Type≠ | Coherent tail risk measure | Conditional volatility model |
| Opprinnelig kilde≠ | Artzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Alias≠ | expected shortfall, conditional value at risk, CVaR, spectral risk measure | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Relaterte | 5 | 5 |
| Sammendrag≠ | 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. |
| ScholarGateDatasett ↗ |
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