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| Tærskel- og jævn-overgangs VAR (TVAR / STVAR)× | ARCH-LM-testen for volatilitetsclustering× | Exponential GARCH (EGARCH)× | GJR-GARCH (Asymmetrisk GARCH)× | Markov regime-switching model (MS-AR / MS-VAR)× | |
|---|---|---|---|---|---|
| Fagområde | Økonometri | Økonometri | Økonometri | Økonometri | Økonometri |
| Familie | Regression model | Regression model | Regression model | Regression model | Regression model |
| Oprindelsesår≠ | 1998 | 1982 | 1991 | 1993 | 1989 |
| Ophavsperson≠ | Tsay (multivariate threshold modelling) | Robert F. Engle | Nelson | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) | Hamilton (1989); Kim & Nelson (1999) |
| Type≠ | Nonlinear multivariate time-series model | Lagrange multiplier diagnostic test for conditional heteroscedasticity | Conditional volatility model (asymmetric GARCH variant) | Asymmetric conditional volatility model | Regime-switching time series model |
| Oprindelig kilde≠ | Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗ | Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987-1007. DOI ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ | Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗ | Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗ |
| Aliasser≠ | TVAR, STVAR, regime-switching VAR, threshold VAR | ARCH-LM Testi ve Volatilite Kümelenmesi Analizi, ARCH LM test, Engle's ARCH test, test for autoregressive conditional heteroscedasticity | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR |
| Relaterede≠ | 5 | 6 | 4 | 5 | 5 |
| Resumé≠ | Threshold VAR and Smooth-Transition VAR are nonlinear multivariate time-series models in which the coefficients of a vector autoregression switch between regimes according to a threshold variable. Building on Tsay's 1998 treatment of multivariate threshold models, they capture different dynamic structures across phases such as the business cycle, financial crises, or policy differences. | The ARCH-LM test is Robert Engle's (1982) Lagrange multiplier diagnostic for autoregressive conditional heteroscedasticity in the residuals of a fitted time-series model. It checks whether the error variance changes over time and clusters into calm and turbulent periods, and it is the standard pre-test run before fitting a GARCH-family volatility model. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. | GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994). | The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions. |
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