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	Progowy i gładko-przejściowy VAR (TVAR / STVAR)	Wykładniczy GARCH (EGARCH)	GJR-GARCH (Asymetryczny GARCH)	Model Markowa z przełączaniem reżimów (MS-AR / MS-VAR)
Dziedzina	Ekonometria	Ekonometria	Ekonometria	Ekonometria
Rodzina	Regression model	Regression model	Regression model	Regression model
Rok powstania	1998	1991	1993	1989
Twórca	Tsay (multivariate threshold modelling)	Nelson	Glosten, Jagannathan & Runkle (1993); Zakoian (1994)	Hamilton (1989); Kim & Nelson (1999)
Typ	Nonlinear multivariate time-series model	Conditional volatility model (asymmetric GARCH variant)	Asymmetric conditional volatility model	Regime-switching time series model
Źródło pierwotne	Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202.	Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370.	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.	Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
Inne nazwy	TVAR, STVAR, regime-switching VAR, threshold VAR	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
Pokrewne	5	4	5	5
Podsumowanie	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.	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.