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GJR-GARCH (GARCH Asimetri)×Model Peralihan Rejim Markov (MS-AR / MS-VAR)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19931989
PengasasGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Hamilton (1989); Kim & Nelson (1999)
JenisAsymmetric conditional volatility modelRegime-switching time series model
Sumber perintisGlosten, 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 ↗
Aliasasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR
Berkaitan55
RingkasanGJR-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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ScholarGateBandingkan kaedah: GJR-GARCH · Markov-Switching Model. Dicapai 2026-06-20 daripada https://scholargate.app/ms/compare