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Model Peralihan Rejim Markov (MS-AR / MS-VAR)×Generalised Autoregressive Conditional Heteroskedasticity (GARCH)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19891986
PengasasHamilton (1989); Kim & Nelson (1999)Tim Bollerslev
JenisRegime-switching time series modelConditional volatility model
Sumber perintisHamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗
Aliasregime-switching model, Markov-switching autoregression, MS-AR, MS-VARGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Berkaitan55
RingkasanThe 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.GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.
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ScholarGateBandingkan kaedah: Markov-Switching Model · GARCH. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare