เปรียบเทียบวิธี

	GJR-GARCH (GARCH แบบไม่สมมาตร)	แบบจำลองมาร์คอฟสลับระบอบ (MS-AR / MS-VAR)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1993	1989
ผู้ริเริ่ม	Glosten, Jagannathan & Runkle (1993); Zakoian (1994)	Hamilton (1989); Kim & Nelson (1999)
ประเภท	Asymmetric conditional volatility model	Regime-switching time series model
แหล่งต้นตำรับ	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.
ชื่อเรียกอื่น	asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)	regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR
ที่เกี่ยวข้อง	5	5
สรุป	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.