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	फूरियर EGARCH: सहज संरचनात्मक विरामों के साथ अस्थिरता मॉडलिंग	जीजेआर-गार्च (असममित गार्च)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	2010s	1993
प्रवर्तक	Extension of Nelson (1991) EGARCH using Fourier approximation frameworks	Glosten, Jagannathan & Runkle (1993); Zakoian (1994)
प्रकार	Volatility model with smooth structural breaks	Asymmetric conditional volatility model
मौलिक स्रोत	Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599.	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.
उपनाम	Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCH	asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
संबंधित	3	5
सारांश	Fourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the model to handle structural breaks in volatility without requiring prior knowledge of their timing or number.	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).