ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Fourier EGARCH: Pemodelan Volatiliti dengan Perubahan Struktur yang Lancar×GJR-GARCH (GARCH Asimetri)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal2010s1993
PengasasExtension of Nelson (1991) EGARCH using Fourier approximation frameworksGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
JenisVolatility model with smooth structural breaksAsymmetric conditional volatility model
Sumber perintisEnders, 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. DOI ↗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. DOI ↗
AliasFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Berkaitan35
RingkasanFourier 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).
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Fourier EGARCH · GJR-GARCH. Dicapai 2026-06-19 daripada https://scholargate.app/ms/compare