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Model EGARCH Tak Linear×Model ARCH (Heteroskedastisitas Bersyarat Autoregresif)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19911982
PengasasDaniel B. NelsonRobert F. Engle
JenisConditional volatility modelConditional volatility model
Sumber perintisNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
AliasNL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Berkaitan56
RingkasanThe Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
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ScholarGateBandingkan kaedah: Nonlinear EGARCH model · ARCH model. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare