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Nelineárny model GARCH×Model ARCH (autoregresná podmienená heteroskedasticita)×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku1991-19931982
TvorcaGlosten, Jagannathan & Runkle; Nelson (1991) for EGARCHRobert F. Engle
TypVolatility modelConditional volatility model
Pôvodný zdrojGlosten, 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. Journal of Finance, 48(5), 1779-1801. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Ďalšie názvyNL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility modelARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Príbuzné66
ZhrnutieThe Nonlinear GARCH model extends the standard GARCH framework to capture asymmetric and nonlinear responses of conditional volatility to past shocks. It allows negative returns (bad news) to amplify volatility more than positive returns of equal magnitude, a phenomenon known as the leverage effect, which is empirically pervasive in financial markets.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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ScholarGatePorovnať metódy: Nonlinear GARCH model · ARCH model. Získané 2026-06-17 z https://scholargate.app/sk/compare