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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Niet-lineair TGARCH-model×ARCH-model (Autoregressieve Conditionele Heteroskedasticiteit)×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan1993–19941982
GrondleggerJean-Michel Zakoian; related work by Glosten, Jagannathan & RunkleRobert F. Engle
TypeConditional heteroskedasticity modelConditional volatility model
Oorspronkelijke bronZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
AliassenNL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variantARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Verwant46
SamenvattingThe Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return series.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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  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: Nonlinear TGARCH model · ARCH model. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare