ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Nelinearni TGARCH model×ARCH model (Autoregressive Conditional Heteroskedasticity)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1993–19941982
TvoracJean-Michel Zakoian; related work by Glosten, Jagannathan & RunkleRobert F. Engle
VrstaConditional heteroskedasticity modelConditional volatility model
Temeljni izvorZakoian, 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 ↗
Drugi naziviNL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variantARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Srodne46
SažetakThe 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.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: Nonlinear TGARCH model · ARCH model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare