ScholarGate
Assistent

Jämför metoder

Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.

TGARCH-modell (Threshold GARCH)×Autoregressiv modell för betingad heteroskedasticitet (ARCH-modell)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1993-19941982
UpphovspersonZakoian (1994); Glosten, Jagannathan & Runkle (1993)Robert F. Engle
TypAsymmetric volatility modelConditional volatility model
UrsprungskällaZakoian, 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 ↗
AliasThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Närliggande66
SammanfattningThe Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.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.
ScholarGateDatamängd
  1. v1
  2. 2 Källor
  3. PUBLISHED
  1. v1
  2. 2 Källor
  3. PUBLISHED

Gå till sökningen Ladda ner bildspel

ScholarGateJämför metoder: TGARCH model · ARCH model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare