ScholarGate
Assistent

Compara mètodes

Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.

Prova ARCH-LM per a l'agrupació de volatilitat×GJR-GARCH (GARCH asimètric)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen19821993
Autor originalRobert F. EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TipusLagrange multiplier diagnostic test for conditional heteroscedasticityAsymmetric conditional volatility model
Font seminalEngle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987-1007. DOI ↗Glosten, 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. The Journal of Finance, 48(5), 1779-1801. DOI ↗
ÀliesARCH-LM Testi ve Volatilite Kümelenmesi Analizi, ARCH LM test, Engle's ARCH test, test for autoregressive conditional heteroscedasticityasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Relacionats65
ResumThe ARCH-LM test is Robert Engle's (1982) Lagrange multiplier diagnostic for autoregressive conditional heteroscedasticity in the residuals of a fitted time-series model. It checks whether the error variance changes over time and clusters into calm and turbulent periods, and it is the standard pre-test run before fitting a GARCH-family volatility model.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
ScholarGateConjunt de dades
  1. v1
  2. 2 Fonts
  3. PUBLISHED
  1. v1
  2. 2 Fonts
  3. PUBLISHED

Ves a la cerca Baixa les diapositives

ScholarGateCompara mètodes: ARCH-LM Test · GJR-GARCH. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare