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Teste ARCH-LM para Agrupamento de Volatilidade×GJR-GARCH (GARCH Assimétrico)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19821993
Autor originalRobert F. EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TipoLagrange multiplier diagnostic test for conditional heteroscedasticityAsymmetric conditional volatility model
Fonte 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 ↗
Outros nomesARCH-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)
Relacionados65
ResumoThe 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).
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ScholarGateComparar métodos: ARCH-LM Test · GJR-GARCH. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare