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Model EGARCH (Exponential GARCH)×Regresi Kuantil×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19911978
PengasasDaniel B. NelsonKoenker & Bassett
JenisVolatility / conditional variance modelConditional quantile regression
Sumber perintisNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHconditional quantile regression, regression quantiles, Kantil Regresyon
Berkaitan65
RingkasanThe Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateBandingkan kaedah: EGARCH model · Quantile Regression. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare