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EGARCH-malli (Exponential GARCH)×GARCH-malli (volatiliteetin ennustaminen)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi19911986
KehittäjäDaniel B. NelsonTim Bollerslev
TyyppiVolatility / conditional variance modelConditional volatility model
AlkuperäislähdeNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
RinnakkaisnimetExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Liittyvät65
TiivistelmäThe 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.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
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ScholarGateVertaile menetelmiä: EGARCH model · GARCH Model. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare