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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

ARCH-model (Autoregressieve Conditionele Heteroskedasticiteit)×EGARCH-model (Exponentieel GARCH)×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan19821991
GrondleggerRobert F. EngleDaniel B. Nelson
TypeConditional volatility modelVolatility / conditional variance model
Oorspronkelijke bronEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
AliassenARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Verwant66
SamenvattingThe 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.The 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.
ScholarGateGegevensset
  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: ARCH model · EGARCH model. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare