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

TGARCH-model (Threshold GARCH)×ARCH-model (Autoregressieve Conditionele Heteroskedasticiteit)×ARIMA model×
VakgebiedEconometrieEconometrieEconometrie
FamilieRegression modelRegression modelRegression model
Jaar van ontstaan1993-199419821970
GrondleggerZakoian (1994); Glosten, Jagannathan & Runkle (1993)Robert F. EngleGeorge Box and Gwilym Jenkins
TypeAsymmetric volatility modelConditional volatility modelTime series forecasting model
Oorspronkelijke bronZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
AliassenThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Verwant666
SamenvattingThe Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.The 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 ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.
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ScholarGateMethoden vergelijken: TGARCH model · ARCH model · ARIMA model. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare