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

ARCH-model (Autoregressieve Conditionele Heteroskedasticiteit)×ARMA-model (Autoregressieve Moving Average)×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan19821970
GrondleggerRobert F. EngleGeorge E. P. Box and Gwilym M. Jenkins
TypeConditional volatility modelTime series model
Oorspronkelijke bronEngle, 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 ↗
AliassenARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Verwant65
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 ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.
ScholarGateGegevensset
  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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