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Model EGARCH (Exponential GARCH)×Model ARCH (Heteroskedastisitas Bersyarat Autoregresif)×Model ARIMA (Autoregressive Integrated Moving Average)×
BidangEkonometrikEkonometrikEkonometrik
KeluargaRegression modelRegression modelRegression model
Tahun asal199119821970
PengasasDaniel B. NelsonRobert F. EngleGeorge Box and Gwilym Jenkins
JenisVolatility / conditional variance modelConditional volatility modelTime series forecasting model
Sumber perintisNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. 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 ↗
AliasExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Berkaitan666
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.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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ScholarGateBandingkan kaedah: EGARCH model · ARCH model · ARIMA model. Dicapai 2026-06-19 daripada https://scholargate.app/ms/compare