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ARCH 모형 (자기회귀 조건부 이분산성)×EGARCH 모형 (Exponential GARCH)×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도19821991
창시자Robert F. EngleDaniel B. Nelson
유형Conditional volatility modelVolatility / conditional variance model
원전Engle, 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 ↗
별칭ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
관련66
요약The 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.
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