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GARCH 모형 (변동성 예측)×지수적 GARCH (EGARCH)×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도19861991
창시자Tim BollerslevNelson
유형Conditional volatility modelConditional volatility model (asymmetric GARCH variant)
원전Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
별칭GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
관련54
요약The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.
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