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自回归条件异方差 (ARCH) 模型×EGARCH model×
领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份19821991
提出者Robert F. EngleDaniel B. Nelson
类型Conditional volatility modelVolatility / conditional variance model
开创性文献Engle, 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 ↗
别名ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
相关66
摘要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 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.
ScholarGate数据集
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  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

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ScholarGate方法对比: ARCH model · EGARCH model. 于 2026-06-17 检索自 https://scholargate.app/zh/compare