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Regression model

GARCH 模型(波动率预测)

广义自回归条件异方差(GARCH)模型由 Tim Bollerslev 于 1986 年提出,用于模拟金融时间序列随时间变化的条件方差。它能捕捉波动率聚类和 ARCH 效应,是估计收益率序列风险和波动率的标准工具。

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来源

  1. Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI: 10.1016/0304-4076(86)90063-1

如何引用本页

ScholarGate. (2026, June 1). Generalized Autoregressive Conditional Heteroskedasticity Model. ScholarGate. https://scholargate.app/zh/econometrics/garch-model

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被引用于

ScholarGateGARCH Model (Generalized Autoregressive Conditional Heteroskedasticity Model). 于 2026-06-15 检索自 https://scholargate.app/zh/econometrics/garch-model · 数据集: https://doi.org/10.5281/zenodo.20539026