Regression model
长记忆模型（ARFIMA, FIGARCH）
长记忆模型是分数阶积分方法，通过双曲衰减的自相关结构捕捉真实的长期记忆。Granger和Joyeux（1980）提出的ARFIMA模型描述了收益率序列中的长期记忆，而Baillie、Bollerslev和Mikkelsen（1996）提出的FIGARCH模型则捕捉了波动率序列中的长期记忆；参数d衡量分数阶积分的程度。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI: 10.1111/j.1467-9892.1980.tb00297.x ↗
- Baillie, R. T., Bollerslev, T. & Mikkelsen, H. O. (1996). Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 74(1), 3-30. DOI: 10.1016/S0304-4076(95)01749-6 ↗
如何引用本页
ScholarGate. (2026, June 1). Long-Memory Time Series Models (ARFIMA, FIGARCH). ScholarGate. https://scholargate.app/zh/finance/long-memory-models
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- ARIMA（自回归积分滑动平均）模型计量经济学↔ compare
- GARCH 模型（波动率预测）计量经济学↔ compare
- 高频数据与市场微观结构分析金融学↔ compare
- 普通最小二乘法 (OLS) 回归计量经济学↔ compare