方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 长记忆模型（ARFIMA, FIGARCH）× | 高频数据与市场微观结构分析× | |
|---|---|---|
| 领域 | 金融学 | 金融学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1980 | 2007 |
| 提出者≠ | Granger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH) | Hasbrouck (2007); Aït-Sahalia & Jacod (2014) |
| 类型≠ | Fractionally integrated time series model | Market microstructure / high-frequency econometrics |
| 开创性文献≠ | 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 ↗ | Hasbrouck, J. (2007). Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading. Oxford University Press. ISBN: 978-0195301649 |
| 别名≠ | ARFIMA, FIGARCH, fractionally integrated models, fractional integration | market microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı |
| 相关≠ | 4 | 5 |
| 摘要≠ | Long-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration. | Market microstructure analysis studies how prices form from tick-level trade and quote data, examining order-book dynamics, the bid-ask spread, and price discovery. The modern econometric framework was set out by Hasbrouck (2007) and extended for high-frequency data by Aït-Sahalia and Jacod (2014). |
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