方法对比
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| 高频数据与市场微观结构分析× | 已实现波动率的HAR-RV模型× | |
|---|---|---|
| 领域 | 金融学 | 金融学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2007 | 2009 |
| 提出者≠ | Hasbrouck (2007); Aït-Sahalia & Jacod (2014) | Fulvio Corsi |
| 类型≠ | Market microstructure / high-frequency econometrics | Linear time-series regression for volatility |
| 开创性文献≠ | Hasbrouck, J. (2007). Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading. Oxford University Press. ISBN: 978-0195301649 | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗ |
| 别名 | market microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı | HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility) |
| 相关 | 5 | 5 |
| 摘要≠ | 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). | The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility. |
| ScholarGate数据集 ↗ |
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