Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Modellen met langetermijngeheugen (ARFIMA, FIGARCH)× | High-Frequency Data en Marktmicrostructuuranalyse× | |
|---|---|---|
| Vakgebied | Financiering | Financiering |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1980 | 2007 |
| Grondlegger≠ | Granger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH) | Hasbrouck (2007); Aït-Sahalia & Jacod (2014) |
| Type≠ | Fractionally integrated time series model | Market microstructure / high-frequency econometrics |
| Oorspronkelijke bron≠ | 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 |
| Aliassen≠ | ARFIMA, FIGARCH, fractionally integrated models, fractional integration | market microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı |
| Verwant≠ | 4 | 5 |
| Samenvatting≠ | 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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