Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Modele cu memorie lungă (ARFIMA, FIGARCH)× | Modelul ARIMA (Autoregresiv Integrat cu Medii Mobile)× | Analiza datelor de înaltă frecvență și a microstructurii pieței× | |
|---|---|---|---|
| Domeniu≠ | Finanțe | Econometrie | Finanțe |
| Familie | Regression model | Regression model | Regression model |
| Anul apariției≠ | 1980 | 2015 | 2007 |
| Autorul original≠ | Granger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH) | Box & Jenkins (Box-Jenkins methodology) | Hasbrouck (2007); Aït-Sahalia & Jacod (2014) |
| Tip≠ | Fractionally integrated time series model | Univariate time-series model | Market microstructure / high-frequency econometrics |
| Sursa seminală≠ | 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 ↗ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Hasbrouck, J. (2007). Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading. Oxford University Press. ISBN: 978-0195301649 |
| Denumiri alternative≠ | ARFIMA, FIGARCH, fractionally integrated models, fractional integration | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | market microstructure, high-frequency financial econometrics, tick data analysis, Yüksek Frekanslı Veri ve Piyasa Mikro Yapısı |
| Înrudite≠ | 4 | 5 | 5 |
| Rezumat≠ | 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. | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | 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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