Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| DCC-GARCH (Dynamic Conditional Correlation)× | Modelul ARIMA (Autoregresiv Integrat cu Medii Mobile)× | Teoria Valorilor Extreme (EVT)× | |
|---|---|---|---|
| Domeniu≠ | Finanțe | Econometrie | Finanțe |
| Familie | Regression model | Regression model | Regression model |
| Anul apariției≠ | 2002 | 2015 | 2001 |
| Autorul original≠ | Robert F. Engle | Box & Jenkins (Box-Jenkins methodology) | Coles (textbook treatment); McNeil, Frey & Embrechts |
| Tip≠ | Multivariate volatility model | Univariate time-series model | Tail / extreme-event model |
| Sursa seminală≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. 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 | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 |
| Denumiri alternative≠ | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold |
| Înrudite | 5 | 5 | 5 |
| Rezumat≠ | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. | 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). | Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold. |
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