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| Модел EGARCH (Експоненциален GARCH)× | Векторна авторегресия (VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1991 | 1980 |
| Създател≠ | Daniel B. Nelson | Christopher A. Sims |
| Тип≠ | Volatility / conditional variance model | Multivariate time-series model |
| Основополагащ източник≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Други названия | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Свързани≠ | 6 | 5 |
| Резюме≠ | The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
| ScholarGateНабор от данни ↗ |
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