Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| APARCH× | Экспоненциальный GARCH (EGARCH)× | GJR-GARCH (Асимметричный GARCH)× | |
|---|---|---|---|
| Область | Эконометрика | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model | Regression model |
| Год появления≠ | 1993 | 1991 | 1993 |
| Автор метода≠ | Ding, Granger & Engle | Nelson | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| Тип≠ | Conditional heteroscedasticity model | Conditional volatility model (asymmetric GARCH variant) | Asymmetric conditional volatility model |
| Основополагающий источник≠ | Ding, Z., Granger, C. W. J., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1(1), 83–106. DOI ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ | Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗ |
| Другие названия | Asymmetric Power ARCH, Power ARCH, APGARCH, Asimetrik Güç ARCH | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| Связанные≠ | 3 | 4 | 5 |
| Сводка≠ | APARCH, introduced by Ding, Granger, and Engle (1993) while studying long-memory properties of stock market returns, extends the GARCH family by allowing both the power transformation of conditional volatility and an asymmetric response to positive and negative shocks. The model nests at least seven well-known ARCH-type specifications as special cases, making it a unifying framework for volatility modelling in financial econometrics. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. | GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994). |
| ScholarGateНабор данных ↗ |
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