Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель GARCH (прогнозирование волатильности)× | Квантильная регрессия× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1986 | 1978 |
| Автор метода≠ | Tim Bollerslev | Koenker & Bassett |
| Тип≠ | Conditional volatility model | Conditional quantile regression |
| Основополагающий источник≠ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Другие названия≠ | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Связанные | 5 | 5 |
| Сводка≠ | The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. |
| ScholarGateНабор данных ↗ |
|
|