Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| EGARCH modelis (eksponenciālais GARCH)× | Kvantīļu regresija× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991 | 1978 |
| Autors≠ | Daniel B. Nelson | Koenker & Bassett |
| Tips≠ | Volatility / conditional variance model | Conditional quantile regression |
| Pirmavots≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Citi nosaukumi≠ | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | 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. | 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. |
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