방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| EGARCH 모형 (Exponential GARCH)× | 조건부 분위수 회귀× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1991 | 1978 |
| 창시자≠ | Daniel B. Nelson | Koenker & Bassett |
| 유형≠ | Volatility / conditional variance model | Conditional quantile regression |
| 원전≠ | 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 ↗ |
| 별칭≠ | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 관련≠ | 6 | 5 |
| 요약≠ | 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. |
| ScholarGate데이터셋 ↗ |
|
|