手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| 極値理論 (EVT)× | 指数 GARCH (EGARCH)× | |
|---|---|---|
| 分野≠ | ファイナンス | 計量経済学 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 2001 | 1991 |
| 提唱者≠ | Coles (textbook treatment); McNeil, Frey & Embrechts | Nelson |
| 種類≠ | Tail / extreme-event model | Conditional volatility model (asymmetric GARCH variant) |
| 原典≠ | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| 別名≠ | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| 関連≠ | 5 | 4 |
| 概要≠ | Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold. | 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. |
| ScholarGateデータセット ↗ |
|
|