Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Value at Risk (VaR)× | Обобщенная авторегрессионная условная гетероскедастичность (GARCH)× | |
|---|---|---|
| Область≠ | Финансы | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2007 | 1986 |
| Автор метода≠ | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan | Tim Bollerslev |
| Тип≠ | Financial risk measure | Conditional volatility model |
| Основополагающий источник≠ | Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956 | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗ |
| Другие названия≠ | VaR, value-at-risk, delta-normal VaR, historical simulation VaR | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli |
| Связанные | 5 | 5 |
| Сводка≠ | Value at Risk is a financial risk measure that estimates the maximum loss a position or portfolio could suffer over a fixed holding period at a given confidence level. It is the standard benchmark in risk management and regulatory capital calculations, developed in the textbook tradition of Jorion (2007) and the Basel market-risk framework. | GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns. |
| ScholarGateНабор данных ↗ |
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