Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Важностное семплирование× | Value at Risk (VaR)× | |
|---|---|---|
| Область≠ | Имитационное моделирование | Финансы |
| Семейство≠ | Process / pipeline | Regression model |
| Год появления≠ | 1951 | 2007 |
| Автор метода≠ | Herman Kahn & Theodore Harris (RAND Corporation, 1951) | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan |
| Тип≠ | Monte Carlo variance-reduction technique | Financial risk measure |
| Основополагающий источник≠ | Rubinstein, R.Y. & Kroese, D.P. (2016). Simulation and the Monte Carlo Method (3rd ed.). Wiley. DOI ↗ | Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956 |
| Другие названия≠ | IS, weighted Monte Carlo, Önem Örneklemesi | VaR, value-at-risk, delta-normal VaR, historical simulation VaR |
| Связанные | 5 | 5 |
| Сводка≠ | Importance sampling is a Monte Carlo variance-reduction technique that shifts the sampling distribution toward the region of interest — typically a rare or extreme event — so that informative samples are drawn far more often than under the original distribution. Developed at the RAND Corporation by Herman Kahn and Theodore Harris around 1951, it makes tail-probability estimation (such as Value-at-Risk or system-failure probability) tractable where standard Monte Carlo would require an astronomically large number of runs. | 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. |
| ScholarGateНабор данных ↗ |
|
|