Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| DCC-GARCH (dinamiskā nosacītā korelācija)× | Vērtība pie riska (VaR)× | |
|---|---|---|
| Nozare | Finanses | Finanses |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2002 | 2007 |
| Autors≠ | Robert F. Engle | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan |
| Tips≠ | Multivariate volatility model | Financial risk measure |
| Pirmavots≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956 |
| Citi nosaukumi≠ | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | VaR, value-at-risk, delta-normal VaR, historical simulation VaR |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. | 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. |
| ScholarGateDatu kopa ↗ |
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