Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Hodnota v riziku (VaR)× | Realizovaná volatilita a model HAR× | |
|---|---|---|
| Obor | Finance | Finance |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 2007 | 2009 |
| Tvůrce≠ | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan | Corsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility) |
| Typ≠ | Financial risk measure | Time-series regression of realized variance |
| Původní zdroj≠ | Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956 | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196. DOI ↗ |
| Další názvy | VaR, value-at-risk, delta-normal VaR, historical simulation VaR | realized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RV |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | 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. | Realized volatility estimates an asset's variance directly from high-frequency intraday returns rather than from a parametric latent process. The Heterogeneous Autoregressive (HAR) model of Corsi (2009), building on the realized-volatility framework of Andersen, Bollerslev, Diebold and Labys (2003), forecasts this measure by combining daily, weekly, and monthly volatility components, and is a strong alternative to GARCH for volatility prediction. |
| ScholarGateDatová sada ↗ |
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