Jämför metoder
Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.
| HAR-RV-modellen för realiserad volatilitet× | Svansrisk-mått (Expected Shortfall, spektrala, expectil)× | |
|---|---|---|
| Ämnesområde | Finansiell ekonomi | Finansiell ekonomi |
| Familj | Regression model | Regression model |
| Ursprungsår≠ | 2009 | 1999 |
| Upphovsperson≠ | Fulvio Corsi | Artzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall) |
| Typ≠ | Linear time-series regression for volatility | Coherent tail risk measure |
| Ursprungskälla≠ | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗ | Artzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗ |
| Alias≠ | HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility) | expected shortfall, conditional value at risk, CVaR, spectral risk measure |
| Närliggande | 5 | 5 |
| Sammanfattning≠ | The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility. | Tail risk measures quantify the loss distribution beyond Value-at-Risk (VaR). Expected Shortfall — the expected loss given that VaR is exceeded — is the leading coherent risk measure, formalised by Artzner, Delbaen, Eber and Heath (1999) and shown to be coherent by Acerbi and Tasche (2002). Spectral and expectile-based measures generalise it. |
| ScholarGateDatamängd ↗ |
|
|