ScholarGate
Assistent

Methoden vergelijken

Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

HAR-RV Model van Gerealiseerde Volatiliteit×Risicomaatstaven voor de staart (Expected Shortfall, spectrale, expectiel)×
VakgebiedFinancieringFinanciering
FamilieRegression modelRegression model
Jaar van ontstaan20091999
GrondleggerFulvio CorsiArtzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)
TypeLinear time-series regression for volatilityCoherent tail risk measure
Oorspronkelijke bronCorsi, 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 ↗
AliassenHAR-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
Verwant55
SamenvattingThe 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.
ScholarGateGegevensset
  1. v1
  2. 1 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

Naar zoeken Dia's downloaden

ScholarGateMethoden vergelijken: HAR-RV Model · Tail Risk Measures. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare