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HAR-RV-Modell der realisierten Volatilität×GARCH-Modell (Volatilitätsvorhersage)×
FachgebietFinanzwirtschaftÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr20091986
UrheberFulvio CorsiTim Bollerslev
TypLinear time-series regression for volatilityConditional volatility model
Wegweisende QuelleCorsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
AliasnamenHAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Verwandt55
ZusammenfassungThe 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.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
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ScholarGateMethoden vergleichen: HAR-RV Model · GARCH Model. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare