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Realisierte Volatilität und das HAR-Modell×ARIMA-Modell (Autoregressive Integrated Moving Average)×Exponential GARCH (EGARCH)×
FachgebietFinanzwirtschaftÖkonometrieÖkonometrie
FamilieRegression modelRegression modelRegression model
Entstehungsjahr200920151991
UrheberCorsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility)Box & Jenkins (Box-Jenkins methodology)Nelson
TypTime-series regression of realized varianceUnivariate time-series modelConditional volatility model (asymmetric GARCH variant)
Wegweisende QuelleCorsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
Aliasnamenrealized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RVBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeliexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Verwandt554
ZusammenfassungRealized 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.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.
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ScholarGateMethoden vergleichen: Realized Volatility · ARIMA · EGARCH. Abgerufen am 2026-06-19 von https://scholargate.app/de/compare