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Volatiliteti i realizuar dhe modeli HAR×Modelet me kujtesë të gjatë (ARFIMA, FIGARCH)×
FushaFinancëFinancë
FamiljaRegression modelRegression model
Viti i origjinës20091980
KrijuesiCorsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility)Granger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH)
LlojiTime-series regression of realized varianceFractionally integrated time series model
Burimi themeluesCorsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196. DOI ↗Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI ↗
Emërtime të tjerarealized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RVARFIMA, FIGARCH, fractionally integrated models, fractional integration
Të lidhura54
PërmbledhjaRealized 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.Long-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration.
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ScholarGateKrahasoni metodat: Realized Volatility · Long-Memory Models. Marrë më 2026-06-17 nga https://scholargate.app/sq/compare