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Modeli wa GARCH (Utabiri wa Msukosuko)×Mfumo wa HAR-RV wa Matumizi Halisi ya Kutikisika×
NyanjaEkonometrikiFedha
FamiliaRegression modelRegression model
Mwaka wa asili19862009
MwanzilishiTim BollerslevFulvio Corsi
AinaConditional volatility modelLinear time-series regression for volatility
Chanzo asiliaBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗
Majina mbadalaGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)
Zinazohusiana55
MuhtasariThe 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.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.
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ScholarGateLinganisha mbinu: GARCH Model · HAR-RV Model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare