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Modeli ARIMA Jolinear×Modeli GARCH (Parashikimi i Volatilitetit)×
FushaEkonometriEkonometri
FamiljaRegression modelRegression model
Viti i origjinës1978-19941986
KrijuesiHowell Tong (SETAR/TAR framework); Timo Terasvirta (STAR extensions)Tim Bollerslev
LlojiNonlinear time series modelConditional volatility model
Burimi themeluesTong, H. (1990). Non-Linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 9780198522249Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Emërtime të tjeranonlinear ARIMA, NARIMA, nonlinear time series model, nonlinear Box-Jenkins modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Të lidhura35
PërmbledhjaThe Nonlinear ARIMA model extends the classical Box-Jenkins ARIMA framework by allowing the conditional mean of a time series to depend on past values and past errors through a nonlinear function. It encompasses families such as Threshold AR (TAR/SETAR), Smooth Transition AR (STAR/LSTAR/ESTAR), and Markov-switching models, capturing asymmetric dynamics, regime changes, and business-cycle asymmetries that linear ARIMA cannot represent.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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ScholarGateKrahasoni metodat: Nonlinear ARIMA model · GARCH Model. Marrë më 2026-06-17 nga https://scholargate.app/sq/compare