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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

GJR-GARCH (GARCH Asimetrike)×Model ARIMA (Autoregressive Integrated Moving Average)×
FushaEkonometriEkonometri
FamiljaRegression modelRegression model
Viti i origjinës19932015
KrijuesiGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Box & Jenkins (Box-Jenkins methodology)
LlojiAsymmetric conditional volatility modelUnivariate time-series model
Burimi themeluesGlosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. 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: 978-1118675021
Emërtime të tjeraasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Të lidhura55
PërmbledhjaGJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).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).
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ScholarGateKrahasoni metodat: GJR-GARCH · ARIMA. Marrë më 2026-06-19 nga https://scholargate.app/sq/compare