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ARIMA (autoregresīvais integrētais slīdošā vidējā) modelis×Generalizētā autoregresīvā nosacītā heteroskedastiskuma (GARCH) modelis×GJR-GARCH (Asimetriskais GARCH)×
NozareEkonometrijaEkonometrijaEkonometrija
SaimeRegression modelRegression modelRegression model
Izcelsmes gads201519861993
AutorsBox & Jenkins (Box-Jenkins methodology)Tim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TipsUnivariate time-series modelConditional volatility modelAsymmetric conditional volatility model
PirmavotsBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗Glosten, 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 ↗
Citi nosaukumiBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Saistītās555
KopsavilkumsARIMA 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).GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.GJR-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).
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ScholarGateSalīdzināt metodes: ARIMA · GARCH · GJR-GARCH. Izgūts 2026-06-20 no https://scholargate.app/lv/compare