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Model ARIMA (Autoregressive Integrated Moving Average)×Modeli GARCH (Parashikimi i Volatilitetit)×
FushaEkonometriEkonometri
FamiljaRegression modelRegression model
Viti i origjinës20151986
KrijuesiBox & Jenkins (Box-Jenkins methodology)Tim Bollerslev
LlojiUnivariate time-series modelConditional volatility model
Burimi themeluesBox, 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 ↗
Emërtime të tjeraBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Të lidhura55
PërmbledhjaARIMA 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).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: ARIMA · GARCH Model. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare