Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modeli ARIMA (Autoregresiv i Integruar Mesatar Lëvizës)× | Modeli EGARCH (Exponential GARCH)× | |
|---|---|---|
| Fusha | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 1970 | 1991 |
| Krijuesi≠ | George Box and Gwilym Jenkins | Daniel B. Nelson |
| Lloji≠ | Time series forecasting model | Volatility / conditional variance model |
| Burimi themelues≠ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Emërtime të tjera | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Të lidhura | 6 | 6 |
| Përmbledhja≠ | The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics. | The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. |
| ScholarGateSeti i të dhënave ↗ |
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