Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modeli ARCH (Heteroskedasticiteti i kushtëzuar Autoregresiv)× | Modeli ARIMA (Autoregresiv i Integruar Mesatar Lëvizës)× | |
|---|---|---|
| Fusha | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 1982 | 1970 |
| Krijuesi≠ | Robert F. Engle | George Box and Gwilym Jenkins |
| Lloji≠ | Conditional volatility model | Time series forecasting model |
| Burimi themelues≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| Emërtime të tjera | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) |
| Të lidhura | 6 | 6 |
| Përmbledhja≠ | The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering. | 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. |
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