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| Model d'ARIMA (Autoregressive Integrated Moving Average)× | Test de Cointegració de Johansen i Model de Correcció d'Errors Vectorial× | |
|---|---|---|
| Camp≠ | Econometria | Finances |
| Família | Regression model | Regression model |
| Any d'origen≠ | 2015 | 1991 |
| Autor original≠ | Box & Jenkins (Box-Jenkins methodology) | Søren Johansen |
| Tipus≠ | Univariate time-series model | Multivariate cointegration / vector error correction model |
| Font seminal≠ | 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 | Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗ |
| Àlies≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | Johansen test, VECM, vector error correction model, multivariate cointegration |
| Relacionats≠ | 5 | 3 |
| Resum≠ | 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). | The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium. |
| ScholarGateConjunt de dades ↗ |
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