Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Модел ARIMA (Autoregressive Integrated Moving Average)× | Експоненциален GARCH (EGARCH)× | Тест за коинтеграция на Йохансен и модел на векторна корекция на грешката× | |
|---|---|---|---|
| Област≠ | Иконометрия | Иконометрия | Финанси |
| Семейство | Regression model | Regression model | Regression model |
| Година на възникване≠ | 2015 | 1991 | 1991 |
| Създател≠ | Box & Jenkins (Box-Jenkins methodology) | Nelson | Søren Johansen |
| Тип≠ | Univariate time-series model | Conditional volatility model (asymmetric GARCH variant) | Multivariate cointegration / vector error correction model |
| Основополагащ източник≠ | 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 | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ | Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗ |
| Други названия≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | Johansen test, VECM, vector error correction model, multivariate cointegration |
| Свързани≠ | 5 | 4 | 3 |
| Резюме≠ | 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). | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. | 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. |
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