Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Teste de Cointegração de Johansen e Modelo de Vetor de Correção de Erros× | Modelos de Memória Longa (ARFIMA, FIGARCH)× | |
|---|---|---|
| Área | Finanças | Finanças |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1991 | 1980 |
| Autor original≠ | Søren Johansen | Granger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH) |
| Tipo≠ | Multivariate cointegration / vector error correction model | Fractionally integrated time series model |
| Fonte seminal≠ | Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗ | Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI ↗ |
| Outros nomes | Johansen test, VECM, vector error correction model, multivariate cointegration | ARFIMA, FIGARCH, fractionally integrated models, fractional integration |
| Relacionados≠ | 3 | 4 |
| Resumo≠ | 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. | Long-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration. |
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