Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo de Markov com Troca de Regimes (MS-AR / MS-VAR)× | Heterocedasticidade Condicional Autorregressiva Generalizada (GARCH)× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1989 | 1986 |
| Autor original≠ | Hamilton (1989); Kim & Nelson (1999) | Tim Bollerslev |
| Tipo≠ | Regime-switching time series model | Conditional volatility model |
| Fonte seminal≠ | Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗ |
| Outros nomes≠ | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli |
| Relacionados | 5 | 5 |
| Resumo≠ | The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions. | GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns. |
| ScholarGateConjunto de dados ↗ |
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