| Título: |
Stochastic models with heteroskedasticity: a Bayesian approach for Ibovespa returns - doi: 10.4025/actascitechnol.v35i2.13547 |
| Autores: |
Oliveira, Sandra Cristina de; Universidade Estadual Paulista Andrade, Marinho Gomes de; Universidade de São Paulo |
| Fecha: | 2013-04-18 |
| Publicador: | Acta Scientiarum. Techonology |
| Fuente: |
 |
| Tipo: |
processos ARCH; inferência Bayesiana; métodos MCMC |
| Tema: |
1.02.02.04-8 ARCH family; Bayesian analysis; MCMC methods; financial returns Inferência em Processos Estocásticos |
| Descripción: |
Current research compares the Bayesian estimates obtained for the parameters of processes of ARCH family with normal and Student’s t distributions for the conditional distribution of the return series. A non-informative prior distribution was adopted and a reparameterization of models under analysis was taken into account to map parameters’ space into real space. The procedure adopts a normal prior distribution for the transformed parameters. The posterior summaries were obtained by Monte Carlo Markov Chain (MCMC) simulation methods. The methodology was evaluated by a series of Bovespa Index returns and the predictive ordinate criterion was employed to select the best adjustment model to the data. Results show that, as a rule, the proposed Bayesian approach provides satisfactory estimates and that the GARCH process with Student’s t distribution adjusted better to the data. |
| Idioma: | Inglés |