Stochastic models with heteroskedasticity: A Bayesian approach for Ibovespa returns

Autor: de Oliveira, Sandra Cristina [UNESP], de Andrade, Marinho Gomes
Přispěvatelé: Universidade Estadual Paulista (Unesp), Universidade de São Paulo (USP)
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Popis: Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-27T11:29:00Z No. of bitstreams: 0Bitstream added on 2014-05-27T14:37:29Z : No. of bitstreams: 1 2-s2.0-84876432682.pdf: 1334284 bytes, checksum: ef5e9c31728b39ff516783479036d4cb (MD5) Made available in DSpace on 2014-05-27T11:29:00Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-04-25 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. Campus Experimental de Tupã Universidade Estadual Paulista, Av. Domingos da Costa Lopes, 780, 17602-660, Tupã, São Paulo Instituto de Ciências Matemáticas e de Computação Universidade de São Paulo, São Carlos, São Paulo Campus Experimental de Tupã Universidade Estadual Paulista, Av. Domingos da Costa Lopes, 780, 17602-660, Tupã, São Paulo
Databáze: OpenAIRE
Externí odkaz: