Dynamic conditional correlation GARCH: a multivariate time series novel using a bayesian approach (2019)
- Authors:
- USP affiliated authors: LOUZADA NETO, FRANCISCO - ICMC ; NASCIMENTO, DIEGO CARVALHO DO - INTER: ICMC -UFSCAR ; XAVIER, CLEBER MARTINS - INTER: ICMC -UFSCAR
- Unidades: ICMC; INTER: ICMC -UFSCAR
- DOI: 10.22237/jmasm/1556669220
- Subjects: MÉTODOS MCMC; MERCADO FINANCEIRO; MINERAÇÃO DE DADOS; INFERÊNCIA BAYESIANA
- Keywords: DCC-GARCH; Bayesian model; visual data mining; financial contagion
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Modern Applied Statistical Methods
- ISSN: 1538-9472
- Volume/Número/Paginação/Ano: v. 18, n. 1, p. 1-17, 2019
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
-
ABNT
NASCIMENTO, Diego Carvalho do et al. Dynamic conditional correlation GARCH: a multivariate time series novel using a bayesian approach. Journal of Modern Applied Statistical Methods, v. 18, n. 1, p. 1-17, 2019Tradução . . Disponível em: https://doi.org/10.22237/jmasm/1556669220. Acesso em: 23 maio 2024. -
APA
Nascimento, D. C. do, Xavier, C. M., Felipe, I., & Louzada, F. (2019). Dynamic conditional correlation GARCH: a multivariate time series novel using a bayesian approach. Journal of Modern Applied Statistical Methods, 18( 1), 1-17. doi:10.22237/jmasm/1556669220 -
NLM
Nascimento DC do, Xavier CM, Felipe I, Louzada F. Dynamic conditional correlation GARCH: a multivariate time series novel using a bayesian approach [Internet]. Journal of Modern Applied Statistical Methods. 2019 ; 18( 1): 1-17.[citado 2024 maio 23 ] Available from: https://doi.org/10.22237/jmasm/1556669220 -
Vancouver
Nascimento DC do, Xavier CM, Felipe I, Louzada F. Dynamic conditional correlation GARCH: a multivariate time series novel using a bayesian approach [Internet]. Journal of Modern Applied Statistical Methods. 2019 ; 18( 1): 1-17.[citado 2024 maio 23 ] Available from: https://doi.org/10.22237/jmasm/1556669220 - Copula bivariate model: predictive analytics on estimation tinnitus psychoacoustic parameters
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Informações sobre o DOI: 10.22237/jmasm/1556669220 (Fonte: oaDOI API)
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