Dynamic conditional correlation GARCH : a multivariate time series novel using a bayesian approach.

Nascimento, Diego Carvalho do; Xavier, Cleber; Felipe, Israel José dos Santos; Louzada Neto, Francisco

Use este identificador para citar ou linkar para este item: http://www.repositorio.ufop.br/jspui/handle/123456789/12846

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Campo Dublin Core	Valor	Idioma
dc.contributor.author	Nascimento, Diego Carvalho do	-
dc.contributor.author	Xavier, Cleber	-
dc.contributor.author	Felipe, Israel José dos Santos	-
dc.contributor.author	Louzada Neto, Francisco	-
dc.date.accessioned	2020-10-15T15:06:35Z	-
dc.date.available	2020-10-15T15:06:35Z	-
dc.date.issued	2019	pt_BR
dc.identifier.citation	NASCIMENTO, D. C. 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, maio 2019. Disponível em: <https://digitalcommons.wayne.edu/jmasm/vol18/iss1/6/>. Acesso em: 27 set. 2020.	pt_BR
dc.identifier.issn	1538−9472	-
dc.identifier.uri	http://www.repositorio.ufop.br/handle/123456789/12846	-
dc.description.abstract	The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and developing countries from different continents. The performances of indices are similar, with a joint evolution. Most index returns, especially SPX and NDX, evolve over time with a higher positive correlation.	pt_BR
dc.language.iso	en_US	pt_BR
dc.rights	restrito	pt_BR
dc.subject	Visual data mining	pt_BR
dc.subject	Financial contagion	pt_BR
dc.title	Dynamic conditional correlation GARCH : a multivariate time series novel using a bayesian approach.	pt_BR
dc.type	Artigo publicado em periodico	pt_BR
dc.identifier.uri2	https://digitalcommons.wayne.edu/jmasm/vol18/iss1/6/	pt_BR
dc.identifier.doi	http://dx.doi.org/10.22237/jmasm/1556669220	pt_BR
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