Dynamic Conditional Correlation GARCH: A Multivariate Time Series Novel using a Bayesian Approach

Nascimento, Diego; Xavier, Cleber; Felipe, Israel; Louzada Neto, Francisco

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.

Más información

Título según WOS: ID WOS:000605728200006 Not found in local WOS DB
Título de la Revista: JOURNAL OF MODERN APPLIED STATISTICAL METHODS
Volumen: 18
Número: 1
Editorial: WAYNE STATE UNIV PRESS
Fecha de publicación: 2019
DOI:

10.22237/jmasm/1556669220

Notas: ISI