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.
Nascimento, D., Xavier, C., Felipe, I., & Neto, F. L. (2019). Dynamic conditional correlation GARCH: A multivariate time series novel using a Bayesian approach. Journal of Modern Applied Statistical Mehtods, 18(1), eP2722. doi: 10.22237/jmasm/1556669220