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The purpose of this article is to study the unidirectional causality from the Infectious Disease Equity Market Volatility Tracker (EMV-ID), towards the volatility of five of the most important Latin American stock and Exchange markets. For this, volatility is captured through the DCC-GARCH t-Copula method. In addition, the time-varying Granger multivariate causality test (TV-GC) and the classical Granger causality test (GC) are applied. It is found that, with both methodologies, EMV-ID causes both series, which highlights the importance of having this new indicator for the analysis of the different agents involved in financial markets, among them, regulators, companies and traders in particular. Our results are consistent with the evidence of other research findings about the predictive power of the EMV-ID index on oil price volatility and some European equity markets, and the positive link between EMV-ID and the time-varying of return connectedness across gold, crude oil, world equities, currencies and bonds. [ABSTRACT FROM AUTHOR]

We model the changes in volatility in the Mexican Stock Exchange Index using a Bayesian approach. We study the time series with a wide set of models characterized by a Markov switching heterogeneity. The advantage of this approach is that it allows for a broader spectrum of possible models since the estimation of the moments of the parameters is done using the finite mixture distribution MCMC method, without relying on assumptions about large sampling and mathematical optimization. This is particularly relevant for emerging markets’ financial data because of its special characteristics, like being more susceptible to jumps and changes in volatility caused by exchange rate swings, financial crises and oil and commodity prices. For model comparison, we use the marginal likelihood approach and the bridge sampling technique. The best representation of the data is given by a switching model with three states rather than any other autoregressive linear or non-linear model. The periods of volatility found by the model coincide with different financial crisis. Whereas other studies of volatility for the same market impose the Markovian model that captures changes in volatility, we let our model to be defined in an endogenous way. [ABSTRACT FROM PUBLISHER]