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The relationship between three different groups of COVID-19 news series and stock market volatility for several Latin American countries and the U.S. are analyzed. To confirm the relationship between these series, a maximal overlap discrete wavelet transform (MODWT) was applied to determine the specific periods wherein each pair of series is significantly correlated. To determine if the news series cause Latin American stock markets' volatility, a one-sided Granger causality test based on transfer entropy (GC-TE) was applied. The results confirm that the U.S. and Latin American stock markets react differently to COVID-19 news. Some of the most statistically significant results were obtained from the reporting case index (RCI), A-COVID index, and uncertainty index, in that order, which are statistically significant for the majority of Latin American stock markets. Altogether, the results suggest these COVID-19 news indices could be used to forecast stock market volatility in the U.S. and Latin America. [ABSTRACT FROM AUTHOR]

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]

Copyright of Investigación Económica is the property of Universidad Nacional Autonoma de Mexico, Facultad de Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Estudios Gerenciales is the property of Universidad ICESI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

This paper is aimed at studying the Adaptive Market Hypothesis (AMH) of the Mexican Stock Exchange Index (IPC, for its acronym in Spanish). To do this, we apply: 1) unit-root tests, 2) nonlinear tests, and 3) episodic nonlinearity tests. The main empirical finding is that the IPC goes through plenty of periods where the market behaves in an efficient way. That is, as a random walk, followed by some periods of adaptability where non-linearity in the series of the IPC returns is found. [ABSTRACT FROM AUTHOR]

This work applies a test that detects dependence between pairs of variables. The kind of dependence is a non-linear one, and the test is known as cross-bicorrelation, which is associated with Brooks and Hinich [1], We study dependence periods between U.S. Standard and Poor's 500 (SP500), used as a benchmark, and six Latin American stock market indexes: Mexico (BMV), Brazil (BOVESPA), Chile (IPSA), Colombia (COLCAP), Peru (IGBVL) and Argentina (MERVAL). We have found windows of nonlinear dependence and comovement between the SP500 and the Latin American stock markets, some of which coincide with periods of crisis, leading to an interpretation of a possible contagion or interdependence. [ABSTRACT FROM AUTHOR]