This paper analyzes the direction of the causality between crude oil, gold and stock markets for the largest economy in the world with respect to such markets, the US. To do so, we apply non-linear Granger causality tests. We find a nonlinear causal relationship among the three markets considered, with the causality going in all directions, when the full sample and different subsamples are considered. However, we find a unidirectional nonlinear causal relationship between the crude oil and gold market (with the causality only going from oil price changes to gold price changes) when the subsample runs from the first date of any year between the mid-1990s and 2001 to last available data (February 5, 2015). The latter result may explain the lack of consensus existing in the literature about the direction of the causal link between the crude oil and gold markets.

In this paper we study a possible synchronization in volatility changes for some Latin America's stock exchange indexes. We also add the S&P 500 index to the analysis. We suggest a heterogeneity Markov switching model to capture changes in volatilities over time.To solve the problem of uncertainty in modeling each index, we suggest the Bayes Factor to identify the best Markov switching specification as the number of states, if any. We found that, all the daily growth rates for each index are well characterized by low, medium and high volatilities in different periods of time. We suggest some measures of synchronization based on the concordance by the changes in volatilities between the indexes. We show that, the Mexican, Chilean and the S&P 500 indexes are closer to each other than the rest

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En esta investigación se estudió la causalidad en el sentido unidireccional de Granger, desde el índice Infectious Disease Equity Market Volatility Tracker hacia la volatilidad del mercado accionario chileno, la cual se modela por un procedimiento autorregresivo condicional. Se aplican tres pruebas de causalidad y, de manera complementaria, la prueba de bicorrelación cruzada. Los resultados indican que este índice causa la volatilidad del mercado con la mayoría de las pruebas aplicadas. Esto señala la potencial relevancia de contar con este nuevo indicador para los agentes que participan en los mercados financieros, entre ellos reguladores, compañías y corredores. Adicionalmente, los resultados son congruentes con la evidencia sobre la capacidad predictiva del índice sobre la volatilidad del precio del petróleo y otros índices.

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This paper analyzes time-varying causality between government bond and oil returns of the United States (US) over the monthly period of 1859:10 to 2019:03, i.e., the longest possible span of historical data, starting from the beginning of the modern era of the petroleum industry. While the standard constant parameter causality test fails to pick up any evidence of causality, the timevarying framework shows evidence of bi-directional spillovers over the entire sample period. The results are robust to inclusion of stock returns as an control variable in the model. We also detect evidence of time-varying causality-in-volatility between sovereign bond and oil markets, as well as spillovers in returns and volatility from the oil market to corporate bonds.

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