Comparing emerging and mature markets during times of crises: A non-extensive statistical approach

Abstract

One of the important issues in finance and economics for both scholars and practitioners is to describe the behavior of markets, especially during times of crises. In this paper, we analyze the behavior of some mature and emerging markets with a Tsallis entropy framework that is a non-extensive statistical approach based on non-linear dynamics. During the past decade, this technique has been successfully applied to a considerable number of complex systems such as stock markets in order to describe the non-Gaussian behavior of these systems. In this approach, there is a parameter q, which is a measure of deviation from Gaussianity, that has proved to be a good index for detecting crises. We investigate the behavior of this parameter in different time scales for the market indices. It could be seen that the specified pattern for q differs for mature markets with regard to emerging markets. The findings show the robustness of the stated approach in order to follow the market conditions over time. It is obvious that, in times of crises, q is much greater than in other times. In addition, the response of emerging markets to global events is delayed compared to that of mature markets, and tends to a Gaussian profile on increasing the scale. This approach could be very useful in application to risk and portfolio management in order to detect crises by following the parameter q in different time scales.