Time-varying synchronization and dynamic conditional correlation among the stock market returns of leading South American economies

摘要

Purpose - The purpose of this paper is to capture the pattern of return volatility and information spillover and the extent of conditional correlation among the stock markets of leading South American economies. It also examines the connectedness of market returns within the region. Design/methodology/approach - The time series properties of weekly stock market returns of benchmark indices spanning from the second week of 1995 to the fourth week of December 2015 are analyzed. Using univariate auto-regressive conditional heteroscedastic, generalized auto-regressive conditional heteroscedastic, and dynamic conditional correlation multivariate GARCH model approaches, the study finds evidence of returns and volatility linkages along with the degree of connectedness among the markets. Findings - The findings of this study are consistent with increasing market connectedness among a group of leading South American economies. Stocks exhibit relatively fewer asymmetries in conditional correlations in addition to conditional volatility; yet, the asymmetry is relatively less apparent in integrated markets. The results demonstrate that co-movements are higher toward the end of the sample period than in the early phase. The stock markets of Argentina, Brazil, Chile, and Peru are closely and strongly connected within the region followed by Colombia, whereas Venezuela is least connected with the group. Practical implications - The implication is that foreign investors may benefit from the reduction of the risk by adding the stocks to their investment portfolio. Originality/value - The unique features of the paper include a large sample of national stock returns with updated time series data set that reveals the time series properties and empirical evidence on volatility testing. Unlike other studies, this paper uncovers the relation between the stock markets within the same region facing the same market condition.