Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula

This paper investigates the dynamic tail dependence risk between BRICS economies and world energy market, in context of COVID-19 financial crisis 2020, order to determine optimal investment decisions based on metrics. For this purpose, we employ a combination novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, vine copula methods. Using data set consisting daily stock crude oil prices, find evidence structure break volatility process, high low persistence processes, with probabilities transition lower higher regimes, as well presence leverage effects. Furthermore, our results C-vine confirm existence two types dependence: symmetric South Africa China, Russia, India, asymmetric Brazil, oil. purpose diversification these markets, formulate an asset allocation problem using raw returns, MS GARCH R-vine copula-based optimize it Particle Swarm optimization algorithm rebalancing strategy. The demonstrate inverse relationship contribution supporting them. suggests that, when African stocks are distress, investors tend shift their holdings market. Similar found Russia oil, Brazil In tail, is have well-diversified that suggesting three markets might be good destinations things not Africa, vice versa.