We examine the nature of BRICS stock market returns using a t-DCC model and investigate whether multivariate volatility models can characterize and quantify market risk. We initially consider a multivariate normal-DCC model and show that it cannot adequately capture the fat tails prevalent in financial time series data. We then consider a multivariate t- version of the Gaussian dynamic conditional correlation (DCC) proposed by  and successfully implemented by [24, 26]. We find that the t-DCC model (dynamic conditional correlation based on the t-distribution) out performs the normal-DCC model. The former passes most diagnostic tests although it barely passes the Kolmogorov-Smirnov goodness-of-fit test.
ISSN: 1792-6599 (Online)