The nature of BRICS currency 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 such as exchange rates. We then consider a multivariate tversion of the Gaussian dynamic conditional correlation (DCC) proposed by [1] and successfully implemented by [2] and [3]. 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. | Garch modelling of conditional correlations and volatility of exchange rates in BRICS countries
