Journal of Applied Finance & Banking

GARCH Modelling of Conditional Correlations and Volatility of Exchange rates in BRICS Countries

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• Abstract

  We examine 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 t- version 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.

  JEL classification numbers: C51, G10, G11

  Keywords: Correlations and Volatilities; MGARCH (Multivariate General Autoregressive Conditional Heteroscedasticity), Multivariate t (t-DCC), Kolmogorov-Smirnov test, Value at Risk (VaR) diagnostics, ML – Maximum Likelihood