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

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  • Smile Dube

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

Suggested Citation

  • Smile Dube, 2019. "GARCH Modelling of Conditional Correlations and Volatility of Exchange rates in BRICS Countries," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(1), pages 1-7.
    • Handle: RePEc:spt:apfiba:v:9:y:2019:i:1:f:9_1_7
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    More about this item

    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;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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