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

Smile Dube

Journal of Applied Finance & Banking, 2019, vol. 9, issue 1, 7

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 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.scienpress.com/Upload/JAFB%2fVol%209_1_7.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spt:apfiba:v:9:y:2019:i:1:f:9_1_7

Access Statistics for this article

More articles in Journal of Applied Finance & Banking from SCIENPRESS Ltd
Bibliographic data for series maintained by Eleftherios Spyromitros-Xioufis ().