Open AccessThe Application of the Multivariate GARCH Models on the BRICS Exchange Rates
Author(s) -
Lebotsa Daniel Metsileng,
Ntebogang Dinah Moroke,
Johannes Tshepiso Tsoku
Publication year - 2020
Publication title -
academic journal of interdisciplinary studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.148
H-Index - 5
eISSN - 2281-3993
pISSN - 2281-4612
DOI - 10.36941/ajis-2020-0058
Subject(s) - autoregressive conditional heteroskedasticity , volatility (finance) , econometrics , conditional variance , multivariate statistics , economics , exchange rate , statistics , mathematics , monetary economics
The study investigated the BRICS exchange rate volatility using the Multivariate GARCH models. The study used the monthly time series data for the period January 2008 to January 2018. The BEKK-GARCH model revealed that all the variables were found to be statistically significant. The diagonal parameters estimates showed that only Russia and South Africa were statistically significant. This implied that the conditional variance of Russia and South Africa’s exchange rates are affected by their own past conditional volatility and other BRICS exchange rates past conditional volatility. The BEKK-GARCH model also revealed that there is a bidirectional volatility transmission between Russia and South Africa. The results from the DCC-GARCH model revealed that Brazil, China, Russia and South Africa had the highest volatility persistence and India has the least volatility persistence. All the BRICS exchange rates show that the fitted residuals are not normally distributed except for Russia. The recommendations for future studies were articulated.