Knowledge Chinhamu

This paper examines the presence of cointegration between South African gold mining index and USD/ZAR exchange rate. The results show that gold index and USD/ZAR exchange rate series are both I(1) and are cointegrated. The Granger causality test shows a two-way directional causality between gold index and USD/ZAR exchange rate for the period 9 June 2005-9 June 2015. By accounting for possible structural breaks, the Zivot-Andrews unit root test suggests two different breaking points in the data. By using the breaking dates to divide the dataset into 3 sub-periods, the results show that gold index and USD/ZAR exchange rate series are not cointegrated. The Granger causality test shows no causality between the two variables. This finding suggests that gold mining index does not play a key role in explaining the trends in the exchange rate and likewise exchange rate does not affect gold mining index.

Keywords: USD/ZAR exchange rate, gold mining index, unit root tests, breaking points, cointegration.
JEL Classification: F3, F4, F63, O47

South Africa’s economy has faced many downturns in the previous decade, and to curb the spread of the novel SARS-CoV-2, the lockdown brought South African financial markets to an abrupt halt. Therefore, the implementation of risk mitigation approaches is becoming a matter of urgency in volatile markets in these unprecedented times. In this study, a hybrid generalized autoregressive conditional heteroscedasticity (GARCH)-type model combined with heavy-tailed distributions, namely the Generalized Pareto Distribution (GPD) and the Nolan’s S0-parameterization stable distribution (SD), were fitted to the returns of three FTSE/JSE indices, namely All Share Index (ALSI), Banks Index and Mining Index, as well as the daily closing prices of the US dollar against the South African rand exchange rate (USD/ZAR exchange rate). VaR values were estimated and back-tested using the Kupiec likelihood ratio test. The results of this study show that for FTSE/JSE ALSI returns, the hybrid exponential GARCH (1,1) model with SD model (EGARCH(1,1)-SD) outperforms the GARCH-GPD model at the 2.5% VaR level. At VaR levels of 95% and 97.5%, the fitted GARCH (1,1)-SD model for FTSE/JSE Banks Index returns performs better than the GARCH (1,1)-GPD. The fitted GARCH (1,1)-SD model for FTSE/JSE Mining Index returns is better than the GARCH (1,1)-GPD at 5% and 97.5% VaR levels. Thus, this study suggests that the GARCH (1,1)-SD model is a good alternative to the VaR robust model for modeling financial returns. This study provides salient results for persons interested in reducing losses or obtaining a better understanding of the South African financial industry.