Quantifying Foreign Exchange Risk in the Selected Listed Sectors of the Johannesburg Stock Exchange: An SV-EVT Pairwise Copula Approach

This paper attempted to apply an EVT-based pairwise copula method for modelling risk interaction between foreign exchange rates and equity indices of the Johannesburg Stock Exchange (JSE) model dependence structure underlying assets with some selected listed stock indices. We filtered return residuals using stochastic volatility GJR-GARCH (1,1) models different distributions, we best-fitted in GARCH framework. applied peaks-over-threshold (POT) fit it by generalised Pareto distribution (GPD), used vine co-movement value at (VaR) quantification. three (USD, GDP, EUR) against South African rand (ZAR) six industry (banking, life insurance, non-life leisure, telecommunications, mining). Our empirical findings show that Student’s t-distribution, combined a regular (R)-vine copula, outperforms alternatives models. Dependence analysis reveals strong co-dependency from financial rates. The results also VaR-based R-vine compared D-vine C-vine before COVID-19 outbreak, while produced appears be most suitable specification quantifying during pandemic. Therefore, is quantification, t-distribution produces better Further, find exhibit higher tail contagion pandemic, non-life-insurance telecommunications sectors appearing investor’s safe haven among JSE. will help investors seek risk-adjusted returns substantially reduce hedging cost potential loss due misspecification make investment decision global health crisis.