Quantile regression and copula-based analysis of risk and dependence in the South African stock market
- 1epartment of Mathematics and Statistical Sciences, School of Pure and Applied Sciences, Botswana International University of Science and Technology, Palapye, Botswana
Abstract
This study examines the relationship between the South African stock market and key macroeconomic factors, namely exchange rate movements, crude oil prices, and gold prices, using monthly data from 2007 to 2025. To capture heterogeneous market behavior and downside risk, the study employs quantile regression, quantile autoregression, Conditional Autoregressive Value at Risk (CAViaR) models, and copula models. The results reveal that exchange rate movements exert a consistently negative effect on stock returns across the conditional distribution, while return persistence remains weak, suggesting a relatively efficient market. Downside risk is found to be time-varying and is driven primarily by past risk and adverse market shocks rather than contemporaneous macroeconomic variables. Copula analysis indicates strong negative overall dependence between the Johannesburg Stock Exchange (JSE) and South African Rand/United States Dollar (USD/ZAR) but no asymptotic tail dependence, while the JSE–Brent relationship exhibits moderate symmetric tail dependence. The JSE–Gold relationship is weak, with negligible lower-tail dependence. These findings demonstrate that macroeconomic influences and market risk vary across different market states, underscoring the value of quantile based approaches for modeling financial risk and informing portfolio risk management in emerging markets.
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BibTeX
@article{mkandla2026quantile,
title = {{Quantile regression and copula-based analysis of risk and dependence in the South African stock market}},
author = {Precious Mkandla and Fastel Chipepa},
journal = {Frontiers in Applied Mathematics and Statistics},
year = {2026},
month = oct,
doi = {10.3389/fams.2026.1934050},
url = {https://doi.org/10.3389/fams.2026.1934050},
note = {CC BY},
}
RIS
TY - JOUR
TI - Quantile regression and copula-based analysis of risk and dependence in the South African stock market
AU - Precious Mkandla
AU - Fastel Chipepa
PY - 2026
DA - 2026/10/26
JO - Frontiers in Applied Mathematics and Statistics
DO - 10.3389/fams.2026.1934050
UR - https://doi.org/10.3389/fams.2026.1934050
AB - This study examines the relationship between the South African stock market and key macroeconomic factors, namely exchange rate movements, crude oil prices, and gold prices, using monthly data from 2007 to 2025. To capture heterogeneous market behavior and downside risk, the study employs quantile regression, quantile autoregression, Conditional Autoregressive Value at Risk (CAViaR) models, and copula models. The results reveal that exchange rate movements exert a consistently negative effect on stock returns across the conditional distribution, while return persistence remains weak, suggesting a relatively efficient market. Downside risk is found to be time-varying and is driven primarily by past risk and adverse market shocks rather than contemporaneous macroeconomic variables. Copula analysis indicates strong negative overall dependence between the Johannesburg Stock Exchange (JSE) and South African Rand/United States Dollar (USD/ZAR) but no asymptotic tail dependence, while the JSE–Brent relationship exhibits moderate symmetric tail dependence. The JSE–Gold relationship is weak, with negligible lower-tail dependence. These findings demonstrate that macroeconomic influences and market risk vary across different market states, underscoring the value of quantile based approaches for modeling financial risk and informing portfolio risk management in emerging markets.
SN - 2297-4687
ER -