Analysis of stock exchange risk and currency in South African Financial Markets using stable parameter estimation

Kimera Naradh, Retius Chifurira and Knowledge Chinhamu
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Kimera Naradh: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South Africa
Retius Chifurira: School of Mathematics, Statistics and Computer Science, University of kwaZulu-Natal, Durban, South Africa
Knowledge Chinhamu: School of Mathematics, Statistics and Computer Science, University of kwaZulu-Natal, Durban, South Africa.

International Journal of Finance & Banking Studies, 2022, vol. 11, issue 1, 120-131

Abstract: In the preceding decade, the South African economy has experienced challenges due to global disruptive events, hence, the implementation of risk mitigation strategies becomes a priority in volatile markets. Stable distributions account for skewness and heavy-tailed behaviour which are frequently observed in financial data. This study aims to investigate the fit of stable distributions for three FTSE/JSE indices and the USD/ZAR currency exchange rate. The maximum likelihood method was applied to fit Nolan’s 𝑆0-parameterization stable distribution. Value at Risk (VaR) is measure assessing market risk, therefore, VaR estimates and Kupiec likelihood test are applied to evaluate the extreme tail behaviour of the fitted stable model. Results show the robustness of stable distributions in the long and short position for each daily returns. This research validates the use of stable distributions aimed at capturing the characteristics financial data. Those concerned with curtailing losses and investigating alternatives for financial modeling in the South African financial industry may benefit the most by using stable distributions.

Keywords: Stable distributions; Nolan’s 𝑆0-parameterization; Stable parameter estimation; VaR; Kupiec likelihood ratio test (search for similar items in EconPapers)
Date: 2022
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