Extreme Value Stable Mixture Modelling with applications to South African stock market indices and exchange rate

Abstract

In recent times, there is a vested interest in the research and applications of extreme value mixture models in the stock market and insurance as well as medical industries. This study aims to evaluate the fit of two extreme value mixture models namely Stable-Normal-Stable (SNS) and Stable-KDE-Stable (SKS), where KDE represents the Kernel density estimator, for three FTSE/JSE indices namely All Share Index (ALSI), Banks Index, Mining Index and the USD/ZAR currency exchange rate. These novel models aim to capture the characteristics of South African financial data as compared to the existing commonly fitted extreme value mixture models. The results highlight the robustness of the SNS and SKS mixed model for each daily returns when conducting a graphical bulk model and comprehensive tail model analysis. Financial practitioners looking to curb losses and study alternatives for financial modeling in the South African financial industry using an extreme value mixed model approach may find the SNS and SKS model application beneficial.