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

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.

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Publication Details

Journal
Statistics Optimization & Information Computing
Published
2024-08-08
DOI
https://doi.org/10.19139/soic-2310-5070-1863
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
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article

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

Kimera Naradh, Retius Chifurira, Knowledge Chinhamu
Statistics Optimization & Information Computing
Financial Risk and Volatility Modeling
article

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

Kimera Naradh, Retius Chifurira, Knowledge Chinhamu
article en

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.

Statistics Optimization & Information ComputingVol. 13(1)
University of KwaZulu-Natal (ZA)
Openalex Percentile: Top 65%
Financial Risk and Volatility Modeling
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Extreme Value Stable Mixture Modelling with applications to South African stock market indices and exchange rate — Kimera Naradh, Retius Chifurira, et al. · Statistics Optimization & Information Computing (2024) | TGRS Research Map | TGRS