Risk quantification using skewed distributions: An application to the South African Financial Index (J580)

\nThis study assesses the reproducibility of a recent publication on the risk quantification of the South African Financial Index (J580) using skewed distributions. That is, four skewed distributions (Burr, exponential, gamma and Weibull) are fitted to the returns (split into losses and gains) of the J580 dataset. In this paper, we redo the analysis in an effort to highlight some of the quantifiable differences in the values of the descriptives, goodness-of-fit and risk measures for all four distributions. In addition, other goodness-of-fit tests are computed for all four distributions to check consistency, and based on this extension, it is observed that the Weibull is a better model for gains due to a majority of the goodness-of-fit test inferring that and yields better risk measures. Finally, the Burr distribution is recommended for losses as it better captures the heavy tail of the loss returns.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-08-21
DOI
https://doi.org/10.1051/itmconf/20246701009/pdf
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
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article

Risk quantification using skewed distributions: An application to the South African Financial Index (J580)

Springer Link (Chiba Institute of Technology)
Financial Risk and Volatility Modeling
article

Risk quantification using skewed distributions: An application to the South African Financial Index (J580)

article en

Abstract

\nThis study assesses the reproducibility of a recent publication on the risk quantification of the South African Financial Index (J580) using skewed distributions. That is, four skewed distributions (Burr, exponential, gamma and Weibull) are fitted to the returns (split into losses and gains) of the J580 dataset. In this paper, we redo the analysis in an effort to highlight some of the quantifiable differences in the values of the descriptives, goodness-of-fit and risk measures for all four distributions. In addition, other goodness-of-fit tests are computed for all four distributions to check consistency, and based on this extension, it is observed that the Weibull is a better model for gains due to a majority of the goodness-of-fit test inferring that and yields better risk measures. Finally, the Burr distribution is recommended for losses as it better captures the heavy tail of the loss returns.\n

Springer Link (Chiba Institute of Technology)
Gender equality
Openalex Percentile: Top 59%
Financial Risk and Volatility Modeling
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