Empirical analyses of extreme value models for the South African mining index
© 2014 Economic Society of South Africa. While the classical normality assumption is simple to implement, it is well known to underestimate the leptokurtic behaviour demonstrated in most financial data. After examining properties of the Johannesburg Stock Exchange Mining Index returns, we propose tw...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/67499 |
| _version_ | 1848761582058733568 |
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| author | Chinhamu, K. Huang, Chun-Kai Huang, C. Hammujuddy, J. |
| author_facet | Chinhamu, K. Huang, Chun-Kai Huang, C. Hammujuddy, J. |
| author_sort | Chinhamu, K. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2014 Economic Society of South Africa. While the classical normality assumption is simple to implement, it is well known to underestimate the leptokurtic behaviour demonstrated in most financial data. After examining properties of the Johannesburg Stock Exchange Mining Index returns, we propose two extreme value models to fit its negative tail with a higher degree of accuracy. The generalised extreme value distribution (GEVD) is fitted using the block maxima approach, while the generalised Pareto distribution (GPD) is fitted using the peaks-over-threshold method. Numerical assessment of value-at-risk (VaR) estimates indicates that both GEVD and GPD increasingly outperform the normal distribution as we move further into the lower tail. In addition, GEVD produces lower estimates relative to that of the historical VaR, and GPD provides slightly more conservative estimates for adequate capitalisation. |
| first_indexed | 2025-11-14T10:33:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-67499 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:33:57Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-674992018-05-18T08:05:20Z Empirical analyses of extreme value models for the South African mining index Chinhamu, K. Huang, Chun-Kai Huang, C. Hammujuddy, J. © 2014 Economic Society of South Africa. While the classical normality assumption is simple to implement, it is well known to underestimate the leptokurtic behaviour demonstrated in most financial data. After examining properties of the Johannesburg Stock Exchange Mining Index returns, we propose two extreme value models to fit its negative tail with a higher degree of accuracy. The generalised extreme value distribution (GEVD) is fitted using the block maxima approach, while the generalised Pareto distribution (GPD) is fitted using the peaks-over-threshold method. Numerical assessment of value-at-risk (VaR) estimates indicates that both GEVD and GPD increasingly outperform the normal distribution as we move further into the lower tail. In addition, GEVD produces lower estimates relative to that of the historical VaR, and GPD provides slightly more conservative estimates for adequate capitalisation. 2015 Journal Article http://hdl.handle.net/20.500.11937/67499 10.1111/saje.12051 restricted |
| spellingShingle | Chinhamu, K. Huang, Chun-Kai Huang, C. Hammujuddy, J. Empirical analyses of extreme value models for the South African mining index |
| title | Empirical analyses of extreme value models for the South African mining index |
| title_full | Empirical analyses of extreme value models for the South African mining index |
| title_fullStr | Empirical analyses of extreme value models for the South African mining index |
| title_full_unstemmed | Empirical analyses of extreme value models for the South African mining index |
| title_short | Empirical analyses of extreme value models for the South African mining index |
| title_sort | empirical analyses of extreme value models for the south african mining index |
| url | http://hdl.handle.net/20.500.11937/67499 |