Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach
In this paper, a dynamic mixture copula model is used to estimate the marginal expected shortfall in the South African insurance sector. We also employ the generalized autoregressive score model (GAS) to capture the dynamic asymmetric dependence between the insurers’ returns and the stock market ret...
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Online Access: | https://www.mdpi.com/2227-7072/9/2/29 |
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doaj-2e1f991f935e4c64aa87f7faa71907712021-06-01T01:44:32ZengMDPI AGInternational Journal of Financial Studies2227-70722021-05-019292910.3390/ijfs9020029Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula ApproachJohn Weirstrass Muteba Mwamba0Ehounou Serge Eloge Florentin Angaman1School of Economics, University of Johannesburg, Johannesburg 2092, South AfricaSchool of Economics, University of Johannesburg, Johannesburg 2092, South AfricaIn this paper, a dynamic mixture copula model is used to estimate the marginal expected shortfall in the South African insurance sector. We also employ the generalized autoregressive score model (GAS) to capture the dynamic asymmetric dependence between the insurers’ returns and the stock market returns. Furthermore, the paper implements a ranking framework that expresses to what extent individual insurers are systemically important in the South African economy. We use the daily stock return of five South African insurers listed on the Johannesburg Stock Exchange from November 2007 to June 2020. We find that Sanlam and Discovery contribute the most to systemic risk, and Santam turns out to be the least systemically risky insurance company in the South African insurance sector. Our findings defy common belief whereby only banks are systemically risky financial institutions in South Africa and should undergo stricter regulatory measures. However, our results indicate that stricter regulations such as higher capital and loss absorbency requirements should be required for systemically risky insurers in South Africa.https://www.mdpi.com/2227-7072/9/2/29dynamic mixture copulamarginal expected shortfallsystemic riskinsurance sector |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
John Weirstrass Muteba Mwamba Ehounou Serge Eloge Florentin Angaman |
spellingShingle |
John Weirstrass Muteba Mwamba Ehounou Serge Eloge Florentin Angaman Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach International Journal of Financial Studies dynamic mixture copula marginal expected shortfall systemic risk insurance sector |
author_facet |
John Weirstrass Muteba Mwamba Ehounou Serge Eloge Florentin Angaman |
author_sort |
John Weirstrass Muteba Mwamba |
title |
Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach |
title_short |
Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach |
title_full |
Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach |
title_fullStr |
Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach |
title_full_unstemmed |
Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach |
title_sort |
modeling system risk in the south african insurance sector: a dynamic mixture copula approach |
publisher |
MDPI AG |
series |
International Journal of Financial Studies |
issn |
2227-7072 |
publishDate |
2021-05-01 |
description |
In this paper, a dynamic mixture copula model is used to estimate the marginal expected shortfall in the South African insurance sector. We also employ the generalized autoregressive score model (GAS) to capture the dynamic asymmetric dependence between the insurers’ returns and the stock market returns. Furthermore, the paper implements a ranking framework that expresses to what extent individual insurers are systemically important in the South African economy. We use the daily stock return of five South African insurers listed on the Johannesburg Stock Exchange from November 2007 to June 2020. We find that Sanlam and Discovery contribute the most to systemic risk, and Santam turns out to be the least systemically risky insurance company in the South African insurance sector. Our findings defy common belief whereby only banks are systemically risky financial institutions in South Africa and should undergo stricter regulatory measures. However, our results indicate that stricter regulations such as higher capital and loss absorbency requirements should be required for systemically risky insurers in South Africa. |
topic |
dynamic mixture copula marginal expected shortfall systemic risk insurance sector |
url |
https://www.mdpi.com/2227-7072/9/2/29 |
work_keys_str_mv |
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