GAS Copula models on who’s systemically important in South Africa: Banks or Insurers?
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This paper makes use of the generalized autoregressive score (GAS) Copula model to estimate the Conditional Value at Risk (CoVaR) measure of systemic risk. The proposed measure of systemic risk considers the score of the conditional density as the main driver of time-varying dynamics of tail dependence among financial institutions. Not only does the GAS Copula-based CoVaR enable us to monitor the amount of systemic risk posed by different financial institutions at a specific date, it also allows for the forecasting of systemic risk over time. Our results based on a sample of daily equity returns collected from January 2000 to July 2017 surprisingly show that in South Africa, insurers are the most systemically risky compared to banks and other financial sectors. Moreover, we make use of flexible GAS Copulas in order to approximate complex dependence structures. To validate the robustness of our results over time, we divide our sample period into two sub samples, namely the pre-crisis period (January 2000 to June 2007) and the post-crisis period (January 2010 to July 2017). We obtain similar results in the pre-crisis period. However, in the post-crisis period banks are found to be the biggest threat to system-wide stability.
KeywordsBanks Copula Generalized autoregressive score model Insurers South Africa Systemically important
JEL ClassificationC13 C58 G01 G21 G22 G28
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