Abstract
This minor dissertation empirically examines systemic risk in the South African Insurance sector from 5 January 2006 to 3 February 2022. To this end, a bivariate multivariable dynamic conditional correlation (DCC-GJR-GARCH) model is utilised to estimate systemic risk measures (i.e. CoVaR and ΔCoVaR). The dissertation makes use of daily returns data of five South African insurance companies (i.e. Sanlam, Santam, Discovery, Momentum, and Liberty) and four developed insurance sectors (i.e. Japan, USA, Germany, and Australia). The insurance companies’ findings show that the three largest insurers in our sample, namely, Santam, Sanlam, and Momentum Holdings, contribute the most to systemic risk. At the same time, the smallest insurers, Discovery, and Liberty, contribute the least. On the other hand, the countries’ findings indicate that Australia and Japan contribute the most to systemic risk in the South African insurance sector, while Germany and the USA contribute the least. Another significant finding is that insurers’ and developed countries’ systemic risk contribution drastically increases during times of economic turmoil. The study concludes by recommending that South African financial regulators should implement diverse risk supervision measures for different insurance companies or countries. For instance, the larger the insurer or country, the stricter is the risk supervision.