Investigation on the efficient frontier based on CVaR under copula dependence structure with applications to South African JSE stocks

Includes bibliographical references.We study the feasihility of using a coherent monetary risk measure, Conditional Value at Risk (CVaR) also known as Expected Shortfall (ES), to optimise a portfolio of South African stocks. Value at Risk (VaR) is not a sub-additive risk measure and therefore does not possess one of the four properties that all coherent risk measures must satisfy. Using copula to describe the dependence structure between the instruments in our portfolio, we implement and backtest a CVaR optimization algorithm and compare the backtested results to those obtained using parametric and non-parametric/Monte Carlo VaR. Finally we optimise the portfolio of stocks and generate an efficient frontier specifying CVaR as the risk measure instead of the portfolio variance traditionally used in Markowitz and CAPM models