Expected Shortfall Modeling in Optimizing Credit Risk Portfolioand Its Solution Based on the Non-Numerical Algorithms
Jianlong Zhang · Systems Engineering - Theory & Practice · 2005
Expected Shortfall (ES) is a new tool for credit risk measure and optimization. As the risk measure tool, ES represents the tail information of loss and is favorable to keep away the extreme finance risk with very little probability. As the tool for risk optimization, it simultaneously adjusts all positions in the portfolio in order to optimize ES, and simultaneously gain corresponding VaR. Fredrik builds a linear program model with Expected Shortfall which can simultaneously optimize Expected Shortfall and VaR of portfolio, but this model has the drawback of dimension obstacle. To overcome this drawback, we revert it to a non-linear program model again and solve it by a Genetic Algorithm with constraints and Simulated Annealing Algorithm. Example illustration shows that the optimized portfolios' standard deviation, VaR and Exepected Shortfall are decreased obviously under the nearly same expected yield through two methods, but Simulated Annealing Algorithm has better effect on optimizing portfolio's ES.