A hybrid heuristic approach to discrete multi-objective optimization of credit portfolios

摘要

A hybrid heuristic approach combining multi-objective evolutionary and problem-specific local search methods is proposed to support the risk-return analysis of credit portfolios. Its goal is to compute approximations of discrete sets of Pareto-efficient portfolio structures concerning both the respective portfolio return and the respective portfolio risk using the non-linear, non-convex Credit-Value-at-Risk downside risk measure which is relevant to real world credit portfolio optimization. In addition, constraints like capital budget restrictions are considered in the hybrid heuristic framework. The computational complexity of selected parts of the algorithm is analyzed. Moreover, empirical results indicate that the hybrid method is superior in convergence speed to a non-hybrid evolutionary approach and finds approximations of risk-return efficient portfolios within reasonable time.