出版社：LLC “Consulting Publishing Company “Business Perspectives”
摘要：This paper presents a framework to portfolio optimization that is superior to the mean-variance approaches utilized for asset allocation.We show how a portfolio with heavily differing asset types in various market phases can be managed efficiently by using a ratio-based portfolio optimization approach and provide a general solution to related optimization problems and the technical challenges arising from them.Portfolio optimization is done by using a modified version of the R ratio in a benchmark-free setting for real estate funds of funds(FoFs).We use a genetic algorithm to solve the non-quasi-convex optimization problem and propose the use of genetic algorithms for related ratio-based optimization problems.Our results show the appropriateness of both the modified R ratio and the genetic algorithm used to optimize the fund portfolios in the benchmark-free environment.The algorithm efficiently solves the non-quasi-convex type of problem and related approaches of portfolio optimization are outperformed by the R ratio focused approach.
关键词：portfolio optimization;genetic algorithm;R ratio;funds of funds;real estate funds;expected tail loss;non?quasi-convex.
