id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_gqmnbfeeevb27g4yjxdcqdqpmi	Sandra García	Time-stamped resampling for robust evolutionary portfolio optimization	2012	13	.pdf	application/pdf	8127	819	62	Traditional mean-variance financial portfolio optimization is based on two sets of parameters, estimates for the asset returns and control the population that enhances the reliability of the solutions provided by MOEAs. The process of optimizing the risk and return of a portfolio relies on two parameters: the estimates for the expected MOEAs testing the population for different values for the parameters, and selecting the portfolios that consistently Optimizing for a single scenario, a set of expected asset returns and the use of a single variance-covariance matrix, process would favor the individuals that show good performance in terms of risk and return over different scenarios, Solutions resulting from different runs of multiobjective algorithms must be compared using quantitative metrics. • Estimation Error: It evaluates the average difference between the expected risk and return for every portfolio Portfolio optimization problems in different risk measures using genetic algorithm.	./cache/work_gqmnbfeeevb27g4yjxdcqdqpmi.pdf	./txt/work_gqmnbfeeevb27g4yjxdcqdqpmi.txt