Estimation of fuzzy portfolio efficiency via an improved DEA approach

DEA (Data Envelopment Analysis) is a nonparametric approach that has been used to estimate fuzzy portfolio efficiency. In this paper, we propose an approach under the fuzzy theory framework that can both improve the DEA frontier and suggest a replicable benchmark for investors. We first construct an improved DEA model using the proposed approach and then investigate the relationships among the evaluation model based on a portfolio frontier, the traditional DEA model and the improved DEA model. We show the convergence of the improved DEA model under the fuzzy framework. The simulation indicates that the improved DEA frontier is closer to the portfolio frontier than to the traditional DEA frontier. More importantly, we incorporate the diversification DEA model and improved DEA model to analyze the performance of China's open-end fund. The empirical results indicate that the improved DEA model not only provides a quicker way to assess the investment funds compared to the diversification DEA model but also makes up for the shortcoming of the traditional DEA model, which overestimates the fuzzy portfolio efficiency.