DEA Frontier Improvement and Portfolio Rebalancing: An Application of China Mutual Funds on Considering Sustainability Information Disclosure

Data envelopment Analysis (DEA) has been a widely used methodology for evaluating the relative performance of portfolios. Extensive work has appeared for realizing the role of DEA in the aspect of assessing portfolio performance and deriving the relative rankings. However, the role of providing realizable benchmarks is not fully explored in the existing literatures. Most importantly, the DEA-based portfolio performance evaluation methods developed in the existing literatures can hardly provide support for fund managers in pursuing sustainability performance. In this paper, we first propose a DEA frontier improvement approach under the mean-variance framework. This approach provides investor with a rebalancing strategy as well as an improved DEA frontier which approximates the portfolio efficient frontier better than the traditional DEA model does. Then, this approach is extended to a general return-risk framework. Our in-sample simulation results verify the effectiveness of the proposed approach for a wide range of applications. In addition, the out-of-sample tests show that the rebalancing investment strategies can achieve higher Sharpe ratios and Sortino ratios than those of the original ones. Finally, we apply the proposed approach to evaluate mutual fund performance in China with the consideration of sustainability information disclosure. We construct a disclosure index to indicate the extent of sustainable information disclosure of each mutual fund. The results show that the proposed approach provides not only investment recommendations, but also references for constructing sustainable green funds.