Value extracting in relative performance appraisal with network DEA: an application to U.S. equity mutual funds

In the mutual fund industry, beating a comparable benchmark index is an important criterion of mutual fund (MF) performance evaluation. Benchmarking MFs against peers also do receive considerable attention in MF performance appraisal literature. Evidence of data envelopment analysis (DEA) playing a big part here is increasing. DEA appraises performance in a multidimensional framework and can accommodate data from different sources and in different formats. A question that arise is how to extract information of value from data in DEA-based performance appraisal. This chapter discusses contribution of network DEA in MF performance appraisal in general and highlight that when MF management process is conceptualised as a network structure, it is possible to extract valuable information from MF specific data analogous to data mining in the case of big data. Information of value in this context aligns with the concept of value dimension in big data. MF performance appraisal studies that use DEA demonstrate how different types of network structures can reveal performance from different perspectives such as operational management, marketing and selling management, disbursements (cost, expenses and fees) management, and portfolio management. Network DEA models enable decomposition of overall management performance at individual sub-process levels. This is valuable information to MF managers to make effective decisions, as they are able to gauge how their MFs operate at sub-process levels from different overall management perspectives. This chapter highlights that information extracted through MF performance appraisal using network DEA is practical and such knowledge inspires solutions to MF management problems in the real world. Moreover, information extracted via such application is valuable to all stakeholders including MF investors to face up to many challenges in managed fund industry landscape.