Data Envelopment Analysis

Abstract

Data envelopment analysis (DEA) is a data-oriented approach for performance evaluation and benchmarking when trade-offs on multiple performance measures and benchmarks are not completely available. There are relative efficiencies and inefficiencies in using DEA in classifying funds of hedge funds (FOF). FOFs provide absolute returns and have non-linear returns because of long-short positions, derivatives, and option-like fee contracts, resulting in significant skewness and kurtosis. Thus the inclusion of FOFs in investor portfolios calls for performance appraisal methodologies that are appropriate for handling the asymmetric returns they produce, such as DEA, and not comparison to traditional passive and active benchmarks. While selecting FOFs can be arduous, DEA can shed light on and further validate the process.