Mutual fund performance evaluation using data envelopment analysis with new risk measures

The data envelopment analysis (DEA) technique has been found very useful for evaluating the mutual fund performance. This applied study extends previous results in two ways: to properly reflect the pervasive skewness and leptokurtosis in return distributions of actively managed funds, new risk measures value-at-risk (VaR) and conditional value-at-risk (CVaR) are introduced into inputs of the existing DEA models; to fairly evaluate the relative performance of the same fund during different time periods, we creatively treat the same fund during different periods as different decision making units. Except for confirming current empirical conclusions, detailed empirical analyses using data of the Chinese mutual fund market show that, VaR and CVaR, especially their combinations with traditional risk measures, are very helpful for comprehensively describing return distribution properties and fund characteristics such as the asset allocation structure, which, in turn, can better evaluate the overall performance of mutual funds. Treating the same fund during different time periods as different funds can not only show the specific performance variation, but reveal the reasons for that variation.