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Abstract
This study uses data envelopment analysis (DEA) to measure the relative efficiency of 257 Australian mutual funds, and logistic regression to examine the dependence of efficiency on fund attributes, management strategy and the operating environment. The sensitivity of DEA efficiency to various input-output variable combinations is investigated. More funds show up efficient when DEA captures fund's long-term growth and income distribution than a shorter time horizon. DEA ranking of funds, however, is independent of the time horizon used. Fund's efficiency depends, to a large extent, on the 'asset allocation score' that we construct from the fund's wealth distribution to various asset classes. In general, the overall technical efficiency and the scale efficiency are higher for risk-aversive funds with high positive net flow of assets.
Keywords: Australian mutual funds, efficiency, data envelopment analysis, sensitivity analysis
1. Introduction
Measuring and comparing the performance of mutual, trust and superannuation funds have become an important issue for managers and investors alike in the finance industry, and hence there is a pressing need for a credible measure for assessing and ranking the performance of these managed funds. The responsibilities of investment managers are enormous, and their potential rewards are great. In order to reward management for good performance, it is necessary to be able to recognize it. Moreover, the past four decades have witnessed proliferation of managed funds, international diversifications to reduce various market risks, and attractiveness to many investors around the globe. Since the important work of Sharp (1964, 1966), Treyner (1965) and Jensen (1968, 1969), numerous studies have been concerned with measuring performance in two dimensions, risk and return, mainly using the Capital Asset Pricing Model (CAPM). The results of these studies appear to depend, to a large extent, on the bench mark portfolio used and the measurement of risk, and the main criticism made on the use of CAPM is the validity of its underlying assumptions; see the survey article by Shukla and Trzcinka (1992) for details. Since then, numerous performance measures have been suggested (Modigliani and Modigliani, 1997). In addition, organisations such as Morningstar Incorporated and Lipper Analytical Services in the US and ASSIRT Pty Ltd in Australia have developed their own fund performance measures due to increasing demand in the financial...