This working paper series is intended to facilitate discussion and encourage the exchange of ideas. Inclusion here does not preclude publication elsewhere. It is the original work of the author(s) and subject to copyright regulations. encouraging creative research

This article builds off the summary of research provided by Edwards and Gaon [2003]. The authors describe: … the structure and operation of the hedge fund industry, the various investment strategies pursued by hedge funds, [and] what we know about the returns and overall performance of hedge funds …” The authors conclude that while there is some evidence that hedge funds may be able to generate excess returns, this conclusion needs to be confirmed with more refined techniques for evaluating hedge fund performance and with better data. It would appear then that any conclusions on hedge funds are still uncomfortably tentative. With that caveat in mind, we will review both academic and practitioner research from the standpoint of a hypothetical institutional investor who is looking into whether hedge funds make sense for their portfolio. 1 Discomfort with MPT After the dramatic losses in the equity markets during the past three years, there has been a struggle to understand how hedge funds, with their promise of absolute returns, might

The advisory service marketing recommendations used in this research represent the best efforts of the AgMAS Project staff to accurately and fairly interpret the information made available by each advisory service. In cases where a recommendation is vague or unclear, some judgment is exercised as to whether or not to include that particular recommendation or how to implement the recommendation. Given that some recommendations are subject to interpretation, the possibility is acknowledged that the AgMAS track record of recommendations for a given program may differ from that stated by the advisory service, or from that recorded by another subscriber. In addition, the net advisory prices presented in this report may differ substantially from those computed by an advisory service or another subscriber due to differences in simulation assumptions, particularly with respect to the geographic location of production, cash and forward contract prices, expected and actual yields, storage charges and government programs. This material is based upon work supported by the Cooperative State Research, Education and Extension Service, U.S. Department of Agriculture, under Project Nos. 98-EXCA-3-0606 and 00-52101-9626. Any opinions, findings, conclusions, or recommendations expressed in this

Over the recent past, stylized facts have not yielded a synthesis regarding the predictability of returns for alternative investment assets such as hedge funds. Recent studies on alternative asset return predictability have added to the ambiguity. These studies suggest that classification prediction methods may dominate more traditional return-level prediction methodology. This paper examines the predictive accuracy of three alternate radial basis function neural networks when applied to the returns of thirteen Credit Swiss First Boston/Tremont (CSFB) hedge fund indices. We provide evidence that the Kajiji-4 RBF neural network dominates within the RBF topology in the prediction of hedge fund returns by both level and classification. The results also show that the Kajiji-4 method is capable of near perfect directional prediction.