Big Data

Fund-Of-Funds Construction

Download Now Date Added: Sep 2009
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Fund-of-Funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. The authors analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical techniques. In particular, at a given point in time, they determine which funds significantly outperform a given benchmark while, crucially, accounting for the fact that a large number of funds are examined at the same time. This is achieved by employing so-called multiple testing methods. Then, the equal-weighted or the global minimum variance portfolio of the outperforming funds is held for one year, after which the selection process is repeated.