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Replicating Hedge Fund Indices with Optimization Heuristics

  • Manfred GILLI

    (University of Geneva and Swiss Finance Institute)

  • Enrico SCHUMANN

    (University of Geneva)

  • Gerda CABEJ

    (University of Geneva)

  • Jonela LULA

    (University of Geneva)

Hedge funds offer desirable risk-return profiles; but we also find high management fees, lack of transparency and worse, very limited liquidity (they are often closed to new investors and disinvestment fees can be prohibitive). This creates an incentive to replicate the attractive features of hedge funds using liquid assets. We investigate this replication problem using monthly data of CS Tremont for the period of 1999 to 2009. Our model uses historical observations and combines tracking accuracy, excess return, and portfolio correlation with the index and the market. Performance is evaluated considering empirical distributions of excess return, final wealth and correlations of the portfolio with the index and the market. The distributions are compiled from a set of portfolio trajectories computed by a resampling procedure. The nonconvex optimization problem arising from our model specification is solved with a heuristic optimization technique. Our preliminary results are encouraging as we can track the indices accurately and enhance performance (e.g. have lower correlation with equity markets).

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File URL: http://ssrn.com/abstract=1623735
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Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 10-22.

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Length: 16 pages
Date of creation: Jun 2010
Date of revision:
Handle: RePEc:chf:rpseri:rp1022
Contact details of provider: Web page: http://www.SwissFinanceInstitute.ch

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