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- W63673150 abstract "Classical methods of portfolio optimization are inadequate for the optimization of hedge fund portfolios. For hedge fund portfolios, investors have different and much more diversified preferences. Reflecting hedge fund investors' specific concerns is much more important for this asset class. Classical approaches typically impose their own definitions of preferences and risk perception, optimizing toward a target that is ignorant of investors' specific situations and risk aversion. In addition, given the non-linear and non-homogeneous dependence of hedge funds on markets, neither pure historic data nor data generated by empirical distributions are adequate bases for an optimization. This article proposes a method that takes investor preferences as the starting point to define an objective function that will be flexible enough to include general investor preferences. In particular, we can include path- and market-dependent objectives. We use a heuristic search algorithm to solve the optimization problem. The article also develops a method to produce a forward-looking data set on which the optimization can be based. It is also particularly apt for a case when a portfolio of hedge funds is used as an overlay. We compare this approach to classical optimizations on empirical data to highlight the effects of the additional degrees of freedom we have included." @default.
- W63673150 created "2016-06-24" @default.
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- W63673150 date "2006-01-23" @default.
- W63673150 modified "2023-09-25" @default.
- W63673150 title "Investor's Choice: An Investor-Driven, Forward-Looking Optimization Approach to Fund of Hedge Fund Construction" @default.
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- W63673150 hasPublicationYear "2006" @default.
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