Abstract
This paper explores a linear hedge fund replication and alternative beta methodology that is robust to the presence of non linearities and the possibility of model mis-specification. In a fashion similar to Roncalli and Weisang (2009a), the problem is cast as a tracking problem in order to allow for a dynamic treatment of the replication problem. In a quasi-experiment, using simulations, I explore the robustness of the methodology, and develop a statistic that helps in detecting the introduction of unmodeled components in hedge fund portfolios. Finally, the methodology is applied to a set of hedge fund indices.
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