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Abstract:
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As hedge fund replication based on factor models has encountered growing interest among professionals and academics, it faced many critics. In this paper, we consider three of the main critiques, namely lack of reactivity of hedge fund replication and its deficiency in capturing tactical allocations; its failure to apprehend non-linear positions and the higher moments of hedge fund returns; and, finally, lack of access to the alpha of hedge funds. To address these problems, we consider hedge fund replication as a general tracking problem which may be solved by means of Bayesian filters. Our results show that, while capturing nonlinearities remains a difficult endeavor, careful implementation of Bayesian filters and a core/satellite approach to HF replication provide answers to the reactivity problem and access to the hedge fund alpha. From there, we consider future research directions.
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