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Mean-variance portfolio selection under partial information with drift uncertainty. (arXiv:1901.03030v2 [q-fin.PM] UPDATED)

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This paper studies a mean-variance portfolio selection problem under partial information with drift uncertainty. It is proved that all the contingent claims in this model are attainable in the sense of Xiong and Zhou. Further, we propose a numerical scheme to approximate the optimal portfolio. Malliavin calculus and the strong law of large numbers play important roles in this scheme.


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