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- W3124920486 abstract "In this paper, we study the mean-variance portfolio selection problem under partial information with drift uncertainty. First we show that the market model is complete even in this case while the information is not complete and the drift is uncertain. Then, the optimal strategy based on partial information is derived, which reduces to solving a related backward stochastic differential equation (BSDE). Finally, we propose an efficient numerical scheme to approximate the optimal portfolio that is the solution of the BSDE mentioned above. Malliavin calculus and the particle representation play important roles in this scheme." @default.
- W3124920486 created "2021-02-01" @default.
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- W3124920486 date "2019-01-10" @default.
- W3124920486 modified "2023-10-18" @default.
- W3124920486 title "Mean-variance portfolio selection under partial information with drift uncertainty" @default.
- W3124920486 doi "https://doi.org/10.48550/arxiv.1901.03030" @default.
- W3124920486 hasPublicationYear "2019" @default.
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