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• W3090852952 abstract "We study a utility maximization problem in a financial market with a stochastic drift process, combining a worst-case approach with filtering techniques. Drift processes are difficult to estimate from asset prices, and at the same time optimal strategies in portfolio optimization problems depend crucially on the drift. We approach this problem by setting up a worst-case optimization problem with a time-dependent uncertainty set for the drift. Investors assume that the worst possible drift process with values in the uncertainty set will occur. This leads to local optimization problems, and the resulting optimal strategy needs to be updated continuously in time. We prove a minimax theorem for the local optimization problems and derive the optimal strategy. Further, we show how an ellipsoidal uncertainty set can be defined based on filtering techniques and demonstrate that investors need to choose a robust strategy to be able to profit from additional information." @default.
• W3090852952 created "2020-10-08" @default.
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• W3090852952 date "2020-09-30" @default.
• W3090852952 modified "2023-09-27" @default.
• W3090852952 title "Robust Utility Maximization in a Multivariate Financial Market with Stochastic Drift" @default.
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• W3090852952 hasPublicationYear "2020" @default.
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