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arXiv · 2506.10103

S-shaped Utility Maximization with VaR Constraint and Partial Information

Dongmei Zhu·Ashley Davey·Harry Zheng
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Abstract

We study S-shaped utility maximisation with VaR constraint and unobservable drift coefficient. Using the Bayesian filter, the concavification principle, and the change of measure, we give a semi-closed integral representation for the dual value function and find a critical wealth level that determines if the constrained problem admits a unique optimal solution and Lagrange multiplier or is infeasible. We also propose three algorithms (Lagrange, simulation, deep neural network) to solve the problem and compare their performances with numerical examples.

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Dongmei Zhu, Ashley Davey, Harry Zheng. 2025-06-11. S-shaped Utility Maximization with VaR Constraint and Partial Information. https://arxiv.org/abs/2506.10103

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