Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/323299 
Year of Publication: 
2025
Citation: 
[Journal:] Annals of Operations Research [ISSN:] 1572-9338 [Volume:] 347 [Issue:] 3 [Publisher:] Springer US [Place:] New York [Year:] 2025 [Pages:] 1265-1309
Publisher: 
Springer US, New York
Abstract: 
Abstract We solve an expected utility-maximization problem with a Value-at-risk constraint on the terminal portfolio value in an incomplete financial market due to stochastic volatility. To derive the optimal investment strategy, we use the dynamic programming approach. We demonstrate that the value function in the constrained problem can be represented as the expected modified utility function of a vega-neutral financial derivative on the optimal terminal wealth in the unconstrained utility-maximization problem. Via the same financial derivative, the optimal wealth and the optimal investment strategy in the constrained problem are linked to the optimal wealth and the optimal investment strategy in the unconstrained problem. In numerical studies, we substantiate the impact of risk aversion levels and investment horizons on the optimal investment strategy. We observe a 20%relative difference between the constrained and unconstrained allocations for average parameters in a low-risk-aversion short-horizon setting.
Subjects: 
Portfolio optimization
Hamilton Jacobi Bellman equations
Utility maximization
Investment management
Stochastic volatility
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version
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