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This work considers the optimal portfolio problem of Merton in the context of an uncertain financial market composed of two types of assets. The Hamilton-Jacobi-Bellman equation associated with this type of problem is posed, and it is shown how physics-informed neural networks (PINNs) can be implemented to find its solution.

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Neural Networks Informed by Physics Applied to Solving an Optimal Investment-Consumption Problem

  • 会议论文

  • 发表日期：

    2025年

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  • John Freddy Moreno Trujillo

摘要

This work considers the optimal portfolio problem of Merton in the context of an uncertain financial market composed of two types of assets. The Hamilton-Jacobi-Bellman equation associated with this type of problem is posed, and it is shown how physics-informed neural networks (PINNs) can be implemented to find its solution.