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Deep Reinforcement Learning for Robust Goal-Based Wealth Management

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  • Tessa Bauman
  • Bruno Gav{s}perov
  • Stjepan Beguv{s}i'c
  • Zvonko Kostanjv{c}ar

Abstract

Goal-based investing is an approach to wealth management that prioritizes achieving specific financial goals. It is naturally formulated as a sequential decision-making problem as it requires choosing the appropriate investment until a goal is achieved. Consequently, reinforcement learning, a machine learning technique appropriate for sequential decision-making, offers a promising path for optimizing these investment strategies. In this paper, a novel approach for robust goal-based wealth management based on deep reinforcement learning is proposed. The experimental results indicate its superiority over several goal-based wealth management benchmarks on both simulated and historical market data.

Suggested Citation

  • Tessa Bauman & Bruno Gav{s}perov & Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar, 2023. "Deep Reinforcement Learning for Robust Goal-Based Wealth Management," Papers 2307.13501, arXiv.org.
    • Handle: RePEc:arx:papers:2307.13501
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    References listed on IDEAS

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