Deep Reinforcement Learning for Robust Goal-Based Wealth Management

Tessa Bauman, Bruno Ga\v{s}perov, Stjepan Begu\v{s}i\'c and Zvonko Kostanj\v{c}ar

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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.

Date: 2023-07
New Economics Papers: this item is included in nep-big and nep-cmp
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