LLM-based Personalized Portfolio Recommender: Integrating Large Language Models and Reinforcement Learning for Intelligent Investment Strategy Optimization

• URL: http://arxiv.org/abs/2512.12922v1
• Date: Mon, 15 Dec 2025 02:12:53 GMT
• Title: LLM-based Personalized Portfolio Recommender: Integrating Large Language Models and Reinforcement Learning for Intelligent Investment Strategy Optimization
• Authors: Bangyu Li, Boping Gu, Ziyang Ding,
• Abstract summary: This paper introduces the LLM-based Personalized Portfolio Recommender.<n>The framework combines Large Language Models, reinforcement learning, and individualized risk preference modeling to support intelligent investment decision-making.
• Score: 0.08496348835248901
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In modern financial markets, investors increasingly seek personalized and adaptive portfolio strategies that reflect their individual risk preferences and respond to dynamic market conditions. Traditional rule-based or static optimization approaches often fail to capture the nonlinear interactions among investor behavior, market volatility, and evolving financial objectives. To address these limitations, this paper introduces the LLM-based Personalized Portfolio Recommender , an integrated framework that combines Large Language Models, reinforcement learning, and individualized risk preference modeling to support intelligent investment decision-making.

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