<ul><li>A new framework leveraging Large Language Models (LLMs) and multi-agent architectures has been proposed for quantitative stock investment in portfolio management and alpha mining.</li><li>The framework incorporates LLMs to generate diversified alphas and utilizes a multi-agent approach to dynamically evaluate market conditions.</li><li>The first module of the framework extracts predictive signals by analyzing numerical data, research papers, and visual charts.</li><li>Extensive experiments on the Chinese stock markets demonstrate that this framework outperforms state-of-the-art baselines, highlighting the potential of AI-driven approaches in enhancing quantitative investment strategies.</li></ul>

Automate Strategy Finding with LLM in Quant Investment

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