用AI模仿投资大师估值，实现可验证的长期自动投资
DBOT: Artificial Intelligence for Systematic Long-Term Investing
- 基于达摩达兰的海量估值数据训练AI，模拟其估值逻辑
- 可对任意上市公司估值，并支持回测验证性能
- 适合金融研究者与量化投资者参考AI在估值中的角色
长期投资传统上依赖人类判断。随着生成式人工智能的发展，自动化系统化长期投资成为可能。本文提出DBOT系统，其目标是像阿萨斯·达摩达兰那样进行估值——达摩达兰是投资领域罕见的专家，曾发表数千份公司估值报告，并撰写大量相关著作，为AI系统提供了丰富的训练数据。DBOT能够对任何公开交易的公司进行估值，且具备回测能力，使其行为与表现可被科学检验。我们对比了DBOT与其分析原型达摩达兰，指出将当前能力提升至达摩达兰水平所面临的科研挑战。最后，探讨了类似DBOT的AI代理对金融行业的影响，特别是其如何改变人类分析师在估值中的角色。
原文摘要 · Abstract (English)
Long-term investing was previously seen as requiring human judgment. With the advent of generative artificial intelligence (AI) systems, automated systematic long-term investing is now feasible. In this paper, we present DBOT, a system whose goal is to reason about valuation like Aswath Damodaran, who is a unique expert in the investment arena in terms of having published thousands of valuations on companies in addition to his numerous writings on the topic, which provide ready training data for an AI system. DBOT can value any publicly traded company. DBOT can also be back-tested, making its behavior and performance amenable to scientific inquiry. We compare DBOT to its analytic parent, Damodaran, and highlight the research challenges involved in raising its current capability to that of Damodaran's. Finally, we examine the implications of DBOT-like AI agents for the financial industry, especially how they will impact the role of human analysts in valuation.
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