用生成模型模拟分析师决策，提升投资预测能力
Distilling Analysis from Generative Models for Investment Decisions
- 设计A3数据集模拟专业投资者决策流程
- 链式决策框架显著提升交易行为预测准确率
- 适合金融AI、量化研究者参考
专业人士的决策在各领域具有决定性影响，例如政治家决策关乎国运，股票分析师决策影响市场走势。为建模金融市场的专业决策过程，我们提出三项新任务，并构建了名为A3的新数据集以模拟专业人士的决策行为。尽管现有模型在预测专业人员行为方面仍存挑战，尤其在交易决策上表现不足，但所提出的链式决策（Chain-of-Decision）方法通过引入循环意见生成器，基于每条新闻内容生成主观分析，显著提升了任务性能。
原文摘要 · Abstract (English)
Professionals' decisions are the focus of every field. For example, politicians' decisions will influence the future of the country, and stock analysts' decisions will impact the market. Recognizing the influential role of professionals' perspectives, inclinations, and actions in shaping decision-making processes and future trends across multiple fields, we propose three tasks for modeling these decisions in the financial market. To facilitate this, we introduce a novel dataset, A3, designed to simulate professionals' decision-making processes. While we find current models present challenges in forecasting professionals' behaviors, particularly in making trading decisions, the proposed Chain-of-Decision approach demonstrates promising improvements. It integrates an opinion-generator-in-the-loop to provide subjective analysis based on each news item, further enhancing the proposed tasks' performance.
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