This study examines how positive and negative news about firms are associated with stock prices and whether these associations extend to suppliers and clients linked via supply chain relationships, using large samples of publicly listed firms worldwide and in Japan. News sentiment is measured using FinBERT, a natural language processing model fine-tuned for financial text, and supply chain links are identified from financial statements for global firms and from large-scale firm-level surveys for Japanese firms. We find that stock prices exhibit systematic associations with positive and negative news even before public disclosure. These associations are also observed for suppliers and clients before and after disclosure. In general, post-disclosure associations are larger than pre-disclosure associations, with the difference concentrated around the time of public news disclosure relative to the pre-disclosure period. However, for Japanese firms, the post-disclosure associations for suppliers and clients are smaller than the pre-disclosure associations, in contrast to the pattern observed for firms outside Japan.

翻译：本研究利用全球及日本上市企业的大样本数据，探讨了企业正面与负面新闻如何与股价相关联，以及这种关联是否通过供应链关系延伸至供应商和客户。新闻情感通过FinBERT（一种针对金融文本微调的自然语言处理模型）进行度量，全球企业的供应链关系从财务报表中识别，日本企业的供应链关系则通过大规模企业层面调查获取。研究发现，即使在公开披露之前，股价与正面及负面新闻已呈现系统性关联。这种关联在供应商与客户之间于披露前后同样存在。总体而言，披露后的关联强度大于披露前，且差异主要集中在公开新闻披露时点附近（相较于披露前阶段）。然而对于日本企业，供应商与客户的披露后关联强度弱于披露前关联，这与日本以外企业所呈现的模式形成鲜明对比。