Stock Price Responses to Firm-Level News in Supply Chain Networks

TL;DR

This paper investigates how firm-level news sentiment impacts stock prices and extends to supply chain partners, revealing pre- and post-disclosure effects with regional differences in Japan.

Contribution

It introduces a large-scale analysis of supply chain effects on stock prices using NLP sentiment analysis and firm network data across global and Japanese firms.

Findings

Stock prices are systematically affected by news sentiment before public disclosure.

Supply chain partners' stock prices are influenced by firm news both before and after disclosure.

Post-disclosure effects are generally larger outside Japan, but smaller for Japanese firms.

Abstract

This study examines how positive and negative news about firms is associated with stock prices and whether these associations extend to firms' suppliers and clients connected through 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 texts, 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, relative to the pre-disclosure period, post-disclosure associations are larger, with the difference concentrated around the time of public news disclosure. 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.