Stock Price Responses to Firm-Level News in Supply Chain Networks
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866912821730607104 |
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| author | Inoue, Hiroyasu Todo, Yasuyuki |
| author_facet | Inoue, Hiroyasu Todo, Yasuyuki |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_06255 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Stock Price Responses to Firm-Level News in Supply Chain Networks Inoue, Hiroyasu Todo, Yasuyuki Social and Information Networks Machine Learning 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. |
| title | Stock Price Responses to Firm-Level News in Supply Chain Networks |
| topic | Social and Information Networks Machine Learning |
| url | https://arxiv.org/abs/2409.06255 |