Global Business Networks

• 成果类型: Article
• 署名作者: Breitung, Christian; Mueller, Sebastian
• 署名单位: Technical University of Munich
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2025.104007
• 发表日期: 2025
• 关键词: Business network; Textual analysis; Natural Language Processing; GPT-3; Large language models

摘要

We leverage the capabilities of GPT-3 to generate historical business descriptions for over 63,000 global firms. Utilizing these descriptions and advanced embedding models from OpenAI, we construct time-varying business networks that represent business links across the globe. We showcase the performance of these networks by studying the lead-lag effect for global stocks and predicting target firms in M&A deals. We demonstrate how masking firm-specific details can mitigate look-ahead bias concerns that may arise from the use of embedding models with a recent knowledge cutoff, and how to differentiate between competitor, supplier, and customer links by fine-tuning an open-source language model.