Textual Analysis by Hedge Funds

• 成果类型: Article; Early Access
• 署名作者: Zeng, Sipeng; Zhou, Kuo
• 署名单位: Chinese Academy of Sciences; University of Science & Technology of China, CAS; Jilin University
• 刊物名称: JOURNAL OF ACCOUNTING RESEARCH
• ISSN/ISSBN: 0021-8456; 1475-679X
• DOI: 10.1111/1475-679x.70074
• 发表日期: 2026-06-09
• 关键词: TEXTUAL ANALYSIS; HEDGE FUND; annual report; performance; RISK; INFORMATION; Sentiment; return

摘要

Combining hedge funds' quarterly position information with their access records on the SEC's EDGAR server, we explore whether hedge funds proactively gather and analyze textual information in 10-K filings related to their stock holdings, and how these behaviors affect their positions. We find that hedge funds adjust their positions according to the textual information in the annual reports they download. Meanwhile, analyzing these reports helps them to generate excess returns. Overall, our evidence suggests that the textual content of annual reports contains crucial company insights, prompting a subset of hedge funds that engage in bulk downloads from the SEC's website to trade based on diligent analysis of 10-K filings.