通过文本主题相似性发现公司间联系:金融市场中的常量分析

Zhiyu Zhang, Zheng Qiao, Yao Ge, Zhe Shen
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引用次数: 0

摘要

我们采用无监督主题建模方法,根据从《管理层讨论与分析》文本中提取的各种主题,构建了一种跨公司相似性度量方法。我们的研究结果表明,文本主题相似的公司的回报率可以预测重点公司未来的股票回报率。在此基础上构建的多空投资组合产生了 17.03% 的年化阿尔法。进一步的分析表明,对于投资者关注度有限和套利受限的股票,收益预测性更强。此外,我们的文本关联测量也能预测未来的盈利意外。总体而言,信息吸收迟缓导致的错误定价是收益可预测性的一个潜在解释。
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Uncovering interfirm links through textual topic similarity: A comomentum analysis in financial markets
Using an unsupervised topic modelling methodology, we construct a cross-firm similarity measure based on the various topics extracted from Management Discussion and Analysis texts. Our findings indicate that the returns of firms with similar textual topics predict the focal firms’ future stock returns. A long-short portfolio constructed on this basis yields an annualised alpha of 17.03%. Further analyses show that the return predictability is stronger for stocks subject to limited investor attention and limits to arbitrage. Additionally, our textual linkage measure can also predict future earnings surprises. Overall, mispricing due to sluggish information incorporation acts as a potential explanation for return predictability.
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