Social Media Sentiment and IPO Pricing

Ye Xian
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引用次数: 1

Abstract

This study attempts to examine the impact of social media attention and sentiment on IPO pricing. Specifically, by using social media sentiment as a proxy for retail investors’ valuation, I attempt to examine the theoretical predictions in prior studies (Ljungqvist, Nanda and Sigh (2006), Cornelli, Goldreich, and Ljungqvist (2006), and Derrien (2005)) that overoptimism of sentiment investors leads to initial overpricing of IPO followed by long-term reversal. Using posts on Stocktwits during pre-IPO period, I have constructed measurements of investor attention and sentiment. The empiri- cal results are generally consistent with the theoretical predictions that retail investor overoptimism leads to higher IPO first day price run up and worse long-term perfor- mance. Additionally, using machine learning techniques to classify untagged posts, I have found similar results when sentiment measures are constructed by classified un- tagged posts. Results with sentiment measures constructed by these classified posts imply that more optimistic sentiment leads to a higher turnover rate shortly after IPO, indicating that informed investors are selling overpriced IPO shares to sentiment retail investors.
社交媒体人气与IPO定价
本研究试图考察社交媒体关注度和情绪对IPO定价的影响。具体而言,通过使用社交媒体情绪作为散户投资者估值的代理,我试图检验先前研究中的理论预测(Ljungqvist, Nanda and Sigh (2006), Cornelli, Goldreich, and Ljungqvist(2006)和Derrien(2005)),即情绪投资者的过度乐观导致IPO初始定价过高,随后长期反转。利用ipo前Stocktwits上的帖子,我构建了投资者注意力和情绪的衡量标准。实证结果与理论预测基本一致,即散户投资者过度乐观导致IPO首日价格上涨,长期业绩恶化。此外,使用机器学习技术对未标记的帖子进行分类,当由分类的未标记帖子构建情感度量时,我发现了类似的结果。利用这些分类帖子构建的情绪测度的结果表明,更乐观的情绪导致IPO后不久的换手率更高,表明知情的投资者正在将定价过高的IPO股票出售给情绪散户投资者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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