What Can Social Media Tell About IPO Performance in China?
38 Pages Posted: 26 Jan 2018
Date Written: January 25, 2018
Understanding whether retail investor opinions revealed on social media can predict stock performance is pivotal for financial investment. We adopt postings from a stock forum in China around the IPO period, utilizing a special setting to separate fundamental information from investor comments and exclude the effect of stock return. Moreover, we use the newest method to extract sentiment and attention: Word-to-Vector plus deep learning algorithm through multi-comparison. Our results illustrate that higher attention and bullishness relate with higher initial day and long-term returns. This relationship still holds when the stock return is measured by medium and long-term alpha. Besides, when attention and bullishness indices are higher, post-IPO turnover ratio, volatility and market capitalization are also higher. Finally, we find retail sentiment and attention are related with institutional investor divergence of opinions.
Keywords: IPO Performance, Retail Investor Sentiment, Retail Investors Attention, Social Media
JEL Classification: G02, G19
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