 Social forecasting: Online social opinion and the cross-section of stock returnsKaibin Yuan, Yuheng Liang and Mengnan Zhu Pacific-Basin Finance Journal, 2024, vol. 86, issue C Abstract: We construct a monthly measure for online social opinions on stocks in the Chinese market by extracting textual data from the internet. By implementing a “social forecasting” strategy, we find a significantly positive alpha of 0.544% per month based on the model of Fama-French's (2015) five-factor plus Carhart's (1997) momentum, and 0.636% per month based on Liu et al.'s (2018) Chinese four-factor model. This anomaly is driven by the mispricing of underexplored information since online social opinions are a strong predictor of firms' earning surprise and are strengthened when there are information frictions, such as low investor attention, high arbitrage costs, high proportions of sentiment-driven trades, and low percentages of institutional investors. Our results are robust to a series of tests and remain unchanged after taking the “factor zoo” into consideration. Keywords: Factor model; Anomalies; Online social opinions; Underexplored information (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:pacfin:v:86:y:2024:i:c:s0927538x24001525 DOI: 10.1016/j.pacfin.2024.102401 Access Statistics for this article Pacific-Basin Finance Journal is currently edited by K. Chan and S. Ghon Rhee More articles in Pacific-Basin Finance Journal from Elsevier |
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