 Stock return predictability and investor sentiment: A high-frequency perspectiveLicheng Sun, Mohammad Najand and Jiancheng Shen Journal of Banking & Finance, 2016, vol. 73, issue C, 147-164 Abstract: We explore the predictive relation between high-frequency investor sentiment and stock market returns. Our results are based on a proprietary dataset of high-frequency investor sentiment, which is computed based on a comprehensive textual analysis of sources from news wires, internet news sources, and social media. We find substantial evidence that intraday S&P 500 index returns are predictable using lagged half-hour investor sentiment. The predictive power is also found in other stock and bond index ETFs. We document that this sentiment effect is independent of the intraday momentum effect, which is based on lagged half-hour returns. While the intraday momentum effect only exists in the last half hour, the sentiment effect persists in at least the last two hours of a trading day. From an investment perspective, high-frequency investor sentiment also appears to have significant economic value when evaluated with market timing trading strategies. We find evidence that the return predictability is most likely driven by the trading activities of noise traders. Keywords: Intraday; Investor sentiment; High frequency; Stock return predictability; Noise trading (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:jbfina:v:73:y:2016:i:c:p:147-164 DOI: 10.1016/j.jbankfin.2016.09.010 Access Statistics for this article Journal of Banking & Finance is currently edited by Ike Mathur More articles in Journal of Banking & Finance from Elsevier |
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