Abstract-The emergence of big data analytics enables real time news analysis. Such analysis offers the possibility to instantly extract the sentiment conveyed by any newly published, textual information source. This paper investigates the existence of a causal relationship between news sentiment and stock prices. As such, we apply news sentiment analysis for unstructured, textual data to extract sentiment scores and utilize the Granger-causality test to determine the causal relationship between daily news sentiment scores and the corresponding stock market returns. Upon successfully identifying such a causal relationship with a time lag, we develop a real-time news sentiment index. This news sentiment index serves as a decision-support system in detecting a potential over-or undervaluation of stock prices given the news sentiment of available news sources. Thus, as a novelty, the news sentiment index serves as an early-warning system to detect irrational exuberance.
Companies issuing stocks through an initial public offering (IPO) are obligated to publish relevant information as part of a prospectus. Besides quantitative figures from accounting, this document also contains qualitative information in the form of text. In this chapter, we analyze how sentiment in the prospectus influences future stock returns. In addition, we investigate the impact of pre-IPO sentiment in financial announcements on first-day returns. The results of our empirical analyses using 572 IPOs from US companies suggest a negative link between words linked to uncertainty and future stock market returns for up to 10 trading days. Conversely, we find that uncertainty expressed in pre-IPO announcements is positively linked to first-day stock returns. These insights have implications for research on IPOs by demonstrating that future stock returns are also driven by textual information from the prospectus and assist investors in placing their orders.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.