The impacts of investors' sentiments on stock returns using fintech approaches

Hao Fang, Chien-Ping Chung, Yang-Cheng Lu, Yen-Hsien Lee and Wen-Hao Wang

International Review of Financial Analysis, 2021, vol. 77, issue C

Abstract: This study uses fintech approaches, including web crawler technology with distributed architecture to select internet news messages largely and efficiently and a dictionary-based linguistic text mining to create sentiment variables, to explore the respective impacts of investors' optimism and pessimism on stock returns. The construction of sentiment variables in network- and dictionary-based messages is more precise and variable than that in traditional-based messages. Our results show that firms with investors' optimistic sentiments have significantly higher stock returns in the current month, whereas those with pessimistic sentiments have significantly opposite effects. The effect of both investors' optimism and pessimism on stock returns subsequently reverses. Then, the negative impacts of investors' largely pessimistic sentiments on stock returns are larger than the positive impacts of their largely optimistic sentiments within a quarter. Next, investors' optimistic sentiments significantly raise stock return volatility by approximately a quarter, but their pessimistic sentiments have the opposite effects. Furthermore, investors' high optimism more significantly and persistently raises stock return volatility than their general optimism, but the negative effects of their high pessimism on volatility become smaller and the persistence is shorter than general pessimism. In addition to the advantage of our methodology in creating sentiment variables, the simultaneous consideration of investors' optimism and pessimism to analyze the effects on the returns and the volatility of individual stocks in this study is more complete than previous related studies.

Keywords: Investors' sentiments; Stock returns; Fintech; Text mining; Web crawler (search for similar items in EconPapers)
JEL-codes: C21 C51 C61 G11 G14 G41 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521921001885
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:77:y:2021:i:c:s1057521921001885

DOI: 10.1016/j.irfa.2021.101858

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().