ABSTRACT
We analyze President Trump’s Twitter posts on the COVID-19 pandemic to quantitatively construct his sentiment proxy to examine its predictive power in industry-level equity returns. With the growing influence of social media, some “special” people have been able to use their celebrity status for wielding significant market influence, thereby causing a new modern crisis. This study parsed words from 2,574 tweets from President Trump’s Twitter account to explore the predictive power of his sentiments on the US market during the pandemic. After controlling for rigorous factors, result shows that an industry-level negative tone in general content is unlikely to be predictive of stock returns. Furthermore, the consumer goods industry exhibited a negative return when Trump displayed a negative attitude toward the pandemic. Industries adversely affected by the pandemic because of travel restrictions, consumption shocks, and public health issues are statistically correlated with Trump’s negative tone on the pandemic.
ABSTRACT
Purpose: This paper aims to use the Covid-19 pandemic situation to conduct an experiment-like study that focuses on industry reactions under stress. Particularly, this study analyzes stock response to eight pandemic related news in 2020 across different industries. This study also investigates the role that the market risk, beta, plays in such stock reactions. Design/methodology/approach: This study computes the cumulative abnormal returns (CAR) around COVID-19 events using adjusted daily stock returns of all stocks in the S&P 500 index between January 2, 2020 and December 31, 2020. This study also sorts all stocks by beta into quintiles and measures the CAR [0, +3] for each quintile around each event date. Findings: This study finds that low beta portfolios exhibit greater abnormal returns (in absolute value) than high beta portfolios during down markets while high beta portfolios exhibit greater abnormal returns (in absolute values) when the market starts to recover. However, this study finds that beta does not seem to explain the abnormal returns reported in various industries during times of negative sentiment. During times of positive sentiment, both the beta effect and industry effect are present. Originality/value: Extant literature almost unanimously concurs that the COVID-19 pandemic has brought about negative stock reactions to financial markets across the globe. Nevertheless, three interrelated issues have not been explored: market reactions during the subsequent recovery, industry heterogeneity and individual stocks’ risk profile. The study addresses these matters. © 2022, Emerald Publishing Limited.
ABSTRACT
During the ongoing COVID-19 pandemic in the US, there has been considerable media attention regarding several US legislators who traded stocks in late January through February 2020. The concern is that these legislators traded in anticipation of COVID-19 having a major impact on the financial markets, while publicly suggesting otherwise. We consider whether these legislator trades were in a time window, and of a nature, that would be consistent with trading ahead of the market. Towards this end, we assess the reactions of US industries to sudden COVID-related news announcements, concomitantly with an analysis of levels of investor attention to COVID. Results suggest that, at an industry-level, for legislator trading to be "ahead of the market" it needed to have been done prior to February 26, and involving the 15 industries we identify as having abnormal returns, especially medical and pharmaceutical products (positive); restaurants, hotels, and motels (negative); as well as services and utilities. These criteria are met by many of the legislator trades. Our results help to both parameterize concerns about this case of legislator trading; as well as provide insight into the reactions and expectations of investors toward COVID-19.