This paper investigates the role of textual information in a U.S. bank merger prediction task. Our intuition behind this approach is that text could reduce bank opacity and allow us to understand better the strategic options of banking firms. We retrieve textual information from bank annual...

In this paper, we use the sentiment of annual reports to gauge the likelihood of a bank to participate in a merger transaction. We conduct our analysis on a sample of annual reports of listed U.S. banks over the period 1997 to 2015, using the Loughran and McDonald's lists of positive and...

In this study, we employ the COVID-19 Twitter sentiment of seven countries to examine the stock market indexes. We conduct our analysis on a sample of 1,616,007 tweets over the period January to June 2021. We process the tweets based on the VADER analyzer, thereby producing both positive and...