Abstract
The use of quantitative tools to analyse the huge amount of qualitative information has been acquiring increasing importance. Market participants and, of course, Central Banks have been involved in this trend. The vast majority of qualitative data can be qualified as non-structured and refers mainly to news, reports or another kind of texts. Its transformation into structured data can improve the availability of information and hence, decision making. This article applies sentiment analysis tools to text data in order to quantify the impact of COVID-19 on the analysts’ opinions. Using this methodology, it is possible to transform qualitative non-structured data into a quantitative index that can be used to compare reports from different periods and countries. The results show the pandemic worsens banking sentiment in Europe, which coincides with higher uncertainty in the stock market. There are also regional differences in the decline in sentiment as well as higher divergence is observed across opinions.
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