We use the text of financial stability reports (FSRs) published by central banks to analyze the relation between the sentiment they convey and the financial cycle. We construct a dictionary tailored specifically to a financial stability context, which classifies words as positive or negative based on the sentiment they convey in FSRs. With this dictionary, we construct financial stability sentiment (FSS) indexes for thirty countries between 2005 and 2017. We find that central banks’ financial stability communications are mostly driven by developments in the banking sector. Moreover, the sentiment captured by the FSS index explains movements in financial cycle indicators related to credit, asset prices, systemic risk, and monetary policy rates. Finally, our results show that the sentiment in central banks’ communications is a useful predictor of banking crises—a one percentage point increase in FSS is followed by a twenty-nine percentage point increase in the probability of a crisis.

Using the text of financial stability reports (FSRs) published by central banks, we analyze the relation between the financial cycle and the sentiment conveyed in these official communications. To do so, we construct a dictionary tailored specifically to a financial stability context, which assigns positive and negative connotations based on the sentiment conveyed by words in FSRs. With this dictionary, we construct a financial stability sentiment (FSS) index. Using a panel of 35 countries for the sample period between 2005 and 2015, we find that central banks' FSS indexes are mostly driven by developments in the banking sector and by the indicators that convey information about the health of this sector. We also find that the sentiment captured by the FSS index translates into changes in financial cycle indicators related to credit, asset prices, and systemic risk. Finally, our results show that central banks' sentiment deteriorates just prior to the start of banking crises.

In a recent paper analyzing the sentiment of central bank communications (Correa, Garud, Londono, and Mislang, 2017), we constructed lists of words conveying positive and negative sentiment-a dictionarythat is calibrated to the language of financial stability reports (FSRs). We then used this financial stability dictionary to generate a financial stability sentiment (FSS) index by comparing the total number of positive and negative words in the text of the FSRs. We found that the sentiment index was mostly driven by developments in the banking sector, and that central banks' sentiment was related to the financial cycle and deteriorates just prior to the start of a banking crisis. In this note, we explain in detail how we made word-level choices in our dictionary. In the note, we also consolidate our lessons from this process into a framework for thinking about dictionary construction.