Abstract
We construct a sentiment-based index of global financial stress (s-GFS index) for the period January 2004-December 2020. It builds on a novel methodological approach, which synthesizes the intensity of Google search for specific terms and word collocations related to financial instability and their prior selection based on the titles and abstracts of more than 2,000 working papers posted on the Basel Bank for International Settlements Central Bank Research Hub. The s-GFS index obtained by means of sparse principal component analysis (PCA) accurately captures major episodes of global financial instability during the observation period, playing a pivotal role for the US financial stress as well as industrial production in the USA, the Eurozone and China. It also Granger causes several well-known measures of global financial instability based on sentiment and “hard” data, e.g. the VIX index, as well as the overall dynamics of the global financial cycle, thereby emphasizing the usefulness of sentiment-based measures in monitoring worldwide financial stress.
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