News-based Sentiment Indicators

By Chengyu Huang, Sean Simpson, Daria Ulybina, Agustin Roitman

December 6, 2019

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Chengyu Huang, Sean Simpson, Daria Ulybina, and Agustin Roitman. News-based Sentiment Indicators, (USA: International Monetary Fund, 2019) accessed November 21, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

We construct sentiment indices for 20 countries from 1980 to 2019. Relying on computational text analysis, we capture specific language like “fear”, “risk”, “hedging”, “opinion”, and, “crisis”, as well as “positive” and “negative” sentiments, in news articles from the Financial Times. We assess the performance of our sentiment indices as “news-based” early warning indicators (EWIs) for financial crises. We find that sentiment indices spike and/or trend up ahead of financial crises.

Subject: Banking crises, Early warning systems, Financial crises, Financial regulation and supervision, Global financial crisis of 2008-2009, Hedging

Keywords: Banking crises, Crisis, Crisis sentiment, Early warning indicators, Early warning systems, Financial crises, Global, Global financial crisis of 2008-2009, Hedging, Risk, Seed words, Sentiment, Sentiment index, Sentiment indices, Term cluster, Vector representation, Word vector representation, Word-vector models, WP

Publication Details

Pages:

56
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2019/273
Stock No:

WPIEA2019273
ISBN:

9781513518374
ISSN:

1018-5941

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