In one of the more astonishing scientific studies I’ve seen lately, computer scientists in Dublin have now tapped the power of linguistic analysis to predict the stock market. Their focus has been on identifying the linguistic trends preceding stock market crashes, but this could be just the tip of the iceberg in terms of research to come.
In “Fewer Verbs and Nouns in Financial Reporting Could Predict Stock Market Bubble, Study Shows,” ScienceDaily explains:
After examining 18,000 online articles published by the Financial Times, The New York Times, and the BBC, computer scientists have discovered that the verbs and nouns used by financial commentators converge in a ‘herd-like’ fashion in the lead up to a stock market bubble. Immediately afterwards, the language disperses.
The findings presented at the International Joint Conference on Artificial Intelligence, Barcelona, Spain, on July 19, 2011, show that the trends in the use of words by financial journalists correlate closely with changes in the leading stock indices.
“Our analysis shows that trends in the use of words by financial journalists correlate closely with changes in the leading stock indices — the DJI, the NIKKEI-225, and FTSE-100,” says Professor Mark Keane, Chair of Computer Science in University College Dublin, who was involved in the research.
Tipoffs of impending financial doom include the proliferation of news items with similar language, which may indicate a narrowing or fixation of attention on a handful of companies and trends to the exclusion of the broader financial markets.