Sentiment analysis

 

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The web and social-networking platforms have resulted in an explosion of words. Many firms apply artificial intelligence technology to get the gist, and use that as a trading signal. One study in 2010 by researchers at Indiana University analyzed millions of tweets to predict the movement of the stock market three days later with an 87% accuracy. Such success has unleashed a new fashion for Wall Street quants to plug so-called "sentiment analysis" of social media into their massive models. 

Until now these indicators have been fairly blunt, usually tracking a handful of companies on a two-dimensional scale of positive or negative sentiment. But on June 25th Thomson Reuters unleashed no fewer than 18,864 new indices, updated each minute. The system, developed by MarketPsych, a start-up in California, can analyze as many as 55,000 news sites and 4.5m social media sites, blogs and tweets (though on an everyday basis, the number it crunches will be much smaller). The indices quantify emotional states like optimism, gloom, joy, fear, anger—even things like innovation, litigation and conflict. And it does it across a slew of assets: 40 equity sectors, 29 currencies, 22 types of energy and materials, 12 agricultural commodities and 119 countries.