NewTwitter 'more accurate' than Wall Street for stock analysis, study finds

Investors might want to put aside all that Wall Street research and instead turn their eyes to Twitter.

A new study by academics at Johns Hopkins University finds that crowd-sourced company earnings estimates and sentiment data generated by tweets may be both more accurate than Wall Street’s offerings and help generate trading profits.

The study examined crowd-sourced earnings estimates gathered by analysis firm Estimize, which allows users to make earnings estimates and then crunches the data, as well as tweet company sentiment data produced by ISentium, a firm specializing in such work.

"It appears that tweet sentiment has power to predict post-earnings risk-adjusted excess returns," Jim Kyung-Soo Liew, Shenghan Guo, and Tongli Zhang of Johns Hopkins write in the paper. "There appears to be some indication that a well formulated strategy incorporating both data sets could be an interesting avenue of future research and may lead to annualized excess gross returns in the 10-20 per cent range."

This conclusion comes, inevitably, with many caveats, but first let’s look at the findings.

The study, based on earnings announcements between November 2011 to December 2014, used ISentium linguistic analysis data to create a positive or negative tweet sentiment value for companies in the run-up to their earnings release.