- Twitter mood predicts the stock market with 87% accuracy (source of the above picture, research paper http://www.technologyreview.com/blog/arxiv/25900/)
- Hedge fund that trades on Twitter sentiment raises almost $100m (http://www.mediabistro.com/alltwitter/higher-than-expected-demand-for-twitter-hedge-fund-causes-delays_b6818)
- Twitter sentiment and the effect on individual stock returns (research paper: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1702854)
- ex-Goldman banker starts hedge fund trading AI algorithm that analyzes Japanese blog sentiment (http://bloom.bg/gPR5q9)
Social media seems like the best way to gauge sentiment without actually asking the person. Bloomberg has already included Twitter feeds on their platform, Yahoo Finance has StockTwits feeds integrated on their stock pages. StockTwits hasn’t even released their API yet. With the rise of social media, will we see the rise of socially generated financial data?
All the above algorithms that trade Twitter sentiment are very short term. This could be due to the fleeting nature of Twitter posts, thus relevant financial tweets are dominated by those from short term traders with short term outlooks. Social media gauges short term sentiment, but its hard to tell whether it can gauge what I call longer term “behavioral biases” such as price momentum (“let’s jump on the bandwagon”) and post earnings announcement drift (people being slow to realize and price in the better prospects suggested by a positive earnings surprise).