Hari Seldon would be proud. Like something out of the Foundation series of books, a hedge fund is using social media to determine the mood of the market.
E-Financial News reports that Derwent Captial is using research from the University of Manchester and Indiana University which demonstrates that the number of emotional words used on Twitter can predict fluctuations in the Dow Jones Industrial Average. It apparently works as Derwent made .76% in July while the S&P 500 fell 2.2% at the same time.
Derwent Capital scans a selected 10% of available tweets at random and will then categorise these messages into one of a range of mood states, which could include 'alert', 'vital' or 'happy' from which the firm's technology will make predictions about potential stock movements. The initial research showed that the algorithm predicted movements in liquid stocks with 88% accuracy.
Although it is early days for the fund, July's performance provides the first indication that the unstructured data provided by Twitter can be successfully used to feed trading algorithms. The results may go some way to convincing sceptics who have argued that the five-year old Twitter's relative youth and its unstructured, unedited nature, makes its data unreliable as a sentiment tool.