For those of you who haven’t followed the news – Twitter earnings report was mistakenly made public on Shareholders.com an hour before the market had closed. The earnings report was only publicly accessible for 45 seconds when scraper bots captured the information and broadcast it on Twitter.com around 3:07 PM. Twitter earnings fall short from expectation. This caused a panic among shareholders which led to a 20% drop in Twitter’s stock price - shaving $5 billion right off Twitter’s market cap.
We ran a backtest on over 100,000 articles related to Twitter over a span of 6 months from November 1st, 2014 to April 29th, 2015. Each article has around 25+ metrics, however, we only used the following 3 metrics in our backtest.
- Article Sentiment (-1 to 1): This metric calculated the sentiment
score of an article which was relevant to a company. This can be used
as a directional trigger. - Event Impact Score on Entity (1 to 100): This metric calculated if
the article would have a greater-than-1% impact on the stock on the
same day. - Overall Source Rank (1 to 10): This metric calculated the timeliness
and reposting of a source information. This can be used as a
trust/credibility or viral factor.
Check out the results in the backtest. Over a course of 6 months, our algorithm returned 71.6% verse Twitter's benchmark return of -5.1%.
Read full story here: https://www.linkedin.com/pulse/avoiding-twitter-leak-using-accern-sentiment-kumesh-aroomoogan
Credits on building the algo: Seong Lee and Derek Tishler
