Traders and investors use Twitter to get ahead of market moves

For many traders and investors, using Twitter has become as much a daily part of their routine as watching a Bloomberg terminal or Reuters screen.

Although some banks ban access to the social media site, many financial professionals rely on it for everything from inside jokes and sarcasm to breaking news and distribution of serious research.

Discussions around particular Russell 1000 securities on Twitter have grown from several hundred thousand messages per quarter in 2011 to several million in early 2014, according to Gnip, a US company that provides social media data to hedge funds. It was bought by Twitter last year.

Twitter's influence as an information provider was recognised two years ago when the Securities and Exchange Commission, the US markets regulator, allowed companies to tweet corporate activity. Companies such as Bloomberg have also incorporated select accounts into its terminal.

To date, its role as source of specific trading activity on the world's financial markets has been hard to pin down. But the roster of tweets that led to measurable market moves had been growing even before Tuesday's premature release of Twitter's earnings.

A fake tweet from a hacked Associated Press Twitter account knocked 140 points off the Dow Jones Industrial Average in 2013 and momentarily jolted futures and commodities markets. When billionaire Carl Icahn used the site to disclose his position in Apple, the technology group's market cap jumped by $12.5bn.

For several years, some traders and hedge funds have been exploring ways of taking Twitter-based trading even further by creating algorithms that can read news and sentiment, and generate automated trades.

A London-based hedge fund dedicated to trading based on sentiment on Twitter called Derwent Capital Markets opened in 2012 but abandoned the effort after just a month.

Exchanges and data providers such as Deutsche Borse and Thomson Reuters have long developed services for investors that can place trades based on economic news and other text from reputable sources, such as government finance ministries.

Now algorithms are scanning messages for key phrases such as "rise", "fall" and "warn" and grade the news on whether it is neutral, positive or negative. That information can be integrated into high-speed trading programmes that place rapid fire trades.

Deutsche Borse's AlphaFlash offers machine-readable ratings from Fitch Ratings agency to automated traders, analysts, asset managers and hedge funds.

Now companies such as Gnip, Ravenpack and Selerity have built a cottage industry in using technology to trawl sites with market sensitive information, such as press release feeds, regulatory announcements and company websites. Nasdaq said on Tuesday that the prematurely released Twitter earnings was on the company's investor relations website for less than a minute.

Still it remains unclear how much trading is generated automatically by Twitter. Many of the providers have acknowledged algorithms have difficulty understanding sarcasm, emoticons and profanity in tweets.

© The Financial Times Limited 2015. All rights reserved.
FT and Financial Times are trademarks of the Financial Times Ltd.
Not to be redistributed, copied or modified in any way.
Euro2day.gr is solely responsible for providing this translation and the Financial Times Limited does not accept any liability for the accuracy or quality of the translation