Can Tweets And Facebook Posts Predict Stock Behavior? "Like …
Can Tweets And Facebook Posts Predict Stock Behavior? “Like” And RT If You Think So
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March 19, 2014
Another social media data analysis firm, Social Market Analytics, used its coverage of 400,000 Twitter (Nasdaq:TWTR) accounts last August to tell its clients that positive chatter on Apple was percolating just before legendary trader Carl Icahn issued a Twitter statement stating he had purchased a huge chunk of Apple (NYSE:AAPL) stock.
On both fronts, those early birds made a bundle on the alert and showed others that leveraging social media to get the fastest news impacting stock prices wasn’t just a theory, it was a reality.
Four months later, so-called “social sentiment indicators” are making big waves in stock market circles, as more evidence pours in showing that SSI really does give investors who leverage the technology an advantage over those who don’t.
According to a study from Markit, a financial data services provider, from December 2011 to November 2013 positive social media sentiment stocks have shown cumulative returns of 76% compared to 14% from negative sentiment stocks.
Back in 2010, Johan Bollen, a business professor at Indiana University, reported that Twitter data could predict the Dow Jones industrial average with 87.6% accuracy.
“There’s been a dramatic shift in the information landscape,” said Ted Bailey, founder and CEO of New Yorkbased Dataminr. “Information is getting on sources like Twitter early and in advance of what the Street is watching.”
Tweets That Beat the Street
While Facebook offers some data mining opportunities, Twitter is the real hotspot for social indicator analytics. Twitter is a beehive of social media activity, with 645 million active users and 135,000 brand new users every day. Until 2012, however, the technology didn’t exist to splice, dice and slice Twitter feeds to discern fresh trading data. Once social sentiment indicator analysts began figuring out how to quantify all that streaming social media data – and offered the results to professional investors – they made good profits.
Now firms like Dataminr, Datasift and Social Media Analytics employ data analysis technology to sift through Twitter feeds from insiders at publicly-traded companies. Last year, social sentiment analysis hit the big time with financial giant Bloomberg adding Twitter messages to its financial data delivery service. Bloomberg includes tweets from Wall Street analysts and regulators, economists and United States government agencies, boils all those tweets down and ships the relevant data to its roster of clients (mostly stockbrokers, traders and hedge fund managers) who then use that data to stay a step ahead of the competition when buying and selling stocks.
Twitter realizes the value of its huge volume of tweets to the investment community – it earned $70 million from its data licensing service in 2013, a 33% uptick from 2012.
According to Tom Watson, a product manager at NYSE Technologies, which recently inked a new partnership with SMA to disseminate social media indicators to financial clients, “The financial services industry has been watching and listening to social media for a while. Now they’re increasingly using and contributing to social media platforms and trying out different trading strategies based on sentiment.”
The technology, unsurprisingly, is highly sophisticated. For example, SMA relies on algorithms designed around key Twitter criteria – including averages, change, volume, volatility, dispersion of tweets and risk – to generate what company analysts refer to as “S-Scores,” which are evaluations based on all of the above algorithms that mirror sentiment on a given stock, over a historical period of time (called a “lookback” period.)
These sentiment scores indicate whether the prevalent chatter is good or bad news for a given stock. With that information in hand, clients can act accordingly and trade the stock based on the sentiment score.
That’s not to say social media indicators are easy pickings. Joe Gits, founder of Social Media Analytics notes that 90% of all the Twitter feeds that SMA analysts dissect are discarded – it’s the other 10% reveal investment opportunities investors are clamoring for. “The key problem stemmed from the fact there was no way to quantify the data,” says Gits. “Twitter users can’t open up 100 different Twitter streams and accurately analyze the results.”
Social media investment indicators do have a down side, however. It’s fairly easy for con artists to create Twitter feeds similar to publicly traded firms and to throw investors off the right track by tweeting false news about a company, like the buyout of an industry competitor or “foreshadowing” new product launches. Investment fraudsters purchase shares of the stock in advance and profit from Twitter watchers who fall for the bogus news.
The Bottom Line
No doubt, social media investment analysis is an ascending, but very much nascent, technology; so far it’s a winning one for Wall Street’s early birds. Should you sign up for alerts from a social media investment analysis firm? It won’t be easy; most products and services from data providers are geared toward institutional investors, not the Main Street tavern owner fiddling with his 401(k). There are, however, some options. Bloomberg’s Eikon trading platform, available to retail investors, offers a Twitter data tracker for free as part of the platform. StockTwits also offers an entry-level Twitter investment news tracking system, but you’ll hear from astute investors and amateurs alike, so, as always, buyer beware.
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Can Tweets And Facebook Posts Predict Stock Behavior? “Like” And RT If You Think So
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