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Big Data Technology That Beat The Market By 50 Percent In 2013 Now Available To Day Traders

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SOURCE Social Market Analytics, Inc.

Active Individual Traders Now Have Access to the Same Up-to-the-Minute "Sentiment" Signals that NYSE and Markit Provide Their Members

www.socialmarketanalytics.com

CHICAGO, Jan. 28, 2014 /PRNewswire/ -- Social Market Analytics, Inc. (SMA) executives announced that they have more than two years of data proving that the tweets of pro investors can consistently predict the movement in specific stocks. SMA, a two-year-old Chicago-based "Big Data" analytics company, currently provides access to its aggregated, weighted sentiment signals to institutional investors and nearly 70 percent of the world's banks, either directly or over the secure data networks of NYSE and Markit. 

(Photo: http://photos.prnewswire.com/prnh/20140128/CG49448)

Active Individual Traders Now Get Access to Big Data "Sentiment" Analysis

"Starting today we're going to level the playing field by giving the individual trader access to the same data," said Joe Gits, president and chief executive of Social Market Analytics. Gits and his team of "blue chip" mathematicians, data management experts and financial markets specialists today are launching three distinct day-trader services.

Priced at $29, $49 and $99 per month, SMA's new services provide the active individual trader with pre-market open reports highlighting the top 10 social media sentiment "winners" and the bottom 10 social media sentiment "losers" and access to specific signals on up to 3,000 U.S. securities, markets and segments. 

At the higher prices, active traders can customize their watch lists and receive up-to-the-minute alerts about sentiment change on the securities they follow. Traders can find out more at www.socialmarketanalytics.com.

Aggregated Social Sentiment Predicts Movement; Extraordinary Reliability (Sharpe Ratios of 1.9)

"Day traders and institutional traders are now following the tweets of professional investors in an effort to beat the market," said Gits. "We've taken the randomness out of monitoring social media so our customers get consistently reliable sentiment signals to feed into their trading models." Had you opened and closed the market each day trading all of SMA's sentiment "winners," you'd be up over 50 percent for the period according to Gits.

Social Market Analytics technology identifies and measures real-time investor sentiment from stock-related tweets for any public U.S. company.  The company uses patent-pending technology and algorithms to actively monitor 400,000 professional investors, media and known "market movers," according to Gits.

The information SMA captures, filters and analyzes results in an "S" (sentiment) Score - part of a series of S-Factor™ markers that help active traders evaluate the source, depth, breadth and dispersion of signals indicating investor intentions to 'buy,' 'sell' or 'hold' specific stocks according to Gits. "Our S-Factors have proven highly reliable indicators of buy and sell movement for specific stocks and have excellent (industry standard) Sharpe ratios (1.9 when 1.0 is considered significant)." Gits cautioned investors that the company's S-factors should be just one of the tools investors use in deciding when to trade.

Scores

Return

Sharpe Ratio




S-Score > 2

54.78%

1.92

1 < S-Score < 2

37.61%

1.43

Universe

26.31%

1.08

SP 500

21.28%

0.97

-2 < S-Score < -1

17.33%

0.74

S-Score < -2

4.38%

.22

About Social Market Analytics

Social Market Analytics is a Chicago-based start-up that now provides active individual and institutional investors (banks, hedge funds, brokerages) with streaming up-to-the-minute social media quantification and analysis that can help them to outperform the market. Its patent-pending technology has consistently proved that the tweets of professional traders can help both institutional and individual traders outperform the market. SMA was selected by NYSE and Markit to provide their members' access to reliable, up-to-the-minute social data sentiment signals.

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