Investor's wiki

S-Score

S-Score

What Is S-Score?

A S-Score is a mathematical value that shows how consumers and investors feel about a company, stock, exchange-traded fund (ETF), sector, or index as expressed over social media. S-Scores are made with data accumulated by social media monitoring engines to assist investors make trades and to assist companies with [market analysis](/relative market-analysis) and decision making.

Understanding S-Score

In 2013, NYSE Technologies and Social Market Analytics (SMA) made the first S-Score to be distributed over an elite execution global network. It was specifically geared toward the financial sector and designed to benefit trading firms, portfolio managers, hedge funds, risk managers, and brokers.

Alongside its reserved S-Score, SMA offers a whole family of metrics (together called S-Factors) designed to capture financial market sentiment about a specific company based on the volume, change, and dispersion of social media comments. These metrics incorporate the S-Mean, S-Delta, S-Volatility, S-Buzz, and S-Dispersion indicators. Their system filters out irrelevant and copy comments and spam to focus on the 10% of comments that give significant data.

S-Score Measurement

SMA's processing motor is comprised of three components: extractor, evaluator, and calculator. As indicated by SMA, the extractor accesses the API web services of Twitter and microblogging data aggregator GNIP. These sources are surveyed to gather analysis (in tweets) on SMA-covered stocks. This process is performed continuously.

In the evaluator stage, each tweet is broke down for financial market pertinence using proprietary algorithms. The characteristics of the person making the tweet are also dissected to decide intent. At long last, the calculator stage determines the "sentiment signatures" for each SMA-covered stock using a bucketing and weighting process based on timing. Then a "normalizing and scoring process" calculates a S-Score.

A S-Score of greater than +2 is associated with significant positive sentiment, while a S-Score of lower than - 2 is associated with significant negative sentiment. A score greater than +3 is considered incredibly positive, while one below - 3 is considered very negative. Anything between - 1 and +1 is considered neutral. Higher scores could be also associated with higher Sharpe ratios, while lower scores could be associated with lower Sharpe ratios.

While market events, such as earnings reports, mergers, and acquisition announcements can present great case studies, they will more often than not overshadow social media sentiment. For investors who are interested in using S-Factors in their stock analysis, it could be interesting to assess S-Factor importance prior to, or potentially, after such market events.

S-Score Usage

Investors can use S-Scores to assist them with picking stocks. At the point when a S-Score changes, the stock price is expected to change as well. Research by Social Market Analytics (SMA) has shown that stocks with S-Scores higher than +2 significantly outflanked the S&P 500 over the period Dec. 2011 through Dec. 2015, while those with S scores less than - 2 failed to meet expectations it significantly.

SMA also provides coverage of cryptocurrency notwithstanding every one of the equities inside the major indices. The S-Score has drawn from an underused data source in social media buzz to give another analysis apparatus that can help investors when they are assessing stocks.

Highlights

  • Investors can use S-Scores to assist them with picking stocks; when a S-Score changes, the stock price is expected to change as well.
  • A S-Score is a mathematical value that shows how consumers and investors feel about a company, stock, exchange-traded fund (ETF), sector, or index as expressed over social media.
  • In 2013, NYSE Technologies and Social Market Analytics (SMA) made the first S-Score to be distributed over an elite execution global network.
  • S-Score was specifically geared toward the financial sector and designed to benefit trading firms, portfolio managers, hedge funds, risk managers, and brokers.
  • S-Scores are made with data accumulated by social media monitoring engines to assist investors make trades and to assist companies with market analysis and decision making.