S-Score
Categories: Metrics
Investors, like everyone else, use social media to communicate. Shouting into the interwebs via Twitter, Facebook...those platforms where everyone can see. Shouting by randos, successful investors, unsuccessful investors pretending to be successful investors, and even head honchos at the companies themselves. Yes, Elon...Twitter and the SEC are not your friend.
The S-Score of a stock, ETF, index, company, or industry is a numerical measure of how well-received it is by people on social media. People gather data, web-scraping, and API-ing wherever that company, stock, or what-have-you is mentioned. Then that data is put into a black box that tells us the general feeling people have about it.
Some argue that this is smart; there's been some evidence that emotions alone on Twitter are a better predictor of the stock market than traditional stock market theories (different form S-score, but related). Others argue that the data might reflect extreme views, causing the S-Score to be either over-or-undervalued, since news stories spread like wildfire and amplify, which doesn’t necessarily reflect the value of a thing. But it can make the value change, at least in the short run. If everyone hears bad news about Brexit, or Tesla, you’ll see corresponding stocks change accordingly. Plus, apparently these algorithms have gotten better at getting rid of unhelpful noise.
The first S-Score was developed in 2013 by NYSE Technologies and Social Market Analytics, designed as a cutting-edge product for portfolio managers, brokers...those types of folks. Changes in S-Scores are used to predict changes in stock prices in the near future. Scores between -1 and 1 are boring and neutral. Over +3 is super-positive, and -3 is absolutely terrible...the worst S-Score you could get.
