This past January, we passed the first anniversary of the meme stock phenomenon where WallStreetBets communities on Reddit and Discord orchestrated a massive short squeeze on GameStop shares. While analysts and experts say the ordeal has not fundamentally changed the mechanics of Wall Street, the rise of the retail trader, and the potential for mass-coordinated buying and selling schemes around popular meme stocks like GameStop, are here to stay.

Meme stocks are a great example of investor sentiment driving stock price and company valuations as opposed to traditional factors like revenue & earnings growth, dividend yields, or enterprise value. Investing or trading meme stocks has demonstrated that some rules of trading are changing, and in the case of meme stocks, market participants are increasingly buying on sentiment vs. other fundamental factors. So, given this phenomenon how can we accurately measure investor sentiment at the ticker or firm level?

There are macro top down measures like the volatility index (VIX), mutual fund flows and investor surveys. However, these do not provide investor sentiment at the company level. The rise of social media is also adding another class of sentiment signal to be considered, of which, is derived almost exclusively from social media. “Social Sentiment” which is touted as “crowd sourced” sentiment indicators, rely on “volume” and “velocity” of social comments as the value creators in terms of reliability and construct validity.

To summarize there are numerous “sentiment” signals being used in the financial industry but each of them measure something different – i.e. they are not really comparable.  Furthermore, the reliability and construct validity of such signals is unclear and opaque due to the nature of the data collected and the inherent challenges to ensuring a meaningful sentiment signal.

StockSnips News Sentiment MSDX (Message Sentiment Decay Model) is derived by transforming news stories into a quantified score & is an accurate proxy, available on a continuous basis. StockSnips sentiment score is derived by analyzing 50K+ financial news media articles from 20+ sources every day, and the relevant – performance related – comments made in the articles are analyzed and broken down into snippets that are attributed to the ticker or company of mention. Using a proprietary machine learning model, these snippets are then classified as positive, negative or uncertain. The aggregate percentage positive score is derived using our unique algorithm (MSDX) that model sentiment by appropriately weighting historical sentiment and current sentiment based on source, frequency and volume of news snippets. Several studies have validated the sentiment signal (Read our whitepaper here).

In this anecdotal example we examine recent activity in GameStop (GME):

GameStop (GME) Sentiment Signal Example

GameStop’s stock recently soared 104% amid renewed interest from the “meme-stock” crowd. The notorious Robinhood traders and the digital frenzy on Reddit, caused the price to surge to heights not seen since January. On March 2nd, StockSnips Sentiment Signal rose from 64.85% to 69.22% in a matter of 11 days. This clear signal to buy GME at $92.70, on March 13th, preceded a price rally of 104% to $189.60 by March 28th.

To learn more on StockSnips Financial News Media Sentiment Signal (Click Here for our Whitepaper) or reach out to