The “Reddit Rally” around GameStop late last year introduced a new phenomenon to the mainstream: significant stock market fluctuations driven by what individual investors said and did online.
The question for many investors, particularly those in the growing cadre of app-driven DIY traders, is how to capitalize on this nexus of social media and the financial markets.
One way is to follow the musings of the new group of market “influencers” whose tweets and posts have had a surprising impact on market movements, at least temporarily, in specific investments. These include institutional investors like Cathie Wood, but also outsiders, like Virgin Galactic Chairman, Chamath Palihapitiya, sports commentator David Portnoy and perhaps most notably, industrialist, Elon Musk. Musk famously started out by influencing Tesla’s own stock price but has since been credited with influencing the dramatic increase in the market value of GameStop and, most recently, crypto-currency Dogecoin.
A second way to potentially profit from the influence of social media is to invest in products designed specifically for this purpose. Among the first of such social media-based offerings is Van Eck’s Vectors Social Sentiment ETF. This innovative product tracks the BUZZ NextGen AI US Sentiment Leaders Index which includes 75 US Large Cap Stocks selected by:
• Collecting and analyzing millions of unique stock specific data points aggregated from online sources including social media and other alternative datasets.
• Filtering the data utilizing natural language processing technology to determine what the online community is saying and whether the sentiment is positive, negative or neutral.
• Ranking each stock based on positive sentiment and selecting the 75 stocks with the highest sentiment scores each month for inclusion in the index.
Van Eck’s Social Sentiment ETF was just launched last month, so it’s too early to judge the performance and value of the approach. However, the ETF has already attracted over $300 million in AUM, indicative of interest in this type of strategy and suggestive of the likelihood of similar competitive products to follow.