Social Arbitrage Investing | Introduction | TickerTrends.io
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Social Arbitrage extends beyond the GameStop or meme stock phenomena. As both consumers and businesses increasingly rely on the internet for their operations, being socially aware involves more than just selecting the next trendy stock. It can also reveal the next major growth story in virtually any industry.
Imagine you are shopping at a Walmart and notice Celsius energy drink products starting to get really popular. Maybe your friends have recently started drinking it and now you notice the Celsius products are flying off the shelves. Alternatively, maybe you also notice at the same Walmart that Mr. Beast Feastables chocolate is starting to get more shelf space and selling far better than Hershey’s recently.
These are examples of Social Arbitrage, where you, as a consumer, notice patterns in your daily life and decide to trade stocks based on that information. Imagine buying Celsius stock ($CELH) or shorting Hershey’s stock ($HSY) based on these observations as a customer of the products. More formally, Social Arbitrage can be defined as the following:
Social Arbitrage Definition: Social Arbitrage means leveraging domain-specific anecdotes, information or knowledge to gain an edge in investable assets that is exceedingly more difficult for someone not in your situation to acquire.
Domain Specific Edge - A Personal Example
Information is the currency of financial markets. Having a deep understanding of factors that can influence company performance is invaluable.
Within everyones life, there is a domain, interest or familiarity with certain sectors that can be leveraged in market speculation. This can come from a job, social scene, friend group, hobby or more.
In my own life an example of this was products I was familiar with working at a robotics company. When looking at requirements and familiarizing myself with the technology we were working with, it was quickly apparent that Nvidia micro-computers were necessary and the only option for the work we were doing. I was in the middle of working with advanced machine learning in the early stages of the AI boom, and I identified that Nvidia was going to be the beneficiary because I had an intimate understanding of what companies needed in the space. At the time, $NVDA was at $271/share (now $943/share).
Another example of this was a hobby of mine going to the gym with friends. Before going to the gym, we would buy energy drinks from a local store and slowly gained information on new energy drinks and which energy drinks were becoming popular. During this time, there was an energy drink that stood out to us, which we had previously never seen before. Celsius energy quickly expanded its shelving space in our local convenience store, and went from a brand that customers had never heard of before, to someone we noticed was becoming one of the most popular energy drinks. At the time, $CELH stock price was about $8/share (now $92/share).
The Problem
You have a busy life. You can’t drive around to stores all day, and who’s to say that a trend happening in your area of the world is happening everywhere in the world?
How do you know if a trending product will be important enough to the company’s overall sales? Many companies are large and sell $100’s of Billions of products a year. What if the product you see trending is too niche to be significant to the company’s stock/revenue overall?
How do you analyze companies that exclusively sell online or are making big pushes to sell online instead of in real life?
As in the Celsius story shared above, being early gives you the best stock market returns. Identifying Celsius by yourself at $40/share would have still led to a great return on investment, but how can we leverage technology to identify trends much earlier instead of being late to trends that might have started before you discovered it?
The Solution - The Importance of Scale
At TickerTrends, we have over 25,000 stocks across the world indexed and analyzed at a glance for the user. TickerTrends generated proprietary values to solve all the problems listed above. Using the power of social media analysis (Reddit, TikTok, Google Search, etc), website traffic data, AI technology, and other digital data sources, users can discover trends that can positively or negatively impact stocks and gain an informational advantage over other stock market participants, allowing them to profit from stock trading. Most importantly, TickerTrends has already accounted for the problem statements mentioned above, and incorporated those insights into the values that the user sees. This makes it seamless to discover the next hottest trending products and brands.