Risk Management and Lessons Learned From Gamestop

The most important lesson to learn from the recent GameStop event is the importance of risk management. But the point is not to try to forecast such an event. For the most part, GameStop being selected by the public for this wave of buying was more or less a random event. There are thousands of stocks that could have experienced the same thing—in fact, there are large stock price swings every day, just with less volume and publicity. Regardless of whether you are an individual or a large mutual fund, knowing if you have a “GameStop Candidate” in your portfolio is critical.

How can you manage the risk of a GameStop type of event adversely impacting your portfolio? There is no way to predict when there is going to be a wave of public opinion that takes over a stock. However, you can look for information that might give you some insight into candidates. Just like most people look for diversification amongst sectors, currencies, and other such factors that might affect a portfolio, there are a couple of other things that could give you similar diversification information.

1. Short Interest—A wave of sentiment could come over any stock that could drive the stock prices significantly up or down. If there is significant short interest in a particular stock, losses can accelerate and keep mounting; but those losses need to be covered, which results in more buying.
2. Ownership—What type of investors own the majority of the assets you are investing in? Generally speaking, this can be accomplished by keeping three broad groups in mind:  insider, institutions and retail. Restricted ownership or insider representation is very well regulated and is reported diligently, but distinguishing between retail and institutional investor representation of stock ownership is less straightforward. However, through top institutional ownership information, “non-institutional” ownership can be inferred.

Knowing the percentage of retail investors vs. institutional, coupled with the amount of short interest could help indicate if a stock is capable of an event similar to what happened with GameStop. 

The SS&C Algorithmics Managed Data and Analytics Service (MDAS) uses a two-step risk approach. The first step is to aggregate positions into “groups” that share similar characteristics, such as thresholds of short interest or ownership interest groups. The second step is analytically determining the contribution that each group has to your portfolio risk. Metrics such as VaR Contribution per 100k$ of Exposure, or Marginal VaR can quantify each group’s risk “contribution.” Importantly, VaR will capture diversification impact.