GameStop Was Always A Bubble That Further Proves Stories Run the World

Vinod Bakthavachalam
Vinod B
Published in
5 min readFeb 14, 2021

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The 17th century was the height of Dutch power, known as the Dutch Golden Age, that saw the Netherlands excel in trade, art, and military power. During this period its citizens had the highest per capita income in the world, and that wealth allowed them to purchase luxury items from foreign trade. One such item was tulips, which became a symbol of luxury among the elite, especially due to the intricate and novel color patterns.

The discovery of tulips coincided with the creation of a futures financial market for tulip bulbs that allowed speculators to bet on the price of tulips. As a result, a frenzy began that saw massive increases in the price of tulips. People flocked into the futures market to try to make a fortune. In some cases, the price of tulips rose to more than 10 times the annual income of a skilled artisan.

However, prices crashed soon after the frenzy began. Whether the crash had an impact on the actual economy or not is debated, but the fact remains that this was the first recorded asset bubble in history that saw asset prices spike above their fundamental values and then quickly crash.

Since that time there have been numerous financial bubbles throughout history (that sometimes coincided with actual economic downturns), including the roaring twenties stock market crash that preceded the Great Depression and the US housing market bubble that preceded the Great Recession.

The most recent example of a financial bubble has been the GameStop saga this year that saw the company’s stock far outpace its fundamental value, reaching above $400 a share at one point.

Economic theory says that a stock price today should be the present discounted value of all future cash flows, which for a stock is the dividends paid out to investors. Dividends are usually a function of a company’s earnings. Therefore, the value of a stock is essentially contingent on a company’s earnings today and its growth prospects in terms of how earnings and therefore dividends might be expected to grow in the future.

One common metric to judge all these factors is the P/E ratio of a stock or its price to earnings ratio, especially compared to its direct competitors. Within an industry/competitive set of companies, the P/E ratio of firms with equal growth prospects should be constant because the firms face similar conditions. For a set of competing firms, we can then conclude that differences in P/E ratios need to be accompanied by differences in expectations of future growth.

GameStop’s current P/E ratio is hard to compute because the company has not been profitable in the last 12 months! This stands in contrast to Best Buy, which can be considered a direct competitor, as they also sell video game and related electronics, that has been profitable recently. Best Buy’s stock never rose to the level of GameStop despite it being a similar company with better prospects and a more diversified business.

It is clear then that GameStop’s stock price surged way above its fundamentals. What allowed this to happen?

The answer is the power of narratives. As Robert Shiller discusses in his paper titled Narrative Economics, stories have the ability to spread like a viral epidemic, causing havoc in financial markets and the real economy.

The GameStop saga is a perfect example of this. It started on a Reddit thread where people told stories about the value of GameStop’s and how it was a great investment. This created a frenzy to buy the stock among everyday investors that caused the stock to surge, which was further fueled by a story about the battle between evil hedge funds and ordinary folk (see Melvin Capital). But these bubbles are always temporary because the mania can’t be sustained forever and prices always return to their fundamental levels in the long run, leading to the crash of GameStop stock (which still seems elevated).

This dynamic is captured perfectly by plotting the Google Trends for GameStop against the stock price.

The Google Trends index had a small spike just before the GameStop stock spike and also had another larger spike that coincided with the stock surge, suggesting that the trading frenzy coincided with increased conversation and interest in the stock among everyday investors.

The story about GameStop being a great investment spread like a viral pandemic. There was an initial set of users who were “susceptible” to the epidemic on the relevant Reddit threads. They became “infected” and then spread the news to other “susceptible” people. This was fueled by social media, which created channels for this transmission to happen. The “infected” then “recovered”, causing the stock to crash in value as people relied how overvalued it was.

The above process is modeled perfectly by the “SIR” model from public health. This was the first model created to understand how viruses spread in a population and underlies all the epidemiological models used in COVID forecasts.

The model has three stages of a person: susceptible, infected, and recovered. People move between the various stages as different rates depending on how effective transmission of the virus (information) is.

While this is the first instance of social media transitioning to a financial bubble with real consequences, we have seen similar dynamics in the political sphere. It is not surprising that this happened.

Technology has lowered the cost of participating in financial markets, which is on net a good thing, but it creates the opportunity for social media to spread false information that can cause wild swings in asset prices and even the real economy.

As technology further expands access to all sorts of things and intersects with the speed at which social media can spread information, these kinds of incidents will only increase in frequency. Understanding how narratives spread among people through fields like sociology, economics, and other social sciences will be essential to understanding how to prevent them from spiraling out of control and leading to real consequences such as recessions.

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Vinod Bakthavachalam
Vinod B

I am interested in politics, economics, & policy. I work as a data scientist and am passionate about using technology to solve structural economic problems.