The markets have been reaching new highs in recent weeks. A situation largely driven by the technology sector and the rise in popularity of AI. It is in this dynamic that we will look together at whether artificial intelligence could be the next technological bubble in the financial markets.
What is a bubble?
Before we begin and go any further, let’s look at the meaning of a bubble. Typically, a bubble can appear under the influence of several aspects. The very principle is represented by a rapid rise in prices often stimulated by the crowd effect. This subsequently creates a considerable deviation from its real or intrinsic value of the asset.
A bubble can concern a particular sector, a commodity, real estate, credit or other types of assets. We call it a bubble because it is a metaphor for a soap bubble. To put it as simply as possible, when a soap bubble grows too quickly and too much, it ends up exploding. It’s the same thing in the markets. Generally, this is accentuated by the phenomenon of herding. That is to say, investors will invest and follow the crowd so as not to miss the potential and this will inflate the price of the asset.
What are the elements that favor a bubble?
Obviously, a bubble can find its origin through several factors. We can name a few here. First, it can originate through the demand for an innovative technology or industry. Low interest rates can also be an incentive to generate a bubble like that of real estate in 2008. Having low rates can generate a bubble over the years since the cost of borrowing will be lower . It is in this dynamic that this will stimulate consumption via credit. The other source of bubbles can also come from a shortage of offers. For example, the housing shortage in Canada is driving up prices.
The different bubbles of history
One of the oldest bubbles is that concerning the tulip. During the 17th century, there was a craze for the tulip. This situation has been called tulipomania. To better illustrate this, we can see the evolution of the tulip price below:
The other well-known bubble is the Internet or Dotcom bubble during the late 90s. The valuations of the companies were highly valued with multiples of up to 60. The rapid variation in prices and the herding effect had the effect of consequence of valuations that are much too high compared to the real growth of the company’s figures. The euphoria ended with a peak in March 2000. The Nasdaq index which had a significant concentration in the technology sector subsequently corrected by 80% vs. 50% for the S&P500.
As the economy entered recession during 2001, the American central bank began to lower its key rates in order to cope with the recession and best support the economy. A rate cut from 6.3% to 1.6%, which leads to talk of the bubble that followed in real estate. Faced with such a drop in rates, this generated a lot of enthusiasm during the years 2003-2006 on the real estate market in the USA as well as the subprime market.
The fashion effect of AI
The artificial intelligence industry has exploded over the past two years and the introduction of Chatgpt has boosted competitiveness within the technology sector. But can we say that we are facing the next dotcom ? There are arguments that demonstrate that we have certain similarities and others that we do not. Craze, hype and euphoria can demonstrate certain similarities. We can see that as soon as a company announces its involvement in artificial intelligence, this can work to its advantage. Consequently, a good majority of companies used the right words to attract investors.
And there are companies that have really invested in the development of AI. We will take the example of NVDA which is one of the favorites. It provides good material for using AI. Here is precisely the evolution of the title since the announcement of its new GPU chip:
Can AI be the next Dotcom?
Since the internet air, we have bubbles of all kinds more often. Communication, the Internet and social networks accelerate the circulation of information. For example, we had the cannabis bubble, the SPACS bubble, the space securities bubble, the blockchain bubble…
However, these bubbles did not have enough impact on the economy to generate a recession when they burst. For example, the Cannabis industry is not necessarily a big contributor to the economy. These last small bubbles are often small market capitalizations. So, they did not have as important a place as the mega caps today. Remember that almost 30% of the S&P500 stock index represents 10 mega caps.
Therefore, it is important to focus on the impact of AI on productivity and the economy, but also on the valuations that will be represented by this industry. If AI represents a small part of companies’ revenues but the company’s valuation increases with the rise in popularity of AI, it will still be necessary to justify the valuations by good results and the impact of AI on these results. If we have a gap between valuation and results, there should be a rebalancing.
Although AI will improve practice transformation and productivity, it is still at the beginning of its potential. It is important to take a close look at the growth forecasts which are quite encouraging when it comes to artificial intelligence. This can be seen in the graph below:
For the moment, only mega caps which are already profitable companies have been able to benefit from this fashion effect unlike the 2000s when several unprofitable companies also exploded. So, we are not exactly in the same context as the Dotcom of 2000. This is also normal because borrowing rates are high and they limit the development potential of the smallest capitalizations.
The AI effect and the concentration of risk
It must be said that artificial intelligence has generated a lot of enthusiasm for the Magnificent 7 in the face of a lack of visibility towards other vehicles or investment companies. On the other hand, these are companies that also had a lot of liquidity to invest in the AI industry. This has resulted in a concentration of risk both in the technology sector but also in a concentration of a few securities (mega caps) within stock market indices in general. A concentration of long-term risk is never sustainable.
A rebalancing of the stock market index would be good but it would be surprising to have a drop similar to the 2000s since the expansion multiples of the index are not at the same level.
The Magnificent 7 are attractive to investors because they have demonstrated their ability to generate performance. They also have cash to invest in research and development and they have very widespread branding. That said, only a small portion of their income belongs to artificial intelligence. The current situation is slightly different from dotcom at the moment, because these companies are profitable.
However, as explained previously, if the upcoming Magnificent 7 results are weaker than predictions made about the potential of AI, this could disappoint the markets. Here is the revision of the results below which at first glance still seems positive:
However, if we look closer, we can see that only the company NVDA has an upward revision of profits. Therefore, it can be said that AI has strongly contributed to NVDA’s results compared to other companies.
On the other hand, a concentration of risk can generate an imbalance and distort impressions. For example, one might believe that the performance of the index in general comes from all sectors of the economy, but this is not the case. Only 7 companies made a significant contribution to performance.
It is in this order that we will find out more. If company figures fail to justify current valuations, a significant correction may take place to rebalance the index.
CONCLUSION
AI is booming and will probably improve productivity in the coming years, but we are only at the beginning of the potential development. However, it will be important to assess the impact of AI on business revenues. Yes, it is from this moment that we will know whether the increase in valuations is stimulated by the results of AI or simply by the effect of popularity.
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