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Markets have been reaching new highs in recent weeks. A situation driven largely by the technology sector and the rise in popularity of AI. It is in this dynamic that we will jointly analyze whether artificial intelligence could be the next technological bubble in financial markets.
What is a bubble?
Before we begin and move on, let’s look at the meaning of a bubble. Typically, a bubble can appear under the influence of various aspects. The principle itself is represented by a rapid increase in prices, often stimulated by the crowd effect. This subsequently creates a considerable deviation from the real or intrinsic value of the asset.
A bubble can concern a specific sector, a commodity, real estate, credit or other types of assets. We call it bubble because it’s a metaphor for a soap bubble. To simplify it as much as possible, when a soap bubble grows too fast and too much, it ends up exploding. It’s the same thing in the markets. This is generally accentuated by the phenomenon of herd. In other words, investors will invest and follow the crowd so as not to lose 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 mention a few here. First, it may originate from the search for an innovative technology or industry. Low interest rates can also be an incentive to generate a bubble like the real estate bubble in 2008. Having low interest rates can generate a bubble over the years, since the cost of borrowing will be lower. It is in this dynamic that consumption via credit will be stimulated. The other source of bubbles can also come from a shortage of supply. For example, the housing shortage in Canada is driving up prices.
The different bubbles in history
One of the oldest bubbles is the tulip bubble. 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 price of tulips below:
The other well-known bubble is the Internet or Dotcom bubble during the late 1990s. Company valuations were highly valued with multiples of up to 60. Rapid price variation and the herd effect had the consequence of valuations being too high compared to the actual growth of the company’s numbers. 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% against 50% for the S&P500.
When the economy went into recession in 2001, the US central bank began reducing its policy rates in order to address the recession and better support the economy. A reduction in the rate from 6.3% to 1.6%, which leads to talk of the bubble that followed in real estate. Faced with this drop in rates, this generated a lot of excitement during the years 2003-2006 in the US housing market as well as the subprime market.
The Fashion Effect of AI
The artificial intelligence industry has exploded in the last two years and the introduction of Chatgpt has boosted competitiveness in the technology sector. But we can say that we are facing the next dot-com market ? There are arguments that demonstrate that we have certain similarities and others that we do not. Mania, 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 in your favor. 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:
Could AI be the next dot-com?
Since the internet went live, we’ve been experiencing bubbles of all kinds more frequently. Communication, the Internet and social networks accelerate the circulation of information. For example, we had the cannabis bubble, the SPACS bubble, the space bonds 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 large contributor to the economy. These latter small bubbles are often small market capitalizations. So, they didn’t have as important a place as mega caps do today. Keep in mind 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 this industry will represent. If AI represents a small part of companies’ revenues, but the company’s valuation increases as AI’s popularity increases, it will still be necessary to justify the valuations by good results and the impact of AI on those results. If we have a gap between assessment and results, there must be a rebalance.
While AI improves practice transformation and productivity, it is still at the beginning of its potential. It is important to pay close attention to the growth forecasts that are quite encouraging when it comes to artificial intelligence. This can be seen in the graph below:
At the moment, only mega-caps that are already profitable companies have managed to benefit from this fad effect, unlike in the 2000s, when several unprofitable companies also exploded. Therefore, we are not in exactly the same context as the dotcom of 2000. This is also normal because interest rates are high and limit the development potential of smaller capitalizations.
The AI effect and risk concentration
It must be said that artificial intelligence generated a lot of enthusiasm for Magnificent 7 given the lack of visibility before 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 resulted in a concentration of risk both in the technology sector, but also in a concentration of some securities (mega caps) in the stock market indices in general. A long-term concentration of risks 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 index’s expansion multiples are not at the same level.
The Magnificent 7 is attractive to investors because it has demonstrated its ability to generate performance. They also have money to invest in research and development and have a widespread brand. That said, only a small portion of its revenue belongs to artificial intelligence. The current situation is a little different from dotcom because these companies are profitable.
However, as explained previously, if upcoming Magnificent 7 results are weaker than predictions made about AI’s potential, it could disappoint markets. Here is the review of the results below which at first glance still seem positive:
However, if we look more closely, we can see that only the company NVDA has an upward revision of earnings. Therefore, it can be said that AI contributed heavily to NVDA’s results compared to other companies.
On the other hand, a concentration of risk can create an imbalance and distort impressions. For example, one might believe that the performance of the index generally comes from all sectors of the economy, but this is not the case. Only 7 companies contributed significantly to performance.
It is in this order that we will know more. If the company’s numbers do not justify current valuations, a significant correction could occur to rebalance the index.
AI is booming and will likely improve productivity in the coming years, but we are just at the beginning of its potential development. However, it will be important to evaluate the impact of AI on company revenues. Yes, it is from this moment that we will know whether the increase in ratings is driven by AI results or simply by the effect of popularity.
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After working for 7 years at a Canadian bank, including 5 years on a portfolio management team as an analyst, I left my position to dedicate myself full time to financial markets. My goal here is to democratize financial market information for the Cointribune audience in various aspects, including macro analysis, technical analysis, inter-market analysis, etc.