Thinking About Concentration Risk and the "Magnificent 7"

Today's investors face an important question: how do you keep your investment portfolio balanced when the stock market keeps reaching new record highs? While it might seem smart to only invest in companies that have done well lately, building wealth over time requires a careful approach that considers both growth potential and managing downside risk.

A group of very large technology companies, known as the "Magnificent 7," has been getting a lot of attention because they benefit from artificial intelligence (AI) trends. These seven companies are Apple, Microsoft, Nvidia, Amazon, Alphabet, Meta, and Tesla. Together, they make up about 35% of the S&P 500 stock index and are seven of the eight biggest companies by value. Some of these companies are called "hyperscalers" because they spend huge amounts of money building computer systems to handle the growing need for AI services.

When a small number of stocks drive most of the market's gains, it becomes especially important to look at historical examples, current stock prices, and how your investments are spread out. Learning how similar situations played out in the past can help investors make smarter choices for their long-term financial goals.

New technologies have always driven stock market growth over time

AI technology and railroad companies might seem completely different, but history shows that game-changing technologies often follow similar patterns. Back in the 1860s, railroad stocks controlled American markets much like technology stocks do now. The Pennsylvania Railroad company was actually the biggest company in the world at one time, and along with other railroad companies, it made up a large portion of the entire stock market. This created excitement among investors and pushed stock prices higher, which sounds very familiar to what we see today.

This same pattern has happened many times throughout history. The dot-com boom of the 1990s, when investors focused almost entirely on internet companies, gives us a clear recent example. But going back to the 1800s, technologies like the telegraph, electric power, and telephones changed how cities worked and created many new businesses. In the 1900s, electronics and computers changed every part of life and business, even before the internet was invented.

Each of these technology waves followed a similar path: first people were skeptical, then they quickly adopted the new technology, then the stock market got very excited, and finally the technology became a normal part of the economy. Railroads didn't disappear but became a standard part of how we move people and goods, supporting the whole economy. While many dot-com companies did fail in the late 1990s and early 2000s, many others became today's technology leaders.

For long-term investing, it's important to think not just about individual companies, but about how new technologies affect the entire market and economy. The real benefit of innovation is that it makes all businesses more productive and efficient. The key difference is that while individual company stock prices can go up and down quickly, it takes much longer for the benefits to spread throughout the entire economy.

History shows that stock prices matter just as much as company growth

Today, the question isn't whether AI will be important, but whether current stock prices make sense. The S&P 500 is trading at 22.5 times its earnings (this means investors are paying $22.50 for every $1 of company profits), which is close to the all-time high of 24.5 times earnings. This means investors are paying high prices that assume these trends will continue at the same speed.

What's causing the high prices for the Magnificent 7? First, recent estimates show that U.S. private companies invested $109 billion in AI in 2024, with hundreds of billions more announced for this year. This is more than the entire economic output of many countries and much more than similar investments by other nations. In recent quarters, investors have reacted positively when companies announced they would spend even more money on AI infrastructure. This is a big change from less than a year ago when investors were worried about whether these big investments would actually make money.

Second, many companies and regular people have quickly started using AI tools, creating more and more demand for computing power. This explains why "hyperscalers" like Microsoft and NVIDIA have seen their total company values soar, with both companies now worth over $4 trillion. This is also why the need for new data centers (large buildings full of computers) and the electricity to run them are major concerns for investors.

These companies are seen as building the basic infrastructure that allows other businesses to use AI technologies, much like railroad companies built the transportation infrastructure that supported all businesses in the 1800s. While this creates enormous long-term value, it's hard to predict how long it will take to see returns on these investments.

The problem is that stock markets often overestimate how quickly game-changing technologies will generate profits, even when the long-term potential might be real. The 1990s provide a warning example. During that time, some investors believed that traditional ways of valuing internet companies no longer applied. When reality didn't meet expectations, the Nasdaq stock index fell 78% from its peak, and many companies failed or were bought out. Yet the internet did transform the economy, just not within the timeframe or in the way that peak stock prices suggested.

Balancing opportunities with the risk of having too much in one area

Similarly, while the Magnificent 7 companies may have led the market higher, they have also led it lower during downturns. For example, in 2022 when interest rates rose quickly due to inflation, these stocks dropped about 50% on average.

Since the Magnificent 7 now represents such a large portion of major stock market indexes, almost all investors have these stocks in their portfolios. For those who have focused on technology stocks, their portfolio allocations may be larger than they intended.

Having too much of your portfolio invested in just a few companies is called "concentration risk," and it's the opposite of diversification (spreading your investments across many different areas). On one hand, these companies have shown strong growth and profits. On the other hand, having a large portion of your portfolio dependent on a small group of companies, no matter how successful they are, can create big swings in your portfolio value as trends change. Even great companies can have periods where they don't perform well.

The common phrase explaining this is that “wealth is made and lost in concentration” and as investors we want to be aware of the risks we take. It wasn’t that long ago that General Electric was the most valuable company in the world. Exxon Mobil also had its day on top within the last 15 years and now there is little discussion around either of these businesses.

For perspective, consider the equal-weighted S&P 500 shown in the chart above, which gives the same importance to each company regardless of its size. This approach has historically provided different return patterns than the standard market-capitalization weighted index (which gives more weight to bigger companies), sometimes performing better when large companies struggle.

Since very large tech companies have performed well recently, some investors may find it surprising that an equal weighted index has still performed better over the past 30 years. This shows the importance of not just focusing on what has driven markets recently and what happens to be in the news.

This doesn't mean that investors should avoid technology stocks completely. Rather, it suggests the importance of maintaining balance and having an appropriate mix of different types of investments.

Current AI trends offer both opportunities and risks to investors. Financial success is not about picking winning stocks, but maintaining an appropriate portfolio balance to match your ability and willingness to assume the risks that come with investing in these types of businesses.

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