The significant gains of a few technology companies focused on artificial intelligence are prompting a re-examination of a long-standing investment principle: diversification. As the U.S. stock market becomes increasingly dominated by a handful of 'AI superstocks,' some financial experts are questioning whether spreading investments widely remains the most effective strategy.
This development has revived a debate within financial circles, pitting traditional risk-management theories against strategies that favor concentrating capital in a small number of promising companies. The discussion centers on whether the benefits of diversification still hold in a market heavily influenced by a few dominant players.
Key Takeaways
- The rise of AI-focused stocks has led to the highest U.S. stock market concentration in a century.
- Modern Portfolio Theory, a Nobel Prize-winning concept, advocates for diversification to reduce volatility.
- Some professional investors argue that a concentrated portfolio of 10 to 30 well-researched stocks can yield better results.
- Data simulations and historical fund performance present conflicting evidence on which strategy is superior.
- Experts like Warren Buffett have suggested concentration for professionals but diversification for average investors.
The Foundation of Diversification
For decades, the standard advice for investors has been to diversify. This approach is rooted in Modern Portfolio Theory, developed by economist Harry Markowitz, who was awarded the Nobel Prize for his work. The core idea is that holding a wide range of assets, including many stocks and risk-free bonds, can provide comparable returns with significantly less risk.
According to this theory, diversification is often described as the only "free lunch" in investing. It allows investors to smooth out the ups and downs of individual stocks, protecting the overall portfolio from the poor performance of any single company.
What is Modern Portfolio Theory?
Developed by Harry Markowitz in the 1950s, this theory provides a mathematical framework for assembling a portfolio of assets. Its central tenet is that an asset's risk and return should not be viewed by itself, but by how it contributes to a portfolio's overall risk and return. The goal is to maximize portfolio expected return for a given amount of portfolio risk.
This principle has been the bedrock of financial planning, leading to the popularity of index funds and mutual funds that hold hundreds or even thousands of different stocks.
A Market Driven by a Few Giants
The recent surge in AI technology has altered the market's landscape. A small number of companies have seen their valuations grow enormously, giving them a disproportionate influence on major stock indexes like the S&P 500.
Michael Kantrowitz, a strategist at Piper Sandler, noted that the S&P 500 is more concentrated now than at any point in the last 100 years. This concentration raises questions for investors who rely on index funds, as their performance becomes increasingly tied to the fortunes of a few top companies.
Unprecedented Concentration
Recent analysis from Goldman Sachs found that the 10 largest stocks in the S&P 500 now represent approximately 40% of the index's total value. This level of concentration means that the movements of these few stocks have a massive impact on the entire market.
This market reality has fueled arguments for a more focused investment approach. Brian Chingono, director of quantitative research at Verdad Advisers, noted a growing preference for concentrated portfolios among professional capital allocators—those who manage large funds for pensions and endowments.
The Case for Concentrated Investing
Proponents of concentration argue that in a competitive market, truly great investment opportunities are rare. Therefore, it makes sense to invest heavily in a few high-conviction ideas rather than spreading capital thinly across many mediocre ones.
A 2017 paper by Cameron Hight of Alpha Theory, a software platform for investment managers, suggested that professional managers could achieve better outcomes with a focused portfolio of 10 to 30 positions. Hight's analysis of his clients' portfolios revealed a key insight: while only 51% of their individual stock picks were profitable, their overall returns were positive because they consistently allocated more money to their winning ideas.
"Diversification is a protection against ignorance. It makes very little sense for those who know what they're doing." - Warren Buffett, 1993 Letter to Shareholders
This sentiment is shared by other legendary investors. Charlie Munger, the late vice chairman of Berkshire Hathaway, reportedly believed a professional investor should own no more than three stocks. However, it is crucial to note that Buffett clarified his view was for experts only, strongly recommending index funds for the average person.
Evidence supporting concentration includes the performance of the Goldman Sachs Hedge Fund VIP Index, which tracks the most popular stocks held by hedge funds. An ETF tracking this index has outperformed the S&P 500 since its inception in late 2016, suggesting that professional managers' high-conviction, often "crowded," bets can pay off.
The Risks of Putting All Eggs in One Basket
Despite these arguments, many experts warn that concentration is a high-risk strategy that is not suitable for most. Critics point out that for every success story, there are many failures.
Owen Lamont, a portfolio manager at Acadian Asset Management, forcefully rebutted the idea that concentration reduces risk, calling the notion "just bonkers, totally untrue and inconsistent with both evidence and theory." He explained that concentrated funds are likely to appear at both the top and the bottom of performance rankings due to their high volatility.
Lamont cited a real-world example: a top-performing fund in 2024 had previously lost 77% of its value in 2022. This highlights the extreme swings that can come with a lack of diversification.
Data Simulations Support Diversification
Research from Verdad Advisers adds weight to the pro-diversification argument. Brian Chingono ran a simulation of tens of thousands of portfolios with holdings ranging from five to 500 stocks, using market data from 1996 to 2023.
The results were clear: the median return for highly concentrated portfolios was lower than that of their diversified counterparts. Furthermore, the simulation found that a staggering 40% of concentrated funds delivered annualized returns of less than 5% over a decade.
Active Management Challenges
According to S&P Dow Jones Indices, approximately 95% of actively managed large-cap U.S. stock funds have underperformed the S&P 500 benchmark over the last 10 years after fees are considered. This statistic underscores the difficulty of outperforming the market, even for professionals.
Chingono also noted a critical flaw in studies like Alpha Theory's, which often overlook survivorship bias. By only looking at funds that are still in operation, such analyses ignore the many concentrated funds that failed and closed down. "Once you can see the full distribution of outcomes, it becomes very clear that it is in an investor’s best interest to be diversified," Chingono stated.
Conclusion: A Strategy for Professionals, Not the Public
The debate over diversification versus concentration is complex. The current market, heavily skewed by AI giants, makes a compelling short-term case for focused betting. However, long-term data and risk analysis continue to support diversification as the more prudent strategy for the vast majority of investors.
While professional investors with deep research capabilities may benefit from making a few large, calculated bets, the evidence suggests this path is fraught with risk. For individuals saving for retirement or other long-term goals, the time-tested principle of not putting all your eggs in one basket remains the most reliable advice.