Dalio's Key Long-Read: How to Position in the Current Market Environment?

marsbitPublished on 2026-06-18Last updated on 2026-06-18

Abstract

Ray Dalio's latest article provides a strategic framework for navigating the current investment landscape, characterized by a market heavily concentrated in AI and other revolutionary new technologies. He argues that investors should view their decisions like moves in a game (e.g., chess, poker), assessing the current "board" shaped by key forces: the AI-driven industry cycle, debt/money, politics, geopolitics, and nature. He warns that such technology-driven periods naturally involve high excitement, volatility, and uncertainty, with historical precedents showing most investors fail by concentrating bets on a few leading companies. The core choice is whether to (a) overweight the new tech sector, (b) match index weightings, or (c) diversify away from this concentration. Dalio strongly advocates for (c) – embracing diversification. He emphasizes that large, new tech companies face inherent risks: over/under-investment, external shocks, future disruption, and intense geopolitical competition (notably from China). His guiding principle is the "holy grail" of investing: a well-engineered portfolio of 15+ high-quality, uncorrelated, and risk-balanced bets. Mathematically, this significantly improves the risk-return ratio compared to any concentrated position. Given the current environment's high uncertainty and concentration, he believes no one can reliably predict outcomes to justify large, concentrated bets. Dalio also expresses a tactical view that future equity returns ap...

This article aims to explore: how you should play your hand in the current investment game.

Imagine you are playing bridge, poker, chess, or Go. When it’s your turn to make a move, there’s a computer beside you that assesses the situation and offers suggestions. In my view, investing is just like that—whether you use a computer's help or not, you should do this: based on the current state of the "board," ask yourself what the next move should be. In other words, you need to act based on the existing characteristics of the market and the various forces influencing it.

I have been playing this investment game for many years. At this stage, my goal is not only to share my own way of playing, but also to build a platform where everyone can explore their own way of investing, learn from and backtest past performance, and truly master the craft. I believe that for a given hand, there are right ways to play and wrong ways to play. Therefore, when faced with a situation like XYZ, you should ask yourself, "How should I bet in this situation?" and be able to give a good answer.

Now, I want to share with you my views on the current market characteristics, what I think should be done, and what I am actually doing.

How to Deal with the Current Environment

What are the most important environmental factors right now? How should one bet under these factors?

In my view (and likely the view of many), we are in an industry cycle driven by a significant new technology—primarily artificial intelligence—with only a handful of companies dominating the market trend. These companies command an extremely high proportion of the overall market capitalization and have a huge impact on the market and economy. All such periods share a common theme: immense excitement, uncertainty, and volatility emerge around the new tech industry, which transmits through the industry to the global stock market. Therefore, the volatility and uncertainty surrounding this industry are crucial.

Additionally, there is uncertainty stemming from other major drivers. I call them the "Five Big Forces":

  • The state of debt and money;

  • Political and social issues (which can significantly impact market factors like taxes);

  • How geopolitical factors (like wars) affect markets;

  • Acts of nature;

  • The development of new technologies.

I would feed these conditions into my investment system to consider how to bet in such an environment, while also thinking independently about the specific directions to bet on.

When thinking about how to deal with this environment, the most important question is: What choice do you really want to make?

  • (a) Overweight the new technology, overexpose to this emerging industry or its top few companies, relative to broad indices like the S&P 500;

  • (b) Keep exposure roughly aligned with index weights;

  • (c) Diversify away from this concentration.

Almost everyone wants to find the best investment and is willing to work hard for it. Right now, a new technology seems to be changing everything. However, history shows that at this stage of the cycle, most people fail because they put most of their chips on the stocks of a few leading tech companies. There is a logic to this, and it has always evolved this way in the past. Although this AI technology is indeed unique, there have been many equally "unique" new technologies in history that serve as analogies and references. People should study these cases; if they choose to ignore them, they must be able to explain well why this time is different.

The Risk is Undoubtedly High

All major new technology cases in the past have shown similar evolutionary trajectories due to the same logical reasons. High risk and great uncertainty are inherent characteristics of these new technology companies. Looking back at the performance of these companies in similar historical environments, even the most revolutionary and long-prospering ones like Microsoft and Apple suffered significant setbacks at similar stages of development. Moreover, in the early stages of these new tech companies, it was not easy to tell which would succeed and which would fail (e.g., IBM). If you look at all these cases, you'll see that major new technology companies have a naturally highly uncertain future.

For example, they either overinvest or underinvest. The reason: if they underinvest to win the competition, they are bound to fail; but they also cannot accurately foresee the future to judge if they are overinvesting. Both overinvestment and underinvestment are costly.

Furthermore, they cannot accurately foresee all changes, including external shocks like monetary tightening, wars, major tax adjustments, etc. Therefore, they all go through intense boom and bust cycles: first exciting investors, then frightening them and shaking out weak hands, eventually leading to exaggerated market swings. And just as these new technologies and companies disrupt their predecessors, most of them are eventually disrupted by newer technologies and companies in ways we couldn't have imagined beforehand. Therefore, we should also consider whether the current new technology and tech companies face the same risks. The impact of quantum computing is one known known risk. What about the risks not yet imagined?

What about risks from competitors? For example, China is producing and promoting AI technology, and Chinese policymakers have fundamentally different views on the economy and AI. We are in a new technology war, and world leaders believe they must win it. Their understanding of AI and its impact on the economy and human well-being will prompt them to offer this technology for free or at low cost because it has a huge productivity boost and raises living standards overall. In their view, the overall benefit of having more people use these new technologies outweighs profits. I believe they will compete internationally, as they have done with cars, solar panels, batteries, and many other products.

The current environment is reminiscent of many historical cases offering valuable lessons. I cannot help but think of how Britain defeated the Netherlands in key industries like shipbuilding at the end of the Dutch Empire and the beginning of the British Empire. AI stocks also face other risks, such as wealth taxes and other tax increases that could force large shareholders to sell massively; and rising anti-AI sentiment that could limit corporate space to advance the technology.

I could list more concerning things, but I could also list an equally long list of the great opportunities AI will create—and that's where I'm willing to place bets. I am not saying these risks will necessarily happen, nor that one shouldn't bet on AI companies. I am only saying that there is undoubtedly a high degree of concentration risk in the market, and people should be aware of how to deal with such an environment. Based on my study of all similar cases and their logical reasons, I am convinced the risk is high, and the best way to deal with this environment is: embrace diversification.

Embrace Diversification

You might be familiar with my mantra of "diversification." My "Holy Grail" of investing is to strive to hold 15 good, uncorrelated, risk-balanced bets. In other words:

A sufficiently diversified portfolio of high-quality bets will outperform a single concentrated bet. It has a higher risk-adjusted return and can be engineered to achieve better returns at the same risk level. The more market risk is concentrated in one area, the more one should diversify; especially when the market is driven by a revolutionary new technology, because the technology itself brings immense uncertainty.

This is not an opinion; it is a mathematical certainty. For example, assume an investment has a risk/return ratio of 0.3 (6% return, 18% standard deviation, a common assumption for stocks); then, if I hold 5, 10, or 15 uncorrelated investments, I can reduce the risk (as measured by standard deviation) to 8%, 6%, and 5% respectively while keeping the 6% return. Therefore, by holding 15 good, uncorrelated bets, my risk/return ratio improves from 0.3 to 1.29, a 4.3x improvement. If desired, you can add leverage on top of that to achieve higher returns at the same risk level. This is a fact.

I have strong confidence in this. It stems from my backtesting, my actual returns over more than 50 years of investing, and the probabilistic logic within it: well-diversified bets, adjusted to fit personal risk tolerance, will, in the long run, yield much better returns than the concentrated bets most investors tend to hold. Specifically, through good diversification, you can achieve a higher risk-adjusted return than any concentrated bet; adjusting it to the risk level you are willing to bear yields a higher return at that target risk than any other approach.

Because I share this method, it is no longer my not-so-secret investing way. However, I rarely encounter investors who truly think about investment strategy this way. That is, I rarely meet people who truly think from a portfolio construction perspective—considering how a well-structured, diversified basket of bets performs differently from simply holding the stock of one great transformative industry company. Most are just thinking about whether those stocks and that industry will perform well and how to bet on them. Those who think about portfolio construction versus those who don't can end up with vastly different performance results. Therefore, I will share my views on this more comprehensively on another occasion.

For all these reasons, in the current environment, when thinking about how to play your hand, you should ask yourself: How concentrated should I be before diversifying?

Expected Returns Look Low

The high risk is undeniable. Next, I'll put forward a view that might prove to be wrong: expected future returns look low. My judgment about expected future returns comes from valuation-related analytical work and the readings from my bubble indicators: the real return on stocks over the next 5 to 10 years seems to be between -5% and -10%, although these numbers carry great uncertainty. In my view, these stocks are long-duration assets with high risk because it's hard to reliably see far into the future; they also appear overvalued and have an unstable holder base.

A question raised by the research team:

In a recent meeting, a member of my research team asked me: Why do you think the market's allocation today is incorrect? How do you know that the lack of diversification in today's market isn't for a good reason? For example, some investors believe AI stocks have very high expected returns; or that index concentration naturally happens when an industry makes up such a high percentage of total market cap; or that when an industry is in a frenzy, many investors buy the stocks without making a wise and reliable calculation of future earnings and how they should be reflected in the stock price.

My response:

Prices rise for various reasons, and not all of them are good. Some investors consider prices and push them higher because they believe the price is still attractive relative to fundamentals; some investors hold these stocks for the long term because they recognize it's a great new technology and see price increases as confirmation these are good stocks; and other investors hold index exposure, passively giving them a large weight in these stocks.

In my view, you can agonize over these issues to decide what you want to do; or you can realize that you don't need to agonize over this problem at all because you don't have enough information to bet confidently. You can simply say, "I don't know enough to bet confidently." And then not bet.

What gets people into trouble is thinking they must form a view and believing their view has value; but more likely, they cannot form a reliable, bettable view.

To be clear, I am not suggesting avoiding bets. Besides, you can't avoid betting because you have to put your money in some portfolio or cash. Most people think cash is the safest investment, but in the long run it is almost certainly the worst. My advice is that even if you have no tactical view on which markets are good or bad, you should know how to make good bets through diversification. Specifically, by holding a balanced strategic asset allocation portfolio and sticking to it when you have no tactical view you can bet on. But that's for another discussion.

So, I believe: Knowing what you don't know and deciding when not to bet is just as important as knowing what you do know and deciding when to bet.

In short, I subscribe to the following principle: because it's usually hard to know enough to justify a concentrated bet as rational, the best practice is to hold only diversified bets you have enough confidence in and that are uncorrelated with each other—i.e., an engineered portfolio designed to match your desired risk level. This is my "Holy Grail."

At this moment, given the current environment, I don't think anyone can see clearly enough what will happen next in this technology-driven market to make large concentrated bets. For me, avoiding concentration and maintaining diversification is the best way to deal with this "unknown." I know this is different from what you read in textbooks. Textbooks basically assume markets are efficient, so you should "believe the market."

In summary, the current market is unusually concentrated around a revolutionary new technology. This fact should remind us: not to confuse excitement about the new technology with whether those tech stocks are attractive, nor to abandon caution by holding a high-risk, highly correlated concentrated bet. Especially when, through clever diversification, we can achieve equally attractive returns at a much lower level of risk.

Postscript:

I won't share my specific holdings or tactical views with you because I don't want to be your investment advisor. But soon, I will share some key perspectives behind these views with you, including my bubble indicators and the logic behind them.

(Note: The above translation was completed with the assistance of DeepSeek. The content is for reference only.)

Link to the original article

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Related Questions

QAccording to Dalio, what are the 'five big forces' creating uncertainty in the current market environment?

AAccording to Dalio, the five big forces are: 1) The debt/money situation, 2) Political/social issues (which can significantly affect things like taxes), 3) Geopolitical factors (like wars), 4) Natural forces, and 5) New technologies developing.

QWhat is Dalio's central piece of investment advice for navigating the current AI-driven market, characterized by high concentration and uncertainty?

ADalio's central advice is to embrace diversification. He argues that a well-engineered, diversified portfolio of 15 or more high-quality, uncorrelated, and risk-balanced bets will provide a superior risk-adjusted return compared to a concentrated bet in a few leading tech/AI stocks.

QWhat is the key question investors should ask themselves when deciding how to 'play their hand' in the current market, as highlighted in the article?

AThe key question is: 'Before diversifying, how much concentration should I have?' This prompts investors to consciously decide their exposure level to the concentrated, high-flying tech sector relative to a diversified portfolio.

QWhy does Dalio believe that making large, concentrated bets on leading AI/tech companies at this stage is particularly risky?

ADalio believes it's risky because history shows that even the most revolutionary new tech companies experience major setbacks in similar early, euphoric phases. They face inherent uncertainties like over/under-investment, external shocks (monetary policy, wars), disruptive future technologies (e.g., quantum computing), and intense global competition (e.g., from China). Their future is highly unpredictable.

QWhat important principle does Dalio emphasize regarding when to make a bet versus when not to bet?

ADalio emphasizes that 'knowing what you don't know and deciding when not to bet is as important as knowing what you do know and deciding when to bet.' He suggests that often, investors lack sufficient information to make a confident, concentrated bet, and the rational choice is to acknowledge that and rely on strategic diversification instead.

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Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

733 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

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