36th Annual Graham & Dodd Event with Li Lu '96, Founder and Chairman of Himalaya Capital
- Li Lu defines wealth as ownership of global purchasing power, accumulated through businesses that create value over time. His framework combines Graham’s business ownership, market independence, and margin of safety with Buffett’s circle of competence and Munger’s advice to “fish where the fish are.” Himalaya’s implementation is to buy great businesses in dynamic economies at advantageous prices and hold long enough to participate in their value creation.
- AI’s usefulness does not remove its recurring costs, capital requirements, or need for human judgment. Li calls the technology “transformative, dangerous, disruptive, and costly” and rejects investment narratives culminating in an “IPO of a God.” He advocates keeping humans in the loop, particularly during recursive self-improvement. Santos suggests that skilled people checking AI output will capture scarce economic rents; Li broadly agrees, while emphasizing nuances.
- Market concentration can create opportunities among businesses overlooked by investors chasing the leaders. Santos puts Nvidia’s capitalization at about 15% of GDP, versus a historical 2–4% range for the largest company. Li contrasts roughly 14–15% annual S&P returns over 16 years since 2010 with approximately zero during 2000–2010: combined, the result returns to high single digits. His conclusion is that widening speculative enthusiasm can improve the opportunity set for investors who remain rational.
- China’s industrial upgrade has coincided with a severe contraction in household wealth and confidence. Li says typical middle-class families had 70% of net worth tied to homes carrying roughly 50% mortgage leverage; a subsequent nationwide property-price decline of about 40% reduced family wealth by 60–70%. Households consequently consume less, save more, and repay debt. He puts saving deposits at RMB165 trillion, about 120% of GDP, while domestic-demand growth has slowed to roughly zero.
- Li’s central question for investing in China is whether a business is a state objective or the cost of achieving one. “Being the cost of a state objective is no fun.” He argues semiconductor restrictions supplied domestic producers with the orders needed to fund improvement, while manufacturing advanced toward the higher end. He expects equities eventually to assume a greater role in household wealth as property’s share declines, but leaves the timing open.
- Li expects commercial interdependence to outlast the geopolitical order currently being reshaped. Leaving the common market sacrifices efficiency, specialization, and access to trading partners, while barriers redirect commerce through third countries. Semiconductor supply chains illustrate the dependence underpinning what he calls “strategic stability.” Countries can compete intensely while sharing an interest in preserving that stability.
- A value strategy requires patient partners and a temperament capable of surviving underperformance. Li warns that demanding good results every year, quarter, or month can turn an investor into a speculator. Downside protection starts with understanding the boundaries of one’s knowledge and expanding them gradually. His rule for compounding—“you don’t lose what you already have”—extends beyond capital to knowledge, relationships, wisdom, and health.
1. Business ownership and purchasing power anchor Li’s framework
Li’s first three principles come from Benjamin Graham: a stock represents business ownership; the market exists to serve the investor; and an inherently unpredictable future requires a margin of safety. Buying shares is therefore equivalent to buying a company, while market quotations provide opportunities rather than instructions.
Buffett’s addition is the circle of competence, especially “knowing the edge of it.” Munger’s is to “fish where the fish are”: crowded markets, industries, and businesses attract competition that averages away returns. Neglected opportunities can offer better fishing grounds, provided the investor understands what is inside that circle.
Himalaya’s sixth principle defines wealth as “the percentage ownership of global purchasing power.” Li implements it by buying great businesses in dynamic economies at advantageous prices and holding long enough to share in their value creation. Santos connects the definition to a concern about preserving purchasing power if fiscal challenges prevent inflation from being controlled.
Li separates investors, pricing arbitrageurs, speculators, and brokers or market makers. The market’s purpose is to channel savings into productive businesses; speculation and intermediation impose costs on that function. Buffett’s “church with a casino attached to it” captures the tension. Li describes Berkshire as a “gigantic cathedral” and Himalaya as an effort to demonstrate that similar churches can be built elsewhere.
2. AI needs human control and continuing financial discipline
Asked whether AI displaces equity analysts, Li first challenges its investment narrative. He traces the claimed progression through reasoning, coding, autonomous agents, recursive self-improvement, AGI, and ASI, culminating in a man-made god. Investors are almost invited into the “IPO of a God.” His categorical objection: either technology does not reach that destination, or humanity unites to prevent it.
His provisional definition is a machine using brute compute and clever algorithms to establish contextual correlations across human-generated data and its derivatives. It synthesizes knowledge and expertise, but he says it does not itself change the physical transformations underlying energy, transport, or manufacturing. “We know how it works and how to make it better, but we don’t quite understand why it works.”
Li’s red line is recursive self-improvement without a human in the loop: independently generated goals would move the system further from human control. Employment, emotional dependency, and cyber, biological, and nuclear risks also enter the calculation. AI will always have incremental costs. Capital needs, profitability, and societal tolerance should therefore shape development; he expects boom-and-bust cycles, potentially several.
Santos’s proposed implication for analysts is that the scarce resource becomes the skilled person checking AI output. Someone who understands a domain and communicates effectively independently of AI may capture the rents. Li broadly agrees—“somewhere along the line”—while explicitly leaving room for “different aspects and nuances.”
3. Concentration can improve the opportunity set elsewhere
Santos’s challenge is concentration: the largest company’s capitalization historically ran at 2–4% of GDP in his chart, versus about 15% for Nvidia now. Li answers with an unnamed research lab burning tens of billions, promising to burn hundreds of billions more, and citing a 10% chance of killing everyone, yet seeking at least $100 billion at a $2 trillion valuation. He treats that combination as irrational and unsustainable.
Li’s grounding comparison is the S&P: roughly 14–15% annual returns over 16 years since 2010, against approximately zero or slightly negative returns during 2000–2010. Across 26 years, that becomes high single digits. He connects the outcome to around 2% real GDP growth, 2–3% inflation, and listed companies doing somewhat better than the broader economy. Long-run returns average out to high single digits.
When capital crowds into the leaders, otherwise attractive businesses can trade cheaply. Li sees that bifurcation in both American and Chinese markets. A technological wave expands the “margin of imagination,” intensifying speculation and exaggeration. Remaining rational is difficult, he acknowledges, but the resulting dispersion can offer better long-term opportunities. Investors need not let the market dictate their decisions.
4. China’s industrial upgrade carries a heavy household cost
Li reads the last decade as a deliberate attempt to escape the middle-income trap. Made in China 2025 targeted a shift from low- and middle-end manufacturing toward the middle and high end. Trump-era trade restrictions and subsequent Biden-era technology restrictions reinforced that direction. By 2021, Beijing doubled down, adding technological self-sufficiency in bottlenecks including semiconductors, aircraft engines, and operating-system code.
Property is the cost side of that choice in Li’s account. At the 2021 peak, a typical middle-class family held 70% of net worth in its home, carrying roughly 50% mortgage leverage. He puts the subsequent nationwide price decline at about 40% and the associated fall in family wealth at 60–70%. The response: consume less, save more, and repay debt.
Li says domestic-demand growth has consequently slowed toward zero, while saving deposits have risen to about RMB165 trillion, or 120% of GDP. Two to three years of roughly flat or slightly declining prices have further weakened confidence. The household experience therefore looks very different from the industrial progress he describes.
Annual new sales in real estate, he says, are down about 70%; the roughly RMB10 trillion figure is also the amount spent annually on manufacturing upgrades and improving technology efficiency, with the divergence around 2021. His development model is sequential: an industry promoted as an objective in one decade can become a cost in the next. Property once delivered urbanization and middle-class wealth, then absorbed the adjustment.
5. Policy objectives shape China’s industrial opportunities
Li says every Made in China 2025 objective has been hit, citing progress in EVs, batteries, storage, new energy, and heavy machinery. He calls US-led semiconductor sanctions a “godsend”: domestic orders generate revenue, profit, R&D, better products, and more orders. He describes mature-node equipment and fabrication as almost self-sufficient and advanced nodes as getting close, with a few missing ingredients; continued progress, he argues, could bring self-sufficiency.
AI is another equalizer in his account: code generation helps address missing software layers, including those serving PCs, servers, and Nvidia’s CUDA system. Asked to distinguish American and Chinese AI, he contrasts Silicon Valley’s question—“what else can this technology do?”—with Chinese companies’ greater emphasis on consumer and enterprise customers. He explicitly says Chinese firms also share the frontier curiosity; the distinction is emphasis.
An audience member asks whether the stock market itself is an objective or a cost. Li leaves the date open but argues equities must eventually take a greater role as property shrinks within family and national balance sheets: they grow with—and help drive—the economy. On rules changing overnight, his answer is to study state objectives, history, and the record. He applies that requirement to the United States and other countries too.
6. Commercial interdependence supports strategic stability
Santos contrasts the openness surrounding Himalaya’s 1997 founding with today’s less generous international atmosphere. Li distinguishes a changing political order from a more durable economic order. The common global market consolidated after the Soviet Union’s collapse; withdrawal sacrifices efficiency, technological improvement, specialization, and access to resources. He sees Washington reconsidering the costs of global stewardship, without successfully withdrawing from those responsibilities so far.
Trade barriers can redirect commerce through intermediaries. Li points to American trade with Mexico plus ASEAN as offsetting declining direct US–China trade. His semiconductor illustration is that producing countries and leading executives “all use chopsticks,” emphasizing the dependence of the AI buildout on those suppliers. His instruction is correspondingly blunt: countries betting heavily on that technology must maintain workable relationships with them.
Li says the US and Chinese presidents find it urgent to meet four times in eight months, and remarks that a meeting’s main accomplishment can be scheduling the next one. The transcript does not make clear how many of those meetings have already happened. “Stability is of strategic importance”: China pursues semiconductor self-sufficiency, America hopes for AI breakthroughs, and each side believes time favors it. Their competition coexists with an interest in preserving the common market and avoiding disruption.
7. Li applies value principles broadly and dismisses crypto
Asked whether value investing works for growth and technology businesses, Li answers that “all intelligent investment is value investment.” A declining business returning cash, a rapidly growing company, and a portfolio of low-probability bets all require understanding what is received relative to price. The common mathematics is discounting future cash flows, insofar as they can be understood and estimated accurately; application depends on competence.
On energy and climate, Li identifies energy and transportation as foundational layers of the economy. Current AI constraints run “from chips to electricity to labor.” He acknowledges climate implications but does not develop a specific directional investment argument from them.
His crypto judgment is categorical: “I think eventually it will disappear on its own.” He calls it “fundamentally bogus,” arguing that currency requires an enforcement mechanism for settlement and a store of wealth. He associates crypto with illicit transactions and favors banning it. He nevertheless treats collecting it, like paying a particular price for art, as a personal preference; that does not establish societal value in his account.
8. Patient capital allows knowledge and trust to compound
An investor two years into practicing value investing asks about career risk during underperformance. Li warns against wanting both long-term value creation and favorable results every year, quarter, month, day, or hour: “Pretty soon you become a speculator.” The choice is whether the market serves or instructs you. For investors unable to maintain that distinction, he recommends indexing.
Building a business around the approach requires like-minded capital that will stay. The necessary temperament accepts being right because logic and facts support the conclusion, independently of others’ agreement. Li says some people fit that psychology and others should not force it. That also limits the ambition to gather the biggest fund or maximize assets under management.
Downside protection starts with the boundary of what can be known. In his twenties, Li began with easier-to-understand balance sheets, gradually moving into more complex businesses as competence grew. “If you can compound your knowledge in a sustainable fashion, eventually you can compound your capital as well.” Each decade’s learning, he says, can leave him almost a different person.
Li credits “so many lucky breaks” rather than treating the record as proof of genius. Munger’s “web of deserved trust” anchors his advice on partners and relationships. The compounding rule is “you don’t lose what you already have,” extended to knowledge, trust, wisdom, and health. Continued engagement may prolong productive and health spans, he suggests, even if it does not prolong lifespan.
Full transcript
Thank you so much. I know you’re incredibly excited to be here, and I know it’s not because of me, but rather because of our guests today, whom I’ll introduce shortly.
Before we start the interview, let me take a couple of minutes to tell you that, as always at this time of year, the Heilbrunn Center year is up and running in full swing. Some of the students here have already taken my Modern Value Investing class. They’re taking the Applied Value Investing class, the CREATE Superhighway, and all the electives. We’re having a blast. They’re all absolutely wonderful.
In addition, we have a new initiative this year at the Heilbrunn Center: our first Global Value Investor Program. The first cohort, a joint effort with Columbia Business School Executive Education, is here. These are all wonderful friends from China who are visiting us this year. Thank you so much for being here.
Michael and I get asked this question a little too often: We’re already working on a new season of the Value Investing with Legends podcast, so episodes will be coming soon. That’s something to look forward to.
We made our new stock selections for the student portfolio, the Tom Russo Student Portfolio. I don’t know what we bought this year: Equifax, Humana, the great Japanese bicycle company Shimano, a classic value play. There was also Copa, the airline company, and Perimeter Solutions, a fire solutions company. So, a lot of fun things. You can download all the reports the students have written over the years on the different companies. It’s a wonderful resource, and I very much encourage you to look at it.
I’m always amazed by Tom Russo’s generosity toward the Heilbrunn Center—not only because of the student portfolio, but because of everything he does for the program. In particular, this year he made sure our friend Li Lu could be here, for which we’re always thankful.
We just had a wonderful week with this new Global Value Investor Program. Andrew Gundlach and Kristen Gilbertson put on a show for them, and I want to acknowledge that publicly. Finally, we’re getting ready for a terrific CSIMA conference. It’s amazing to see the names coming this year: Howard Marks, Bill Ackman, Josh Wolfe of Lux Capital, and Samantha McLemore from Patient Capital. I very much hope to see many of you there.
Now to the main event of the year. Li Lu needs no introduction. He’s truly one of the great modern value investing legends and, of course, the founder and chairman of Himalaya Capital, which he founded in 1997. He’s built an enormous record of performance over the last 30 years.
Li Lu, as many of you know, is one of our most distinguished alumni. He graduated with a law degree, an MBA, and a BA from Columbia College, because why get just one degree when you can get three? Apparently, that’s how he thought about it. His personal story is well known, so I won’t repeat it here. Li Lu is famous as an early investor in BYD and many of the great Chinese companies. We’ll have the opportunity to discuss issues related to the Chinese stock market today.
First of all, Li Lu, welcome, and thank you so much for being here.
Thank you, Tano.
Fabulous. I’m going to talk for about 50 minutes, and then I’ll open it up for questions. I’m going to ask you to keep them short and to the point, and I will be ruthless. If you take more time than I consider necessary to get your point across, I’ll cut you off and give you a nasty look. So keep them short, because I’m sure there will be many, many questions.
Li Lu, you’re one of the great names in modern value investing. You’re deeply intertwined with the story of value investing at Columbia Business School. We were talking about that over lunch. You were there at the very beginning, when Bruce was launching this program. We know about your friendship and partnership with Charlie and Warren and how many things you did together. We’ll be celebrating 30 years since the founding of Himalaya Capital next year, which is a remarkable achievement.
I want to start here. Tell us a little about what you learned about value investing and where you think we are today. What do you wish you’d known at the beginning? What lesson do you think we have now that we didn’t have when you were studying at Columbia Business School?
Thank you, Tano. First of all, thank you all for being here. It is such a wonderful occasion. When I was a student and a young professional, I also attended a few of those luncheons. They were a highlight. I hope I can do some justice to the occasion now, 30 years later.
1. Six Principles of Value Investing
The discipline of value investing started at Columbia. When Ben Graham first started teaching these classes, it was almost 90 years ago. Of course, he had practiced for 10 or 20 years before that. So we can call it a 100-year-old discipline. It has evolved, but some of its core principles have remained timeless.
If I had to distill the main principles of value investing, I’d say there are six. Three come directly from Ben Graham, the namesake of today’s lunch, and one each from Warren and Charlie. Then we add a small twist to make six. These are the six basic principles that have guided our discipline, or at least our practice, over the last 33 years.
Ben Graham laid out three basic ideas as he started this discipline. First, a stock is a piece of ownership, not a piece of paper to trade. Buying a stock is really the same as buying a company. Second, the market is there to serve you, not to instruct you. That’s a profound insight when you’re in the midst of market activity. Third, investing is about predicting the future, which is inherently unpredictable. Therefore, you always want to require a margin of safety to help protect the downside and give you a better upside.
I think Warren added a further discipline: the circle of competence. Over time, all of us are probably predisposed to certain interests. We develop particular expertise and try to study more and get better. The most important concept of the circle of competence is knowing its edge, because most of us are wired to think we know a little more than we actually do. Understanding the edge is as important as understanding what’s inside it.
Charlie had the idea that you’ve got to fish where the fish are. He was a lifelong fisherman, and it’s a wonderful analogy for the market. Certain markets, industries, and businesses draw a lot of attention. With that attention comes competition, which averages out your returns. Other industries, businesses, countries, or markets don’t attract as much attention. There are fewer fishermen, and you do much better fishing where the fish are. It’s a simple idea, but in practice it’s amazingly effective.
Lastly, over my 33 years of practice as a global investor, applying the principles of value investing globally as commerce becomes one single market, we’ve had one insight: wealth, in the end, is really your percentage ownership of global purchasing power. It isn’t expressed, especially in the modern economy, by the amount of gold, diamonds, or currency of any kind. With inflation, all of those dissipate over time. What really matters is what you can buy with it and what you can use it for. A better measurement of wealth is your percentage ownership of global purchasing power.
We express that by buying great businesses in the most dynamic economies at advantageous prices, then waiting long enough for value to be created over time and sharing proportionately in the upside. Those are the six basic ideas that I think can withstand the test of time and serve everyone well.
I like that last point very much. I’m already deviating from the script you and I agreed on, because I think keeping an eye on purchasing power is going to be key if we’re not going to be able to control inflation in the presence of these fiscal challenges. If we have time, we’ll come back to this.
I want to get a question in before we run out of time, for the benefit of my students in the room. That’s my prerogative as the person asking you questions. I don’t want to run out of time. Value investing as a practice has seen ups and downs. It’s been improving conceptually over time, thanks to Bruce, your leadership, and many other people in this room. What is the future of the equity analyst in the age of AI? Do you think we can still teach what we do at Columbia Business School going forward?
Let me answer that in two different parts. First, what investors do, and then let’s talk about AI separately. An investor basically looks at the market participants. There are really only four different kinds of people. There are investors who invest in the company over time for value creation. There are also people who arbitrage the wrongs of market pricing.
In Ben Graham’s terms, that’s arbitrage: you buy from the pessimist and sell to the optimist. Then you have people who are mostly in it for speculation, mostly guessing what other people would buy or sell a security for. They don’t care about either the security’s value or the value it creates. And then there are brokers and market makers who facilitate all of that.
Most people aren’t purists. They encompass some of all 4 types. Indexing is exactly that average, in a sense. But value investors are really focused on price discovery and on waiting for value creation over time. I would say Ben Graham was more focused on arbitrage, while Warren Buffett uses arbitrage pricing but is mostly focused on value creation.
The social benefit of each type is also interesting. Speculators, by definition, don’t stay in long enough for any value to change or be created. What they make and lose probably adds up to roughly zero. So, net to society, speculation is a cost to the functioning of the market. Brokerage and market making are also costs to the market’s functioning.
The market exists primarily to put excess savings to productive use in deserving companies and to create a modern economy with compound economic growth. That’s why the stock market exists in the first place. So why do we have this speculative side? It’s just part of the human condition. Warren Buffett has always described the stock market as a church with a casino attached. The church is where value is created, and the casino is almost part of the building permit: a necessary cost because of the human condition.
When the market was created 400 years ago, this was how you inspired the animal spirits. Four hundred years later, it’s still doing that.
Doing that.
This is where students have to make a choice. Do you want to be in the zero-sum game, or do you want to be in the value-creation game? That’s a personal choice. As a society, we also have a choice. We don’t want the casino side to become so disproportionate that it overwhelms the primary objective of why the market exists in the first place. That’s a choice at both the individual and societal levels.
The fact that over 400 years, despite all these huge booms and busts and giant waste, this mechanism has somehow survived and continued to propel society as a core function is pretty miraculous, to say the least. It’s important for students to make that distinction early on: What do you want to do personally? As a society, we should also calibrate the proportion of each. But they coexist as part of the human condition.
2. AI and the Human Role
Now, AI and the market are a more complex question. First of all, what is AI, or this wave of generative AI? It’s obviously a technology, a huge technological wave. We’ve been dealing with technology for the last few hundred years, ever since the Industrial Revolution. We’ve had wave after wave of technological change, and the disruption and creation associated with the process of creative destruction. We understand some aspects of it, but somehow we feel that this wave is different. Of course, every wave is different, but this wave is unusually different from anything we’ve experienced so far.
What makes it so different this time? On the surface, you can see the pace of change, the scale involved, and the concentrated financial impact at the top. The nature of that concentrated impact is unprecedented. Then you ask why that’s the case. The narrative is slightly different. Until now, most of the time we’ve dealt with technological changes as a fundamental tool for human productivity. With this technology, we introduce a different element: a spectrum from tool to creature. We’ve begun to change the balance along that spectrum.
The moment it was first introduced nearly 4 years ago was the moment of the Turing test. At that point, we could no longer tell from language whether it was a machine or a human. From there, we were introduced to reasoning, and it began to gain more and more human features. From reasoning came coding. With coding capability, it became an autonomous executing agent that functions much as a human does. Then comes the collaboration of agents on complex, long-lasting tasks called long-horizon reasoning. Much like a human society, agents organize and self-organize, prioritize and execute tasks in ever more sophisticated fashion, using their own language and communication tools.
That’s where we are. If you look at the Silicon Valley narrative, generative AI will go to the stage of RSI, which we’re partially in: the idea that all improvement would eventually be self-made, without a human in the loop. From RSI, we come to AGI and ASI, intelligence that exceeds that of any human individual and perhaps all of us, individually and together. From there, you would say we’re creating something like a demigod, a man-made creation. Because it is so powerful and all-encompassing, the economic impact by definition has to be huge, justifying all the different investment costs.
So you’re all invited, when you have the trillion-dollar IPOs, to participate in the IPO of a god or something. That’s the narrative, and that’s what makes it different. But if you step back and ask what will become of humans if this were indeed the case, we’d be living in a society lorded over by a man-made god, accessed by very few, understood by none, and not even controlled. We can’t say that, because nobody understood it at that point. Would humanity really want to live in such a society? Elsewhere, the answer would probably be a resounding no. I don’t think anyone would want to live in such a society.
So there are only 2 possible outcomes. Either this technology doesn’t progress in that direction, and we can discuss what it is and why it isn’t; or, if it really is progressing in that direction, we would all at some point unite to stop it from becoming that. In neither case are we going to have a man-made god living and lording over human society.
That’s what distinguishes this generation of technology and makes it different, and that’s why it has all these different impacts, particularly on financial markets. Leaving that aside, when you come back and ask whether it’s a useful technology, the answer is also a resounding yes.
At its essence, if I were to give it a provisional definition based on observing what it does and where it came from, I would say it is a machine that applies brute compute with clever algorithms and uses all human-generated data. It is a first derivative that establishes systematic contextual correlations among near-infinite variables in human-generated data, and it is a first derivative. In doing so, it establishes capabilities that include much of human reasoning and intelligence.
At present, we know how it works and how to make it better, but we don’t quite understand why it works, just as we don’t quite understand how the human machinery works. With that provisional definition, and observing what is happening now, it does equalize a layer of the economy in a way that’s very helpful.
At the bottom of the economy, we have energy and transportation, and on top of that, manufacturing. On top of that, we have communication and digital media. Then we have this enormous amount of knowledge-based, technology-based services that synthesize all the knowledge we’ve accumulated and serve all the different layers of the economy. Generative AI today, at its current stage, is a great tool to synthesize and equalize all the knowledge and expertise that have accrued to that layer, helping all the different ones.
But it can’t really change energy and transportation. It doesn’t change manufacturing, which is essentially the combination of different items, molecules and atoms, and their transformation into different combinations. Communication and digitalization are already great synthesizers. So that’s the realm where it’s going. It hasn’t gone beyond human capabilities. By this extension, you can also understand that it may not rise to whatever the narrative or the detractors would lead you to believe. We’re still firmly within the realm of human-generated data.
To get to the biological level requires a whole different level. For example, this may be going too far.
Go for it. Knock it out.
Each cell contains about 50 megabytes of data, and you need to multiply that by trillions to really get to the biological level. So we’re nowhere close to that, and may never get to that level.
But what has already been established has begun to tip the balance between tool and creature. One argument would persuade you to stop any further development without a human in the loop. RSI, recursive self-improvement without a human in the loop, would be very, very dangerous because it would develop goals and subgoals of its own, and that would take it further from human control.
In summary, this technology is enormously helpful and transformative, and it is extraordinarily dangerous. As human beings, we have to establish a firm red line as a society: the development, learning, or use of these tools cannot happen without a human in the loop. In other words, we have to firmly establish that we are on the human side rather than the creature side.
Of course, it is also enormously disruptive, from employment and emotional dependency to risks from cyber, bio, and nuclear threats. What we want society to develop, in the end, is a balanced pace of development that balances benefits and risks. The cost of this technology will always be incremental. This is fundamentally different from the internet or many previous technologies, where you make a one-time investment and can amortize it over a long time. That is not the case here, so there will always be an incremental cost associated with it.
The cost and revenue profile is also very important. Capital needs and financial discipline will always be in operation. So will the pace of development and the level of society’s tolerance. You have four or five different layers to consider when setting the pace of development.
How human society adapts to these kinds of changes is not always determined by planning. We’re going to go through big booms and busts, or even multiple cycles. That’s basically the nature of how this will develop. But those are the lines we always have to think about as we approach this transformative, dangerous, disruptive, and costly technological wave.
I think what you said, Li Lu, about this combination of being extraordinary and dangerous, and about how we don’t completely understand why it’s generating some of the answers it does, means we need a human in the loop to check its work. Once again, the scarce skill of the person monitoring artificial intelligence output is going to determine where the rents are located.
That’s right.
So effectively, if you’re smart and can communicate effectively in any domain without AI, you’re going to be the scarce resource, and the rents are probably going to accrue to you. Do I understand that correctly?
Yes. I think that’s somewhere along the line. There are obviously different aspects and nuances, but I think, in the end—
Okay. Let’s start projecting these ideas. One of the things that’s most striking when we walk into the classroom is that many of my colleagues here teach capital markets or financial markets, investing in general. This is one peculiar market, so let’s start talking about it.
I have a very vague question for you. The market seems to be driven by a very small number of companies that are really pushing the technological frontier. The world seems dependent on these companies to push that frontier, and as a result, valuations are completely distorted by them. There’s a chart I show my students: the market capitalization of the company with the highest market capitalization, normalized by GDP. Traditionally, that number has been between 2% and 4%. With Nvidia, it’s now about 15%.
How do you think about this market, which is becoming overly dependent on those few companies and has very high beta to them? How do we design portfolios to protect ourselves against the shocks of this technology?
3. Markets Through the Extremes
Markets have always done peculiar things. From the very beginning, we’ve gone through this, and we’ll probably continue to do so. You don’t have to be dictated by what the market decides to do at any given time. This is one of the most important insights and contributions from Ben Graham himself.
At this point, consider the proposition in one recent prospectus I read. Here is a company that calls itself a research lab, has burned through tens of billions and promises to continue burning through hundreds of billions of dollars, and promises transformative technology, while also saying there’s a 10% chance it could kill everyone. It wrote this in its prospectus and invited everybody to put in at least $100 billion at a $2 trillion valuation. There’s an ironic inconsistency here. This is an extreme illustration of how irrational the market can get. Those things cannot both be true, but that’s where they are.
It also tells you that things are not rational or sustainable. Eventually, this won’t continue. That is also what the rules of the market tell you when you look across the centuries. Markets do strange things over long periods of time.
Take the S&P 500 since 2010, for example. Over the last 16 years, it has averaged 14% or 15%. In the preceding 10 years, from 2000 to 2010, it averaged exactly zero. In fact, it was slightly negative over those 10 years. Average the last 26 years, and you get a high single digit return. That’s roughly right over the long term. If GDP grew by maybe 2% during that period and you had 2% or 3% inflation, you’d average about 4% or 5% nominal growth. Publicly listed companies do slightly better than that, especially those selected as the 500 best companies. So you end up with what you’d call a high single digit return, which is exactly where the long-term average has been.
But markets are punctuated by extremes, sometimes over long periods. The example we just cited strikes people as minimally odd. That happens throughout history. If we ground society in the idea that a superintelligence is simply not allowed or tolerated, then it won’t go there. If it stays in the realm of tools, this will be like any other tool, with costs and benefits associated with it. Financial discipline and capital market discipline would eventually apply. The way you get there is through multiples going up and down and through boom and bust cycles, and that’s fine too.
From that perspective, the bifurcation means that at any given time, you don’t create an enormous amount of new capital. If the market is overwhelmingly driven by the top companies, that means it is also bifurcated, with a whole bunch of otherwise wonderful businesses trading at very low prices. This is true here, in China, and in other places. In China, it’s probably more extreme, as some of the Chinese participants would be well aware.
Over time, the weight of the market still dictates investors’ long-term returns. You still get what you deserve in the end. There’s not much of a free lunch, even if it appears that way for a period of time, or even a long period. Over the longer term, things are weighed out by the natural weight of the market’s own rationalization. That’s why it has existed for a few hundred years already.
I would say this bifurcation offers those with a rational mind a better opportunity set than at other times. Again, it’s very difficult to stay rational. It’s not that easy. You can get swept up easily. Especially when you have a bigger technology wave, your margin of imagination expands dramatically. The speculative side of the market becomes much more active, and the imagination becomes wilder. The forces of exaggeration also tend to become more extreme. But for a rational mind, I would say that creates a better long-term opportunity set than otherwise.
You mentioned China briefly there.
Yes.
Let’s talk a little about that. I just came back from China. I was teaching the participants there in Hong Kong, and I took advantage of the occasion to do a couple of cases on Chinese companies and study the Chinese market a little. It’s been quite a ride over the last few years, let’s put it that way.
I wanted to ask you about this. How do you think about the Chinese market these days, with the problems in the Chinese economy associated with the real estate bust and the banking crisis? It looks very reminiscent of some of the things we’ve seen in other places, but I wanted to hear a little about how you see investing in China these days.
4. China’s Economic Tradeoffs
Yes. You also mentioned the Chinese market. If you look at the last 10 years, it has been stagnant for basically a 10-year period. What happened during those 10 years is fascinating. Ten years ago, the Chinese government had a decision to make. It had achieved somewhat of a middle-income level, and the question was: How do we break away from it?
Many countries have reached that level and then stagnated. There’s even a term for it: the middle-income trap. Many dozens of countries have achieved that level and stayed there 40 or 50 years later. China is a large economy, so the question naturally is: What keeps a middle-income country stagnant and prevents it from breaking through the ceiling? You manufacture and industrialize, moving into mid- to low-end manufacturing, but never really break away from it.
So they had a decision to make: Do we want to break out of it, and can we do something to accelerate that process and make sure it happens? Because, on a natural course, many countries have failed to achieve that. They stagnate and stay there for 40 or 50 years.
In some countries, even longer. They embarked on a deliberate process of moving the economy from low- to mid-end manufacturing into mid- to high-end manufacturing. Instead of a five-year plan, they now had a 10-year plan called Made in China 2025, which listed about 10 major objectives aimed at transforming Chinese manufacturing from low- to mid-end into mid- to high-end.
A few years after that process began, the Trump administration came on board and started the trade war. That reinforced the idea that the economy might not reach that ceiling or break through it on its own natural course. Other countries might deliberately constrain China below that ceiling. Then, after Trump, the Biden administration not only kept the tariffs but also added more technology restrictions.
Five years into the 10-year plan, by 2021, the Chinese government doubled down on that direction. In addition to moving manufacturing into the mid- to high-end, it also decided to pursue technology self-sufficiency, particularly in areas where China faced real bottlenecks: semiconductors, big aircraft engines, operating system code, and so on. China had a long list of these challenges, and it began another five years of accelerated effort to address them.
When you try to achieve goals that so many countries have failed to achieve, it comes at a deep and heavy cost. That has been the model of Chinese economic development: in different periods, there are always big objectives and targets, with big costs associated with them. You mentioned real estate. Over the last five years, one of the principal costs of achieving that goal has been the balance sheet and wealth of middle-class Chinese families.
By 2021, real estate prices had reached their peak. A typical middle-class Chinese family had 70% of its net worth tied up in the home it owned, and that home carried roughly 50% mortgage leverage. In the next five years, through today, real estate prices nationwide have lost about 40% of their value on average. So families saw their fortunes fall by 60% to 70%, on average. When that happens, what do you do? You consume less, save more, and, to the extent possible, pay down debt. That’s exactly what typical middle-class Chinese families have done over the last five years.
Domestic demand has been growing more and more slowly, and today it’s roughly zero. The savings deposits have risen to about 120% of GDP, which is probably the largest savings deposit anywhere in the world: basically, 165 trillion RMB. People have also been through two or three years of roughly zero price increases, or slightly negative price changes, and that has given them some concerns about the future.
That’s one tier of the economy. But when you look at the other tier, at the Chinese government’s objectives over the last 10 years, and especially the last five, you see a remarkably different picture. Chinese manufacturing has finally broken through the low- to mid-end and moved firmly into the mid- to high-end. Every one of the Made in China 2025 objectives has been met.
Over the last five years, China has also made tremendous progress in solving bottleneck problems. Take semiconductors, for example. It turns out that U.S.-led technology sanctions have been a godsend for the Chinese semiconductor industry because they created one of the most precious things in a market economy: demand. Ask any entrepreneur what the most important thing is, and they’ll say it’s the order book. If you have revenue, the whole ball starts rolling: more revenue brings profit, which brings R&D, which brings improvement, which brings more revenue.
That has happened to the point where, on mature nodes, China has achieved almost complete self-sufficiency on both the equipment and fabrication sides. On more cutting-edge, advanced nodes, China is getting close to self-sufficiency, with a few key ingredients still missing. If things continue this way, that self-sufficiency will come about naturally.
That’s just one aspect of it. One of the key capabilities of generative AI is producing intelligence at scale, on demand. One of its biggest applications is code generation, which solves the biggest problem in some of these bottlenecks: the missing operating system code layer. From PCs to servers to NVIDIA’s CUDA system, one by one, all of these are now being replaced with the help of AI. So this becomes a great equalizer.
Field after field, over the last 10 years, you’ve seen remarkable progress in moving manufacturing from the low- to mid-end into the mid- to high-end. In some areas—new energy, EVs, storage, batteries, you name it—it goes on and on. In heavy machinery, they’re dominant and becoming global leaders. In areas where they face bottlenecks, China is also beginning to move forward and close the gap.
At the same time, this has come at a very heavy cost to other industries. Real estate, for example, is now down about 70% in annual new sales. That 10 trillion is also exactly how much has been spent on upgrading manufacturing and improving technology efficiency—about 10 trillion RMB a year. If you look at the divergence, it’s exactly around 2021.
But that has been the development model. If you look back at how China has developed over the last 50 years, roughly every 10 years, in my mind, there’s a new set of objectives and targets, and they come with a heavy cost. Sometimes, over the next 10 years, the objectives become the cost. In the early days of industrial takeoff, the environment—air pollution and rivers—became the cost. In the following two decades, those became the objectives, and new environmentally friendly technologies were developed. The polluters became the cost.
Then, during urbanization, real estate developers were the objective. They built out China into what it is, creating home ownership and a firm middle-class wealth base. Over the last five to 10 years, they became the cost, and they’ve suffered quite a bit. But overall, you can see the country’s progress through those periods. That’s how you can compress a few hundred years of development into, say, 40 years.
At any given time, as an investor or entrepreneur, you always want to know whether you are the objective or the cost. I’m sure all of those people from China would strongly identify with that. Being the cost of a state objective is no fun. I’m sure all of you know that intimately, or have friends who have been intimately involved in the process, but that’s how development has happened.
Overall, if you give it a score, you would say that, through all of those changes, a country of this size and population has now emerged and finally embarked on a complete course of modernization. But because of the two-tiered economy and the general loss of confidence, the financial market has been stagnant for 10 years, going nowhere. Meanwhile, some of the greatest globally competitive companies are trading at very low prices. Again, you have the bifurcation you see here. But if you’re one of the few rational investors who looks at the whole picture, you might take a different perspective. I would say that in today’s market, you’ll probably find better opportunities than you would at other times.
Yeah. What do you want to—
I’m going to take questions in a moment, so get your questions ready and raise your hands. I want to ask you one last question, very quickly. You founded Himalaya Capital in 1997. I arrived at the University of Chicago around the same time as a young assistant professor. The world, at least to me—I don’t know how it looked to you then; we didn’t know each other—was very different from how it looks to me now. It was open and transnational, a world where we could travel and do so many things. It had a generosity of spirit that seems to be a little lacking today. It looks very different to me now. I want to ask how you see it going forward, and whether you incorporate any of those ideas into the way you think about investing.
5. The Global Market Order
Yeah, it’s a great question, Tano. The world has changed over the last 30 years. There’s no question about that. The world order, or the big questions of how the world governs and operates itself, changes on a slow scale. It takes a decade, sometimes a hundred years, for the order to form and transform.
The current order was founded through two great world wars, which brought the whole world to the brink of collapse. Out of that emerged the American-led order, which, through the Cold War and the end of the Cold War, became one order. Now it’s transforming once again into something yet to be seen—to see what emerges out of it.
But underneath, there’s another order that has been steadily forming for the last few hundred years: the economic order. The economic order forms when more and more countries and populations join in common trade and transact business with each other.
They form a common market. That common market was finally formed roughly 30 years ago, with the collapse of the Soviet Union and the end of the Cold War. Virtually all countries and populations began to join one market economy.
What is interesting about this economic order is that once a common market is formed, it is very difficult for any single country to withdraw voluntarily. Out of the market come efficiency and a flywheel of continuous improvement through technology, division of labor, and trade in resources. Any country that withdraws for an extended period of time would incur a great deal of cost. Once formed, the market is very difficult to disintegrate. It lasts much, much longer.
You look at the trade wars and trade frictions over the preceding 100 years. No matter what frictions or barriers you erected, people would find a way to trade through a third country, essentially along the same principles of comparative advantage. Take U.S.-China trade as an example. Of course, that has declined. But if you look at overall U.S. trade with, say, Mexico plus ASEAN, you see the exact offset. Basically, U.S.-China trade has remained the same; it just goes through a third-party country. That is roughly true in most other markets as well.
The political order is that the U.S., having led the globe for 80 years and shouldered most of the cost of ensuring the economic common market functions as it sees fit, began to realize that the cost and the benefit it derived from it were probably a bit out of proportion. It began to voluntarily withdraw some of those responsibilities, though not very successfully so far, and left a vacuum.
The single biggest change in the political order is the rise of China over the last 30 or 40 years. It has become an enormous economic entity, with a complete set of manufacturing and technology capabilities, self-sufficiency, and the single largest market, which is also open and has unified regulation. That is a huge change to both the political order and the economic order that we are now witnessing. Those are the changes we are seeing.
At the same time, our mutual dependency—as I said, we have one single market—has increased, not decreased, over that period of time. I’ll give you one example. In generative AI, the one thing everybody needs is chips: semiconductor chips. Where are those chips being made? Think about all the countries that produce semiconductor chips. They have one thing in common. What do you think that might be?
Sorry, I’m not putting you on—
You’re putting me on the spot. Now I have to think about semiconductors. I was thinking that I needed to open it up for questions.
Oh, you’re not—
What do they all have in common? One thing that all the places producing semiconductor chips essential for this current technological wave, which the whole country seems to be betting on, have in common is that every country and all the people who produce semiconductor chips use chopsticks. Think about that.
Sorry.
Actually, India doesn’t produce semiconductor chips. You don’t use chopsticks.
Yes, that’s right. I mean fabrication.
And, of course, all the people leading the semiconductor companies in this country also use chopsticks: Jensen, Lip-Bu, Lisa, you name it, Hock—all of them. So there is a great deal of mutual dependency, as you can see. If you’re betting to the extent that we’re currently betting as a country, as a company, as companies, on this new technology, whatever the problems and perils may be, you have to be nice to people who use chopsticks. And it’s not changing. It didn’t really happen by accident. We can go into why.
Look, there is a reason the president of the United States and the president of China find it urgent to meet four times in eight months. Okay, two of them—the other two, really—the most important accomplishment of every meeting is that we schedule the next meeting.
Yeah.
And this comes from the term “strategic stability.” In other words, stability is of strategic importance. It highlights the sense of one common global market, the cost of withdrawing voluntarily from it, and mutual dependency to keep it peaceful. And, of course, everybody is meanwhile competing fearlessly, all believing that time is on their side. China wants to complete semiconductor self-sufficiency and all kinds of other things; the U.S. is hoping for an AI breakthrough; other countries have different calculations.
But it all highlights that peaceful stability is of paramount importance to everyone. It is of strategic importance, and the largest countries really do have the responsibility and also the desire to keep it that way. All countries will feel the weight of one single common market and the cost of withdrawing from it. And so the world, by and large, will continue to progress in that regard.
The order that we have been familiar with since the end of World War II is somewhat changing and transforming. What will emerge from it, and in what format, is yet to be seen. But the underlying formation of something else with a more permanent impact—the formation of one single global common market—is here to stay.
Now, what is the implication for an investor? We come back to our basic tenet of value investing. Of the six principles, the last one that we added is that, as a global investor, your wealth is expressed as your percentage ownership of global purchasing power. One way to accomplish that—and certainly the way we have been practicing—is by buying great businesses in dynamic countries and markets at advantageous prices and holding them for the long term to create value, preserve our percentage, and grow it over time. That’s the way we have practiced it.
Back to Warren’s analogy of the stock market as a church with a casino attached to it: what Berkshire has accomplished over the last 60 years is to build that church into a gigantic cathedral, in which it not only symbolizes and functions, but people can also find spiritual solace because it provides the right function, what the market exists for.
What we have been trying to practice over the last 30 years, back to your question, is that we want to prove that the gospel can be spread. We can build churches in other countries. We chose to build that church in Asia, as well as in other regions, as a global investor. Over time, some of the churches will appear in different countries. Some of them might grow into a cathedral as well.
And that comes back to your other question to the students and the young professionals: what would you choose to do in this market? This is the basic setup: a church with a casino attached to it as part of the permitting process, because of the human condition. But they do have different implications for society as a whole. On one side, you have a win-win approach and a net benefit to society. On the other side, you have zero-sum and a net cost, a net negative impact on society. The choice is all yours, and technology, including AI, will remain a tool, not a replacement.
If it has any tendency to replace a human, as I said, we will all be united to oppose such a creation of a man-made god. Therefore, my view is that you don’t have to participate in perspectives that call that an IPO of a demigod. That is one way to express our collective duties to a good society. That’s why this program exists, and I think it ought to continue. So thank you very much.
Thank you. That’s perfect, actually. We have 15 minutes for a couple of questions. All the way in the back—you were the first to raise your hand, so you get the right to do it. The only thing is that I’m going to ask you guys seriously to make it quick. Okay?
Yeah, just real quickly. Ed Lugo from EL2 Capital. Thank you again. I really appreciate it. I just want to get your sense of the difference between Chinese AI and American AI. That would be great. Thank you.
Good. I’ll take two more questions at the same time. Someone else was raising their hand. Yeah, all the way in the back there. You have one, and someone here too.
It’s from Johns Hopkins, and you mentioned the Chinese market. I want to hear your opinion about whether the Chinese stock market could be an objective or a cost.
That’s a good question, actually. Yeah.
Hi, Dan Bakularz from Unison. I’m just curious how you underwrite political risk when the rules can change overnight, considering you’ve been so successful investing in Chinese businesses.
Okay, good. So, the Chinese approach toward AI, whether the Chinese market is an objective or a cost, and how you underwrite political risk—they’re all connected, of course.
If you describe the Silicon Valley approach to AI, the fundamental question is, “What else can this technology do?” That’s the primary question. That’s why they still call them labs—as research labs. “I want to see what else it can do. How far can we push the edge of it?” That’s why I also call it a frontier. The Chinese AI companies, I would say, are fundamentally curious about those questions as well. But in addition, and more importantly, they ask, “What can this technology do for my customers, both my consumers and enterprise customers?” There lies a very different approach, and you can see from various metrics how the results will be different.
The Chinese stock market: is that an objective or a cost? At different times, the emphasis is different. But when you think about the primary balance sheet of both individual families and a nation, when real estate as a proportion begins to really go down—in one way, by the way, it doesn’t really go down forever, because it has real value—what in its place would constitute the wealth of the nation and the wealth of the people and the families? When you answer that question, you would say that at some point, whether it’s today or another time, it has to be.
And so that is the only asset that grows with the economy. In fact, it grows because of the economy, and it is also the reason why the economy grows. They are all basically in a flywheel together.
On political risk, that comes down to really understanding the objective at any given time, the history, and examining the record of all of it. That doesn’t really relate just to China; it relates to the U.S. and a whole bunch of different countries. Our whole world is still somewhat organized around sovereign nation-states, and that’s just the reality we live with. So, with all the considerations we’ve talked about, we should apply that to every country in which we operate.
Okay, next set of questions. As many questions as we can get. Let’s say there’s one gentleman over there and another young man over here. Please go ahead.
Daniel Chief[?], from New Jersey. Can you apply some value investing principles and strategies to invest in growth companies or high-tech companies? Thank you.
Okay, the tech question.
My second question is about the convergence of energy and intellectual capital, because the energy markets are now highly correlated with the consumption of knowledge-based businesses. I’m wondering whether this has implications for solving problems or creating problems, including climate and environmental issues. I’d also love to hear your thoughts on crypto markets in the context of global financial conditions. Thank you.
You’ve got three questions there in one, but I’ll forgive you.
I’m Homing Li[?], representing ACT Capital and a Columbia alumnus. I’m already in the Columbia Value Investing Group and have been practicing for two years. In the investment business, when you try to preach value and see everything leap away, the risk of underperformance can become a real career risk. How do you think about it?
That’s a wonderful question.
There are five or six questions in there somewhere.
Yeah, exactly. We’ll leave tomorrow morning.
Value investing principles and growth and technology companies, energy and its implications for current AI and climate change, and somehow I have to relate it to crypto.
You can do it, Li Lu.
Sure. In fact, I can do it very easily. On the question of underperformance and how you keep yourself in the business even now that you’re two years into it: first of all, the value principle. Put it this way: I think all investment—all intelligent investment—is value investment, because you always want to get a little bit more than what you pay for. What you pay is a price; what you get is value. That value could be in a business that is stagnant or even declining but pays you a whole bunch of money back, a company that is rapidly growing, or a bet with a small probability of winning and a large probability of losing, where you therefore spread your bets.
All of that comes down to your understanding of where value will be created. At the basic level, they are all discounting future cash flows to the extent that you can understand and estimate them accurately. So they all come down to the same mathematics. That’s why I said almost all intelligent investing is value investing. The basic principle doesn’t change; it can apply differently depending on where your circle of competence is. I’ll go back to the concept Warren articulated so well: the circle of competence.
Energy is obviously essential. It’s an essential layer of the economy. I’d say energy, transportation, manufacturing, communication, and knowledge-based services essentially make up the entire economy. Of course they have applications at every single layer. Right now, the constraints on AI run from chips to electricity to labor. Of course it applies differently, and of course it has an impact on climate. We could analyze almost any aspect of any one of those subjects.
But your third question, about crypto, has a very simple answer: I don’t think anything of it. I think eventually it will disappear on its own, and that’s okay. It’s fundamentally bogus. What really constitutes a redeemable currency? It is reinforced by the force associated with it. Without that enforcement mechanism, you can’t really have an enforceable means of settlement or a store of wealth. Some guys creating something in a garage doesn’t do the job.
It helps criminals and facilitates all kinds of illicit transactions. I think we’d all be better off banning it, but that’s okay. If somebody wants to collect it, the same way people think a certain artist is worth a certain price, that’s a personal preference. But as a society, I think nothing of it.
Your question is very real. You’ve bought into it, but then of course you also want the corporation to cooperate with you. As I said, that’s where human psychology comes in. Everybody wants the best of both worlds. They want to be doing win-win, but they also want to report good numbers every year—preferably every quarter, every month, every day, every hour. Pretty soon you become a speculator.
You can’t have both worlds. Either you think the market is there to instruct you, or you think the market is there to serve you. You can only take one of the two. If you want to mush all of it together, you’re better off indexing, because that’s exactly the average of all the market participants. The four different kinds of market participants average out to the index, so you’re better off doing that.
If you ask how to make a business out of it, in the end you have to have people with a like-minded approach who stick with you. The difficult thing about doing this line of work is that you have to be a bit of a contrarian in terms of human nature. You’ve got to have some element of a mutant gene to think you’re right because logic and facts say so, not because anybody else agrees or disagrees with you. That requires a different kind of psychology, and some people fit it. If you decide you don’t, then don’t even try.
You also need people who believe in it to be along with you. You can’t say, “I want to have the biggest fund and the most AUM.” It doesn’t happen that way. You get what you deserve in the end. I hope that’s helpful.
Yes. On equal opportunity grounds, I’m going to take a question from this side.
Hi, Li. Thanks so much for doing this. Alex Captain with Cat Rock Capital. You’ve been such a successful investor for such a long period of time. What have you learned in the last 10 years that you think are the most important lessons that make you a better investor today than you were 10 years ago?
If I can sneak in a second question: you keep your mind and body very sharp. At 60 years old, you’re taking three questions at a time and remembering all the nuances. I’d love to hear about your daily or weekly routines to keep your mind and body sharp.
This is a question about—
You’ve got a few questions.
This is like the Martha Stewart segment of the conversation, about your diet and—
Yeah. Okay, good. Anybody else? Or let’s just kind of—
Yeah, another quick question.
Maybe two more.
My question is about structural changes in the U.S. and Chinese capital markets.
Say that again.
Looking ahead a decade or more, what are the most important structural changes in the U.S. and Chinese capital markets? Thank you.
The most important structural changes we can expect in the Chinese capital market?
Structural changes about China and also the U.S. capital market.
If you’re very comfortable saying “Chinese,” why don’t you say it in Chinese?
I’ll translate.
Say it in Chinese. Now I got it.
You got it? I’m still struggling. I choose to understand whatever I can understand with my limited ability, now that I’m 60 years old. Thank you for reminding me.
Yeah, exactly. One more. Last one.
Hi, my name is Wai, with First Manhattan. When you’re underwriting an investment, how do you ensure you have an adequate margin of safety and downside protection?
Okay. From the mundane to the more structured questions: where do you see the margin of safety, what did I learn in the last 10 years, and how do I stay engaged this far into my career? And the structural changes between the U.S. and Chinese markets, which I’m not sure what that means, but I’ll say something along those lines. I’ll take a guess.
One of the distinguishing characteristics of a value investor, compared with most other investors, is the enormous premium they place on downside protection. Investing is obviously predicting the future, which is inherently unpredictable. So what you do is invest in the things you know. What you know may be limited. Everybody starts with very limited knowledge, and that’s how I started when I was in my 20s. I didn’t know much, so I went with the things I knew were there. The balance sheet obviously works, as Ben Graham teaches, because some things are easier to understand. Then I gradually progressed from things that were simple to things that were less simple and more complex. That’s a natural progression in terms of the circle of competence.
With the circle of competence, one thing is to understand its boundaries; the other is consciously to expand it gradually over time. I always say: if you can compound your knowledge in a sustainable fashion, eventually you can compound your capital as well.
So that's really back to your question: what have I learned over 10 years? Every 10 years, I find I've learned so much that you almost have to become a somewhat different person. In a way, you do want to have that renewed sense that, over a long period of time, if you do the right thing in the right way, it's remarkable to find that you actually compound.
This is another reason I would say that if you choose to go toward a win-win situation rather than a zero-sum one, you can compound your ability and your knowledge, and perhaps your health, too. Maybe not your lifespan, but you can prolong your productive span and your health span because you keep life engaging and interesting. You know it's helpful to society, and you're not taking away from society.
The trouble with zero-sum games is that a lot of human nature tends toward zero-sum thinking in the short term. Whatever you learn today is useless tomorrow. You don't accumulate. And so you rely more and more on impersonal things. You get bigger computers, and now you use AI, and of course you'll be replaced at some point. So what is the value of that as a human? Of course, I like the human in the loop. I advocate learning, having an engaged life, improving over time, and compounding your knowledge, as well as other people's capital, in a trusting way.
What my mentor, partner, and teacher Charlie Munger always advocated was the relationship. You can discover the highest order of relationship in a web of deserved trust—a web of deserved trust. There lies a whole philosophy of approaching life in a productive way that is win-win for society as well. So I recommend that anyone starting their career lean toward that way of life.
Yeah, it could really take years; it could be slow. But slowly, surely, you'll get where you deserve to go. That is just a better way of living, in a sense. Of course, some people have a little more luck than others along the way. Our lives, our successes and failures, are sometimes a combination of lucky and unlucky breaks. We get a fair share of all of it. And I, for one, never felt our record was entirely due to genius or anything. We got so many lucky breaks along the way.
But if you choose the right partner, the right approach, the right people to bet on, and the right things to do, over time, it's remarkable how compound returns work. The basic idea of compounding is that you don't lose what you already have. And that's a profound idea: you don't lose what you already have. That includes your knowledge, your trusting relationships, your wisdom, and even your health. Those are amazingly powerful things to have in life.
Okay. In that regard, I think the U.S. and China are structurally the same. In fact, that's the structure of humanity. That doesn't necessarily answer your question. I'm sure maybe we'll find a different time to discuss exactly what you mean by structural changes. But there are always changes in life. This is the one constant that we're always going to have to deal with, and you'll always have your share of luck and bad luck, and there will always be great opportunities, no matter which way you naturally lean.
But finding something you're naturally inclined toward and building on it over time, in a compounding and cumulative fashion, is just a better way of living a productive life. So with that—
Thank you. Thank you so much, Li Lu. This has been wonderful.