One of the more frustrating aspects of being an investment manager is that markets can outlast your convictions far longer than you can endure the pain of losses. The past three years have been that kind of period. Watching portfolio holdings that generate high free cash flow margins, high returns on capital, and continue to grow market size lag behind anything associated with artificial intelligence is very difficult. These underperformers are all companies with deep competitive advantages that value investors like to call wide moats. 
 
So, why aren’t these wide-moat stocks holding up better? It’s a question we've had since 2024, and it intensified in the first quarter of 2026. During that period, the broad US stock market declined by more than 4% and many high-quality, competitively advantaged companies, as defined by the Morningstar Economic Moat Rating, fell even further.
 
These stocks underperformed when one might expect a move toward quality, driven by worries about higher interest rates or a collapse in the AI story, to make their attributes a welcome haven. But they have not proven to be a sight for sore eyes. Rather, the exact opposite. 
 
What Is a Moat?
 
Since I began my career as an investment advisor, I have religiously followed the idea of investing in companies with deep competitive moats. First articulated by Warren Buffett, the concept is that, much like a medieval lord, the most important assets can be protected by digging a moat around a castle, thereby preventing a rival from easily capturing his/her home ground. The deeper and wider the moat, the better the protection. Buffett’s concept was no different for corporations. By digging a competitive or economic moat, a company can prevent competitors from stealing market share, cracking a technological advantage, or forcing economic changes that drive down margins or profits. 
 
At Nintai, we see moats providing both defensive and offensive advantages. For instance, a pharmaceutical company might dig a deep competitive moat by securing patent protection for a new therapeutic drug (a defensive moat). At the same time, these patents provide the company with a jumping-off point to greatly expand the
 
 
company’s reach within a specific therapy class, such as Type 2 diabetes (an offensive-oriented moat). 
 
Morningstar (MORN) has led the way in making moats an integral part of valuing potential investments. Here’s what they say. 
 
“Morningstar analysts assign every company they cover a Morningstar Economic Moat Rating of wide, narrow, or none. A company whose competitive advantages we expect to last more than 20 years has a wide moat. One that can fend off its rivals for 10 years has a narrow moat. A firm with no advantage, or one we think will quickly dissipate, has no moat. Morningstar has identified five sources that create economic moats:
 

1. Network effect occurs when the value of a company’s service increases for both new and existing users as more people use the service.
2. Patents, brands, regulatory licenses, and other intangible assets can prevent competitors from duplicating a company’s products or allow the company to charge higher prices.
3. Firms with a structural cost advantage can either undercut competitors on price while earning similar margins, or they can charge market-level prices while earning relatively high margins.
4. When it would be too expensive or troublesome to stop using a company’s products, these switching costs indicate pricing power.
5. When a niche market is effectively served by one or only a handful of companies, efficient scale may be present.” 

 
A company that can hold off competitors from advancing their own products and has deeply embedded itself in its customers’ operations should be able to outperform those competitors. You would think – all other things being equal – that a basket of companies with wide competitive moats would outperform a similar basket filled with a blend of wide, narrow, and no-moat companies. 
 
But since 2021, that hasn't been the case. According to Morningstar, the Wide-Moat Index has underperformed the broader US Market Index, and it’s not even close. Over the trailing three-year period, the US Market Index outperformed the Wide-Moat Index by 9.39 percentage points, with returns of 20.48% versus 11.09%. A major driver of 
 
 
this underperformance was the 35% annual returns generated by no-moat semiconductors. It doesn’t improve over a trailing five-year period. Over that period, the US Market Index outperformed the Wide-Moat Index by 12.45% to 8.86%, a 3.59% gap. At Nintai, we’ve seen similar returns, with our portfolio holdings having the widest moats, significantly underperforming the S&P 500.  
 
So, what gives? Is there a plausible explanation for this extended period of underperformance, or is it just bad luck?  Is our ability to define, measure, and identify outstanding companies suddenly deeply impaired? Have we lost our mojo? 
 
Looking back, two main reasons explain why the wide-moat cohort has performed so poorly relative to its no-moat cousins. First, nearly all the truly outstanding returns over the past three years have come from the artificial intelligence (AI) space, where nearly 80% of the stocks are narrow or no-moat. That makes sense, since it is extremely difficult to model how these companies’ return on capital will exceed their cost of capital over the next decade or two. Second, nearly all the huge gains (not just AI)  have been concentrated in the technology space. Entire industries – energy, consumer defensives, healthcare, etc. – have lagged tremendously over the past three to five years. It’s impossible to tell when this remarkable concentration of returns might disperse, but for now it continues along the same path. Since Nintai doesn’t invest in many AI technology companies, our portfolios have lagged the Morningstar Wide-Moat Index in the same way since 2021.  
 
In the past quarter, we’ve seen wide-moat companies break out from their slump and handily beat their narrow and no-moat competitors. Will it continue and replicate the performance during the 2016-2020 bull market? We have no idea, but we like our chances. Until then, we will continue investing the only way we know: high-quality companies with deep competitive advantages and rock-solid financials. 
 
I look forward to your thoughts and comments. 
 
DISCLOSURE: None
 

​A quick update on last week’s article about single-stock levered ETFs. In the article, we discussed the potential dangers of these financial instruments and how they play no role in an individual investor’s portfolio. Shortly after publication, we learned how quickly things can go sideways in such an investment. 
 
In April 2025, Granite Shares launched a leveraged single-stock ETF (LCDL) that provided 2x leveraged exposure, less fees and expenses, to the daily price movement of Lucid Group (LCID) shares. On July 14, 2026, the share price of Lucid Group, Inc. declined intraday by more than 50% from the previous day's closing price. 
 
In accordance with the Fund's governing documents and the terms of its swap agreements, the swap counterparty exercised its contractual right to close out the swap position after the intraday decline. On July 14, 2026, the ETF's per-share value fell to approximately -$0.016. This negative NAV resulted in a $0 return for investors upon liquidation.
 
This comes while South Korea's financial regulator stopped new listings of single-stock leveraged ETFs and increased the minimum deposit requirement to 30 million won after the Kospi index dropped roughly 26% from its June high. These ETFs, which provide double the daily returns of Samsung Electronics and SK Hynix shares, along with the two chipmakers, represent over 70% of total trading value in the Korean market.
 
These single-stock leveraged exchange-traded funds, which debuted in May and aim to double the daily performance of Samsung Electronics and SK Hynix, hit the market as excitement for Korean stocks was hitting a peak. They have drawn flak for intensifying volatility in the nation's top AI-related equities. 
 
As we mentioned in our article, investors’ understanding of the risks associated with these funds and the method in which returns are generated is extremely limited. They should never have been offered to individual investors and are another sad story where money can be made, the financial markets will ignore basic risks and dive in headfirst. 
 

“Sometimes getting everything you wish for can be a very dangerous thing. Purchasing a single stock levered ETF is just that – an investment in a completely focused manner, leveraged to add rocket fuel to returns. Add in volatility decay and compounding, and you're looking at a quick way to suffer devastating losses.”
                                                                                -    John Thurber  

“Levered ETFs may appeal to those who wish to hedge other positions, those with strong directional views, or those with so-called ‘lottery preferences’.” 
 
                                                                                -      Hendrik Bessembinder

Overview
 
In 2025, with the Magnificent Seven stocks in focus, investors have sought ways to capture returns from individual members of the group. Single-stock levered exchange-traded funds (ETFs) have adopted these strategies and have proliferated. In particular, retail investors have focused on names such as Nvidia, Tesla, Meta, and Amazon. Once considered tools for professional traders, these funds have now become the latest playthings for day-traders and other individual investors/speculators. 
 
Single-stock levered ETFs are designed to provide magnified exposure, typically two to three times, to the daily price of a single stock. Rather than using margin, these funds use derivatives (such as futures contracts or swaps) to achieve their leverage. Unlike traditional ETFs that track a broad index or basket of securities, these funds concentrate all exposure on one stock, making them inherently more volatile. 
 
These products first appeared in 2022 and were immediately identified as prime opportunities for individual investors to lose a substantial amount of money. This assessment was based on concerns that expenses were prohibitive, and volatility decay was poorly understood by retail investors. Did that stop Wall Street? Not a chance! Within a few years, companies such as GraniteShares and Direxion were flooding the market with hundreds of such products. They perfectly met the growing desire for short-term trading (minutes rather than hours, days, or, God forbid, weeks) that (supposedly) promised potentially very high returns. 
 
There are a couple of reasons why these ETFs have suddenly become so popular. First, retail investors are increasingly attracted to speculative strategies as they get an ever-increasing amount of research from sites such as X (formerly Twitter) and Reddit. Similar to the meme stock craze, these sites have become hubs for increasingly ridiculous trading strategies. Second, it isn’t enough to recommend rapid day trading; it also encourages leveraging the size of your return (or, more likely, your losses). Investors don’t need to open margin accounts or meet regulatory requirements when they can simply click to purchase shares of a 3x leveraged ETF. For those seeking that kind of workaround, single-stock leveraged ETFs offer a compelling way to supercharge bets on momentum names without the complications of margin trading. 
 
What Could Possibly Go Wrong?
 
Of course, for every person who boasts at the neighborhood barbecue that they tripled their investment on the Hot Stock Triple Levered ETF, there are another four who remain silent and unwilling to share the shame of losing three-quarters of their investment in a similar ETF. 
 
Single-stock leveraged ETFs were not created for investors. Rather, they were designed to serve a very narrow niche of traders seeking additional exposure over the course of a single day’s trading. These funds can erode value incredibly quickly, to the point where the underlying stock might go up slightly while the fund loses money. How can that be? To better understand these two, we can turn to our go-to academic investment guru, Hendrik Bessembinder, at the W.P. Carey School of Business at Arizona State University. In a paper published in 2025[1], Bessembinder divided the cause of ETF underperformance into two buckets: daily rebalancing trades and frictions such as fees, trading costs, and excess loan margins. 
 
Bessembinder found that long-levered single stock ETFs underperform by an average of 0.79% per month, with 0.26% attributable to daily rebalancing and 0.53% to frictions. Breaking the ETFs into positive leverage versus inverse leverage, Bessembinder found that friction costs were higher for positive leverage (average of 0.53% per month) than for inverse leverage funds (average of 0.26% per month), while rebalancing costs were higher for negative (average of 0.73%) than for positive leverage (average of 0.27%) funds.
 
What investors need to understand is that even if they ignore the high friction costs Bessembinder identified, these products are designed to provide leveraged exposure to daily returns, not long-term performance. Anyone who invests in these funds, thinking they can buy and hold or seek long-term gains, will be quickly disabused of these notions. As an example of truthful marketing (ever so rare in today’s investment world), Direxion (one of the leading providers of levered ETFs) describes its target market as follows: “Now risk-hungry traders can get daily 2X bull or -1X bear exposure to heavily traded individual large cap stocks.” (emphasis mine). Note that “risk-hungry” and “daily” are specifically mentioned as attributes of their target investor. 
 
A Working Example: The CSOP SK Hynix Daily (2X)
 
Ground zero for the explosion of single-stock leveraged ETFs is Hong Kong. The South Korean company SK Hynix is a major player in the artificial intelligence (AI) market. Together with Samsung, the two companies account for over 60% of the benchmark KOSPI index's total market capitalization. Given SK Hynix's importance in the AI space, investors poured into the CSOP SK Hynix (2X) leveraged product. Launched in October 2025, the CSOP SK Hynix leveraged ETF has ballooned into a $13 billion fund, the largest of any leveraged fund. On volatile days, the ETF and its smaller peers can account for two-thirds of trading in SK Hynix shares. This is shocking for a company with a $1.2 trillion market cap. This has placed enormous strain on financial players around the globe to create a system using a disparate group of financing and hedging to support the ETF’s operations. The numbers have become so large that it is unclear who is driving the stock price – the stock or the ETF.  This is all part of the broader leveraged AI-focused fund market, which has grown to $250 billion. (Remember: this is just AI-focused!)
 
The problem with this is that the CSOP SK Hynix ETF can drag down the entire South Korean market and even significantly impact global equity markets. This past Thursday (June 25, 2026) delivered another reminder of that risk: The ETF plunged more than 20%, as it had early last week, helping drag the stock down more than 10% and triggering a 2% slump in MSCI’s benchmark emerging-market index. Just one ETF provoked these results.  
 
Conclusions
 
It’s hard to say where this is going to end. The rise of single-stock leveraged ETFs marks a significant evolution in retail speculative investing, offering powerful tools to those seeking amplified returns while also carrying equally significant risks. As with all high-powered investment vehicles, success depends not just on opportunity but on understanding. There aren’t many investors (or should we say, speculators?) who fully understand the underlying danger of levered single-stock ETFs. The risks associated with volatility decay and operating expenses far outweigh potential gains for most investors/speculators. By their very design, levered single-stock ETFs are a loser’s game. It shouldn’t surprise us that Wall Street and other financial engineers have created such ugly beasts. The question is how much damage these products will cause. The worst losses in Wall Street’s history have stemmed from failing to recognize the link between risk and the additional dangers of leverage. We can only hope this product’s life is short enough to prevent a truly global problem. Unfortunately, history – and investor greed - doesn’t give us much hope.  
 
DISCLOSURES: None
 
[1] “Returns to Constant Leverage Strategies: General Principles and Application to Levered Single-Stock ETFs”, Hendrik Bessembinder, July 28, 2025

In the mid-2000s, we began to observe a shift that could affect our investment theses across several of our holdings and create new opportunities on our investment watchlist. When we began our investment journey (all those years ago!), if someone wanted to purchase software, you went to Circuit City (really showing our age now!) and plunked down money for a box with several discs that we used to install the application on our computer. By the mid-2000s, a movement began in which software no longer resided on our computers but was hosted on a remote entity called “the cloud”. Goodbye discs. Goodbye to updates from additional discs. Goodbye to those afternoon runs to Circuit City. Instead, the applications became known as software-as-a-service (SaaS). This new model revolutionized software providers, from the largest, such as Microsoft and Adobe, to the most niche vendors. This move from software to SaaS underpinned many of our investments, ranging from Guidewire (GWRE) in P&E insurance to Veeva (VEEV) in life sciences informatics. 
 
We are now at the beginning of a new era in technology. In the past several years, the idea of SaaS has been gradually replaced by the recent rollout of fully functional artificial intelligence (AI) technology. Will it be as powerful as SaaS was? Who knows. Technologists and investors alike are harkening it to the creation of the Internet. That’s pretty powerful! 
 
What is artificial intelligence?
 
So, what exactly is artificial intelligence (AI)? We think NASA has done a great job of creating a working definition that is easy enough for us laymen to understand. 
 
“Artificial intelligence (AI) is a branch of computer science dedicated to creating systems capable of performing complex tasks that typically require human intelligence, such as reasoning, learning, problem-solving, perception, and decision-making. These systems, including machine learning and neural networks, analyze data to identify patterns, make predictions, and act autonomously.”[1]
 
They list the four major components of AI as:
 
Learning: AI systems, particularly through machine learning, improve their performance over time by analyzing data rather than relying solely on explicit programming.
 
Reasoning & Problem-Solving: AI can process information to make decisions, solve puzzles, or deduce conclusions.
 
Perception: Technologies enabling machines to interpret visual data (computer vision) or audio (speech recognition).
 
Autonomy: The ability to operate under varying circumstances without continuous human intervention. 
 
The use and scope of AI are nearly unlimited. It is expected that AI can replace millions of jobs and streamline business processes. Entire segments of the national economy can be improved and, in some cases, eliminated through full integration into our nation’s economic systems. Of course, one of the major issues in the stock market today is which industries will be most adversely affected by this adoption of AI. In terms of our portfolios, the greatest impact will be with our software/SaaS-based vendors such as Veeva (VEEV), Guidewire (GWRE), ServiceNow (NOW), Arista Networks (ANET), and F5 (FFIV). 
 
The threat and opportunity posed by artificial intelligence
 
AI poses a serious, transformative threat to traditional SaaS by shifting value from user interfaces to automated agents, which is forcing a move away from per-seat pricing. While AI will not "kill" SaaS, it threatens to commoditize basic software, disrupt business models, and reduce headcount-driven revenue. However, enterprise SaaS with deep data moats and workflows will likely adapt by integrating AI rather than being replaced. A great example of this is Veeva. The company is deeply embedded in nearly every mission-critical process in the pharmaceutical and biotechnology industry. Ranging from drug discovery and development to product sales and promotional support, Veeva is unlikely to be replaced by AI, but rather enhanced by its capabilities. 
 
The following are the key components of the AI threat.
 
The "SaaSpocalypse": We think the markets are overreacting to the potential impact of AI on the SaaS business model. Over the past several months, we have seen a bloodbath in software stocks – from some of the larger firms to privately held companies in private equity portfolios. This led to the “Saaspocalypse” you’ve been hearing about in the financial media. While we think AI could have an impact, we don’t expect wholesale destruction in the software industry. (See our previous description of Veeva.) 
 
Workflow Automation: We think this will be one of the greatest areas of impact. We could see AI “agentic” offerings automating everything from simple to relatively complex workflows. This could make companies that build human-facing user interfaces (UI) redundant. 
 
Pricing Models: Many SaaS models are billed per seat (i.e., per user). It is assumed that AI's ability to perform the work of several individual users will significantly impact revenue due to the loss of billable seats. This is what the industry calls “agentic work unit” pricing.
 
There are some more general risks that AI presents to the SaaS model. These include: 
 
Commoditization of Software: AI lowers the barrier to entry, enabling rapid, low-cost development of competing products, which pressures existing SaaS companies to differentiate.
 
In part 2 of this article, I will discuss how our portfolio holdings companies are addressing the encroaching risk of AI. We are comfortable that all of our holdings are either building out AI into their offerings or face little risk. 
 
As always, please let us know any questions or comments you have on this article. 
 
Disclosure: Nintai Investments currently owns shares in Veeva, Guidewire, ServiceNOW, and Arista Networks.  

[1] Executive Order 13960, “Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government”,  
Section 238, National Defense Authorization Act of 2019

“We find whole communities suddenly fix their minds upon one object, and go mad in its pursuit.” - Charles Mackay, Extraordinary Popular Delusions and the Madness of Crowds 
 
As we’ve pointed out quite a few times (some say we are perseverating) over the past few years, we believe the markets are showing classic signs of a bubble. At the risk of continued underperformance, we have taken profits from many of our positions over the past twelve months. Many of you will see that we have reached double-digit cash positions. We have decided to break this article into two pieces. The first will be a brief explanation of what we think are the characteristics of today’s market bubble. An upcoming second article will discuss several key measurement tools we use to ascertain when/how the market data support our thesis. 
 
In 1929, at the height of the post-World War I economic boom in America, Joseph P. Kennedy Sr. was working as a stockbroker on Wall Street. As the story goes, Kennedy was heading back to his office when he decided to get a shoeshine. While polishing his shoes, the young worker shared some of his favorite stock picks. As he listened, Kennedy realized that when shoeshine boys give their patrons stock picks, it’s time to get out of the market. Kennedy exited his market positions and took short positions that bet on the market going down. Was the story true? While probably apocryphal, it certainly proved a point. Market bubbles and their associated tops generally have similar attributes. One of them is that even the most unwise of investors feel like geniuses as their portfolios keep increasing in value with each move. 
 
Having said that, it’s nearly impossible to call the exact moment when bubbles reach their apex. It can be one day, one month, or three years after you become convinced the markets are in one that the bubble finally pops. 
 
So how does one predict when a bubble might implode and take action to protect their portfolio? We think there are several attributes common to all bubbles. When markets begin to exhibit these simultaneously, we begin to reduce our positions and raise cash at Nintai. The major signs we look for are a.) valuations at sky-high levels, b.) a constant refrain of “it’s different this time”, c.) the bubble's theme becomes an inordinately large percentage of market share, and d.) companies beginning to spend like drunken sailors on the new-fangled toy. As we look out today, we believe the market exhibits all of these, and then some. 
  
We should be very clear: we have no idea when or how this bubble will collapse. But it will. Looking back at history, the devastation in the marketplace is usually broad and deep. In this instance, we aim to prevent the one thing that can devastate long-term returns: the permanent loss of capital in our investment partners’ portfolios. 
 
Valuations Have Reached Nosebleed Levels
Overall market valuation metrics, such as the cyclically adjusted price-to-earnings (CAPE) ratio, are at or near historical highs, indicating that investors have extremely high expectations for future growth. The Shiller PE ratio has reached levels comparable to those seen during the 1999-2000 Internet Bubble. In December 1999, the market’s CAPE ratio reached an all-time high of 44.2. In January 2026, the market reached a second-highest CAPE ratio ever of 40.6. The historical mean is roughly 17 - 18. We believe the levels we are seeing in today’s market are certainly indicative of a market bubble. 

Figure 1: Historical CAPE Ratio: 1870 - Present, Source: https://www.multpl.com/shiller-pe

No, really….it’s different this time.
During bubbles, investors are often confronted with questions about their willingness to pay what seem like incredibly high prices for what they’re investing in. The almost invariable response is the assertion that “this time is different.”[1] In recent years, as prices and valuations have slowly risen to nosebleed levels, we have begun to hear this phrase used all too often to explain such conditions. Here are some recent examples:
 
“It’s Different This Time”: Debt
One of the things cited as the major difference between the last technology or real estate bubbles is that AI generates lots of revenue, unlike the 1999-2000 Internet hype. That may be true, but it also matters a great deal about the underlying costs of generating this revenue. For many years, large tech could fund initiatives with strong free cash flows and cash on the balance sheet. No more. In 2025 alone, large tech issued over $121B in debt. In the first three months of 2026, an additional $42B was raised. In Oracle's (ORCL) case, the company has gone from $37B in cash/short-term instruments on the balance sheet in 2020 to less than $10B in 2025. Conversely, total debt has gone from $71B in 2020 to $123B in 2025. The company expects to raise an additional $20-$40B for AI investments over the next five years. Meta's AI spending frenzy has taken the company from a net cash position of nearly $30 billion in 2023 to minus $7 billion today. Some relatively large assumptions are being built into the ability to service such debt. 
 
“It’s Different This Time”: Investors are wiser
We like to think that after the technology bubble of 1999 - 2000 and the real estate/credit crisis of 2007 - 2009, it would be painfully evident to most investors that remarkable returns, inflated valuations, and accounting shenanigans are too good to be true. Unfortunately, this simply isn’t the case. Two instances in particular show that investors never lose their desire to make big profits quickly. Both were fanned by rates close to zero percent, leaving savers with little choice but to seek investment gains in the bond market. 
 
In 2020 and 2021, Wall Street saw an explosion in Special Purpose Acquisition Companies (SPACs). SPACs offered a faster, less regulated path for private companies (especially in tech, EV, and space) to go public than traditional IPOs. SPACs would raise billions of dollars as “blank check” companies, then use these funds to acquire a private company and merge it into their publicly traded SPAC. Over 600 SPAC-based acquisitions received billions of dollars in less than two years. Inevitably, the market collapsed for several reasons. First, SPAC owners made their profit on the acquisition, not on the acquired company’s performance. Second, the explosion in SPACs created a race to acquire with a relatively small pool of quality companies. With both factors at work, most SPACs began to fail within months, as their acquired companies simply weren’t good investments. As usual, Wall Street movers and shakers made their profits, while individual SPAC investors were left holding the bag. 
 
After the SPAC model imploded, they were quickly replaced by the MEMO stock craze. 
A meme stock is one whose company’s financials and business fundamentals appear very weak, yet whose stock price suddenly surges, driven by social media hype (such as Reddit communities or subreddits) and massive retail buying. Frequently, these stocks are heavily shorted by Wall Street players, including private equity firms. This model was a way to profit from short squeezes against these players. It should be noted that this model has nothing to do with investment models utilizing valuation metrics or business fundamentals. This is wholly market gambling, with little interest on investing for the long term. Originating in 2021 with GameStop, the phenomenon has shown resilience, with resurgences occurring as recently as 2024 and 2025. In its later stages, the MEMO stocks began to create their own groupings, such as the “DORK” stocks - "DNUT (Krispy Kreme), OPEN (Opendoor Technologies), RKLB (Rocket Lab), and KSS (Kohl's).
 
It’s Different This Time: Profits
One factor that led to the bursting of the Internet bubble in 1999 was the proliferation of companies that went public with no reasonable way to generate profits, short-term or long-term. We are beginning to see the first ripples of concern as the AI model is questioned about how companies expect to generate a profit. In Q4 2025, Harvard Business Review published a report[2] that questioned this very issue.
 
There’s been a push to have investors focus only on gross revenue, assuming that many of the costs that go into generating net revenue will go away over time. This seems an awful lot like the move to using EBITA as the valuation criterion or the old days of not expensing stock options. As Warren Buffett stated: "If options aren't a form of compensation, what are they? If compensation isn't an expense, what is it? And, if expenses shouldn't go into the calculation of earnings, where in the world should they go?" Or as Charlie Munger so niftily stated, “EBITDA is bullshit earnings.” 
 
Clearly, we haven’t figured out how AI will be profitable. In 2024, OpenAI lost $5B, and Anthropic lost $5.3B. In 2025, OpenAI was expected to lose roughly $8B, and in 2026, roughly $14B. Anthropic, after initially estimating a $3B loss in 2025, saw the actual number come in at $5.2B. Last year, OpenAI committed to $1.4T (yes, that’s trillion) in capital spending on data centers and related infrastructure before reaching profitability. 
 
To become profitable, OpenAI will need to generate roughly $200B in revenue (15x current revenue in 2025) by 2030. Sam Altman, CEO of OpenAI, stated that investors are overexcited and "someone is going to lose a phenomenal amount of money." Not what one wants to hear as an AI investor.  
 
“It’s Different This Time”: AI Lifts All Boats 
In their recent post, “Valuing AI: Extreme Bubble, New Golden Era, or Both?”, 
Jeremy Grantham and Edward Chancellor discussed how AI has become the central focus for market capitalization growth. They write:
 
“The United States, whose companies are at the center of the AI boom, now makes up more than 70% of the MSCI World index. J. P. Morgan estimated last September that 44% of S&P 500 capitalization—over a quarter of total world market capitalization—was accounted for by just 30 AI-linked names. In January 2000, 7 of the top 10 companies by market cap came from the technology, media, and telecoms (TMT) sectors. At the time of writing, the eight largest companies in the world were Nvidia, Apple, Google, Microsoft, Amazon, Meta, Broadcom, and TSMC. Of those eight, Apple is the only one 
that is not a highly active participant in or apparent beneficiary of the AI race (although doubtless there will be synergies between AI and Apple's products). Saudi Aramco, the producer of 10% of all the world's oil, is down in ninth place.”
 
It is easy to see why the Magnificent Seven (or is it Ten now?) has generated most of the equity gains over the past few years. This is where almost all the profit growth across the S&P 500 has come from. This is evident in the chart below. The M7 has delivered consistent earnings growth of more than 20% annually since 2023. Profit growth from the S&P 493 has been much lower, averaging 3% over the same period.

Conclusions
 
The past five years have been extraordinarily difficult for those who haven’t invested in AI/Magnificent 7/Meme stocks. At Nintai, we’re among those who missed out on this cycle. Not investing in any of these stocks has crushed our returns relative to the S&P 500. That said, we aren’t disappointed with the business returns of our portfolio holdings. On average, our companies increased free cash flow by 11.9% annually over the past 5 years. Our average return on invested capital is 31.6%. While our investment returns have been difficult, our underlying businesses are doing just fine. When will things turn around from an investment perspective? We have no idea, but the case we’ve laid out in this (far too) brief article gives us some comfort that we will avoid the inevitable return to the mean. We didn’t boast when we outperformed in the first four years of our investment management services, and we aren’t going to cry in our cups about missing out on bubble-like returns. We will continue to do what we know best – find outstanding businesses with great capital allocators at the helm and let long-term compounding do its work. Until then, we thank our investment partners for their patience and trust in our investment process. 
 
Disclosures: None

[1] We, of course, would be remiss not to thank Sir John Templeton for his classic rejoinder, “The four most dangerous words in investing are ‘it’s different this time.’”

[2] “AI Companies Don’t Have a Profitable Business Model. Does That Matter?”, Danielle Kost, Harvard Business Review, November 12, 2025

“It's not whether you're right or wrong that's important, but how much money you make when you're right and how much you lose when you're wrong." 
 
                                                                                                   -     George Soros 
​
We’ve always valued the wisdom of George Soros and have a copy of the quote seen at the beginning of this article displayed in our office. But over the past five years, we’ve begun to quibble with this quote. We think there is a third option: how much money you make when markets are making even more. Over the past five years, Nintai Investments has generated solid returns for our investors. In fact, we have outperformed our proxies—the Russell Mid-Cap Growth Index and the Russell 2000. That said, we have significantly underperformed the S&P 500 over the past 1, 3, 5, and 10 years. 
 
Monolithic Power Systems: Good, But Not Good Enough
 
We have owned Monolithic Power Systems (MPWR) since 2021 in most of our portfolios. During that time, the company has been performing exceptionally well. As shown below, growth and profitability have been impressive over one-year, five-year, and ten-year periods. 

On October 30th, the company reported its third-quarter results. Third-quarter revenue came in above guidance, rising 19% year over year to $737 million. Fourth-quarter guidance was positive, implying 19% year-over-year revenue growth to a midpoint of $740 million. Here was Morningstar’s take on the quarter and the company’s 2026 outlook.
 
“MPS' strong momentum is continuing, with widely diversified growth across its served markets. We like MPWR’s' ability to win new customers, move up the value chain in key markets, and take market share. Artificial intelligence and automotive growth continue to be bright spots.

• AI revenue was a headwind in the first half of the year, with lumpy order patterns and MPS ceding some of its dominant share. We like that this business is back to growth and anticipate further expansion with the firm qualifying into custom AI accelerators at new customers like Google.
• MPS' march up the value chain in automotive is impressive. The firm won another advanced driver-assistance system design in the quarter. We expect ADAS strength to continue and for MPS to layer in battery management and electric vehicle drivetrain solutions longer-term.
• We expect another year of 20% sales growth in 2026 and see double-digit growth enduring into the long term. We expect data center revenue to grow most rapidly but expect the firm's attractive end-market diversity to prove durable behind widely strong growth across its markets.

The bottom line: We've raised our fair value estimate for wide-moat MPS to $920 per share from $840. We like the company's diverse growth opportunity and continue to see the highest growth in data centers and autos.”
 
From this review, you would consider the company’s quarterly report and 2026 outlook exemplary. Indeed, few companies in today’s market have achieved such levels of profitability, growth, and capital allocation. 
 
For all of this, the day after announcing earnings, the stock dropped by 12% by midday. What in the world would cause the markets to slash the stock price by double digits after such a report? 
 
Two words: artificial intelligence (AI). Market participants didn’t see enough discussion (and market growth) related to AI. Management reported that, in Morningstar’s words, “AI revenue was a headwind in the first half of the year, with lumpy order patterns and MPS ceding some of its dominant share.” We’ve now reached a stage in a market, driven by AI, where a company with double-digit growth foreseeable through 2035 and free cash flow estimated to grow by 18-20% over the same period sees a double-digit price decline because AI revenue was “lumpy.”
 
Conclusions
 
We are in a market that challenges many of the values we've upheld for the past few decades. We've always focused on companies that generate high returns on capital, strong free cash flow margins, little or no debt, and trustworthy management. We have always preferred to let the company and its management handle the heavy lifting over time. Eventually, the returns will follow. Over the past five years, we've seen two market segments—artificial intelligence and cryptocurrencies—drive most of the market’s outperformance. Don’t get me wrong—our portfolios have performed well, delivering roughly 10% returns over the past decade. However, these returns have simply not kept pace with assets that either lack obvious value (crypto) or haven't produced significant free cash flow yet (AI). Ultimately, we are unlikely to invest in either market category. We believe companies like Monolithic Power Systems are excellent organizations that will yield strong long-term returns. AI and crypto? We’re not so sure. But one thing we are confident about is that we will not risk our investors’ hard-earned dollars on such hollow ventures. 
 
As always, we look forward to your thoughts and comments.
 
DISCLOSURE: We hold Monolithic Power Systems in our current investment partners’ and personal portfolios. 
 

To Our Readers:

We will be on vacation from July 27th through August 10th. We are posting an article from the archives in replacement of any new writing. 

“I used to be Snow White, but I drifted.”
                                                                                 -    Mae West
One of the more interesting stories in aviation history is the example of the Gimli Glider. The incident took place in 1983 with the new Boeing 767. Halfway through the flight, the plane ran completely out of fuel and was forced to glide to a former Canadian airbase and make an emergency landing. The mistake was made by a series of human errors and the simple fact that fuel calculations were made in metric (liters) versus imperial (gallons). Having loaded less than 50% of the fuel necessary for the planned flight, the crew found itself flying a glider over Manitoba rather than a jet airliner.
The Gimli Glider story has quite a few similarities to value investing. In the final analysis, a simple mistake can turn an event, a company, anything really, into something quite different than your expectation. The journey getting from point A to point B can become quite different than first envisioned. If a company’s strategy begins to wobble in year two, it’s likely you will be investing in a very different company in year five and something not even remotely the same in 20 years.
The Gimli flight crew thought they were flying the most modern jet airliner in the world. In a matter of moments, they were flying the largest and heaviest glider over flown. Sometimes a value investor thinks they are buying a jet but get a glider. Avoiding these unexpected conversions is one of the top ways to be a successful long-term investor.
In my time at Nintai Partners, I averaged an 8.7-year holding time for each portfolio member. Each year, we would evaluate our investment case of each holding with a particular focus on what we called the “drift factor.” This evaluated how different the company was from a strategic, operational and management sense year over year. Over time, we found that those holdings with the largest “drift” factor were almost always our largest losers. We also found the quicker (or larger) the drift, the worse the loss. Essentially, we were buying a jet that drifted into a glider (no pun intended).
Andrew Carnegie once said the way to become rich is to put all your eggs in one basket and then watch that basket. As a focused investor (from both number of holdings and number of industries), my job as an investment advisor is to allocate capital in companies that minimize drift over the long term. With such focus, the smallest amount of such drift can cause dramatic changes in the quality of the portfolio in a very short time.
That’s why it’s vital to be a very different critical thinker if you want to be a long-term investor. The idea of sitting by a lake reading Barron’s as your companies compound cash is somewhat correct but mostly wrong. Watching that basket all the time is like flying that jet – it takes considerable work.
To me the importance is to track the drift within the context that your holding period will be a decade or more. It’s a difficult path to follow. Here are the important criteria I use to assist in meeting these goals.
Confidence of same industry business in 10 to 20 years
It’s very difficult to invest in a company that you are confident will be doing the same thing in a decade or two. It’s a challenging exercise, but I think can be done with some (the operative word) accuracy. Research in five areas in particular can give an investor a reasonable shot at the potential for drift.
M&A: Has the company had a history of M&A? Are acquisitions largely accretive or small snap-on purchases to enhance current offerings? Do they enhance the company’s moat, making it harder for competitors to catch up? Conversely, has management done a deal that clearly destroys shareholder value?
Regulatory: Does the company have an advantage supported by government regulations? For instance, biopharmaceuticals will have a regulatory moat for branded products that can last a decade or longer. Conversely, is there a risk that regulations may restrict the company’s strategy or operations?
Technology innovation: In 1978, the head of Encyclopedia Britannica was famously quoted to the effect that encyclopedias were the safest product line to bet on in the future. I’m not sure what happened to that executive, but I hope he didn’t bet his future retirement based on his market predictions.
Business process innovation: The phrase “to build a better mouse trap” has been around as long as there has been ... well ... mousetraps. And yet for all the amount of times you’ve heard that phrase, a mousetrap is still a mousetrap, and the model designed in 1934 still has 90% of market share. The catch (no pun intended) is that the price has dropped roughly 90% since its introduction. Almost all of the cost squeezed (OK, that might have been intended) has been in better business processes (cheaper raw materials, cheaper labor, design tweaks, and so forth). 
Competitive moat: Competition can lead your investment company quickly astray. When you think of companies with wide moats from small (WD-40) to jumbo-sized (Coke or Pepsi), you can imagine them selling the exact same product 15 to 20 years from now. Investing in a product with a deep moat managed by great capital allocators is the value investor's dream.
Length of time of the investor’s ownership
As I mentioned earlier, my experience has been that the drift factor can be exponential when it comes to owning a stock for 15 to 20 years. In the doldrums in the history of Coca-Cola (KO, Financial) in the 1980s and early '90s the company actually owned a shrimp farm and Columbia Pictures. How it got from carbonated beverages to raising future cocktail hors d'oeuvres and shooting films is a story in itself, but not the kind of story you want to hear as an investor.
Fortunately, the board and Bob Goizueta recognized the drift factor when they saw it. From 1981 until his premature death, Goizueta increased the stock price by 65 times. If you had held the stock during the '60s and '70s, you might have missed the slow drift away from Coke’s core competency. But for those who held on for the entire tenure of Goizueta, the lack of drift and return to laser-like focus on its core business made many peoples’ fortunes (just ask Warren Buffett (Trades, Portfolio)).
Conclusions
Over the course of my investing career. I’ve had quite a few holdings that fell prey to the drift factor. Several have been due to the deadly urge to acquire while being pushed by consultants’ assurances of “synergies.” Others have been simply that management and the boards didn’t keep their eye on the ball and saw competition fly by. In the case of Coke, they were saved by the fact that their CEO figured out less was more.
Which brings us back to the Gimli Glider. Passengers that day learned that gifted leaders and intense focus (with a little luck) can turn a rather dramatic drift problem into a positive solution. Quick reaction, identification of the problem and a practiced checklist can help an investor too. It can make all the difference between a safe smooth flight or a short and bumpy ride.
As always, I look forward to your thoughts and comments.

“Patience in Market, is worth Pounds in a year.”
 
                                                                   -     Benjamin Franklin, ‘Poor Richard’s Almanack’ 

Over the last four years, we have observed a clear split in the returns of Nintai portfolio holdings. Eight of our holdings (40%) have experienced losses greater than 30%. Conversely, four have returns exceeding 100%, and five more have returns over 50%. The stocks with the biggest losses have hampered the portfolio’s performance during this period. Interestingly, these same companies fueled our strong outperformance in the first four years. Frustrating times, indeed. 
 
This quarter, we decided to review the worst-performing positions and see if any raise concerns about our business case. One of our main worries is the permanent loss of our investment partners’ capital. This can occur for various reasons. The company may have lost its competitive advantages (or moat), the business model could be outdated, or management might have proven to be poor at allocating capital. The question we seek to answer is whether Mr. Franklin’s thoughts apply here - will patience be worth pounds in a year (or more)? There are currently eight stocks that have losses greater than 30% since our initial investment. 
 
Some Initial Thoughts
 
As we examine each of these companies, we try to assess underperformance in various areas. Some of our holdings have more influence over these than others. These include:
 
Regulatory Status: Because a high percentage of our holdings work in a regulated industry (healthcare), those companies in that industry are overseen or regulated by several federal agencies, such as the Food and Drug Administration (FDA) or the Centers for Medicaid and Medicare Services (CMS), which oversee patents, prices, product marketing, sales, and promotion, etc. 
 
Government Policy: Over time, as new congressional leadership and Presidential administrations come to power, there may be significant policy changes. For instance, the latest Trump Administration took an aggressive stance regarding tariffs, which had an enormous impact on nearly every industry. Our role as investment managers is to identify companies that can withstand and overcome numerous unforeseen challenges. 
 
Competitive Moat: Morningstar identifies five potential sources of a competitive moat: switching costs, intangible assets, network effects, cost advantage, and economies of scale. We mainly focus on network effects and switching costs when selecting portfolio holdings because most of our investments are in "asset-light” business models. Within that model, we appreciate companies that provide underlying platforms that enable the company’s relationship to extend deeply into the customer’s operations. 
 
Allocation of Capital: We believe that over time, companies that produce returns on invested capital (ROIC) exceeding the weighted average cost of capital (WACC) will deliver exceptional returns for their investors. To do so, management must be outstanding allocators of capital. This means they must avoid expensive acquisitions, investing in businesses where WACC exceeds ROIC, or investing in assets that generate inadequate returns. 
 
Free Cash Flow Growth: At Nintai, we believe the only real measure of value is the amount of future free cash an asset returns, discounted back to its present value. That amount is the basis for calculating our estimated intrinsic value. If our assumptions are off (and in the cases of these holdings, they most certainly are), then it’s likely our investment case is impaired. 
 
Balance Sheet Strength: Another key factor we look for in any investment is a strong balance sheet. We prefer no short- or long-term debt, ample cash or short-term investments, and only a small amount of goodwill as part of total assets. We want the company to be fully prepared financially for the worst-case scenario we can imagine moving forward. 
 
Some High-Level Thoughts
 
After spending considerable time working through each company’s numbers over the past five years, we’ve identified some common themes in their underperformance. These include the following.
 
There were no cases of decreased financial strength: None of the underperforming companies have seen a decline in their balance sheet strength. None have taken on any debt (short- or long-term) in the past five years. This reassures us that they can withstand an economic shock like the 2007-2009 Credit Crisis. 
 
We were significantly off in our cash flow estimates: While their balance sheets remain strong, we underestimated the free cash flow of some holdings. Six of the eight companies that underperformed have seen free cash flow stay flat or decline. In each case, we projected a (positive) growth rate for the next decade. We didn’t do a very good job with our prognostication. 
 
We overpaid in some cases: Due to our inaccurate estimates of free cash flow, we overpaid on several occasions. In others, we failed to maintain our margin of safety, which led to underperformance not reflected in our purchase price. Whether this was caused by environmental factors (such as tariffs or regulatory changes) or investing outside our circle of competence still needs to be addressed.  
 
We overestimated customer “must-haves”: Several times in our investment history, we have mistaken our holding company’s offerings as a “must-have,” not a “nice-to-have." Several years ago, we believed that Corporate Executive Board (now part of Gartner) was a must-have for their clients. It seems we have made the same mistake in recent years as well.  
 
We were poor policy prognosticators: Some of our underperforming assets have been influenced by changes in the regulatory environment. In these cases, we should have done a better job of identifying potential impacts and modeling the downside more accurately. Some impacts were unforeseen (such as conditional FDA approval), while others were fairly apparent (such as tariffs). 
 
All these reasons challenge some part of our investment research process. We are reviewing them to determine (a) why they occurred and (b) how we can prevent them from happening again. Some say that achieving 60% accuracy in your stock picks is quite good. But that only tells part of the story. What really matters is how much each holding outperforms or underperforms. In this case, our winners have been successful enough to beat our closest benchmarks - the Russell 2000 and the Russell Mid-Cap Growth Index. Unfortunately, they haven’t been enough to beat the S&P 500, though we rarely invest in large-cap stocks. 
 
Over the next several weeks, we will review each of our underperformers to identify what we got right, but most importantly, what we got wrong. We will discuss whether our investment case has been broken, and if so, why. Discussing your losers isn’t an easy thing to do, but it’s the right thing to do. We strive to continually improve our investment process, which is vital to achieving this goal. 
 

We utilize free cash flow as our primary valuation component because it is one of the most difficult statistics for a corporation to manipulate. Alfred Rappaport summed it up nicely: “Profit is an opinion; cash is a fact.” So why is free cash flow a better (or more realistic) measure? 
 

1. FCF accounts for changes in working capital, such as accounts receivable and payable, which can affect a company's cash position. Earnings may not fully reflect the effects of these changes on cash flow. 
2. Earnings encompass items such as depreciation and amortization, which are non-cash expenses that do not represent actual cash outflows. FCF, in contrast, emphasizes the actual cash a company generates, offering a more realistic view of its financial health. 
3. FCF considers capital spending on items such as property, plant, and equipment, which are vital for maintaining and expanding operations. Earnings may not fully capture the cash needed for these investments, while FCF does.
4. FCF helps investors assess a company's ability to reinvest in its operations, pursue strategic initiatives, and sustain long-term growth. It also offers a clearer view of a company's financial health and its ability to endure economic downturns.

 
Why Free Cash Flow and Not Earnings?
 
Earnings, also known as net income, refer to the profit a company generates after subtracting all expenses from its revenue. It is calculated on the income statement by deducting expenses such as the cost of goods sold, operating expenses, interest, and taxes from gross revenue. Earnings can encompass both cash and non-cash items. For example, depreciation, which is an expense that reduces earnings, does not involve an actual cash outflow. Earnings are reported on the income statement. It’s essential to remember that earnings focus on profitability, whereas cash flow emphasizes liquidity—the ability to access cash. So why do we use free cash flow rather than earnings in calculating value in potential or actual portfolio holdings? Here are a few areas that can help illustrate the differences between earnings and cash flow:
 
Reporting Sources
Companies primarily use three financial statements to assess their overall performance and health: balance sheets, cash flow statements, and income statements. The cash flow statement records the company's accounts payable and accounts receivable. It helps reconcile the other two statements by illustrating the company's financial activity, like a checkbook; however, it doesn't always provide a complete view of all expenses and activities. The income statement reflects earnings, displaying the company's profits over a specific period. Income statements can provide a broader perspective on a business's performance and growth potential since they show profits after deducting expenses and costs.
 
How It’s Calculated
Another key difference between earnings and cash flow is how they are calculated. To determine earnings, accounting and financial professionals subtract a company's expenses from its revenue. Expenses include costs such as labor, supplies, rent, taxes, and interest. They can use these calculations to display earnings over a specific time frame, such as a quarter or a year. For cash flow, the calculation focuses solely on the company's actual inflows and outflows of cash. Any transactions occurring on a non-cash basis will not appear in the cash flow statement. The statements serve as an ongoing ledger that reflects the company's cash balance as of the end of a period.
 
The Two Can Create Two Distinct Views
When investors and shareholders conduct business valuations, they consider the company's price in relation to its earnings, cash flow, book value, or equity value. Therefore, both earnings and cash flow represent crucial figures to comprehend, as they provide unique insights to stakeholders. To achieve long-term, sustainable success, organizations must maintain both profits and positive cash flows. However, success in one area does not always equate to success in another. For instance, a company may be profitable yet still lack sufficient available cash to cover essential expenses, such as payroll or supplies, especially if it is waiting for customer payments or has not yet sold its inventory. In this case, profitability does not necessarily mean positive cash flow, and cash flow becomes a more critical figure for stakeholders. 
 
Similarly, a company may temporarily enhance its cash flow by securing loans or selling assets. However, if its earnings are not adequate to generate profit, achieving profitability becomes increasingly crucial. Therefore, it is vital for companies to achieve profitability to ensure their ongoing operations.
 
Conclusions
 
Nintai is not entirely averse to using net income/earnings to evaluate a holding. Free cash flow is a more applicable measurement tool because cash is king. Our results in the 2007-2009 Credit Crisis have further strengthened FCF’s appeal in our research and valuation methods. We should note that this can require considerably more research time as we convert a company’s quarterly earnings report into a free cash flow quarterly report. But we think the effort is worthwhile. 
 
FCF represents excess cash generated by a company that is available for distribution to investors, debt repayment, or reinvestment in the business. Because of that, our role as a shareholder and fiduciary for our investment partners means we are acutely interested in how cash will be deployed. If a company can achieve greater returns on invested capital by deploying funds toward strategic acquisitions or expanding existing operations, then we fully support such efforts. However, this is only if those returns exceed what Nintai, or its investment partner, can achieve independently. If the latter is accurate, we would like to see the capital deployed in the form of dividends. Additionally, if the company’s shares are trading at a significant discount to our estimated intrinsic value, then share buybacks might be the best use of cash. Free cash flow can assist us in any of these calculations where net income might not provide us the insight to recommend them. 
 
For all these reasons, in addition to the previous analysis of FCF compared to earnings, we dedicate a significant amount of time to examining a holding’s FCF figures. We believe that, over the long term, a company’s share price will closely follow its free cash flow numbers. 
 
I hope this provides you with a solid overview of why our valuation spreadsheets, along with many other documents, use FCF as a fundamental measure. Please don't hesitate to contact us with any questions or comments. My best wishes. 
 
DISCLOSURE: Nintai Investments does not own shares in any company mentioned in this article.