In Part 1 of this three-part series, I examined Michael Mauboussin and Dan Callahan’s work on Return on Invested Capital and suggested Indivior Pharmaceuticals could be an interesting investment to consider as a result.

In Part 2, I dig into more companies from the study, those on the frontier of ROIC, and discuss another very interesting and potentially undervalued stock.

As we discussed in Part 1, Mauboussin and Callahan break a company’s return on invested capital into two components: its operating margin (how much revenue can the company “keep”) and its invested capital turnover (how much and how quickly can it sell stuff).

I then discussed how Mauboussin and Callahan show each of the top 500 companies in the Russell 3000 as a dot on a chart plotting these two terms using 2022 data. I updated the chart to widen the scope, ultimately including 1,769 companies, and using data from the trailing twelve months.

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That chart is below, along with a view that highlights the companies with the highest invested capital turnover. See Part 1 for more.

Mauboussin and Callahan identify those companies toward the top left of the chart as “cost leaders,” those companies with high turnover and low operating margin. These are companies that sell a lot of goods or services, but that don’t generate very high profits on any given sale.

On the right and bottom right of the chart are “differentiators,” those companies with low turnover and high operating margin. These companies sell comparatively less, but on each sale, they generate very large profits.

I started digging deeper into the chart by looking at those companies with the highest turnover (the right chart in Figure 1), and from that work, found Indivior Pharmaceuticals, one of three companies on the chart with very high turnover and operating margins.

Now, let’s continue the work by looking at some other companies on the chart, starting with some names that are more familiar.

The Top 25 Companies by Market Cap

The chart below shows the same breakdown of companies by turnover and operating margin. On the left, I have truncated the y-axis to make the trends more visible, and on the right, I highlight the top 25 companies by market cap.

These are names you will recognize.

With this view and these familiar companies, Mauboussin and Callahan’s point really hits home. Pretty quickly, we can see what the authors were referring to with the two buckets, cost leaders and differentiators. At the top of the chart are Costco and Walmart. These are companies that seek to sell a lot of goods and services by selling them for low prices. Costco and Walmart also do this by having stores conveniently located close to their customers. Other companies in the cluster (that are not shown because their market caps are lower) have higher turnover by requiring less invested capital, like service businesses, or by having recognizable brands or strong distribution.

In the bottom right live those companies that differentiate. They offer their customers something no other company can provide. Visa and Mastercard, of course, have the dominant credit card networks in the world. Nvidia creates computer chips that are unparalleled in performance. Palantir is a cutting-edge software company focused on the defense sector and built to use modern technologies in an industry the founders felt was becoming too complacent.

That list goes on, and all of the names on it are well-known. Many (but not all) trade at multiples of annual earnings or cash flow that are relatively high. An investor could make a whole career out of studying this chart and focusing on the best names at the best prices. Chris Hohn springs to mind.

But what about smaller companies? We have a couple thousand dots on the chart to explore after all.

Examining the Frontier

Are there any differentiators or cost leaders buried in the dot plot that might surprise us? Instead of arbitrarily cutting off the data at some level of turnover or some high level of market cap, let’s try to isolate another set of companies: the ones that are as close as possible to the top-right edge of the cluster.

“Top-right” means those companies with either high turnover or high operating margin or both. By maximizing those two metrics, we will be focusing on those companies with the highest ROICs.

The chart below shows just that: a curve that isolates 44 companies that are highest in combined turnover and operating margin, with pre-tax ROIC over the last twelve months greater than 45%.1

The companies on this chart produced a pre-tax return on invested capital greater than 45% over the past twelve months. Interestingly, we can see names from both the Part 1 breakdown and the one above:

1. There are a few companies on the chart, like McKesson (MCK), Indivior (INDV), and AnaptysBio (ANAB) that have the highest turnover of invested capital out of any companies, and

2. there are also some of the largest companies in the world with the highest operating margins on the chart, like Nvidia (NVDA), Mastercard (MA), Visa (V), Micron (MU), and Apple (AAPL).

Looking at the chart above is akin to selecting for those companies that have the highest pre-tax ROIC of any in public markets. It’s a pretty good place to start to study great companies and to search for great investments, but it tells us nothing about the valuation of each company in the market and therefore nothing about each company’s relative attractiveness as an investment.

So, in the table below, I added a valuation measure. For each of the names on the chart, I show the Forward Price to Free Cash Flow ratios from Fiscal.ai. To make the list a little more manageable, I also introduced one more constraint: I required company operating margins to be increasing every six months for the past year and a half. I wanted to narrow the list to those companies that had both strong ROICs and whose business appeared to be improving.

That constraint limits us to eight names out of the original 44. They are shown below, along with their forward P/FCF ratios.

Each of the companies on this list is great in some way, but the companies toward the top of the list are especially interesting because of their relative cheapness. And one name stands out versus the others.

Clear Secure (Ticker: YOU)

Clear Secure, Inc. is a secure identity company that is best known for its CLEAR+ security subscription service which provides travelers a more convenient security experience at airports. They also have other security products, like a similar offering for stadium security and a B2B product for identity verification.

As of October 11, the company had a market cap of $5.7 billion, an enterprise value of $4.8 billion, and a stock price of $42.47. (Note this is slightly different than the data in Figure 4, which was taken as of September 25.)

The company went public on June 30, 2021 at $31 per share and has delivered revenue growth each quarter since that time. Its latest quarterly revenue was $277.8 million, up 26.6% year-over-year. The company’s total number of CLEAR members (which is a free product) grew to 43.5 million, up 30.0% year-over-year, and the number of active CLEAR+ members grew to 8.3 million, up 15.2% year-over-year.

Their latest quarterly financial report also exhibited a 68.6% gross margin (up consistently from 58.5% since Q3 2021) and a 29.9% operating margin (again, up consistently from -48.2%).

Below is the company’s income statement from the past three years (plus the trailing twelve months), highlighting the increases in revenue and margins.

At a market cap of $5.7 billion and earnings of $72.3 million for the quarter ended June 2026, the company trades at a P/E on annualized earnings of 19.9x, with quarterly earnings that were up 86% year-over-year.

In addition, the company has the benefit of taking CLEAR+ subscription payments up front, which is why it has $572.9 million in deferred revenue on its balance sheet. That has the benefit of boosting cash flow for the business, reducing invested capital needed, and increasing ROIC.

There are, of course, risks around the company. The investment case for Clear Secure will depend heavily on the company’s ability to continue growing, which will involve convincing more travelers and businesses of the value of convenient, streamlined security. The company’s main product is discretionary and not critical, which poses some risk in the event of a recession or otherwise.

Also, the company went public with an Up-C structure that resulted in four classes of stock being created, two of which are outstanding today, Class A and Class C.2 Anyone analyzing the company should be aware of this distinction, which can confound per-share metrics and forward projections if not properly accounted for.

At 19.9 times earnings, Clear Secure is not obviously cheap, but if growth can be expected to continue, the stock may be a bargain. The company has executed very well to date, as evidenced by the high return on capital it achieves and its continued growth.

I will be doing more work on Clear Secure in the future to determine if it rises to the level of attractive enough to own.

In Part 3, we’ll examine one other surprising aspect of Mauboussin and Callahan’s ROIC work and discuss two more potential investment opportunities, companies that are not on the frontier but may soon be.

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Disclaimer

The Owner’s Memo is published for informational and educational purposes only. Nothing here is investment, legal, or tax advice, or a recommendation to buy or sell any security. The content is general and does not consider your individual circumstances, objectives, or risk tolerance. I am not a registered investment adviser or broker-dealer.

I may own positions in securities I write about, and I disclose any position at the time of publication. My views may change without notice, and I have no obligation to update prior posts.

Investing involves risk, including loss of principal. Past performance is not indicative of future results. The information here comes from sources I believe to be reliable, but I make no guarantee of its accuracy or completeness. Do your own research and consult a qualified professional before making investment decisions.

This is Part 1 of a three-part series examining Michael Mauboussin and Dan Callahan’s work on Return on Invested Capital. Today’s piece features one interesting potential investment idea that I discovered while breaking down and updating their work.

Parts 2 and 3 will continue the work and identify three more potential ideas.

What’s written above is one of my favorite investing lessons. It’s a simple statement, which also accords with Munger’s advice to “take a simple idea and take it seriously.” If a business can earn high returns on the capital it uses (and it can continue redeploying those returns at similarly high returns), then the returns to the company’s stock should follow suit.2

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Michael Mauboussin is a long-time business and investing analyst whose work is singular in the space, clearly written and packed with lessons and insights. He has written some great pieces outlining the fundamentals of return on invested capital, some of the strategies companies employ to create high returns, and detailing the character of specific, modern companies in that regard. Here are three of Mauboussin’s pieces, written with co-author Dan Callahan.

Decomposing Return on Invested Capital

In each of these papers, Mauboussin and Callahan make the point that the return on invested capital that a company generates can be decomposed into two separate terms. The authors first walk through a simple definition of ROIC:

Then, they point out that the expression is equivalent to two other expressions:

The first expression is relatively straightforward, and the second expression (with two terms) provides a little more insight: the return a company earns on its capital can be thought of as (1) how much the company earns relative to how much revenue it generates and (2) how much revenue it generates versus the amount of capital it uses.

These two terms are, of course, the company’s operating margin (how much revenue can the company “keep”) and its turnover (how much and how quickly can it sell stuff).

While this insight is familiar to any student of finance, Mauboussin and Callahan bring it to life by breaking apart the universe of the largest companies according to the two metrics. They plot the top 500 companies in the Russell 3000 according to these two metrics. The chart below is from their 2023 paper, and it shows each company as a dot, according to the turnover and operating margin they produced in 2022.3

Mauboussin and Callahan then point out that there are two domains into which many companies fall to one degree or another:

• High turnover and low operating margin (top of the chart) - These are companies that sell a lot of goods or services, but that don’t generate very high profits on any given sale. They make their money on volume. Mauboussin and Callahan label these companies as cost leaders. They are able to sell a lot because they have better prices than their competitors for any variety of reasons. I would also add that these are companies that have great distribution; they sell a lot because they make it easy for the customer to obtain their goods.

• Low turnover and high operating margin (bottom right) - These companies sell comparatively less, but on each sale, they generate very large profits. They keep a large chunk of the revenue from each sale. How might a company do this? By differentiating. If a company makes something that you want or need, but you can’t get it anywhere else, then that company can charge you a lot more for the good or service than it costs them to ultimately produce it.

Updating the chart for today

The first thing I thought of when I saw the chart was “I wonder which companies fall into each domain.” Mauboussin and Callahan address this briefly, and I immediately wanted more.

I set out using Bloomberg to create an update of the chart above. By doing so, I could check out each company for myself.

Also, instead of charting only the top 500 companies, it would be nice to expand the universe a bit and see if there are smaller companies that stand out as cost leaders or differentiators.

The updated chart is below. It shows 1,769 companies based on their invested capital turnover and operating margin over the latest trailing twelve months.4

The pattern in the updated chart is similar to Mauboussin and Callahan’s, although ours is much more exaggerated. Whereas the company with the highest invested capital turnover on Mauboussin’s chart has a value of 1,600%, because we included more companies than the top 500, there are several outliers above that level on our chart.

The figure below identifies those companies.

And the table below identifies each company by name.

A company’s presence on this list does not necessarily imply it is a great company, of course. Most of the companies simply feature very high rates of turnover, that is, they sell a lot of stuff relative to the capital invested in their businesses. But their operating margins are low, which implies that their returns on invested capital are not incredibly high.

Also, the list tells us nothing about each company’s valuation in the market, which is critically important in considering any of these as investments, obviously.

There are three companies, however, that have high operating margins in addition to their high rates of turnover. I’ve listed them below, along with each company’s estimated forward P/E ratio for next year, obtained from Bloomberg.

1. Verisign (VRSN) - Forward P/E of 25.9x

2. Indivior Pharmaceuticals (INDV) - Forward P/E of 7.7x

3. AnaptysBio (ANAB) - Forward P/E of 11.0x

Of the three companies, two are pharmaceuticals, and the remaining one, Verisign, is a company that provides domain name registry services and internet infrastructure. Verisign produced a very high 67.9% operating margin over the prior twelve months (a level that has been relatively consistent for many years), and the company’s revenues grew 6.0% year-over-year in the latest June 2026 quarter.

Verisign appears to be an excellent company at first glance, but, at 28.2 times next year’s forecasted earnings, it doesn’t immediately appear to be a screaming bargain.

Of the other two companies on the list, AnaptysBio is a biotech company that appears to have some pretty wild swings in revenue and net income, so I’ll set that one aside.

The other company is Indivior Pharmaceuticals.

Indivior Pharmaceuticals (Ticker: INDV)

Seeing a pharmaceutical company pop up on any screen always makes me a little angry. Maybe some of you understand. The stock may look good on the screen, but a deeper dive almost always reveals an odd one-time surge in revenue or income, a data error, or most often, a research company that is outside my circle of competence.

Indivior seems different. It has been doing business for over 25 years, initially as part of another company, and it specializes in the development, manufacture, and sale of prescription drugs for the treatment of opioid-use disorder. Its core product is called SUBLOCADE, which is a once-monthly injectable medication.

SUBLOCADE enjoys a leading 76% market share in the long-acting injectables category, and company revenues have been increasing as a result. Over the last twelve months, the company captured $1.3 billion in revenue, up 13.6% year-over-year.

The company has a market cap of $4.2 billion, an enterprise value of $4.5 billion, and a stock price of $35.82 as of September 25.

Management has also been focused on cost savings, which has resulted in operating margins increasing from negative levels in 2022 and 2023 to 30.2% over the last twelve months. Operating margins for 2026 Q2 came in even higher, at 46.6%. For the full-year 2026, management is forecasting a continued surge in cash flow, with their measure of adjusted EBITDA up 68% YOY to a midpoint of $720 million.

In addition, management has been repurchasing stock, which suggests they are being somewhat thoughtful of shareholders in their use of capital. In 2026 Q2, they repurchased 4.7 million shares, or 3.8% of shares outstanding.

Now, pharmaceutical companies are almost always outside my circle of competence, and Indivior and its products are too. But while a major part of the story here lies around SUBLOCADE retaining its market share and growing its market, another chunk lies around financial practice, like cost savings and share repurchases, which are more familiar topics. The investment thesis here does not center around a breakthrough moonshot treatment.

More than that, I noticed another major development when doing this first bit of research on the company. Indivior has agreed to a merger with another company, Supernus Pharmaceuticals, which is still subject to shareholder and regulatory approval. Here is the announcement from August 3:

Supernus Pharmaceuticals, Inc. (Nasdaq: SUPN) and Indivior Pharmaceuticals, Inc. (Nasdaq: INDV) today announced that they have entered into a definitive agreement to combine in a tax-free all-stock merger of equals transaction to create a leading diversified, central nervous system (CNS) biopharmaceutical company with significant scale. The transaction is expected to generate significant value for stockholders of both companies, realizing $125 million in expected annual cost synergies.

Supernus is a company focused on the development of products for central nervous system diseases, and it is not consistently profitable. Its revenue increased by 32.4% YOY in the most recent quarter, and it has a robust pipeline of potential new treatments, which is part of Indivior’s motivation to merge. It has a market cap of $2.5 billion, an enterprise value of $2.2 billion, and a stock price of $42.69 as of September 25.

Great, another pharma company to figure out. Thanks Tim.

Hold on a second. What caught my eye about the merger was the cost savings that management intends to pull out of the combined companies: $125 million in expense savings. With Indivior forecasting adjusted EBITDA of $720 million and Supernus sporting the opposite, a trailing-twelve-month EBITDA of -$28.8 million, those cost savings mean that the combined company should have a rough (adjusted) EBITDA around $816 million. (Indeed, in the merger announcement, the company projects a pro forma adjusted EBITDA of $888 million.)

In addition, Indivior plans to pay a special dividend to its shareholders of $1 billion prior to the closing of the merger, financed in part by a $650 million term loan. If the merger takes place, pre-merger Indivior investors will receive a dividend of $8.47 per share and will own a combined company with an implied enterprise value of about $6.7 billion on $816 million of EBITDA.

The combined company will be named Supernus, Inc. Indivior holders will have about 56.5% of the combined company, and closing is anticipated to be in Q4 of 2026.

Obviously, a lot more work should be done on the business of both companies, but the situation is certainly interesting.

An idea that started as a profitable and somewhat mature pharma name also looks like a potential Joel-Greenblatt-type special situations investment.

Examining the outliers proved to be a valuable piece of work. In Part 2, we’ll dig deeper into the largest companies in the world and to even smaller companies on the frontier, where the highest-ROIC businesses sit, and discuss another potentially undervalued company.

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Disclaimer

The Owner’s Memo is published for informational and educational purposes only. Nothing here is investment, legal, or tax advice, or a recommendation to buy or sell any security. The content is general and does not consider your individual circumstances, objectives, or risk tolerance. I am not a registered investment adviser or broker-dealer.

I may own positions in securities I write about, and I disclose any position at the time of publication. My views may change without notice, and I have no obligation to update prior posts.

Investing involves risk, including loss of principal. Past performance is not indicative of future results. The information here comes from sources I believe to be reliable, but I make no guarantee of its accuracy or completeness. Do your own research and consult a qualified professional before making investment decisions.

“Talent” is perhaps the most pervasive lay explanation we have for athletic success. Great athletes, we seem to believe, are born with a special gift, almost a “thing” inside of them, denied to the rest of us—perhaps physical, genetic, psychological, or physiological. Some have “it,” and some don’t. Some are “natural athletes,” and some aren’t. While an athlete, we acknowledge, may require many years of training and dedication to develop and use that talent, it is always “in there,” only waiting for an opportunity to come out.

[…]

But talent fails as an explanation for athletic success, on conceptual grounds. It mystifies excellence, subsuming a complex set of discrete actions behind a single undifferentiated concept.

The above quote is from Daniel Chambliss’s landmark study The Mundanity of Excellence, published in 1989. I wrote briefly about Chambliss’s work in a prior edition of The Owner’s Memo.

But Chambliss’s view on talent was gnawing at me, and it wouldn’t let go.

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Chambliss’s three controversial points

Daniel Chambliss is a professor of sociology and was an amateur swim coach. In the 1980s, he conducted research to discover what made the most elite swimmers different from others. He spent roughly a year and a half attending national and international swim meets, including the 1984 Olympic Games, and he was a swim coach in New York State for five years.

In the paper, Chambliss makes three main points, and all of them go against the grain of conventional wisdom. The first two are:

1. Excellence in swimming requires qualitative differences rather than quantitative ones. Top swimmers do things differently than the rest. The styles of strokes, dives, and turns are dramatically different at each level. Top performers do not merely train for more hours or “work harder.”

2. Excellence (and motivation) is much more mundane than we think. The very best swimmers find a way to make the necessary practice and repetition interesting, competitive, or compelling in some way.

However, it is Chambliss’s third point that I found the most interesting and perplexing:

3. “Talent” is a meaningless description. Chambliss argues that the common refrain, that great athletes are “talented,” is meaningless and circular because we only call an athlete “talented” after they achieve success, like winning competitions or performing some great feat.

“Talent” is meaningless

Immediately after reading Chambliss’s article for the first time, I recall feeling a little uneasy. Was there really no such thing as “talent”?

On one hand, great athletic performances do have a mystical, amazing quality about them and seem so far removed from what we ordinary humans are capable of. We see Lionel Messi leading his team to an improbable World Cup comeback win or Michael Phelps winning a record eight gold medals at the 2008 Olympic Games or Usain Bolt running the 100-meter dash in 9.58 seconds, and we know we are incapable of doing the same. We sit stunned for a moment at the thought that a person could come through for his team again and again or win eight separate competitions under the highest pressure or be so much faster than the fastest people in the world. We elevate them to the status of gods.

It’s virtually impossible for a casual observer to understand, in detail, all the hard work, practice, and development that went into creating a Messi, Phelps, or Bolt. So, we reach for the easier explanation: they have something we don’t; they have talent.

On the other hand, Chambliss makes a strong point. I have never heard the word “talent” used to describe a person beforethey achieve something great. It’s almost laughable to think we could look at a two-year-old, for instance, and say “That kid’s got a lot of football talent,” before they’ve ever touched a ball.

That fact should give us pause. If the word “talent” is never used beforehand, if it only emerges after the fact, after the championship was obtained, the gold medal was won, the race was run, the catch was made, or the defense overcome, then it is not reporting anything new at all. Chambliss would argue that it is better simply to say the person was successful or that they beat everyone else.

Really? Is there no such thing as talent?

I understood this line of reasoning the first time I read Chambliss’s article, but I felt skeptical. Surely, talent existed. Every time I saw my children’s sports teams practice, I saw talent, didn’t I? Some kids were clearly better than others. What else could explain a nine-year-old spinning, then leaping, then catching a football in the air if not “talent”?

This was the same argument I recently received from a reader, Blake:

Mr Chambliss’ contention that [“talent”] is circular, that we call them talented after they succeed, is obviously incorrect to any parent, grandparent or coach who has ever watched the first t-ball practice full of 6 year olds. You won’t be able to spot every talented athlete, but you can pick out most of them. It was a pretty good indication that my 6 year old granddaughter had something going on when she outran everybody in her class. She eventually won 3 state championships in track.

Blake’s argument does a good job of summarizing how I felt while reading Chambliss’s article. On a first reading, it seems ridiculous that talent might not exist.

But after thinking about it awhile, I believe Chambliss is right.

Chambliss’s foundational argument is that if two people are different, then there must be something causing that difference, and that holds for success in sports as much as anywhere else. Critically, some of the time, the cause of success may not be apparent to the naked eye or even yet measurable with the means we have available.

Chambliss tries to address this point by listing a variety of factors that, in his experience, tend to produce better swimmers:

…geographical location, particularly living in southern California where the sun shines year round and everybody swims; fairly high family income, which allows for the travel to meets and payments of the fees entailed in the sport, not to mention sheer access to swimming pools when one is young; one’s height, weight, and proportions; the luck or choice of having a good coach, who can teach the skills required; inherited muscle structure—it certainly helps to be both strong and flexible; parents who are interested in sports. Some swimmers, too, enjoy more the physical pleasures of swimming; some have better coordination; some even have a higher percentage of fast-twitch muscle fiber.

Notice how long Chambliss’s list is. Once I saw the list, I also got the impression that it could be much longer. For instance, I might add a host of psychological traits too, like resilience, which would help in brushing off losses, and a tolerance for repetition, since the sport consists of going back and forth over the same stretch of water.

There are many potential reasons a person, even a very young person, might be a better swimmer than someone else, and their superiority might even be visible at their very first swim practice.

For very young people, I think it is particularly helpful to think about physical differences because other benefits, like psychological ones, might not yet be apparent in their first attempts at a sport. We must also bear in mind that some physical differences may be hidden from view.

What is it about a six-year-old that makes him able to throw the baseball harder than the rest? Physical size is often readily apparent and can make a big difference, as proponents of youth redshirting will tell you. But sometimes there are kids who are no bigger than their teammates but can still throw harder. Chambliss suggests there may be physical characteristics, like the proportion of fast-twitch muscle fibers, that aren’t visible and may explain their success. It’s also possible there are other invisible factors: maybe Dad loves baseball and tends to keep a foam ball around the house that he and the kids are always playing with. And if Dad were asked, the behavior might be so second nature to him that it wouldn’t even spring to mind as having benefitted his child.

It’s better to believe talent doesn’t exist

Of course, neither I nor Chambliss can prove that any hidden factors are the cause of any success, but there are three reasons I think it’s preferable to consider what factors might be behind success rather than claiming it is due to that magical “talent.”

1. Searching for factors shows us what to work on

Using “talent” as a simple explanation for success prevents us from understanding how we ourselves could be better at whatever we are considering.

Imagine for a moment that you had a child who was a classmate of Blake’s granddaughter, whom I’ll call Betty, and who wanted to run as well as Betty did. (Let’s also imagine that these girls are old enough to want to work on improving.)

By studying Betty more closely, we might find some reasons she was so great, and that could help encourage our own child to work on improving in the same vein.

If, for example, Betty was lean and muscular and this tended to help her burst off the starting line, and if Blake told us that Betty also loved gymnastics, we might infer that she was effectively working out when her classmates were not, and that might encourage our child to believe she could improve by doing the same.

What about factors outside Betty’s control? What if Betty was simply taller than everyone else or had longer legs than the other girls? Well, we could marvel at her “talent” or the “gifts” God bestowed upon her, or we could encourage our own daughter to focus on other factors that might confer success (for instance, discipline in practice or mental toughness) to attempt to counter Betty’s natural advantages.

It seems far healthier to me to look for ways to improve or compete than to assume it cannot be done because we are not “talented,” which leads to number two.

2. Believing in “talent” stops us from experimenting

To the extent that you or I believe that some people, whether athletes, salespeople, actors, or physicists, are gifted with some mystical property that cannot be understood, we lose the impetus we might otherwise have to explore.

How many times have you seen a great performance, maybe a great speech, and heard someone say “I couldn’t do that, I’m a terrible public speaker”? Comments like that are common, and they assume that the speaker was always great, endowed with the talent of public speaking.

But how do we know that’s the case? I was reminded of this recently when Shopify CEO Tobi Lütke, during an interview with David Senra, said he was once terrified of public speaking. His solution was to use affirmations. Every day, he wrote down repeatedly that he liked public speaking, and, to his surprise, it worked. In his words:

If you tell yourself or write down something about yourself 100 times, it writes into the [brain] at such a deep level that your brain will start reconciling you to that. It just works.

Now, if Lütke had believed that public speakers had some mysterious power, do you think he could ever have mustered the willpower, creativity, or open-mindedness to try something he initially considered absurd? I doubt it.

3. Believing in “talent” relieves us of responsibility

Using the word “talent” as an explanation for success might actively prevent us from exploring ways we can get better, but there is also a more insidious problem with it. It silently relieves us of the effort of trying. It’s a subconscious admission of the fear we have that, if we discovered the banal secrets of success, we would see that success was possible, and then we would need to confront a call to improve ourselves. If success became plain, we might have to answer for not having achieved it.

Chambliss describes this well:

Still, we want to believe in talent. As Jean-Paul Sartre put it, “What people would like is that a coward or a hero be born that way”, knowing that it protects us by degrading the very achievements that it pretends to elevate… magically separating us from those people who are great athletes, ensuring that we are incomparable to them; and relieving those of us who are not excellent of responsibility for our own condition.

It is easier for the vast majority of us, for the vast majority of the time, to continue moving through our lives, simply believing in gods and ignoring the potential pain, uncertainty, and work that would come from responding to a call to improve.

This unspoken fear exists in investing, too. We hear about the records of great investors, and we are amazed. We know from experience how difficult it is to select and hold great investments. We hear great investors advise amateurs to avoid picking stocks and to invest in index funds instead. Buffett says this repeatedly; for example, at the 2008 Berkshire Hathaway annual meeting, when asked how someone who was not a full-time investor should invest, he said:

Well, I’ll be very simple: under the conditions you name, I’d probably have it all in a very low-cost index fund… I would recognize the fact that I’m an amateur investor… and then I’d forget it and go back to work.

Hearing this can lead an investor to believe that those who can invest well have a gift, that they have investing talent. But it ignores the other half of Buffett’s advice, that with study, work, and the right temperament, an individual may be able to see beyond the veil of talent and do quite well on their own. From his 1993 annual letter:

On the other hand, if you are a know-something investor, able to understand business economics and to find five to ten sensibly-priced companies that possess important long-term competitive advantages, conventional diversification makes no sense for you.

Buffett is suggesting that the way to investing success is, among other things, to work toward an understanding of business economics and the ability to find good companies at sensible prices. That means reading, thinking, practicing patience, and developing the right temperament, the same kind of mundane ingredients Chambliss found at the pool.

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The price of a stock varies inversely with the thickness of its research file. The fattest files are found in the stocks that are the most troublesome and will decline the furthest. The thinnest files are reserved for stocks that appreciate the most. This kind of file generally consists of a single prospectus.
- Martin T. Sosnoff, Humble on Wall Street1

Perhaps it’s overstated slightly, but there is something interesting and true in the above quote. The best investment ideas, I’ve found, are usually the ones that can be explained in a short paragraph and sometimes just one or two sentences.

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So much of professional money management makes it seem otherwise. Impressive-sounding stock pitches abound, and, to an untrained eye, it can feel like longer investment cases mean better investment cases, but I generally don’t believe that.

By studying great investments from the past, I’ve come across many examples. Here are a few:

Carl Icahn’s investment in Apple starting in 2013 (and Warren Buffett’s investment starting in 2016)

On August 13, 2013, Carl Icahn announced on Twitter that he had begun buying shares of Apple, saying he believed the company was extremely undervalued.

On October 23 of that year, he released a public letter to Apple’s CEO, Tim Cook, explaining his reasoning. Icahn later followed up his letter with five more, the most interesting of which was his letter to shareholders on January 23 of the following year in which he discussed his rationale for investing in Apple.

Icahn’s letter comes in at just over 3,000 words, but the key point can be summarized in just two sentences: Apple is the premier consumer products company in the world, and the price of its stock implies that it is trading at a discount (versus the earnings it produces) relative to the rest of the S&P 500. Furthermore, a potential catalyst exists to close this gap: returning some of Apple’s excess capital to shareholders via stock repurchases. Here is a sample from his letter:

The rest of Icahn’s letter is secondary: he spends time making the case that it would not be imprudent for the company to be even more aggressive with its share repurchase program, and he walks through the tremendous potential he believes Apple has to develop new products and increase earnings even further. But his main point was a simple one. Apple was perhaps the best company in the world, trading at a discount to other companies.

Icahn initially purchased 3,875,063 shares of Apple in Q3 2013, per his 13F filing at the time. He continued accumulating the stock through the beginning of 2014, even as it moved higher, disclosing on January 23 that his position had reached $3.6 billion. His 13F for the first quarter reported that he owned 7,537,264 shares. (On June 9, Apple’s stock split 7-for-1, giving Icahn 52,760,848 shares, the number he reported for the second quarter.) He described his investment in Apple as “the largest position in our investment history”.

Icahn eventually sold the position, disclosing the sale to CNBC on April 28, 2016 and reporting that he made $2 billion on his investment. Although he never disclosed his cost basis, I estimate Icahn made total return of about 40-50% over the 2+ years that he owned the stock.

His investment was a success, but ironically, he seems to have forgotten his own simple thesis upon selling the stock. Although the valuation disconnect with the S&P 500 had closed as Apple’s stock ran up in 2014, the stock had actually declined during 2015, and by April of 2016, around the time Icahn sold his stock, the valuation discount was even greater than when he started buying.

When asked why he sold the position, he cited antagonism from the Chinese government, which was making it difficult for Apple to sell products there, as the main reason. In his initial letters, China wasn’t mentioned at all, and one could argue that his thesis was still solidly intact: Apple was still one of the best companies in the world, and the future remained bright.

This kind of in-the-moment anxiety or frustration happens to all investors, even some of the best, like Icahn. And it is another benefit to having a simple investment thesis. When the inevitable worries come along and the stock’s price has dropped, having a clear and simple thesis to question can help an investor see whether Mr. Market is merely overreacting or not.

Interestingly, at almost the same time Icahn was selling his investment in Apple, Warren Buffett was starting to accumulate a position in the stock. Berkshire Hathaway reported owning 9,811,747 shares of the company as of Q1 2016 and kept buying through 2016, ’17, and ’18, eventually owning over 250 million shares by Q2 2018.2

Although Buffett’s comments are sparse regarding exactly why he made the investment in Apple, in a few interviews, he cited the extraordinary franchise and moat that the company commanded. From a CNBC interview in 2018:

“Apple has an extraordinary consumer franchise,” he said. “I see how strong that ecosystem is, to an extraordinary degree. … You are very, very, very locked in, at least psychologically and mentally, to the product you are using. [iPhone] is a very sticky product.”

I could not find any direct quotes made by Buffett on the price of Apple’s stock at the time he made his purchases, but the table above tells the story: at the end of Q1 2016, when Berkshire began making its purchases, Apple’s TTM P/E ratio was 12.2 versus 18.2 for the S&P 500. The Apple discount persisted until 2019.

I suspect Buffett’s thesis for investing in Apple was as simple as Icahn’s a few years earlier. He believed Apple was an incredible company with a very strong moat, that its earnings would continue growing, and that buying it at an 8.2% current earnings yield was a great bargain.3

Peter Thiel’s investment in Facebook in 2004

Peter Thiel has described the investment he made in Facebook in 2004 in several interviews, and by those accounts, the decision to invest was a clear one, and he made it quickly.

Why did he invest in the company? Thiel describes a situation that was “straightforward”: Facebook was already doing very well. Here is he in an interview with Bill Kristol:

…people always ask was [it] extremely hard to figure out how to invest in Facebook when I did it in [2004]. At the time, it felt like a relatively straightforward investment. They were already on 20 college campuses.

[Mark Zuckerberg is] in California summer of 04 looking for investors. And my friend, Reid Hoffman, who started LinkedIn, and I ran across Zuckerberg and basically decided to give him another half million or so dollars to scale it. It was generally a good sign when the only thing you needed money for was to buy more computers because there was such demand for the product.

In another interview with Dave Rubin, Thiel repeats the sentiment with some more color.

He reports that his first meeting with Zuckerberg was not sophisticated or complicated at all. Zuckerberg was nineteen years old at the time, and Thiel saw that Facebook already had a rapidly growing product.

…the main thing he had going for him was that they were just growing really fast. They were at something like twenty college campuses. They had about 100,000 people on the network, and they just needed more money for computers because there was such demand for the product as they were going to launch at more colleges in the Fall.

…It was already working.

One also gets the sense that Thiel realized he was in a goldilocks zone, not so early that the product was a long shot and not so late that Zuckerberg was already well funded. He did not know Zuckerberg before meeting him for the first time, but it did not stop him from agreeing to invest in Facebook on the spot. Thiel realized that the most prudent thing to do after that brief first meeting was to act quickly. From the Rubin interview:

We told him to leave for an hour. Then he came back and we gave him a term sheet about an hour later. It was a fast decision.

Thiel did not ask Zuckerberg for more information. He did not set a follow-up meeting. He did not tell him he would get back to him in a week. He realized that the thing that mattered more to the investment than anything else (was it growing like wildfire among its first users?) had already been proven to him. All he had to do was give Zuckerberg the money he needed to allow the growth to continue.4

Charlie Munger’s investment in Tenneco stock and bonds

At the 2017 annual meeting of the Daily Journal Corp., Munger told an alluring story about his investment in the stock and bonds of automotive parts maker, Tenneco. Munger’s recounting of the investment captivated the audience but lacked a lot of detail, so I researched what he saw at the time and wrote about it earlier this year.

Munger’s commentary implied that the stock was simply cheap on the basis of Tenneco’s sticky business:

It was a cigar butt... It was [the maker of the] Monroe shock absorber...

[…]

I kind of knew based on experience how sticky some of that auto secondary market was, and how many old cars needed Monroe shock absorbers, and I just knew it was too cheap. I didn’t know it would work for sure but I knew [it was cheap].

Furthermore, when asked by an audience member how long it took him to make the decision to invest, Munger replied, “Oh, about an hour and a half.”

After researching the investment, I was surprised to find that Munger could make the decision that quickly. Tenneco was not simply a great company with a stock that was cheap; it was also on the verge of bankruptcy. I concluded that Munger must have reasoned that the best course of action for the company and its lenders would not be a liquidation, but, based partly on its hidden, underlying profitability, a recapitalization would be better and would leave the current equity holders with much more value than the price of the stock suggested.

I think Munger likely reasoned about how a potential bankruptcy might play out, and I think this was the most important point of all, prompting him to make his investment.

If Tenneco was forced into bankruptcy, its lenders would then have to decide on the best course of action that might get them a full recovery on their lending amounts. The total amount of long-term debt outstanding was $989mn plus the $500mn of subordinate bonds which Munger would invest in.

Tenneco’s lenders would rightly ask themselves: How are we best off to recover our $989mn?

[…]

1. We could effectively realize the value of those brands by recapitalizing the company and operating as usual. One way to do that might be to forgive Tenneco’s debt completely, take an equity stake in the new company without debt, and then sell the equity in the new company to make ourselves whole on the lending amounts.

Now, you might argue that only an investor as brilliant as Munger could sort all this out in an hour and a half, and I wouldn’t argue with that. But the overall lesson still holds. It may take a genius investor 90 minutes to distill the major driver upon which the success of an investment hinges, or it may take a lesser person a full day or two. But agonizing over the fate of Tenneco by seeking more and more information would have been a waste of time.

Munger did not attempt to divine whether the recession underway at the time would abate. He did not attempt to call colleagues or friends or do channel checks to see how Tenneco’s sales were progressing that quarter.

He developed a simple and solid thesis: the company still produced valuable products and did so profitably (under the right balance sheet capitalization), and that made the debt and equity worth much more than the market was indicating.

He also realized he could be wrong and that sizing his bet appropriately was just as important as the thesis. I estimate that he bet roughly anywhere from $11 million to $18 million on Tenneco’s stock and bonds, which would have been on the order of 1% of his net worth. He made about $80 million on the investment.

Some lessons

I have many more examples than these three, but part of the reason I like these ones is that they are sufficiently different from one another. Icahn and Buffett invested in a great company at a low price, Thiel’s investment was in a startup company but one that already had a huge amount of risk removed, and Munger’s investment was based on Tenneco simply having more value than the extreme price declines indicated.

There are a few lessons I take from these examples and many others.

First, in situations like these, I’ve found it very tempting to drown myself in information to avoid the pain of making a decision, but doing so would be a big mistake. Excessive research can become a form of avoidance, a place to hide from the fear of choosing a path. Ultimately, it can be more harmful than making the decision.

Second, I should be skeptical of investment ideas or pitches that require a lot of explication. As more information is needed for an investment thesis to go right, the risk increases that one of those pieces will go the wrong way and confound the investment. In addition, a more complex thesis is likely to confuse the investor as the environment inevitably changes in the future. If there are more factors that you believe your investment hinges on, there will be more chances you’ll see a boogeyman in one of them and bail out when you should be holding (or, like Icahn should have done, even adding to your investment).

From time to time, I’ll come across investment pitch decks that are 50 or 100 pages long, some even longer than that. What could possibly be said on page 92 of a slide deck that could be important to the investment thesis? How could one be sure of every piece of information on pages 1 to 91? Instead, I tend to think that overly complicated investment theses are designed to impress one’s clients or limited partners (or even to trick oneself). It is harder for a client to criticize an investor when the investor has clearly put in a lot of work, and it may seem cruel to suggest that all that effort was misplaced.

Third, the existence of simple and great investments from the past pairs well with the punch-card mentality of investing, which I think the vast majority of individual investors would do well to remember. If I find myself struggling to understand an investment thesis, straining with assumptions whose validity is unclear, or wrestling with relative value and whether or not an investment might qualify as cheap, I am better off saying no. If you have trouble with that, just remember…

You only have to get rich once.
- Charlie Munger

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In Parts One and Two, we discussed the global crude oil shipping industry, the particular risks to Frontline and its shareholders, and what was intriguing about the company. Now, we’ll examine how Pabrai dimensioned the risks to the company, when he made his investment, and how it fared.

Frontline’s balance sheet

We now have a little better understanding of Frontline’s strategy and how it seemed to mitigate the risks around spot chartering and Fredriksen’s cowboy persona. But we still need to understand how Frontline would handle the current downturn.

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While history suggested that charter rates would one day recover, there was still the real risk of Frontline generating losses for several quarters of even several years. What if the company suffered losses so great that it exhausted the cash or capital available to it? What if the cycle downturn forced the company to declare bankruptcy?

Pabrai knew this could be a danger, so he turned to the company’s balance sheet. From The Dhandho Investor:

Let’s recreate some of the work Pabrai likely did on Frontline’s balance sheet to see if the company was as protected as he said. Below, I’ve reproduced Frontline’s balance sheet as of Q2 2002. The balance sheet shows a book value per share of $15.89, or $1.22 billion, with most of the asset value tied up in ships.

Since goodwill is the only intangible item on the balance sheet and it is small, the book value of $15.89 squares well with Pabrai’s commentary about a tangible book value of $16.50.

But what about the ships? Could Pabrai be certain that the $2.3 billion of carrying value on the balance sheet represented their true value at the time?

Frontline listed 82 ships in total in its 2001 20-F annual filing, with an as of date of June 14, 2002. Of those, 69 were owned or partially owned by the company, eight were “chartered in” by the company from other owners, and five were newbuildings being constructed. (Shipping companies will sometimes charter the boats of others if they think they will be able to charter out the boat to another company at spot market rates higher than the charter rate they paid.)

First, by reading the 20-F annual report, we find that the ships were accounted for at historical cost less accumulated, straight-line depreciation (over a life of 25 years). This is a good fact, and should mean that the ships tend to be carried at conservative values.

However, Frontline did not report the market value of each of its ships (only the gross carrying value). So, how could we get a feel for whether Frontline’s balance sheet accurately reflected the current value of the ships? After all, the current environment for charterhire rates was depressed, and it should follow that ship prices would be too. Can we get a feel for how ship values were reacting in the downturn?

The following chart shows just that, once again from the great shipping data resource Clarksons. The chart shows secondhand tanker sale prices for VLCC’s aged five and ten years and around 300,000 dwt in capacity. Frontline’s VLCC tanker fleet averaged 5.6 years in age.

You can see from the chart that VLCC secondary sale prices (for five-year-old ships) hovered in a range between $45 million per ship and $70 million per ship from 1988 through 2002. In the 2001-2002 market downturn, they had fallen to $55 million.

Using this data and other sales data from Clarksons as of August 2002, I bucketed Frontline’s fleet into age groups and ship types, and estimated a value for the entire fleet. That value was $2.30 billion, remarkably close to the $2.32 billion of carrying value as of June 2002.

So, it appears that Frontline was carrying its ships pretty close to the values they would fetch on the secondary market in September 2002.

But what if there was a further downturn? Would Frontline be able to survive? Would it be able to generate the cash needed to ride out the market cycle trough?

Frontline generated more cash than it appeared

In his explanation for making his investment in Frontline, Pabrai acknowledges the shipping cycle downturn of 2002 and that, if the downturn continued, Frontline could simply raise cash by selling ships. That seems like a rational argument given what we just uncovered about their fleet value. Pabrai from The Dhandho Investor:

As we’ll see, Pabrai’s interpretation here is a little generous, but his point is still valid. Frontline had a strong balance sheet and could sell ships to help it manage through a downturn.

In addition, there is another feature of Frontline’s business model that Pabrai doesn’t mention: even when Frontline was generating losses, the company generated a lot of cash. Why? Because Frontline, by virtue of the large number of ships it owned, bore a large depreciation expense that flowed through net income. Naturally, Frontline’s cash flow statements added back this non-cash expense, such that, even in periods when Frontline generated losses, it still generated positive amounts of cash.1

There is no better period to see this, perhaps, than the first half of 2002. Frontline lost -$16.9 million in net income during the period but generated $69.4 million in cash from operations. This was a period when TCE rates were slightly below Frontline’s profit breakeven rate.

A comparison of Frontline’s income statement and its cash flow statement from 1H 2002 is shown below.

So, Frontline was in a better position than its net income and profit breakeven figures would indicate. Yes, the company needed to make a positive net income to be long-run sustainable, but in a cycle downturn, the company’s high depreciation expense meant that it was generating more cash than it otherwise seemed, which could help it weather the storm and continue to meet its obligations.

Importantly, we can even estimate the level of charter rates that the company would need to suffer to be cash flow breakeven, as opposed to profit breakeven. Taking the company’s H1 2002 cash flow statement, zeroing out non-recurring items, using the profit breakeven rate, and recalling the number of vessels the company owns produces a pro forma cash flow breakeven charter rate of $14,475 per vessel per day, nicely below the $17,400 profit breakeven figure.

How long could Frontline survive?

With this in mind, can we get a feel for how long of a downturn Frontline could survive if necessary?

The company ended the first half of 2002 with about $180 million in cash and current assets against $286.3 million in current liabilities. (Most of this was in the form of short-term debt, which I imagine Frontline was in the process of refinancing given the relative strength of its balance sheet. Let’s ignore this $106.3 million obligation for the moment.)

Can we apply some stress to Frontline’s balance sheet to get a feel for just how healthy or not the company was? That is a bit subjective.

Let’s assume for the moment that charter rates drop to $10,000 per day, which is the lowest level they saw over the prior 12 years, and let’s assume they stay there for some extended period (which seems pretty draconian). Then, with Frontline’s cash breakeven rate of $14,475 and with just over 75 vessels owned and chartered in (accounting for partial ownerships), the company would be burning through about $120 million per year.

On top of that, the company had debt coming due. Here is the debt maturity schedule from the company’s 2001 20-F report.

So, let’s imagine the year 2003 in a draconian charter rate environment of $10,000 TCE rates. The company would burn through $120 million in operating expenses and it would need to come up with an additional $294 million to pay down its maturing debt (assuming that it could not refinance that debt). That’s a total $414 million of cash the company would need.

Frontline’s $1.20 billion of debt was almost all floating rate debt indexed to LIBOR and collateralized by its vessels. To be clear, in just about any environment (even cycle downturns), the standard procedure for these debt maturities would be for Frontline to refinance its debt with its banks as long as the company was still meeting financial covenants and amortization payments. But we are trying to stress test Frontline’s ability to weather a financial storm, so let’s imagine that it was cut off from refinancing and needed to sell some ships to meet its cash and debt maturity obligations.

How many ships would the company need to sell to come up with our hypothetical $414 million cash shortfall in 2003?

The answer depends on how much it could sell ships for. Recall from earlier that we estimated the current value of Frontline’s fleet in September of 2002 at $2.30 billion, very close to its carrying value. Against that $2.30 billion, Frontline carried $1.20 billion of debt, most of it mortgages against those ships. I’ve reproduced Frontline’s balance sheet from earlier (Figure 15). The loan value ($1.20 billion) versus the market value ($2.30 billion) tells us that Frontline was carrying debt that was 52% of its vessel value.

In other words, at current market valuations, Frontline could sell a ship, allocate 52% of the proceeds to paying down debt, and use the remaining 48% to fund its operations.2

Let’s simplify the analysis a little by focusing on Frontline’s VLCC ships, the market price of which we saw earlier in Figure 17. Let’s take Figure 17 and imagine how much cash the company could generate with tanker secondary values at three levels for an extended period. I’ve called those levels “Stress #1” “#2” and “#3”, and they correspond to five-year-old VLCC prices being (1) at the current market value of $55 million, (2) down 24% to $42 million, and (3) down 45% to $30 million.

The bars in Figure 20 represent how much equity Frontline would generate for itself from the sale of a VLCC vessel at each level of pricing and helps us understand how much distress (or lack thereof) Frontline was facing.

In stress scenario #1, which assumes the current market pricing (in this case, $55 million for a 5-year-old VLCC) holds for the next few years, Frontline could sell a ship, pay off the approximately $28.5 million of debt collateralized by the ship, and keep $26.5 million in cash for the company. In that scenario, surviving our distressed 2003 scenario of $10,000 charter rates and coming up with more than $414 million could be doable by selling nine VLCC’s of various ages. (In this scenario, banks would almost certainly be working with Frontline on refinancing, forgoing even the need to sell.)

In stress scenario #2, which sees 5-year-old VLCC prices down 24% to $42 million (and down 41% from their peak), the company could generate over $414 million by selling eleven VLCC’s, not ideal, but very well doable. (Whether Frontline’s banking partners would allow the company to refinance in a scenario like this depends heavily on circumstances.)

What about scenario #3? In that scenario, selling sixteen ships would generate proceeds of $437.5 million, but almost all of it would go toward paying down mortgage debt. The company would only be left with $21.8 million in equity, not enough to meet its operating costs for the year. That is obviously a very bad situation for equity holders, and the company would be beholden to the mercy of its bankers to extend it more credit to muddle through the difficult times. A bankruptcy and liquidation at values like these would mean a near complete wipeout of equity holders.

Pabrai’s bet

Now, we have a pretty good fundamental understanding of what Mohnish Pabrai saw in Frontline in September 2002. While a scenario like #3 above would be bad, Pabrai assessed that it was likely remote and Frontline and its stock had a lot going for it:

• A company trading at less than half its (accurately stated) book value

• One that generated cash even as it produced income statement losses

• A new, mostly double-hulled fleet purposely acquired to benefit from the single-hull scrapping trend and resulting vessel supply pressure

• A strong balance sheet able to survive charter cycle downturns (although not incredibly severe ones)

• A company designed to benefit to the maximum in cycle upturns, reflecting the personality of its unique CEO.

All these things made Pabrai pretty comfortable that a purchase of Frontline’s equity in September 2002 was a pretty good bet. While there was some small, non-zero chance that the company might not survive, the fundamentals seemed to favor a more modest cycle downturn, and, if that was the case, Frontline was dramatically undervalued.

At a purchase price of, for example, $5 per share, Frontline would have been trading at a market capitalization of $382 million, which was almost exactly equal to the income earned by the company in 2001. That year was a great one for charter rates, but even so, if charter rates reached the more modest level of, say, $30,000 per ship per day, with a profit breakeven rate of $17,400 per ship per day, Frontline would still be earning roughly $300 million.

In a nutshell, that was Pabrai’s bet: that Frontline was way too cheap for a well-protected company and one that was purpose-built to benefit from the upside.

Pabrai purchased Frontline’s stock at an average price of $5.90 per share in the fall of 2002. From his interview with Shaan Puri:

I put 10% of my fund into Frontline because I just couldn’t see a way that we could lose money.

Pabrai makes 55% on his investment

Almost immediately after Pabrai made his investment, the cycle for shipping started to recover. According to Clarkson, tanker charter rates rose from the low levels of $12,761 per day in September 2002 to $47,000 per day in December and as high as $64,000 per day in March 2003.

And Frontline’s stock price followed suit. It quickly rose from the September low of $3.43 to much higher levels in the subsequent months.

Pabrai, knowing charter rates at those levels were high relative to history, chose to sell his stock at an average sale price of $9.15, good for a 55% return over four months of time. Here is Pabrai again in The Dhandho Investor:

What happened next? A word of caution

Now, Pabrai’s investment seems like a great trade, and, indeed, it was very good.

But what happened subsequently provides another lesson to be learned from this case study. You see, the tanker supply dynamics we studied earlier (an undersupply of ships driven by the scrapping of single-hulled tankers) took hold in full force and charter rates rocketed higher than ever before.

From 2003 through 2006, tanker charter rates averaged $55,100 per day, briefly touching as high as a mind-boggling $140,000 per day. This was a boom time for Frontline. In each of those years, the company made net income of $409.4 million, $1.02 billion, $606.8 million, $516.0 million, each figure more than the pro rated amount Pabrai had paid for the entire company in the fall of 2002.

And the stock price followed.

For Pabrai, this was a particularly difficult lesson. He made a fantastic 55% return on his investment in just four months time, but forewent a potential 10 times return on his $5.90 investment. Here is Pabrai again from his interview:

I didn’t make even 3% of the money I should have. Okay? You know, I mean, it was given to me on a platter and I blew it. I still made money, but… the best ideas when you finally figure them out, they’re very simple.

That was an example of where I did first order thinking but I did not do second order thinking... We had this dynamic, if I had thought about it, that once the demand became tight you really couldn’t increase supply for at least 3 or 4 years… when that price is not going to come down. It’s only after 3 or 4 years more ships start getting delivered and you start getting more balance and all of that. That’s an insane amount of cash flow.*

Personally, I find Pabrai’s humility here pretty incredible. Most investors wouldn’t have the confidence to broadcast to others that a pretty good investment should have been a stupendous one and that they “blew it”.

The lesson I take away from this end to the case study is to beware of anchoring your view of value on the price you paid for a stock or, for that matter, any price in the market. The only thing to be considered are the future prospects for the company versus the current price of the stock and any competing investments in which to put your money.

Buffett once said something along these lines. He was warning students not to get attached to their investments, but his message reads just as well as encouragement to disregard what I paid for a stock in assessing a decision to sell.

The stock doesn’t know you own it. Stock just sits there. It doesn’t care what you paid. It doesn’t care that you owned it or anything. So any feeling I have about the market is not reciprocated.

- Warren Buffett, lecture at the University of Florida, 1998

Summary and takeaways

• The work Pabrai did to understand Knightsbridge in 2001 did not result in an investment at that time, but it helped him immensely when the industry, particularly Frontline, suffered a downturn in 2002. In investing, any knowledge I accrue is cumulative and can help me in the future. Read curiously and study continuously. Having as many models in my head as possible about how various businesses work could be very profitable at the right times.

• Frontline’s stock price dropped quickly and precipitously in 2002. It went from $12.94 in May 2002 down to a low of $3.43 in September. But the decline was brief, with the stock price below $5 per share for only two weeks and four days. It quickly rebounded, and by the end of November, the price was $7.02. Being prepared in advance was crucial for Pabrai to act quickly and decisively when the time came. As an investor, I need to be prepared at all times for wild opportunities to present themselves and cognizant that they may disappear quickly.

• Pabrai’s investment in Frontline is a great example of how to invest in a cyclical industry. I am not an expert on the shipping industry. Doing things like trying to call a bottom in the cycle of any given industry is very hard to do. I should be reserving any investment for those times when prices are very low (like being 50% of the company’s accurately-stated and liquid book value) and the company has obvious protections against an extended downturn (like Frontline having an inventory of ships mostly unencumbered by long-term charters).

• In addition, as much as possible, wait for the perfect pitch. Pabrai’s investment in Frontline wasn’t simply a bet that the cycle would turn. He had a rational analysis that the cycle bottom should be shallow because single-hulled ships needed to be scrapped in the coming years, and that would limit tanker supply, pressuring charter rates upward. Moreover, Frontline was purpose-built to withstand a downturn while maximizing upside in the upturn. Try to resist accepting less-than-great situations, instead waiting for those for which almost all factors are pointing in the right direction.

References:

Stopford, Martin. (1997). Maritime Economics (2nd edition). Routledge.

Stopford, Martin. (2009). Maritime Economics (3rd edition). Taylor & Francis.

McCleery, Matt. (2012). The Shipping Man. Marine Money International.

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In Part One, we discussed the global crude oil shipping industry and how Mohnish Pabrai found it in 2001 and rediscovered it and Frontline in 2002, as the company’s stock price fell sharply. Now, we’ll turn to some more details around the company: what was particularly risky and particularly intriguing about it.

Frontline: A particularly risky shipping investment

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Mohnish Pabrai was naturally intrigued by the steep decline in Frontline’s share price that had occurred from May through September of 2002.

But an investment in Frontline wouldn’t have been without risks that he must have considered. In Part One, we briefly discussed one of them: TCE charter rates in 2002 had fallen to a level below Frontline’s expense base. What if they remained there indefinitely? There were other risks in the company as well. Let’s discuss those and try to determine how Pabrai got comfortable with each.

Risk #1: Frontline bet heavily on the spot charter market

In deciding how to utilize their ships, many shipping companies will opt to diversify their chartering business among long- and short-term chartering, that is, between the three types of chartering we discussed before: bareboat chartering for very long charters and the most highly assured revenue stream, time chartering for chartering revenue over the medium-term, and voyage (spot) chartering, whereby rates change every day and are set with every trip.

Spot chartering is the riskiest of the three in that a company will be unprotected when a downturn in the charter cycle arrives. Of course, spot chartering also allows a company to capture the upside when the cycle turns up as well.1

Time charters are for weaklings.

- Coco Jacobsen, a character in The Shipping Man by Matthew McCleery, at least partially based on Frontline CEO John Fredriksen

Frontline was a company that was unabashed in its desire to play the spot market. Of the company’s 69 owned vessels in 2002, 48 (70%) were being chartered on the spot market. Teekay, one of Frontline’s competitors, on the other hand, reported 57% of its revenues from spot chartering in 2001. OMI Corporation reported 50% of its vessels operated on the spot market. Stolt-Nielsen reported 46% of its tanker business was done under spot contract.

This exposure to the spot market hurt Frontline in 2002. In the second quarter, the company reported that TCE rates were between $15,300 and $17,600, still hovering below the $17,400 breakeven cost we referenced earlier. Frontline also reported a net loss of -$16.9 million for the first half. Compare that figure to the five of Frontline’s competitors.

No other competitor in the group (except one) had produced a net loss in the first half of 2002, but Frontline had, which was a consequence of its bet on spot market chartering and the down cycle in charter rates.

Frontline’s appetite for risk was hurting the company in the downturn in 2002, and that was reflected in the stock price. Frontline’s stock was down 73% over the four months from May to September 2002. During that same timeframe, for example, OMI and Stolt-Nielsen saw their stock prices fall by only 42% and 37%. The market was punishing Frontline for its risk appetite.

Moreover, Frontline’s risk-loving nature seemed directly attributable to the man at the helm. John Fredriksen was the CEO of Frontline, and he had a reputation for being a swashbuckling risk taker.

From a Bloomberg profile of Fredriksen in 1997:2

“He’s a bit of a cowboy,’‘ said Cato Hellstenius, an analyst at Handelsbanken Markets. He has a completely different style than the other shipowners, and takes extremely high risks.

By 2002, Fredriksen was already a legend in the industry and had apparently amassed a sizable fortune.

His assets now include a stake in Vaalerenga ASA, the local football club, as well as ships, real estate and art worth about 4.2 billion kroner ($577 million), according to Kapital.

Reading about Fredriksen, I was genuinely torn. While his adventurous style, evident in the way Frontline was run, did have something to do with the market’s negative perception of Frontline in the fall of 2002, it’s also quite possible that in the tough and unpredictable industry of shipping, Fredriksen’s nature is what led Frontline to become the success it had been.3

Also, there was one very important point that might assuage an investor who was wondering about Fredriksen: the man was aligned with shareholders. Per the company’s 2001 20-F report, Fredriksen owned 34,579,054 shares of Frontline’s stock, a stake of 45.2%.

Risk #2: Frontline’s web of transactions and the Golden Ocean bankruptcy

Frontline Ltd., the company Pabrai was considering in 2002, was built by Fredriksen in a series of mergers and purchase transactions of other companies. Fredriksen had been acquiring shares in Frontline AB through his vehicle called Hemen Holding Ltd. and AB was acquiring other small companies, growing its fleet size. On September 22, 1997, AB announced a merger with London & Overseas Freighters Limited (LOF), and Frontline Ltd. was born.

From 1996 to the fall of 2002, Frontline engaged in many acquisitions or mergers with the stated goal of increasing its fleet and gaining scale in the industry. By 2002, it had the largest fleet of VLCC and Suezmax tankers in the market.

For a shipping industry outsider, this might look like hyperactivity, but for a shipping man, this was not all that strange. The shipping industry was a highly fragmented industry in 2002 (and still is today, albeit less so), and acquisitions were common as companies looked to consolidate and gain scale as an advantage.

Moreover, the corporate structure of shipping companies differed from that of companies in other industries. For every ship (or a few ships) that a shipping company owns, it creates a separate subsidiary company. The main reason for this is to ring-fence liability as much as possible. If a ship was involved in an oil spill, for example, having the ship be owned by a separate company limits legal risk as much as possible. In addition, some jurisdictions operated under a “sister ship” theory of liability in which a claimant against the company may arrest both the vessel which is subject to the claimant’s lien and any “associated” vessel controlled by the same owner. Separating vessels helps to limit this risk too. Finally, should the company need or desire to sell the ship (as was common), the sale could be effectuated easily by selling the stock in the individual shipco.

Indeed, most of what look like corporate acquisitions in the table above are simply the effective purchase of one or more ships by Frontline.

However, there was one transaction that could have raised an eyebrow: Golden Ocean Ltd.

Golden Ocean (GO) was a company that owned or owned interests in 14 VLCCs and 10 dry bulk carrying ships. The company embarked on an aggressive newbuilding program in the late 1990’s near a cyclical peak for the industry. It took delivery of those ships (and needed to service the mortgage debt that came with them) just as the tanker market started to weaken in 1999. The company ended up filing for bankruptcy protection in January of 2000.

Frontline’s 2001 20-F tells some of the story:

The story seems concerning on its surface, but a more detailed read of the 20-F reveals that Frontline actually swooped in as a distressed buyer of GO after it declared bankruptcy and hence a kind of solutions provider for the company’s lenders.

So, Frontline’s agreement to purchase GO in October 2000 was both beneficial to GO’s creditors (allowing them to receive from Frontline what they felt was the maximum recovery on their loan to GO) and it allowed Frontline to acquire, either directly or through options, up to the 24 vessels that GO owned. The cost of this transaction to Frontline was $63mn.

A further read of the 20-F reveals that Frontline appears to have taken on zero or minimal liability with respect to the GO bankruptcy.

In the end, what seemed to the casual reader or investor like an overactive management team acquiring company after company, one of which was in bankruptcy, seemed, upon closer inspection, to be much less risky.

Frontline was executing a consolidation of a fragmented industry (and focusing on the sub-industry of VLCC and Suezmax tankers), and it was looking for opportunities to acquire those assets in distressed situations, while limiting its own risk.

Risk #3: A potential extended downturn in charter rates

Perhaps the most severe risk of all to Frontline was the potential for charter rates to enter a prolonged downturn. Should that have been the case, Frontline, by virtue of its bet on the spot rate market, would have had to deal with losses for an extended period.

The downturn of the 1970’s and 1980’s

In fact, such a downturn would not have been unprecedented. Stopford describes the brutal and prolonged downturn of the mid 1970’s to 1980’s.4

Well, that’s frightening isn’t it?

The deep cycle of the 1970’s saw tanker prices go from as high as $60 million for newbuildings to as low as $3 million in the secondary market. If the market after 2002 experienced a continued decline like that one, there would be almost nothing Frontline could do to survive.

But the downturn of the 1970’s was different from the decline Pabrai was working with in 2002. The 1960’s saw large increases in world trade, with seaborne trade growing from 990 million tons in 1959 to 3,233 million tons in 1973, according to Stopford. Along with this huge increase came a surge in shipbuilding capacity and in ships delivered.

However, the Yom Kippur War in 1973 and recession in 1975, followed by dramatic increases in the price of oil ended the good times for shippers. Here is Stopford again:

The 2002 downturn

As difficult as it may have been for an investor to confront a potential shipping downturn like that of the 1970’s, there were reasons to believe the downturn in 2002 was not nearly as bad as that.

First, the increase in world seaborne trade over the 1990’s was much less than that of the 1960’s. Second, the number of ships in the world fleet had hardly increased much over 1980’s and 1990’s. The figure below from Stopford shows the difference between the two periods.5

Moreover, there were two positive trends that ship owners had going for them in the year 2002.

Positive trend #1: The rise of China

First, China was growing rapidly and had recently joined the World Trade Organization. The Chinese economy had averaged 10% GDP growth in the 1990’s and was becoming a bigger participant in world trade. The country joined the WTO on December 11, 2001, a move designed to pressure domestic reform, especially of a bloated state-owned enterprise system, to secure market access and trade stability, and to commit to export-led growth and integration into global supply chains.

Importantly, WTO membership also came along with a commitment by China to lower tariffs.6

Oil importing, in particular, was pointed to in the International Energy Agency’s 2002 report:7

Though these changes wouldn’t be carried out overnight, they signaled that China was ready to be a much larger trade partner with the world, which would have been a boon to shipping.

Positive trend #2: Increased scrapping due to regulation

This is a critical detail, and it is one that Pabrai cites in his reasoning for purchasing Frontline’s stock. It is also cited across Frontline’s annual report.

The oil tanker industry in 2002 was composed of two kinds of tankers: single-hull and double-hull. In 1989, the single-hulled VLCC Exxon Valdez grounded on Bligh Reef in Prince William Sound, Alaska, spilling about 11 million gallons of crude oil. The result was swift regulation from the US and later, from the International Maritime Organization and the EU.

Per Frontline’s 2001 20-F annual report, the effect of this regulation was to mandate the phasing out of single-hull tanker ships completely between 2005 and 2015. That same report shows that, of Frontline’s 64 owned oil tankers (59 vessels and 5 newbuildings on order), 44 of them were double-hull and 20 were single-hull (31%).

On its face, this might look concerning for Frontline, but when weighed against the rest of the market, it was actually an advantage. Frontline’s fleet was deliberately dominated by double hulls.

As we discussed before, Frontline was formed in a roll-up of the industry by John Fredriksen starting around 1996, well after the single-hull regulation was announced and put in place. Fredriksen’s strategy in building the company wasn’t just to buy up any ships; it was to (1) buy modern ships built after 1990 (when single-hulls stopped being built) and (2) to create scale advantages in the VLCC and Suezmax markets specifically.

The slide below, from a Frontline presentation in November 2001 states as much.

And a careful examination of industry data shows that Frontline was executing on its plan. According to industry research from Clarksons, in September of 2002, 66% of the tanker market was single-hull versus 31% for Frontline.8

What would this mean for Frontline?

In a market downturn when charter rates were low, like the one the industry was going through in the first half of 2002, many companies would be forced to raise cash by either selling ships or scrapping ships. Single-hulled ships would be the first to be scrapped, as shipowners, worried that the ships would soon be out of service, could not currently be operated profitably, and were burning cash on maintenance, opted to scrap and receive a few million dollars of value rather than continue to pay for a money-losing ship.

In fact, that trend was already beginning. Stopford’s Maritime Economics shows scrapping rates below. After the high charter rates (and low scrapping rates) from 1988 to 1991, scrapping began to increase in the 1990’s, mainly composed of older single-hulled ships that would ultimately need to be removed from service.

Frontline, on the other hand, was purpose-built to have an advantage in a downturn.

By deliberately focusing on buying the newest double-hulled ships, which naturally had longer lives, its fleet would benefit as single-hulls were scrapped in the downturn and tanker supply was taken out of the world market.

In addition, by deliberately focusing on scale as the largest VLCC/Suezmax owner, it would be well-suited to survive any downturn because of lower operating costs and having more ships to potentially sell if it needed to raise cash.

That was Frontline’s strategy in a nutshell. Limit the downside in a cycle downturn by owning newer ships and a lot of them, while competitors with older ships and fewer of them felt the pressure of losses and the need to resort to more scrapping, which would limit the global supply of tankers and, in turn, limit any cycle downturns, allowing Frontline to remain standing and benefit in the upturn.

Now it becomes a little more clear why Frontline focused on spot chartering. Fredriksen wasn’t simply gambling. He had a reasonable strategy for making it through cycle downturns, which he expected to be shallow because world fleet capacity would remain low from the single-hull phase out. Spot chartering would allow him and Frontline shareholders to make the most money in the cycle upturn.9

In Part Three, we’ll get to the crux of the investment, how Pabrai dimensioned the risk to Frontline, when he made his investment, and how it fared.

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References:

Stopford, Martin. (1997). Maritime Economics (2nd edition). Routledge.

Stopford, Martin. (2009). Maritime Economics (3rd edition). Taylor & Francis.

McCleery, Matt. (2012). The Shipping Man. Marine Money International.

Pabrai can regularly be seen on his Youtube channel giving interviews or talks to student groups who can ask him any questions they want. He answers freely, often recounting past investment successes and equally telling self-effacing stories of his own misses and boneheaded plays. His style is refreshing.

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One of the successes that Pabrai discusses in a few interviews is his investment in Frontline Ltd., a company engaged primarily in the shipping of crude oil, as well as other commodities. There are two great sources for Pabrai’s recounting of his Frontline investment, and one is his interview with Shaan Puri, linked below.

Pabrai also wrote the fantastic book, The Dhandho Investor, and in it, he describes the Frontline story over seven pages. He discusses how he first encountered the shipping business by scanning the pages of The Value Line Investment Survey in 2001 and finding an oil shipping company called Knightsbridge that was trading at a dividend yield of 15%.1 He studied Knightsbridge and the oil shipping industry to discover why the dividend yield was so high.

Pabrai describes a market whereby ship lease rates (called charter rates) were historically high and which was very profitable for shipping companies, and he was skeptical that the good times could be sustained. The high charter rates, as I learned, occurred toward the end of the year 2000, a year in which Knightsbridge earned $48.7 million in income, or $2.85 per share. The company was set up to distribute its profits to shareholders in the form of dividends, and it distributed nearly all of its income that year. In the third and fourth quarters of 2001, the company’s stock traded between $22.69 and $14.32, which explains the high dividend yield that Pabrai saw.

Because Pabrai thought the recent results were bound to abate, he ultimately passed up an investment in Knightsbridge in 2001. However, as he reflects in his book and as Buffett is fond of saying about investing,

Everything you learn is cumulative… What I learned at twenty is useful to me now. What I learned at twenty-five is useful to me now… It’s not a field that changes dramatically in terms of the underlying principles.

- Warren Buffett, interview with Forbes (April 2014)

Being patient and finding opportunity later

Sometime in the late summer or fall of 2002, Pabrai rediscovered the shipping industry when charter rates declined to very low levels and the industry was suffering.2 He reports in The Dhandho Investor,

The stock price had gone from $15 to $3 in short order.

Pabrai is talking about the rapid decline in Frontline’s stock price from a peak daily close for the year of $12.94 on May 20, 2002 to a low of $3.43 on September 24. Frontline’s stock had fallen 73% in just four months. Based on comments Pabrai made in his interview, I believe he started revisiting the shipping industry and looking at Frontline around the end of August or beginning of September when the stock was around $6 per share. We’ll use September 15, 2002 as the cut-off for any information Pabrai would have had available.

As of that date, Pabrai would have had access to the 2001 annual filing form 20-F (filed on July 12, 2002) and the semi-annual 6-K (filed August 22, 2002), in addition to any material prior to that date.

A quick glance at those two documents shows that Frontline made $382 million in 2001, and it lost -$16.9 million in the six months from January to June 2002. In fact, those glaring differences reinforce how volatile Frontline’s business was, something Pabrai already knew from studying the sector back in 2001.

At a stock price of, for example, $6 per share, with 76,466,566 shares outstanding, Frontline would have had a market capitalization of $458.8 million, just 1.2 times the total amount of profit the company made in 2001. It may have been this simple comparison alone that led Pabrai to dig in deeper to see if this was an overreaction by Mr. Market or if there were more serious problems with Frontline.

Let’s take a look ourselves.

Frontline and the global shipping industry

Frontline is a shipping company whose business is the ownership, operation, and chartering out of ships, the majority of which were oil tankers. Oil shipping companies make money by building or purchasing oil tankers and then chartering them out to other companies that need to move oil from one location on the globe (like the Middle East) to another (like the US or China). These other companies can be major oil companies, like Shell or BP, national governments, and commodity trading firms.

The shipping industry is filled with jargon, so let’s review some of it so we can examine the opportunity in Frontline intelligently enough.

Crude oil carriers are generally delineated by their size and/or the amount of cargo they can carry. Their capacities are expressed in “deadweight tonnage” (dwt), which is the amount of stuff a ship can carry, including cargo, fuel, fresh water, stores, and crew.

Crude oil carriers are typically categorized into six segments:

• VLCC (very large crude carrier) - tankers over 200,000 dwt and up to 320,000 dwt; generally carry about 2 million barrels of oil. Used for long hauls.

• Suezmax - 120,000–200,000 dwt; carry roughly 1 million barrels of oil; these tankers are able to transit Suez Canal fully loaded, hence their name. Generally medium hauls.

• Aframax - 80,000–120,000 dwt; typically carrying around 0.5 million barrels of oil

• Panamax - 60,000–80,000 dwt; Generally very short hauls.

• Handy (or “Products”) - 10,000–60,000 dwt

• Small tankers - less than 10,000 dwt

In 2002, Frontline owned one of the largest fleet of crude oil carriers in the world, if not the largest. It owned a total capacity of 14.0 million dwt, much more than its closest competitors. Its owned fleet consisted of 29 VLCC’s, 30 Suezmaxes, and 10 other ships that were engaged in the business of shipping dry commodities. A report from Clarksons in September 2002 lists the world VLCC fleet at 428 ships and the world Suezmax fleet at 270 ships. Frontline was a big player in a fragmented industry.

Shipping companies typically put their ships out for charter in one of three ways:

• Bareboat charter. The owner provides only the ship, and the charterer operates the ship fully. Rates are long-term, often five to twenty years, which can help insulate the owner from the vagaries of charter market rates but also deny it any upside.

• Time charter. The owner provides the ship and the crew. The charterer directs trade and pays for fuel. Rates are medium-term, often months to a few years.

• Voyage (or spot) charter. The owner bears all shipping costs. Rates reset every trip and expose the owner to the full risks and benefits of the charter market. Most of Frontline’s ships were on the spot charter market.

The oil shipping business is fundamentally a very difficult business. In general, there are many competitors, and it is difficult to differentiate your product (which is moving oil from one location to another) from that of others. So, the companies that operate in the space are all supplying roughly the same commodity. Worse, the price of that commodity, which is the market rate for chartering a ship, can be volatile and difficult to predict.

Shipping cycles

I read many great sources as I was building this case study, from annual reports to a textbook to even a great fiction work called The Shipping Man by Matthew McCleery. In every piece, it was readily apparent that the shipping industry is deeply cyclical.

Why is shipping cyclical? Because charter rates depend on two factors, the demand for shipping (crude oil in the case of Frontline) and the supply of ships for hire. From the Frontline 2001 20-F annual report:

The demand for shipping oil depends primarily on activity in the world economy. When the demand for oil is high, so too is the demand to ship it, and oil shippers can earn healthy profits. However, when oil demand increases, the price of oil also naturally rises in free markets, which both curbs the demand for shipping and makes shipping more expensive through higher fuel costs. When the demand for oil drops, demand for shipping does too, and the profits of oil shippers can decline.

The supply of tankers also influences charter rates. However, while the demand for shipping oil can change over the course of just a few weeks or months, the supply of ships is much more fixed. From the great reference book Maritime Economics by Martin Stopford:3

So, what do we have?

1. When the demand for shipping oil is high, particularly because the economy is doing well, the supply of ships is relatively fixed because they take a while to build, and shipping companies can earn good profits.

2. Then, many of them take some of those profits and order new ships (called “newbuildings”), so as to capture more business.

3. Inevitably, something happens to cause the demand for shipping oil to decline, like a recession or the price of oil increasing or exogenous effects like tariffs, causing charter rates to decline. Meanwhile…

4. The new ships that were ordered start being delivered, causing an oversupply of ships while charter rates are already on the decline. This exacerbates the decline in charter rates, forcing many companies to charter out their ships at too low a rate, leading to losses. Ship owners cease ordering new ships and now need to hunker down and survive.

5. The most unprepared companies are forced to sell their ships. If a ship is too old to be used, meanwhile, it gets scrapped. This removes ships from the world fleet and helps supply balance out again.

6. When the demand for shipping oil recovers, so too do charter rates, bolstered by all the scrapping that has occurred over a few years. The cycle upticks and begins anew.

Here is Stopford again:

So, charter rates are difficult to predict, highly cyclical, and can be very volatile, dropping by large amounts even over the course of a short period.

What’s worse, many of the expenses that a shipping company must bear are fixed for the long-term, so they cannot be easily managed as charter rates fall. Fixed costs, those that do not change regardless of how much charter business the company does in any period, include crew costs, ship maintenance, insurance, and the company’s capital costs, like interest payments on its vessel mortgage loans and vessel depreciation expenses. Frontline and other shipping companies also bear variable costs, increasing as the company does more business, particularly fuel costs (known as “bunkers” in the shipping industry) for spot chartering.

The simplest way to think of the shipping business, and indeed the way Pabrai describes his investment in his interview and in his book, is that shipping companies carry a bunch of expenses related to owning and maintaining their fleets, expenses they cannot easily control or manage, and the ship charter revenue that the company brings in must exceed these costs in order for the company to make money. But charter revenue is very cyclical and outside the control of the company.

These two parts of the income statement, cyclical revenue from volatile charter rates and the relatively fixed expenses of owning, maintaining, and running ships, are well known in the shipping industry. Maritime Economics shows a succinct representation of the cyclical economics of the shipping business in the figure below on the left.

Because this balance between charter rates and a shipping company’s costs are so important, Frontline and other shipping companies typically report both the average charter rates they realized for the period and their expense breakeven number.

Frontline’s realized charter rates shown below for the period 1998 through 2001. I have highlighted the average spot charter rates the company was earning. (Shipping companies refer to the revenue they earn in the spot chartering market as “TCE”, “time charter equivalent”. The term signifies revenue flowing to the company, as distinct from the more generic “charter rate”.)

Those TCE rates give a sense for how much revenue Frontline was able to earn each year. The years 2000 and 2001 saw high charter rates, and, as we’ll see, were great years for the company. 1999, on the other hand, was very poor, and 1998 was modest.

What about the cost side of the equation? How much did it cost the company to run its ships, and therefore what level of charter rate was good enough for the company?

Frontline’s reported average operating costs per ship per day are reproduced below.

These rates, however, only tell a portion of the story.

When shipping companies report operating costs, like above, they include only the cost of “running the ship” which is roughly fixed per day regardless of whether the ship is on voyage or idle. They exclude some other costs, primarily bunker costs (fuel) and the company’s capital costs.

However, by searching other company filings, I was able to find just a few mentions of the figure we are after: the all-in breakeven cost of running the company per ship per day. This figure is not reported as regularly as the operating cost figure, but the company’s 6-K report from March 2002 had a good (and, for Pabrai) timely disclosure:

These two figures include all the costs Frontline had to bear, so they tell us the TCE rates that Frontline must earn to be profitable as a company. I calculate the weighted average figure to be $17,400 based on the number of each vessel type Frontline owned.4

Now that we have an idea for the charter rates the company needed to earn to generate a profit, can we get a sense for how likely the company was to see a profitable charter market? How does this breakeven TCE rate compare to TCE rates historically? Those are shown in the chart below, using data from Clarksons Shipping Intelligence Network.

So, after a bit of analysis, tanker TCE rates had dipped below Frontline’s breakeven rate for most of 2002. As of September 2002, industry TCE rates reported by Clarksons were around $12,700 per ship per day, almost $5,000 less than Frontline’s breakeven rate. If these rates persisted, and with 67 tankers in its fleet,5 Frontline stood poised to lose on the order of $120 million a year.

This is the situation Pabrai encountered in September of 2002, when he rediscovered Frontline and the shipping industry. Frontline was one of the largest shipping companies in a highly cyclical industry whose stock price had taken a deep dive during another of the industry’s downturns.

Given everything I just described, like the highly cyclical and unpredictable nature of the shipping industry, why would anyone except the most risk-seeking gamblers in the world want to be involved in an investment? The answer, of course, is the potential price of that investment.

I don’t know exactly how Pabrai rediscovered Frontline in 2002, but I suspect he saw just how low its stock price dropped and thought “maybe that’s too low”.

But how could he assess how low a price was too low? After all, given the fixed breakeven cost of the company, if TCE rates never rose above $17,000 to $18,000, then Frontline would be a company that never made any money at all.

In Part Two, we’ll delve deeper into some other risks around Frontline and then discuss Pabrai’s rationale for making an investment.

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References:

Stopford, Martin. (1997). Maritime Economics (2nd edition). Routledge.

Stopford, Martin. (2009). Maritime Economics (3rd edition). Taylor & Francis.

McCleery, Matt. (2012). The Shipping Man. Marine Money International.

The Owner’s Memo is on vacation this week and will return next week with another case study.

In lieu of a regular article, I’d like to highlight four pieces of reading that have stuck with me over the past year or so. None of them have to do with investing per se, but they do by extension. The pieces discuss work and performance, and, as such, they contain lessons applicable to the work of investing (and other work).

I hope you find them interesting.

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The Mundanity of Excellence by Daniel F. Chambliss

Daniel Chambliss is a professor of sociology and was an amateur swim coach. In the 1980s, he conducted research to discover what made the most elite athletes in the sport of swimming different from other swimmers. He spent one and a half years attending national and international swim meets, including the 1984 Olympic Games. The result of his work was this journal article published in 1989.

In it, Chambliss makes a few interesting and unintuitive points:

1. “Talent” is a meaningless description. Chambliss argues that the common refrain, that great athletes are “talented”, is meaningless and circular because we only call an athlete “talented” after they achieve success, like winning competitions or performing some great feat.

2. Excellence in swimming requires qualitative difference. Top swimmers do things differently than the rest, and there are step-change differences at each of the higher levels of the sport. The styles of strokes, dives, and turns are dramatically different at each level.

3. Excellence is much more mundane than we think. Motivation is too. From the article:

“People don’t know how ordinary success is,” said Mary T. Meagher, winner of 3 gold medals in the Los Angeles Olympics.

…

”When Mary T. Meagher was 13 years old and had qualified for the National Championships, she decided to try to break the world record in the 200 Meter Butterfly race. She made two immediate qualitative changes in her routine: first, she began coming on time to all practices. She recalls now, years later, being picked up at school by her mother and driving (rather quickly) through the streets of Louisville, Kentucky trying desperately to make it to the pool on time. That habit, that discipline, she now says, gave her the sense that every minute of practice time counted. And second, she began doing all of her turns, during those practices, correctly, in strict accordance with the competitive rules. Most swimmers don’t do this; they turn rather casually, and tend to touch with one hand instead of two (in the butterfly, Meagher’s stroke). This, she says, accustomed her to doing things one step better than those around her—always. Those are the two major changes she made in her training, as she remembers it.”

…Within a year Meagher had broken the world record in the butterfly.

Beyond nature and nurture by David Bessis

This article by mathematician and writer David Bessis pairs well with Chambliss’s work. Bessis makes the argument that mathematical talent isn’t primarily the result of genetics, and he provides commentary from elite mathematicians to support his claim.

It is popular to debate whether someone’s achievements in a given field are the result of “nature” or “nurture”. Bessis, citing geneticist Eric Turkheimer, discusses a third factor that he calls “idiosyncratic cognitive development”, which is his attempt to grasp at the vague factors in one’s life not covered by genetic makeup nor by the family environment. What is it that happened to some of the greats that was different from the rest?

He tells a brief story about Bill Thurston, a celebrated mathematician and Fields Medal winner, who was able to visualize geometric structures in 4 and 5 dimensions. How did he gain this unimaginable skill? Thurston had a congenital squint that deprived him of the ability to see the world in three dimensions. To rectify it, he had to practice imagining “stitching” together the 2D images he saw to form the 3D world around him.

As a first-grader he made the decision “to practice visualization every day.” Asked how he saw in four or five dimensions he said it is the same as in three dimensions: reconstruct things from two-dimensional projections.

Thurston practiced his way to elite performance, and the anecdote squares with Bessis’s own experience in learning elite mathematics.

Since reading this article, I’ve become enamored with Bessis’s writing. You can find other articles on his website. I recommend also reading Attention is all we have and Writing is hard - and it should be.

What’s the next physical action? by Oliver Burkeman

This is a short article that I come back to regularly. While the Chambliss and Bessis pieces are helpful and inspirational, giving an “ordinary” person hope that deliberate practice can bring about excellence, Burkeman’s article is a nice reminder of some of the basics of good work.

Namely, Burkeman reviews some popular and classic work, and recalls the advice pioneered by David Allen and written about by Cal Newport that, in order to get something done, it helps immensely to break it into chunks that are tangible, even physical.

Cal Newport makes the excellent suggestion (also explored in his book Deep Work) to set targets for focused work in terms of tangible products. If you aim to spend the morning planning a given project, aim to produce, say, a two-page strategic plan which you can print out and hold in your hands. Then print it out, and hold it in your hands.

Burkeman’s advice is especially valuable in a world in which so much information resides online. It’s easy to have good intentions about your work but get dragged into a vortex of online information and emerge feeling like you didn’t actually do the work you intended.

I’m constantly creating to-do lists for myself, and constantly needing to remind myself of Burkeman’s counsel. Work goes much better when it is broken into concrete steps rather than vague ones.

After Automation by Dan Shipper

This piece is a bit different from the prior three, but I include it here because it relates to the work we do, and it tries to tackle the question that so many of us are wrestling with as AI continues to advance: “does AI progress mean that human work will be redundant or replaced?”

Dan Shipper is the CEO of Every, a media and software company. The article he wrote discusses how his company is using AI today (or at least as of May 2026, when it was written). It is replete with examples, which makes it especially enjoyable and useful. Much of Shipper’s discussion describes agentic-style work at Every, and he offers a balanced view of the quality; the agents help the team, but it cannot yet completely replace most work.

Because everyone has access to the same models, and the models are all based on yesterday’s competence, by default the models end up creating work that ranges from “a decent start” to “it’s just plain slop.”

I’ll leave you with Shipper’s commentary about whether humans might be replaced.

And yet, the paradox remains. If you talk to anyone in the AI industry—or to early adopters outside of it—you’ll hear the same thing we’ve noticed internally: There’s more work to do than ever.

The big question, within the industry and without, is: Is this just a temporary state of affairs? Will the next model drop be the one to replace everyone? We watch the benchmarks and sweat, wondering if there’s a tipping point around the corner where all of the jobs go away.

There’s no tipping point coming where things flip and the jobs are gone. The new reality is the opposite—the more we automate, the more expert human work there is to do.

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The Owner’s Memo is on vacation this week and next, so, in lieu of a regular article, I thought I would write briefly about three books I have enjoyed over the past many years. Two are business biographies and one is about some great investing case studies. Each of the books is excellent, and the biographies would make great reading for your own vacation.

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Buffett: The Making of an American Capitalist by Roger Lowenstein

I first read this book perhaps fifteen years ago, and I was captivated. Roger Lowenstein is a fantastic writer, with seven books under his belt, and was a journalist for The Wall Street Journal and other financial publications. This book, arguably the one he is best known for, is the most readable and pithy biography of Warren Buffett for my money. (The Snowball by Alice Schroeder is easily the definitive biography of Buffett; it is massive, was written later, and is more complete than this one, but Lowenstein’s book is a more enjoyable read.)

Lowenstein takes the reader through Buffett’s life (up to the time of publication in 1995) and gives a real feel for the obsession and dedication with which Buffett conducted his work, and he does it while propelling the reader through the book. I could not put the book down when I first read it. Leafing through the pages now, I have a smile on my face.

Here is one passage about Buffett making a large investment in GEICO in 1976 that highlights how the book provides investment details while keeping the reader riveted.

Today, of course, Berkshire Hathaway owns GEICO completely, and Lowenstein reveals the story of how that came to be with the fine detail that defines a great nonfiction writer.

The entire book is written like that.

You Can Be a Stock Market Genius by Joel Greenblatt

Okay, this one is probably not beach reading and the title is notoriously bad, but it may be my favorite book about investing.

Joel Greenblatt is a hedge fund manager, author, and adjunct professor at Columbia Business School. He’s a great investor with the track record to prove it. In the back of YCBASMG (as this book is lovingly known), Greenblatt highlights the performance of his hedge fund, Gotham Capital, over the years 1985 to 1994, when he managed money for outside investors: the fund returned a stunning 50% per year before fees.

Greenblatt is also a talented professor; you can find some of his lectures from Columbia in online videos along with detailed notes from the classes. And he is also an excellent and entertaining writer. YCBASMG is filled with case studies from Greenblatt’s time running Gotham Capital. Two things make the book unique and satisfying.

First, the examples Greenblatt writes about are the types of investments most people never consider or study: company spinoffs, rights offerings, and restructurings to name a few. Second, he gives the reader enough detail to make them feel like they are understanding a subtle and complex situation. The reader feels that the work is not easy, but also like they could do it themselves. This is one of the first books that made me fall in love with investing. If you want to read some great investing case studies from a manager who walked the walk, this is the book.

The case studies are a little too deep to quote in brief, but here is a passage from the start of the book:

A Sportsman’s Life by Leigh Perkins

While the other two on this list may be already known by some readers, I bet this one won’t be. My father gave me the book about two years ago, and I tore through it.

Leigh Perkins owned the outdoor sporting goods retailer Orvis. Leigh didn’t found the company; he bought it from the prior owner, Duckie Corkran, in 1965. The book tells the story of Leigh’s life, from his early years as a boy through his retirement from Orvis, passing the business on to his son in 1992.

It’s a very easy read, with Leigh telling the story in an informal and conversational tone. (Kudos to the co-author Geoffrey Norman.) Leigh is straightforward and direct, admits his faults and failures easily, and leaves the reader with the conclusion that Orvis succeeded in large part due to his love of fishing, hunting, and the outdoors, his commonsense approach to understanding what the customer wanted, and his hardworking nature. Here he is explaining how he adapted the idea for a very successful product:

Can you imagine a professional CEO who wasn’t into fly fishing in this way trying to compete with Leigh and Orvis?

A Sportsman’s Life is full of fun anecdotes like this and also deeper financial and business lessons.

I’ll leave you with one last passage from the book. Leigh was born into a wealthy family, but did not rely on his family’s wealth. (He purchased Orvis for $400,000, half of it borrowed and half of it his own money earned and saved by working as a salesman up to the age of 37.) Why didn’t he sit back and live a relaxed life?

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These models are incredibly capable and getting more capable all the time. Almost everyone reading this will have fully adapted to what Ben Thompson calls the first paradigm of AI, “the ChatGPT era” (which I define as being an active chatbot user as a replacement for Google searching), but I suspect most of you have not fully adapted to the second paradigm, “the reasoning era,” in which I include automated coding. As Ben describes it:

Reasoning entails an explosion in chain-of-thought tokens, and different models need different amounts of reasoning tokens to arrive at the right answer.

For those of you who have been following the progress in LLMs and coding wrappers and harnesses, the following will be no surprise, but I hope some of the details and results will jog a new idea or two for you. Also, I suspect many of you are having a similar experience to mine. We read an article or see a video almost every day that claims another new and massive breakthrough in artificial intelligence, and we feel a tinge of panic or inadequacy in our own AI usage. Agentic workflows can automate all of your work! Some agent or model you’ve never heard of before has solved a long-standing mathematics problem! People are running entire small companies using only an AI model!

For me, the cure for rising anxiety is almost always to put my head down and do some work, and with that in mind, let me show you what I’ve created. I’ll focus on the four simple applications that are related to making my personal investing a bit easier.

You can make your own software now

Over the past year or so, I have used Claude Code and, to a lesser extent, Codex to create at least nine rudimentary applications to help me with my work and personal life:1

1. an application to search, display, and download corporate filings from the SEC’s EDGAR database,

2. an application to search the names of investment firms and display their current holdings through their 13F forms,

3. a portfolio tracker that unifies holdings in a few different investment accounts,

4. an investment ideas tracker,

5. a customized calendar and task manager,

6. a dieting and meal-planning application,

7. a landing page for my personal website,

8. a financial calculator,

9. three different mortgage amortization and refinancing calculators (these were early experiments).

Some of these, like the mortgage calculators, were pure experiments that I no longer use, some, like the meal-planning application, are still being developed, and some, like the four investing applications, I am using every day or every week and continuing to add features here and there. I’ve been amazed at the capabilities of the models to quickly and easily generate applications that I’m getting so much use from. The biggest takeaway I’ve had from all of my experimenting is that it is now possible for someone with little technical ability to create personalized software for themselves.

I should say here that I am a reasonably “technical” person, but I don’t have any formal training in software engineering. If you divided the world up into professional (or formally trained) software engineers and non-professionals, I would guess I’d be in the upper five percent of the laypeople.

That being said, the LLMs dramatically shrink the gulf between not knowing how to code and being able to produce software. Without LLMs, I would only have been able to create the web applications listed above with many months (years?) of coursework first. The models have definitively opened up software creation to every educated person with no formal software engineering training. What’s more, for anyone feeling doubtful about that statement or about their own abilities, the solution resides in these tools themselves; if you don’t know how to start, ask the LLMs themselves how to. You will find step-by-step instructions for any level of understanding, in a way textbooks or online videos cannot replicate.

Why build your own applications?

Why did I feel the need to create my own software? After all, nothing I described in the list of nine applications above is new or revolutionary; there are probably several off-the-shelf options for each of them. In Apple’s App Store, for example, a search for “financial calculator” brings up five to ten decent options and many more depending on what features or design appeals to you most.

Yes, there are some applications that are so generic and so well-designed that I don’t need my own. But there are three instances in which I do want my own solution:

1. when I am looking for a very specific use case to support my own workflow,

2. when existing free applications are bloated by advertising or their paid counterparts cost too much, or

3. when existing applications are poorly designed.

Take my first example above: an application to search the SEC’s EDGAR database. The existing solutions are a case in which all three apply.

The SEC’s EDGAR interface is poorly designed

I’ll quickly explain what’s wrong with the existing solution here. The SEC’s website, while a good effort, hardly behaves in the way any reasonable end user would want.

First off, there are, to my count, three separate landing pages one can find if one searches for something like “EDGAR database”. One of those is defunct, and the other two are functional. Why are there two functional versions? I don’t know, and to make matters worse, the more modern-looking version only returns documents back through 2001, while the older version returns documents as far back as the early 1990s. So, depending on what the user wants (a more modern system or more document history), he or she must remember to use one address or the other.

For most of my work, I choose to use the older system, with access to documents back to the early 90s. The online access to old documents is great, but it raises a second problem. After a user searches for a company, a table of documents is returned. If the user finds their document in the table, visits another website and then returns to the SEC site, their position in the table is cleared and they need to find the original document all over again. For high-volume document searching, this makes the website almost unusable.

Finally, there is no good way to bulk download any set of documents a user might want. Frankly, although it is possible, there is no decent way to download even a single document.

Off-the-shelf software is good, but costly

OK, enough ragging on the SEC for a moment. Others have run across these and other problems in the past, and so, there exist several software front-end applications that allow users to search EDGAR filings in a friendly way.

The website BamSEC is the best of the bunch. It offers the kind of functionality a user would want to see:

• Useful search functionality with autocomplete and autosuggest: search “Cost” and “Costco Wholesale Corporation” appears.

• Filings split out and categorized based on what they contain: 10-Ks and 10-Qs for financial data, 8-Ks for timely company news and disclosures, Form 4s and others for insider transactions, etc.

• A well-designed and easy to use interface

Unfortunately, BamSEC provides only a limited amount of its functionality for free. If a user wants to access more than roughly the past five documents in any given category, he or she can only do so with a Pro plan, which comes at the price of $69 per month.

My own EDGAR Explorer solves these problems

So, after suffering under the yoke of a clumsy government website and moderate annoyance at the thought of paying $70 per month to access public documents, I decided to build my own front-end for EDGAR. It was a pretty simple process, and the results were better than I imagined they would be.

I started by using Anthropic’s Claude suite of applications and accompanying models via the Claude desktop app on my iMac Pro. I selected Claude Code and chose a folder on my Mac that I wanted Claude to work from. At the time I created the application, I was using Opus 4.7. My first prompt was a simple description of what I wanted to create:

I want to build an application that simplifies the SEC Edgar database. Basically, I want to be able to type the name of the company and be able to download specific types of its documents and have them appear in an organized fashion.

After that, Claude prompted me with a few additional questions, which I answered.

What kind of application do you want to build?

Web app (Recommended)

Which document types matter most to you?

Ownership statements, 10-K (Annual reports), 10-Q (Quarterly reports), 8-K (Current reports), Proxy statements (DEF 14A)

I gave it permission to run commands on my computer to create the software. After what was probably 10 to 20 minutes, it returned a successful first version of the web application, written in TypeScript with React library (neither of which I have coding experience with), and it told me the few simple steps I needed to take to run the application and see the results.

Pretty amazing. Claude had created 23 files and a moderately functional front-end application for the EDGAR database.

After that first version was created, I probably spent an additional four or five hours of time over a few days prompting Claude to create additional features, fine tune some design, and fix some minor bugs it inadvertently created. Claude tells me that I prompted it 48 times in total, and the model output approximately 40,000 tokens in prose responses to my prompts and another roughly 30,000 tokens worth of actual code.

For the most part, the application was functional right from the start. Claude got only a few things wrong, and they all seemed to be at the level of what a conscientious human developer might also miss. For example, I pointed out that one of the first versions of the app only returned filings back through 2015. Claude responded that documents beyond the first 1,000 are referenced in a separate SEC data file, and it fixed the issue. There were other quirks too, like file count totals not being correct when the user applied a filter, and Claude had little problem fixing them after I pointed them out.

The end result, as it exists today, is a truly useful piece of software, screenshotted below.

The “EDGAR Explorer” is a functional web application with some great features:

• autocomplete and autosuggest search functionality,

• the option to show all the filings from a company at once or as one of five categorized subsets,

• the full history of SEC electronic filings (in the case of Costco, back to 1994),

• the ability to narrow the search by filing date or “as of” date,

• search capability within filings themselves,

• bulk download capability, and my favorite,

• “single page mode”, which allows you to select a filing and read it all in the same web page. No more jumping from browser tab to browser tab.

I use the application several times a week, doing things like bulk downloading documents for case studies that I’m writing or quickly finding the latest financial filings, earnings presentations, or other documents for any public company I’m doing some research on. For a total investment of about five hours of my time, it’s amazing how well the software works and how useful it is for me. I also can’t emphasize enough how enjoyable the software is to use since I “built” it and set the features just the way I want. And anytime I’m stymied by some feature, I can ask Claude to adjust it.

Other applications

As I mentioned above, I also created three other simple applications to assist my investing work.

A Form 13F viewer to see the holdings of various investment firms

This one was fun to build. Investment firms with over $100mn in Section 13(f) securities under discretionary management need to file a Form 13F every quarter with the SEC. The forms can be good sources of investment ideas; I especially enjoy finding companies I’m unfamiliar with in the portfolios of investors I admire. (There is a big caveat with “cloning” the ideas of other investors. Too many investors will ride the coattails of their heroes without doing the work themselves. Do your own work, and resist the urge to follow blindly.)

There are plenty of websites and applications (paid and free) that follow these filings, and some of them are good, but just about all of the free websites out there clutter the page with advertising, some to the point of crippling their utility. In addition, many of the sites report options holdings incorrectly, displaying the nominal value of the options instead of an estimated market value (or instead of simply flagging the nominal value as not comparable to the value of outright stock holdings).

Because 13F information is public, with just a few hours of prompting Claude, I was able to create a better 13F viewer that has no ads, segregates option holdings (to better see top equity holdings without miscalculation), and adds a few additional features too, like showing other investment firms that hold the same stock and showing how much a given stock is up or down in price since the filing was made.

A portfolio tracker

I manage my own personal investment portfolio alongside those of some family members. There are both personal accounts and retirement accounts to manage. Over the years, as more accounts were added and life events happened, there are some accounts with one online brokerage and some with another. In the past, I would track the holdings in each account with a spreadsheet. When I wanted to make a new investment, I would need to spend 30 to 60 minutes deciding what, if anything, to sell, which accounts to place the trades in, and I would need to create and monitor a checklist of each trade to be executed.

There is, of course, software to help with this problem. Also, I could solve part of the problem by transferring all the accounts to Interactive Brokers, which offers the ability to unify trading by prorating any trades across “client” accounts. I’ve used that in the past, and I’ll probably use it again in the future. To date, I’ve treated this management somewhat informally, so I haven’t used a third-party software solution or taken the time to transfer the accounts to a single broker.

I was having so much fun developing other software with Claude, however, that I took a few hours to create a unified portfolio tracker that shows me everyone’s account holdings in one place. When I want to make an investment, the app can suggest how much cash I have to use in each account and how much of another investment I need to sell, all based on some rules I provide. The app is like a streamlined and supercharged version of the old spreadsheet I was using before. Also, I can adjust the app at any time to suit a new feature or presentation, something not possible with off-the-shelf solutions.

An investment ideas tracker

I created this last one almost purely for fun. It’s a simple web app that lets me track any stocks that I may be interested in doing more work on or in reevaluating later if the price declines. I can enter a stock ticker, a target price, and some notes, and the app simply keeps the list for me. I run across potential ideas for research all the time, and this app is a brain dump of sorts.

Now, there is no feature in this particular app that cannot be had with an off-the-shelf version or with a simple spreadsheet, but there are two things I think are important: self-ownership and malleability.

First, by creating and owning the work, I tend to feel much more invested in and excited about revisiting a growing list of ideas than if they were typed into (yet another) spreadsheet.

Second, I envision all four of these small apps I’ve created ultimately living in one personal webpage or application. That app will become a go-to piece of software I fire up whenever I’m doing investing work, and that makes the work more enjoyable and less burdensome than if, each time, I needed to recall where I stored my idea tracking spreadsheet before opening it. Ditto for the SEC EDGAR webpage, the right 13F tracking webpage, and my portfolio tracker spreadsheet. By creating all of these and storing them in one “place”, I’ve reduced the mental burden of recalling how and where I store my work.

Remote use

What about deploying the software for use when I’m not at my desktop computer? I have a version of the app deployed at my personal website, so I can access it whenever I want. Alternatively, there are web hosting services, like Vercel, that will host your software for free with limits. There are some steps to take to deploy an app to Vercel, but Claude walked me through it quickly and easily.

If you’ve made it this far and would like to try the application, you can do so by visiting EDGAR Explorer on Vercel. I’ll keep the link live as long as I don’t get any warnings about high usage.

Personalized software

The age of personalized software for non-software-developers is here, at least for relatively simple applications like the one I described above and the other simple applications I’ve vibe coded over the past year. If there are any software applications that you currently use but that are not quite right or that simply don’t exist in the way you wish, today’s LLMs are more than capable enough to build simple (and even relatively complex), personal applications in very short periods of time. Consider putting some time aside over a weekend to experiment.

The applications that should prove most promising are those for which data is public, like SEC EDGAR data, or personal, like a more personal task management app or customized dieting app. (There are public databases that tabulate the macronutrient and calorie counts for thousands of foods.)

Think about things you use your smartphone, tablet, or computer for today that could be app-ified. Any notes you take using your smartphone may be a good place to start. Maybe you have a brain dump of notes on your phone. Maybe you record stats for a sport you or your children play in a note on your phone. Either of these could be good candidates for a personal app that can make the recording more fun and, in the case of statistics, dynamically show you the trends. What about your work? Do you send information or analysis to clients using third-party software? Would it be useful to have some of your own custom ideas added or even your own branding?

Developing a simple piece of software may be a good way to start using the information you’re recording or getting some more business or a leg up at work.

One investing takeaway

Finally, there is one important takeaway as it relates directly to investing here.

For a long-term investor interested in investing in software companies, I think it is useful to group them into one of two types. Within the first type are those companies that provide something that the LLMs can also provide, something akin to judgment or intelligence, software development included, with the LLMs increasingly providing it at a fraction of the cost.

It was so easy for me to create my own front-end EDGAR software. One result is that I was able to save the $69 a month that I would otherwise have paid to BamSEC. Pieces of software that charge their users simply for great user interfaces should have a tough time from here on out. I’ve cited BamSEC here, but some others spring to mind as well.

Within the second type are those companies that provide something the LLMs cannot provide, like proprietary data, access to a network, social or otherwise, human judgment, and potentially something like taste or curation.

Some examples spring to mind in this category, like social networks (Reddit) or similar (Roblox) and financial network or data providers (CME Group, Intercontinental Exchange, Tradeweb, MarketAxess).

Many publicly-traded software companies have been crushed in the past year on exactly the concerns I mentioned, particularly those in the type-1 bucket, while those in the type-2 bucket are not down in price nearly as much. So my commentary here is not particularly new or revealing.

What’s more, no investment can be assessed without considering its price. A simple classification of companies into type 1 or type 2 is not, in and of itself, a judgment on the potential of any of these companies as investments. For that, price must be taken into account. Almost certainly, there are some type-1 companies that will be much better investments at current prices than some type-2 companies.

However, actually creating my own software and deploying it showed me up close just how easy it is for anyone to mimic many existing software solutions currently available at a fraction of the cost and with extreme customizability, and the ease of doing this should only become greater as these models rapidly get better. If you find yourself tempted to invest in a type-1 company and you’re dismissing the potential for the company to lose subscription revenue, I would at least urge you to consider a more precise thesis. Why will this particular company, X, keep its revenue base if its software can be duplicated easily? Does it provide something that obviously cannot be replicated with an LLM?

As I said, there may be software type-1 companies that are great investments from here on out because they are priced too low today. But remember the punch-card philosophy of Buffett: the best investments are not those that merely appear cheap, but those so obviously compelling that they merit one of the hypothetical twenty investments you get over your entire life.

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There is no exoneration from pain, uncertainty, or the need for constant work.
- Phil Stutz, True and False Magic

In his book True and False Magic and in several other works, psychiatrist Phil Stutz makes the provocative statement that all people, no matter who they are, must deal with three constants in their lives: pain, uncertainty, and the need for constant work.1 Consider the last one for a moment.

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Danny Meyer

Bill Gurley’s book Runnin’ Down a Dream profiles nine well-known people as they search for their callings. The book grew out of his equally great lecture, and both are inspirational. What many people take from them, and which seems undoubtedly true, is that, in order to be great at what you do, you must love it.

Here is Gurley describing Danny Meyer, the famous restaurateur, early in his career when he was working at Pesca in New York City:

What would have been hard, unpleasant work for others was a joy for Danny Meyer.

That certainly sounds like love, but there is another force buried in each of Gurley’s nine stories: compulsion.

Here he is again, describing Meyer as he foundered early on, trying to decide what to do with his life. The night before he was set to take the LSAT, he complained to his uncle Richard that he didn’t even want to be a lawyer.

On its surface, the story seems surprising: Danny Meyer didn’t realize he should have been in the restaurant business? But upon deeper thought, is it so shocking? All of us, to some degree, have things we do naturally, our compulsions, that we become a little blind to. Meyer’s compulsion for restaurants was so deep that he had trouble seeing it himself at that point.

Michael Burry

Michael Burry has been an investor I’ve admired for years. Burry made a name for himself creating a way to short subprime mortgage bonds in the years leading up to the 2008 financial crisis. I’ve always thought of him as an investor who would put in more work than 99% of his investing peers.

Burry got his start as a professional investor in an odd way. In the late 1990s, he completed medical school at Vanderbilt University and then began a residency in neurology at Stanford University Hospital, where he realized his heart wasn’t in the practice of medicine. Investing, on the other hand, was a different story. After working sixteen-hour shifts at the hospital, he would somehow find the energy and effort to study the craft, often after midnight. He particularly relished the diligent, scrupulous work of unearthing great investments, reading documents and piecing together information few others had. I like Burry’s start because it gives me a feel for the type of dedication it takes to be a superior investor.

What’s more, rather than simply reading passively, Burry was sharing his work on the internet message board Silicon Investor. In fact, his posts are still live on the website, and anyone can go back and study the work he did. Over the course of the 1,736 days he was active on the site, from 1996 through 2001, Burry posted 3,277 times, averaging almost two posts a day for nearly five years, much of it while working a more-than-full-time job.

Michael Lewis’s book The Big Short profiles Burry, and Lewis recounts several anecdotes throughout that describe how hard Burry worked. Here is his account of the work Burry did to understand the fine details of subprime mortgage-backed securities:

That is an impressive amount of detail, and it emphasizes how much work it took for Burry just to understand what was happening in subprime mortgages in the mid-2000s. And there’s more than that. Not only did Burry need to understand these securities, he also needed to convince the Wall Street investment banks to create and trade the credit default swaps necessary to actually short subprime. That market effectively did not exist until Burry prodded the banks.

Here is Lewis again:

If you’re amazed, like I am, at the level of focus and dedication Burry brought to executing this investment, there is another detail to the story. Burry was diagnosed at some point in his adult life with Asperger’s syndrome.2

Here is Burry, from a 2010 interview with Jon Erlichman on Bloomberg TV:

Erlichman: I think what fascinates a lot of people about your story is that you didn’t know then what you know now, which is you do have Asperger’s syndrome, which some people will say in certain cases will contribute to someone’s ability to be able to really focus in one area.

Burry: Right.

Erlichman: And I have to ask you about thinking back now and your early fascination with the markets, whether or not you think, oh, yes, that played a role too?

Burry: Oh, absolutely it did. I don’t know, why would a second or third-grader get so fascinated with the markets? He’s washing money and pressing it in books and creating stock computer games... I’ve had these interests that have been very intense in my life. The two interests that are really intense being music and the markets. And every once in a while there’s something else that will catch my fancy for a little bit, but it always comes back to those two things.

For Burry, his prowess as an investor seems to stem from his intensity of interest, to some degree enabled by his Asperger’s. Is this a love of the work or a compulsion for it? Is it both?

I could recount similar stories of hard work, love, and compulsion for Buffett and other investors too. But for now, recall the words of Stutz from earlier.

The need for constant work

There are three constants in life: pain, uncertainty, and the need for constant work. Let’s consider the last one.

First off, note that Stutz does not say that “constant work” is a part of everyone’s life. He says the “need” for it is, which implies that our work can be ignored for a period of time, even a long time, but by ignoring it we are depriving ourselves of our need for it. If we deprive ourselves of anything we need, we’ll suffer ill effects, and constant work, according to Stutz, is one of those things we need like food and water.

Second, Stutz is saying that each of those three things will always be with us. There is no escape from them.

Suddenly, the work Burry, Meyer, and the rest of us do, whatever kind, seems like less of a choice; work will always be with us and we have a need to do it. Recognizing this puts the work any of us do in a different light. The choices we make, career or otherwise, tend not to be clean or passive, whereby we look at ourselves in the mirror, and say “I love investing” or “I love restaurants,” and then go to work in that field. Rather, we are under constant bombardment from the work being thrown at us, and it is under this bombardment that we take up work, sometimes any work, to fulfill our need to do it.

The two groups

The point of all this is that the work we “choose” tends to involve less choice than we think. Once again, our lives involve a constant stream of unending work, according to Stutz, and we have a need to do it. That need compels us to start doing the work, whether it is work we enjoy or are compelled by or not.

But the greats somehow have found their way to the work they are compelled to do, in whatever way. In Meyer’s case, he had an uncle there to wake him up and give him permission, so to speak, to do the thing he was compelled to do. In Burry’s case, he somehow summoned a superhuman level of energy to study investing after working long shifts at the hospital; his Asperger’s seems to have helped with that to some degree. Some other greats start working their compulsions from an early age, which makes later life changes, like the ones Meyer and Burry needed to make, less necessary or difficult. Buffett springs to mind there.

There is a mental model I carry in my head for this: to some degree, people can be split into two groups, those doing what they are compelled to do and those who are not. All people have a constant stream of work being thrown at them at all times, and all people have a need to do the work.3 The greats, whether by bold choice or otherwise, are working in the streams that they have a natural compulsion to work in. In this model, those who don’t have a natural compulsion don’t have a chance because the relentless stream of work will eventually exhaust them. It is as if they are ordinary humans swimming in the rapids. From time to time, they can grab onto a rock and take a rest, but they will need to return to swimming, which they cannot keep up forever. They look over and see Danny Meyer with fins and gills.

What you find at the very tail end of the distribution, the top 1% of 1%… they tend to gravitate toward their calling intuitively. The reason why they do it is for the love of the craft itself. It’s a calling and they protect that purity.
- Dr. Gio Valiante on The Knowledge Project Podcast

Understanding my compulsion

By now, you can probably tell what I think. In order to be a truly great investor (or truly great at anything for that matter), the work must be a compulsion. It must be the thing I would be doing if I didn’t need to do it. An investor who wants to generate very high returns must be willing to turn over rock after rock in order to find the one best investment idea out of hundreds or thousands. There is no way to be great at such a game if you don’t feel a compulsion toward it, a love for it, a natural joy in waking up every day faced with the deluge of work. Thankfully, and not incidentally, the work of investing does feel compulsive for me.

I hope it does for you too, but if not, don’t fight the rapids. Maybe you have wings and are built to fly instead.

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In Parts One and Two, we built the case that AutoZone was an excellent business with a long runway in a fragmented industry. The 1996 financials showed a company growing 20-25% per year on improving margins, and the competitive landscape, with Sears in slow decline above, mom-and-pop jobbers without scale below, suggested that runway was real. AutoZone held perhaps 6-7% of a $30 billion non-tire auto parts retail market and was opening stores at a record pace. With that backdrop in mind, we can now turn to the question that ultimately mattered for Lampert: what would the next five to fifteen years actually look like?

What could AutoZone look like in the future?

Given the positive backdrop, let’s try to construct a pro forma income statement for AutoZone that might show what the future could look like for the company. Such an income statement can help us understand what I expect to see as the company progresses.

In trying to imagine the company’s future, I’ll make two important estimates: one for how the company’s revenue might grow and one for how much capital the company will consume in opening new stores, financing this growth. We’ll start with the second.

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AutoZone’s capital consumption

In estimating how much capital AutoZone needs to open new stores, the company’s cash flow statement holds the key. Very basically, the creation of a new store involves two uses of capital: one slug for the purchase of land, creation of the building, and purchase of any equipment needed and one slug for the merchandise inventory with which to stock the store. Furthermore, company filings indicate that AutoZone has been able to lower the net cost of new merchandise inventory by negotiating favorable payment terms (which is essentially the extension of credit) with suppliers. From the 1996 10-K:

The table below shows an abbreviated version of AutoZone’s abbreviated cash flow statements and highlights the amount of capital AutoZone required to open each new store from 1994 to 1996. That amount is $1.245 million, highlighted in yellow. (We’ll use $1.3 million in making our estimates.) Most of this $1.3 million will come from the operating cash flow of the existing stores, but AutoZone was growing so quickly that it required some additional financing.

AutoZone’s revenue growth

As for the first assumption (revenue growth), we’ll keep things somewhat simple and conservative and imagine that the company’s revenue continues to grow, but that it begins tapering off from 24.0% in 1996 to 16.7% in 2001 and that the rate of revenue growth equals the growth in the number of stores (which conservatively assumes same-store sales growth is zero). Importantly, these assumptions are not meant to be exact; they are meant to be placeholders to see if even reasonable revenue growth figures could produce compelling per-share returns.

The table below shows an income statement that combines these two pro forma assumptions and sketches out what might happen to net income and share price performance, assuming a constant P/E ratio, as a result. The table shows AutoZone’s actual financials in 1995 and 1996, along with a pro forma forecast five years out through the year 2001.

The table above contains a ton of information, but it is relatively straightforward if one walks through it slowly.

1. Revenue growth. First, the pro forma numbers above assume the revenue growth mentioned above, and as such, should not be taken as gospel. A big part of doing all the competitive analysis earlier in the case study was to get comfortable that good levels of revenue growth could continue in the future. Line 37 provides an estimate for AutoZone’s market share in pro forma 2001, showing it to be 14.3%.

2. No change in margins. The pro forma numbers assume no changes in the company’s growth and operating margins. One could argue, however, that AutoZone’s increasing scale should improve both gross margins (as its negotiating power gets larger and it is more capable of selling its own branded products) and operating margins (as the company continues to benefit from centralized resources and store operating experience).

3. Line 34 matches the growth in the number of stores with the growth in revenue assumed. Line 20 shows how much capital would be needed to open that number of stores in any given year (assuming $1.3mn per store), line 21 shows how much could be funded with the operating cash flow of the business, and line 22 shows the remainder that would be needed in the form of new capital.

4. Debt financing for new stores. Line 24 assumes this capital comes in the form of new debt. I imagine Lampert had a little debate with himself here. From 1991 to 1995, the company issued $150.4mn of common stock, which it used to finance its expansion (after paying off $67.6mn of debt in 1991). By 1996, however, the company was indicating that it would use debt to finance its new store growth, which Lampert must have preferred. I assume the new store expansion shown above is financed with debt at a 7% interest rate, conservatively a bit higher than the 5.67% rate on the company’s $94.4mn debt Revolver.

5. The company’s net income per share increases by 17.6% per year for the five years through 2001. Its share price also increases by the same amount because I am assuming the P/E does not change.

The pro forma analysis shows very good results for the company and its stock price. And, in order to believe it is possible, building an intimate familiarity with the business and competitive landscape, as we did earlier, is critical. AutoZone had such a different and compelling store offering than either the large competitors or the mom and pop shops that believing its market share could increase from 6% to 14% does not seem like a stretch at all.

Now, as a result of taking on pro forma debt through 2001, the company’s net income growth lags behind its revenue growth. The additional debt service (interest) payments put a greater drag on profit margins. However, since AutoZone’s business was regular, highly recurring, and protected from economic downturns, the company could handle the debt load quite well and, as Lampert knew, had room to take on much more to the benefit of shareholders.

Could AutoZone’s stock do better than slightly lagging the company’s revenue growth?

Here is where things get interesting, and likely a big part of Lampert’s thesis.

Since AutoZone was such a great business with very little debt, it had a lot of runway to take on debt to finance its expansion. But it also had a ton of runway to use debt to buy back shares to better the position of its common stock holders.

As I mentioned earlier, the company issued $150.4mn of common stock from 1991 to 1995, which it used to finance its expansion. Hindsight is 20/20 of course, but it doesn’t take much to see that this share issuance was a mistake on management’s part. One simple way to see that is to compare the IPO price of $5 3/4 per share in April of 1991 to the price of AutoZone’s stock around the time Lampert was looking at it (e.g., $23 3/8 on June 30, 1997). The return achieved by those shares was approximately 26%; it would have been much better for existing shareholders to issue debt at a cost of 6-8%.

When Lampert was analyzing the business and making his first purchases in 1997, he saw this distinctly. He knew that the company’s shareholders could do even better by shifting the capital structure toward more debt (which the company was very capable of bearing) and away from equity.

The table below shows another view of the income statement we saw above, with one difference: the company issues another $225mn of debt each year and uses the proceeds to repurchase shares at the then-outstanding share price.

As you can see, the position of equity holders is improved. Line 30 shows the annualized appreciation of AutoZone’s stock price has increased by almost two percentage points to 19.5%. Meanwhile, the company’s debt service coverage ratio is still a comfortable 4.8x.

Now, the benefit of taking on debt to finance stock repurchases is not without risk, of course. And one might rightfully wonder whether taking on almost $2bn in debt is worth it for an extra two percentage points of annualized stock price gain. All in all, I think Lampert saw in AutoZone two things:

1. First and most importantly, an excellent business at the start of a long runway of taking market share from competitors who were on their heels, and

2. less importantly, a company that also had enormous financial flexibility and room for balance sheet improvement. AutoZone was not just in a great competitive position, it was also the type of business, by virtue of what it sold, that was buttressed from potential economic downturns. Lampert likely thought he could (and subsequently did) influence the management team to use debt both prudently and aggressively to improve the outcomes for shareholders while still keeping the company in good financial health.

With that pro forma in hand, we can now see how Lampert’s actual investment unfolded against it.

Lampert’s investment results

Lampert is reported to have first invested in AutoZone in 1997,1 although the first public filings of his ownership appear in Q3 1998, after his management vehicles crossed over owning 5% of the company’s common stock. Below, I show a chart of Lampert’s holdings of AutoZone stock, as reported in the SEC’s EDGAR data.

Lampert began buying AutoZone shares in 1997, although I could find no public data for those amounts beyond the simple commentary in the BusinessWeek article mentioned above. He eventually accumulated as much as 30.68 million shares of the company in 2001 before selling down some shares in that year to diversify his holdings and some more in 2003.2

Shortly after Lampert began buying the stock, AutoZone began embarking on a plan for share repurchases, reportedly after Lampert advocated strongly for it. Lampert joined the company’s Board in 1999 and held that position through 2006, after which he handed the position to ESL’s General Counsel, Theodore Ullyot. Because of AutoZone’s aggressive share repurchases, Lampert’s percentage stake in the company continued to rise, eventually reaching 42.7% in Q1 2009. AutoZone’s share count over time is shown below.

Lampert’s estimated return from owning AutoZone for 15 years

Lampert owned AutoZone stock from 1997 through 2012. During that time, AutoZone’s stock price went from $23.39 to $370.60.3 The company’s revenue rose by 3.2x to $8.60bn from $2.69bn, its store count grew to 4,685 from 1,728, and its net income rose by 4.8x to $930mn from $195mn. Its net income per share rose by even more than that, a whopping 18.3x to $23.48 from $1.28. By 2012, the company had only 39.6mn shares outstanding versus 151.0mn in 1997.

Although I don’t know the exact prices he paid for each share of stock, I make some simplifying assumptions, like imagining that he paid the quarterly average price for any purchases made during a given quarter (and similar for any sales). Using such assumptions suggests that Lampert invested roughly $1.2bn in the company’s stock, ultimately grossing $6.8bn from the sale of that stock years later, multiplying his money by 5.7 times. Over the 15 years he owned AutoZone stock, I estimate his annualized internal rate of return to be around 21.3%.4

The stock became a large part of his hedge fund. In his 13F filing from Q4 2007, for example, Lampert reported owning $2.6bn worth of AutoZone stock, 23.3% of his total holdings.

Lampert sold down his stake in AutoZone in the years from 2009 to 2012. The Financial Crisis was unfolding around the start of that time, and Lampert seemed to be increasingly focused on turning around the retailer Sears, an investment that ultimately did not turn out well for Lampert. (Sears was Lampert’s largest holding in that Q4 2007 report, at $6.7bn and 59% of his holdings.)

AutoZone’s continued success

Ultimately, for AutoZone, the success continued. The company has continued expanding and still repurchases its stock to this day, with 16.5mn shares outstanding as of its February 2026 10-Q. From the end of 2012, around the time Lampert sold his last remaining stake in the company, to March 31, 2026, the stock price has increased from $370.60 to $3,377.78, representing an annualized rate of return of 18.1%.

In Poor Charlie’s Almanack, Peter Kaufman presents an investing checklist based on the principles and behavior of Charlie Munger. Entry number seven reads:

“Compound interest is the eighth wonder of the world (Einstein); never interrupt it unnecessarily”

Hindsight is 20/20 of course, but one can’t help but notice that Lampert would be better off today effectively sitting on his hands, sticking with his non-operating position in AutoZone, and not interrupting his great investment in the company.

Summary and takeaways

In the late 1990’s (and even for years after that), AutoZone was starting to expand its store presence and take market share in the auto parts retailing business. The company’s success to date was clearly visible in the company’s 1996 financials and even in financials from years prior. Moreover, the company had very little market share in auto parts retailing, was rapidly expanding to increase it, and seemed to be poised to do so for years to come.

The company provided customers with an excellent product (that is, their retail experience) they couldn’t get elsewhere. In addition, because of the sheer amount of work it took to build out new stores and operate them well, the company seemed to have runway to expand to much higher market share numbers.

When you find a retailer (or any customer offering) that is different, like AutoZone’s, with competitors who are locked into inferior ways of doing business, like the large retailers and small mom and pop shops, the most natural course of events may be for the retailer to take market share for a long period of time. If you are lucky enough to buy it, be very picky about selling it.

With respect to AutoZone, yes, hindsight is 20/20, but one cannot help but be struck by just how compelling the company’s offering was and just how good the business was already doing, even back in 1996. I’m reminded of Charlie Munger describing Berkshire Hathaway’s investment in Coca-Cola in the late 1980’s. He recalled reading Coca-Cola’s financial filings and seeing it “perfectly obvious” that Coke would continue expanding and dominating markets. Reading AutoZone’s financial documents from the 1990’s felt the same way.

If you can find those rare great companies doing everything right, like AutoZone, think hard about whether the price is too high or just seems that way. Business success can continue longer than we often think, especially for cases like AutoZone, where the company spent many years of effort and a lot of money building the best auto parts retailing experience possible for the customer.

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In Part One, we looked at AutoZone through its 1996 10-K and found a business that was growing consistently, earning improving margins, and generating high returns on capital. The financial picture was compelling on its own. But Eddie Lampert had to figure out whether the company’s runway was long enough to keep that performance going.

Part Three is now available as well.

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AutoZone and the auto parts market

From AutoZone’s financial statements, it seems like the company was doing very well in 1996. It was running a very profitable set of 1,423 stores and it had been growing its store base at higher rates each year while the company’s profitability actually got better. That is a strong indication that management’s investment in new stores was paying off very well. AutoZone grew its store count by 3.6 times in just nine years, from 396 stores in 1987 to 1,423 in 1996.

But would that growth and performance be likely to continue into the future? How could Lampert be sure that the great trends would be maintained?

To understand the answer to that question, let’s look at the competitive landscape of the auto parts retailing industry. We’ll start with this quote from the 1996 10-K:

There are two parts of that statement that are most important:

1. the automotive aftermarket industry was “highly fragmented”, and

2. the largest share of it was held by “independently owned jobber stores”, which I think of as mom and pop owners or, in some cases, very small franchises.

In order to get a feel for how large the auto parts retail industry was and how much of it was being served by AutoZone, I’ll reference the 1992 Census of Retail Trade in the US.1 The Census data is very comprehensive; the 1992 report is 87 pages long and full of data on every page. There are a few pieces of information there that are relevant for us in sizing up the retail auto parts industry. Table 1 of the Census summarizes all the data in the report, and it lists $45.1 billion in sales of “Automotive tires, batteries, accessories” and $3.5 billion of “Automotive lubricants”, for a total of $48.6 billion of automotive parts sales.

Now, AutoZone was not in the business of selling tires. So, from that $48.6 billion total figure, I need an estimate for how much of it was tire sales in 1992. Another public report, the Economic Analysis of the Rubber Tire Manufacturing MACT, lists the wholesale amount of 1992 tires sales in the US as $13.0 billion. From that figure, I estimate roughly that retail tire sales were about $18.9 billion in the US that year.2 The table below summarizes these figures, and it suggests that AutoZone was competing in an auto parts retail market (ex-tire sales) that had roughly $29.9 billion in sales in 1992.

AutoZone only had a small market share in 1997

Now, out of that total market of $29.9 billion, AutoZone’s 1992 sales total was just over $1 billion, which suggests that the company had captured only 3.4% of the total market (ex-tires). One could also restrict the analysis to “Auto & home supply stores” (nomenclature from the Census data), of which AutoZone was a part, and there the company had a 6.8% market share. (I lean toward the first comparison because AutoZone seemed to be so effective that it was disrupting all auto parts retailers.)

So that’s the 1992 data. What about 1996? It’s possible that Lampert had access to that more recent retail sales data, but I could not find any that would have been available at that time. No problem. We can simply walk the retail sales data forward, using CPI inflation data, to get a better sense as to AutoZone’s market share around 1996. It’s crude, but it gives a sense of where AutoZone was at the time in its quest to increase market share.

I estimate that, as of 1996, AutoZone had approximately only a 6.7% market share of the larger auto parts retailing industry (ex-tires). In the more restricted “auto and home supply stores”, which were direct competitors to AutoZone, the company had a 13.7% share. Using either measure, AutoZone seemed to have a very small portion of a market in which it was continually bringing a better offering to customers.

The retail auto parts industry was highly fragmented, with few large competitors and a lot of smaller competitors

As I discussed earlier, the auto parts retail industry was highly fragmented, and indeed, the Census data suggest as much: auto parts were sold by a variety of stores. And from researching public filings, newspapers, and trade publications, it was apparent that AutoZone did have a lot of competitors, but none of those competitors had more than about 10% of the market, at the very most.

Sears

The primary competitor at the time seems to have been Sears (the department store operator ran auto retail shops as well), whose operations were fragmented even within the company itself. Sears had five different auto retailing operations: (1) Sears Auto Centers, (2) Tire America, (3) NTW stores, (4) Western Auto stores, and (5) Parts America stores.

Sears reported total merchandise and service sales of $33.8 billion in its 1996 10-K. It did not break out its retail auto sales alone, but it did report the sales totals for its “off-the-mall” stores, which was composed of both Sears’ Auto business and Home business. Off-the-mall store sales totaled $6.3 billion in 1996, so I deduce that the retail auto business of Sears generated less than that amount. A reasonable estimate might be something like $3-4 billion (which includes tire sales). That figure can be compared to total auto retail sales in the US of $48.7 billion (back in 1992). So, Sears seems to have commanded a market share in the high-single digits percent.

Pep Boys

Pep Boys, which was founded in 1921 and which had been a public company since 1946, appears to have been doing rather well around the time Lampert was considering his AutoZone investment. In their 10-K for the year ended February 1997, they reported total revenue of $1.8 billion, of which $273 million came from service revenue and the balance from merchandise sales (compared to AutoZone’s $2.2 billion which was entirely from merchandise). Revenues had grown at a 4-year CAGR of 12%, less than AutoZone’s 22%.

O’Reilly Auto Parts

I mention O’Reilly Auto Parts here because many investors know it today as another great auto parts retailer. At the time of Lampert’s investment, O’Reilly was performing well too, but it was much smaller than AutoZone (or Pep Boys), with 1996 revenue of $259 million. Revenues had grown at a 4-year CAGR of 24%, which was comparable to the rate at which AutoZone had grown.

Others

Of course, those three names are not nearly all the competitors that sold auto parts to the retail market in 1997. There were many other names, including Wal-Mart, Montgomery Ward, Penske Auto Centers (Kmart), Caldor, PACCAR and a variety of other companies and stores, and none of them seemed to have very large part of the industry.

Most importantly of all, the industry had a large smattering of “independent” retailers, small shops around the US run by mom and pop owners. This group, as a whole, seemed to make up the majority of auto parts retail sales in the US in 1997.

AutoZone’s competitive strategy was compelling

I think of AutoZone’s competitors as falling into one of three types:

1. larger and more diversified retailers, like Sears,

2. smaller auto parts retailers (mom and pop shops or “jobbers”) that did not have scale, and

3. dedicated auto parts retailers (like Pep Boys or O’Reilly, that were smaller than AutoZone).

Let’s discuss the first two in more detail. (The third group were, for the most part, executing a similar overall strategy as AutoZone. But AutoZone seemed to have a head start over the smaller companies, like O’Reilly, and it seemed to be growing faster than and outperforming Pep Boys. At the very least, I assume Lampert’s view at the time was that firms like this might do well in the future and might have to share the large pie they were all attacking.)

Large retailers were complacent and unfocused...

For the large retailers, AutoZone’s proposition was that the company could do a better job by focusing on a single line of business (auto parts retailing) than those diversified retailers for whom auto parts was one of many businesses. As far as its competition with Sears, AutoZone’s strategy seemed to be working as of 1997.3

Not only were sales growing more slowly at Sears, they were in year-over-year declines as reported in the company’s 10-Q from 1997 Q2:

Once again, I am reminded of a passage from Sam Walton’s autobiography, whereby he expresses disbelief that the existing, large retailers did not simply adopt Wal-Mart’s strategies and kill the young company. Ultimately, however, they were too complacent to change:4

...And small retailers were suffering from their lack of scale

So, for the large retailers, the inability or difficulty in competing with AutoZone was a symptom of large corporate culture. On the other hand, for the small retailers, the inability to compete was much more cut and dried:

Small shops could not match AutoZone’s merchandise selection, store experience, customer service, and prices.

Finding proof of that is more difficult than searching the filings of large, public companies, but I was able to find some evidence in trade publications from the time. Here is one article discussing a franchisor (Auto Aid Stores) criticizing the refusal of his own mom and pop franchisee owners to adapt, while the mom and pop owners criticize the franchisor for being uncompetitive in pricing:5

And here is another article describing a small auto parts retailer in Ohio effectively admitting that he cannot compete on price with the ever-expanding AutoZone (and some other large retailers):6

As we saw in AutoZone’s financials, with their high levels of profitability, the above critique is wrong. The company was not simply loss-leading in an attempt to gain market share.

For this part of the research, it may be difficult to imagine doing this work back in 1997. Some of the AutoZone’s value proposition to the customer is qualitative rather than quantitative (like having cleaner stores versus mom and pop and the attractive layout and design of stores). These trade journal articles provide some evidence, but it’s important to note that in-person scuttlebutt was an important part of Lampert’s research at the time. From the BusinessWeek article on Lampert from 2004:7

Although I cannot prove it, I’m inclined to think this scuttlebutt was not just one part of Lampert’s work, but was critical research that actually proved to him that what he was seeing in AutoZone’s financials was real; AutoZone’s stores were head and shoulders better than the competition, and this is why the company was so profitable.

AutoZone was well-positioned to continue growing revenue and earnings

Now the opportunity that AutoZone had in front of it begins to become apparent. The company was positioning itself in the middle, so to speak, between large, diversified retailers on one hand and small mom and pop jobber shops on the other.

Large retailers were having trouble competing with AutoZone because AutoZone, by being a monoline retailer focused on auto parts, could offer better service to its customers.

Small retailers were having trouble competing because AutoZone’s scale allowed it to be more profitable than those businesses, which allowed it the capital to create better stores with more selection, better service, and lower prices.

Critically, the industry was so fragmented and AutoZone’s market share was so low in 1997 (around 6.7% of the non-tire auto parts retail market) that the company seemed to have a long runway of growth ahead of it.

The 1996 10-K shows the company was only in 27 states out of 50 in the US, and notably not yet in California or New York:

The same report also showed no signs that their expansion was slowing:

So the qualitative case was strong: a differentiated retailer, in a fragmented industry, with weak competition above and below it, and a market share low enough to grow into for years. The question Lampert still had to answer was a quantitative one. If AutoZone simply kept doing what it was doing, opening stores, taking share, financing the expansion, what could the business actually look like five years out, and what would that mean for the stock?

Part Three will answer those questions next week.

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This is Part One of a three-part series. Here are links for Part Two and Part Three.

There has been one investment story I’ve been obsessed with for many years, and now, I’ve finally taken the time to break it down: AutoZone.

Over the past 35 years, since the company’s IPO in April 1991 through July 13, 2026, AutoZone’s common stock has increased 448-fold, which equates to a compounded annual growth rate of 18.9%. Moreover, the company is famous for dramatically shrinking its share count during that time by 89%, from 152.7 million shares at the peak in June 1998 to 16.5 million shares as of May 2026.

Share buybacks are a widely misunderstood corporate action, both by critics and, to a lesser extent, by adherents.

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AutoZone has been the poster-child for share buybacks done well. And the conventional explanation is that these share buybacks were the primary driver that led to great returns. But that conventional explanation is incomplete

Eddie Lampert and AutoZone

What first turned me on to AutoZone was reading, perhaps around the year 2007, about Eddie Lampert, then a superstar investor who had accumulated a large stake in the retailer, had apparently prodded management to begin buying back stock, and had earned stellar returns on his investment.1 I’ve always wondered what Lampert saw in the stock and how and why share buybacks seemed to be very effective in producing returns for the company’s equity investors.

Although AutoZone has produced tremendous returns for shareholders over its entire life as a public company, I’ll limit the analysis here to Lampert’s investment in AutoZone, from 1997 to 2012, so as to definitively restrict us to a single point in time at the start so we can try to see the same potential he saw when he invested.

The first public disclosure of Lampert’s ownership that I could find is a 13D filing from August 1998 for several of Lampert’s investment vehicles that lists a combined ownership of exactly 11 million shares, or 7.2% of the company’s stock.2 According to a BusinessWeek article, Lampert started accumulating AutoZone in 1997, although no specific date is given. The SEC requires investors to file a 13D within five business days of acquiring 5% or more of a company’s stock, so it seems likely that Lampert owned less than 5% of AutoZone’s stock starting sometime in 1997. I’ll assume he started buying in Q2 of 1997 and that he had access to the 1996 annual report and any disclosures prior to March 31, 1997.

AutoZone was an excellent company

AutoZone was and still is in the business of auto parts retailing, and it’s been in business since 1979. Here is a succinct explanation of the company’s business from the 1996 10-K:

The Company began operations in 1979 and at August 31, 1996, operated 1,423 stores in 27 states, principally located in the Sunbelt and Midwest regions of the United States. Each AutoZone store carries an extensive product line, including new and re-manufactured automotive hard parts, such as alternators, starters, water pumps, brake shoes and pads, carburetors, clutches and engines; maintenance items, such as oil, antifreeze, transmission, brake and power steering fluids, engine additives, protectants and waxes; and accessories, such as car stereos and floor mats.

Two things jumped out at me when I opened the 1996 10-K report:

1. how consistent their business was, and

2. how profitable it seemed to be.

In fact, as a loose confirmation of the consistency, AutoZone conveniently laid out 10-year financial histories in its annual reports and 10-K’s; I couldn’t help but feel that management was showing off how consistently the company was growing sales and earning more and more income. Below, I reproduce an abbreviated version of AutoZone’s income statement that appeared in the 10-K.

From the data above, it is not hard to see that AutoZone had been doing very well over the ten years prior to 1997:

• Net sales were growing consistently in the range of 20-25% per year. That suggests the company was continuing to tap into some form of unsatisfied demand.

• Gross margins were high, and they had improved. That suggests that customers were willing to pay up for whatever AutoZone was providing them and/or AutoZone was paying less to obtain salable items.

• Operating and profit margins were good, and they had improved a lot. That suggests the company had been improving the way it was run and/or that its business model was benefitting from scale.

Why was AutoZone able to perform so well? What was the company’s business model?

AutoZone had a simple and compelling business model: It was “professionalizing” the auto parts retailing business, opening larger stores with more selection, in convenient locations, with good prices. From the 1996 10-K:

AutoZone is dedicated to a marketing and merchandising strategy to provide customers with superior service, value and parts selection at conveniently located, well-designed stores. The Company has implemented this strategy primarily with knowledgeable and motivated store personnel trained to emphasize prompt and courteous customer service, through an everyday low price policy and by maintaining an extensive product line with an emphasis on automotive hard parts. AutoZone’s stores are generally situated in high-visibility locations and provide a distinctive merchandise presentation in an attractive store environment.

Management takes the time in its 10-K to expound upon each part of its retail strategy by discussing customer service, product selection, price, and store location and design at length. For those interested in a more in-depth look, I’ve reproduced their strategy and philosophy on each below:

I’m quoting extensively from the 10-K here in order to relay something important about the retail industry: customers do not shop at great retail stores for one reason alone. They need several compelling reasons. I’m reminded of the following quote from Sam Walton’s autobiography, Made in America:3

...the secret to successful retailing is to give your customers what they want. And really, if you think about it from your point of view, as a customer, you want everything: a wide assortment of good quality merchandise; the lowest possible prices; guaranteed satisfaction with what you buy; friendly, knowledgeable service; convenient hours; free parking; a pleasant shopping experience. You love it when you visit a store that somehow exceeds your expectations, and you hate it when the store inconveniences you, or gives you a hard time, or just pretends you’re invisible.

Of course, it would be naive to suggest that AutoZone was another Wal-Mart simply on the basis of quotations from the management team. In fact, a skeptic would argue that “superior service, value and parts selection at conveniently located, well-designed stores” are the kind of thing any retailer would claim.

In order to understand whether or not the stores were truly resonating with customers, I needed some better proof. And I found it in the company’s financials. The table below shows an expanded version of the financials shown earlier.

These financials show a few things over the course of ten years through 1996, which I have highlighted in different colors:

1. Green lines: AutoZone was growing consistently over those ten years, with net sales growth, as evidenced by line 2, in the 20-25% range. A careful reading of the 10-K shows that the company was doing this with a combination of good same-store sales growth, and, more importantly, very strong new store growth (see line 20). In fact, new store growth was accelerating from 1990 to 1996; the company was growing faster.

2. Teal lines: AutoZone’s underlying business was improving too. Lines 5, 8, and 13 highlight the company’s margins. Each had increased over the past several years since 1989. Higher margins indicate that the company was benefiting from scale by getting more favorable purchasing terms from suppliers, benefiting from centralization of certain expenses (like advertising), or simply benefiting from its experience in running a better, more profitable business as time went by.4

3. Blue lines: AutoZone consistently generated a high amount of profit relative to the capital the business employed, as shown in lines 15 and 17, return on average assets and return on average equity capital. This implies that the company was delivering something (or things, plural) to customers that other retailers were not or could not. Otherwise, I would expect the company’s return to be falling as other competitors swooped in and deployed their own capital to challenge AutoZone.

So from the 1996 10-K alone, AutoZone looked like an excellent business, growing, profitable, and earning high returns on its capital. But a great business in a tapped-out market is a different proposition than a great business with room to run. Before Lampert could be confident that what he was seeing would continue, he needed to understand the industry AutoZone was operating in: how large it was, who else competed in it, and how much of it AutoZone had already taken.

Next week, in Part Two, we’ll cover each of those things.

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The best investing records

Below are some of those examples. For sources, see footnotes1.

• Warren Buffett: From 1957 to 1968, he produced annualized returns of 31.6% for his partnership.

• Charlie Munger: From 1962 to 1975, 19.8% annualized for his partnership.

• Walter Schloss: From 1956 to 1984, for 28 years, 21.3% per year.

• Ted Weschler: From 1989 to 2012, he turned $70,385 into $131 million in his IRA account, equivalent to about 39% per year.

• Joel Greenblatt: From 1985 to 1994, a stunning 50% per year.

• George Soros: From 1969 through 1994, the Quantum Fund produced 35% annualized returns.

• Stan Druckenmiller: Returned 31% per year over 30 years. I believe this record overlaps with Soros’s above.

• Jim Simons: From 1988 to 2018, Renaissance Technologies’ Medallion Fund generated an incredible 66.1% average gross annual return.

• Peter Lynch: From 1977 to 1990, for the Fidelity Magellan Fund, he produced a 28.9% annualized return. The fund grew from $18 million to $14 billion.

• Bill Ruane: From 1970 to 1984, the Sequoia Fund generated 17.2% annualized returns for investors. (Bill also produced 14.7% annualized returns from 1970 to 2015, a 45-year record.)

• Tom Knapp: From 1968 to 1983, for Tweedy, Browne Partners, 20.0% annualized returns.

• Lou Simpson: From 1980 to 2004, 20.3% per year for the GEICO equity portfolio.

• Nick Sleep and Qais Zakaria: From 2001 to 2014, the Nomad Investment Partnership generated 20.8% gross returns for investors.

How much return should we seek?

Warren Buffett has stated that, if he were managing small sums of money, he could produce annualized returns of 50% or more. Buffett’s claim here is so interesting that he has been asked this question many times at Berkshire’s annual meetings, at student talks, and elsewhere.

The highest rates of return I’ve ever achieved were in the 1950s. I killed the Dow. You ought to see the numbers. But I was investing peanuts then… I think I could make you 50% a year on $1 million. No, I know I could. I guarantee that.
- Warren Buffett, “Homespun Wisdom from the ‘Oracle of Omaha’”, BusinessWeek, July 5, 1999

I think the lack of good, comprehensive studies of stock returns is one reason why this question of Buffett has been so popular and why investors are so mesmerized by return records like the ones listed above. Most people, even after hearing Buffett say it aloud, are quietly incredulous. How could it be possible to return 50% a year?

Many investors know that an index of large-cap stocks, like the S&P 500, has produced something like 8-10% returns over the long-term, and many understand that even modest outperformance of a few percent can lead to huge long-term outperformance, but how many are familiar with incredible return performances?

I think most investors only have a vague sense of what is possible. An enterprising investor should understand what the very best return performances look like to get a sense of how high they should be shooting. When I am considering an investment, and I think it has the potential to return, say, 15% per year, should I pull the trigger or should I continue looking at other investments?

It is important for me as an investor to have an understanding of what level of stock returns has constituted greatness in the past, however defined. That way, when my research suggests that a stock might produce forward returns around some level, I might have a little more confidence around using up one of my twenty punches.2

Bessembinder’s study of great companies

In a prior article, I discussed a research study by Hendrik Bessembinder from 2017 that analyzed wealth-creation among US-listed public companies over the 90-year period from 1926 to 2016. Bessembinder showed how rare it was to find a great company that could produce dramatic outperformance over its life.

In the study, Bessembinder analyzed the dollar-wealth created by companies3, which is useful but somewhat abstract. His study was so popular, and he must have wanted to provide more performance than the dollar-wealth metric, so he published another study in 2024 that measured US companies and stocks by their compounded annualized growth rates. Many investors find it more natural to think in annualized rates, of course. The study is called Which U.S. Stocks Generated the Highest Long-Term Returns?, and it has some very interesting takeaways.

A newer study focused on annual returns

The second study is useful because it can provide a kind of gauge for the enterprising investor, as I described. It shows us how much return the best stocks have produced over various periods of time. It can help provide us with a historical point of view when aiming for returns.

Bessembinder performed his new study using the daily common stock database from the Center for Research in Security Prices (CRSP), just as he did in the 2018 analysis. However, this time he studied the 98-year period from December 31, 1925 to December 31, 2023. He analyzed 27,731 publicly listed companies and their common stocks, and he calculated the annualized returns that the stocks generated over their lifetimes.4

The chart below shows the amount of time that each stock was listed in the CRSP data. The median time for a stock being listed was 6.8 years, suggesting that half of all companies undergo a delisting (due to merger, bankruptcy, or other reasons) in less than that time. Only 10% of companies are in the database for 28 years or longer. Very long-lived companies are rare.

What level of annual returns have stocks produced?

Focusing now on the 27,731 stocks that were listed for more than one year, what can we glean about the annualized returns they produced?

The chart below shows those stocks bucketed by the annualized return that they generated over their listed life. The black line separates stocks that generated a negative return over their lives from those that generated a positive return.

Most companies produced a negative return

One of the most striking observations is that most companies (51.1% of them) generated a negative annualized return (implying, of course, a negative outright or total return) over their lives. The median return for all stocks was -0.8%. In other words, randomly selecting a company’s stock to invest in is likely to produce a majority of outright losers over the respective lives of those companies.

How do we reconcile this with the observation that stock indexes tend to produce significant gains over the long-run? For instance, the S&P 500 produced an annualized return of 10.5% per year over the last 100 years.5

Two reasons. First, the profile shown above has a large positive skew. Even though only a minority of companies (48.9%) produce positive returns over their lives, there are enough of them, and enough that produce high returns, that it drags upward the total returns for the entire group.

Second, the S&P 500 is naturally biased to select longer-lived, stalwart companies, and that bucket is less likely to feature the loser companies. For instance, in the bucket of companies that have lives of 1 to 5 years, 63% generated a negative annualized return, while in the bucket of 20 to 40-year companies, only 30% generated a negative annualized return. (Side note: Yes, there are a lot of long-lived companies that end up with negative returns at the end of the day.)

Extremely-high returns are short-lived and likely not accessible repeatedly

What about that long tail on the right side of the chart? There is only a small minority of firms that produce very high annualized returns over their lives. One thing is clear about those companies: they tend to have short lives. In fact, for the firms that produced annualized returns greater than 53%, none of them had lives over 10 years. Why? The highest-returning companies are bought by other firms and taken private, and, if they are not, their ability to produce very high returns abates with size and age.

The figure below shows the top 20 companies (out of 27,731) by annualized returns in Bessembinder’s study. Not surprisingly, all of these companies were listed for less than three years before they were bought and delisted. Because of their short lifetimes, almost none of these companies are familiar, but some may make good case studies in the future.

So, the first takeaway for an enterprising investor is that extremely high annualized returns are likely to be very short-term, and, because of their nature, may not be possible to capture systematically.

For example, the third company on Figure 5 is Synthorx Inc. Synthorx was a pharmaceutical company founded in 2014 that underwent an IPO in December of 2018 and was acquired by Sanofi in January 2020, in part because of one major drug that Synthorx was developing. Capturing such gains would have been difficult unless I was neck-deep in drug development research and keeping up rigorously on progress at Synthorx.

Ok, then what about company lives that are a bit longer?

Let’s take a more detailed look at Bessembinder’s data. The figure below shows annualized returns versus the lifetime of each company for all 27,731 companies in the study. It becomes easy to see that, the longer a company is around and the larger it gets, the more difficult it becomes to keep producing astounding returns. The second chart below zooms in on the y-axis. On that chart, I’ve also drawn a crude kind of “frontier” for annualized returns generated by firms over their lifetimes. That line can give a sense for what the absolute best historical return levels have been for companies that have lived for various amounts of time.

The best returns across times

Using this data, we can get a feel for the best returns posted by the best companies over longer periods. To do that, we’ll divide the list of companies in the study into various buckets based on the lifetimes of the stocks in the database. The figure below shows the lifetime returns for companies in these buckets.

I’ve broken out companies in the 99th percentile to show the levels of returns that the very best companies have put up over their lives. I also show the median company return for comparison.

There are some astounding numbers in the above figure. Those companies in the top 99th percentile (that is, 1 out of 100) have produced annualized returns anywhere from 18.4% (over very long lives of 40+ years) to 105.5% (over very short lives). One could rightly wonder if the 99th percentile is too high a bar to be targeting, but I think it is a healthy target (1 in 100) to keep in mind for an enterprising investor who is devoting his time to sifting through many ideas in an attempt to find the very best ones. Keeping the 99th percentile returns in mind as a target also reinforces Buffett’s advice of investing with a punch card mentality: when making an investment, imagine that it is one of only 20 investments you will get to make in your life. Set the bar high.

Breaking out the return levels by stock lifetime is useful too. As mentioned before, I might be attracted to that 105.5% level of annualized returns in the 1-5 year bucket, but such stocks often produced those returns over very short lifetimes from events like buyouts that are very difficult to predict.

What about longer time frames?

What about stocks in higher lifetime buckets? There, the longer lifetimes over which great returns were generated might afford me the time to learn about the company, follow its progress, and capture some of those great returns. Indeed, the lists of companies by lifetime seem to bear that out.

The figure below shows the top 20 companies, ranked by annual returns over their lives, for four buckets: those stocks in the database for 5-10 years, 10-20 years, 20-40 years, and those with over 40 years of life.

The trend I mentioned above holds for these company lists as well. Among the shorter lived companies, there seem to be several for which high returns would have been dependent on predicting a high-priced merger, which is difficult to do. In another example, US Robotics Corp is on the 1-5 year list, and it was purchased by 3Com in 1997 amid the dot-com frenzy.

As we go out further in stock lifetime, however, the degree of predictability seems to increase, and annualized returns can still be stellar. Netflix, for example, produced 32.1% annualized returns over its life from May 2002 to the end of the study at December 2023. One could complain that it would have been very difficult to predict how great a business Netflix would become in 2002, so capturing those great returns would have been difficult. However, even if we give ourselves ten years of leeway and restrict ourselves to the period from December 2013 to December 2023, the stock still returned 25.0% per year.

Return targets for the enterprising investor

It is incredibly hard to try to go back in time, and making great investments like that is always more difficult than it seems in retrospect. However, this exercise can show us just how many companies (and how few on a percentage basis) have actually put up great returns and what those levels might be for a great investor who could find them.

The companies listed in Figure 8 bear that out. The figure suggests that investing in the very best companies over the long term could produce returns that are in the rough range of 20% to 50% (judging by the companies in the 10-20, 20-40, and 40+ year lifetime lists). The data serves as a good reminder that great investment returns have been out there in the past and are likely to continue in the future.

There is one issue with the above analysis that might cause the annualized returns to be boosted a bit. The study ends at 2023, which we can think of as being 14 years into a bull market that started in 2009. Several of the top stocks in the study show December 2023 as their last listing period, which means that the returns of those stocks will be benefitting from that bull market. For example, in the bucket of stocks with 20-40 year listed lifetimes, 30% of the top returners (95th percentile) have December 2023 as their endpoint.

On the other hand, there is one critical point that argues for returns that could be even better than shown for the enterprising investor.

The returns listed are extreme buy-and-hold returns. They show the annualized returns that would have been available for an investor who simply bought each company’s stock at the time it was first listed and simply held the stock until delisting (or through December 2023). The analysis makes no accounting for valuation and company fundamentals. While there is something to be said for the simple approach, the enterprising investor should be able to increase their returns through fundamental research and buying stocks in the best companies when their market prices are suffering versus their fundamentals and future returns are likely to be higher than ordinary.

Summary and takeaways

• Hendrik Bessembinder produced a valuable and unique study in 2024 that shows the best annualized lifetime returns from the stocks of publicly listed US companies.

• The very best annualized returns are produced over very short lifetimes, and those may be hard to predict and thus inaccessible to an investor.

• However, there are many great companies that have produced incredible lifetime returns over medium or longer terms, like 10-40 years.

• An investor seeking to put up the best possible performance should be shooting for annualized returns in the range of the very best companies and above. Data from the Bessembinder study suggests that number could be the 20-50% range.

  • To be fair, the data may be biased high because the end of the study coincides with a bull market.

  • On the other hand, the enterprising investor may be able to obtain even higher levels than those cited above by leveraging fundamental research and buying stocks in the best companies when their market prices are depressed.

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In Parts One and Two, we discussed the government plan to privatize Russian businesses using an interesting voucher system after the fall of communism, and we saw just how cheap Russian businesses were at that time. We also discussed a host of risks in investing in the country at that time.

With the value case established and the risks weighed, we can now attempt to put together Li’s actual investment in Lukoil at the time.

Piecing Together Li’s Investment in the Company

At the end of Part Two, we recreated Lukoil’s market cap from three different sources. I’ve reproduced that chart below.

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Now that we have that recreation, can we piece together Li’s investment more specifically? Li speaks briefly and vaguely about the market prices of Lukoil and Gazprom around this time and is not very specific about the exact time when he bought and sold the stock, but he does provide some clues:

Forget about the earnings. Just... the assets on the balance sheet. At the time oil prices [in the world market], I think the four or five year average was around twenty dollars [per barrel], and the [value per barrel of proven oil reserves for Lukoil was] at really low prices... about 10 cents to 20 cents per proven barrel of oil on the balance sheet and that’s not even counting the earnings... This is how low it went. It was ridiculous.

From this quote and others throughout the talk, it seems that Li’s main focus was just how cheap Lukoil was trading relative to how much proven oil reserves were on its balance sheet. He seems to have virtually ignored any loss (or any income) that the company was making at the time, reasoning that such an extreme undervaluation relative to the company’s assets dwarfed the numbers on the income statement.

Let’s take Lukoil’s proven oil reserves of 10.9 billion barrels from its 1996 annual report and translate the above chart, this time showing the market cap of the company per proven barrel of reserves.

Now, we are beginning to see what Li saw around the time of his investment. More from Li’s talk:

For the longest period of time [the market cap of Lukoil or similar firms] was at 20 or 30 cents [per barrel of proven oil reserves], [then] 50 cents, then quickly moved to a dollar and briefly traded to three dollars.

From this quote (and Li’s discussion of the 1992-1994 voucher period in his talk), I am going to surmise that Li made his initial investment in Lukoil somewhere in early 1995 to mid-1996.

More clues:

And then a few years later the Asian Financial Crisis occurred and Russia devalued the currency. All of a sudden that two dollars [per proven barrel of] oil no longer looks very protected because the currency [is] literally at one point... down ninety percent... But if you bought [Lukoil] at ten cents [per proven barrel of reserves]... you still came out all right. In fact, you still probably made 10 times your money.

For example... in Lukoil and Gazprom, I sold it two years after I first bought it... but at the time they [were] still kind of trading probably 80 to 90 percent discount, but i think the 80 to 90 percent discount is warranted somehow. Today [Author’s note: “today” was the year 2012], they are still trading at a huge discount.

When Li talks about the 80 to 90 percent discount for the stock, he seems to be referring to Lukoil’s market cap per proven barrel of oil and gas reserves versus the market price of crude oil. I’ve recreated that in the chart below, effectively showing the price of Lukoil’s stock (its market cap) versus the market price of Lukoil’s “stuff”: all of its proven oil and gas reserves.

When I saw this chart, I thought I might be off a bit, since Li mentions that he sold when Lukoil was trading at a discount of “80 to 90%”, but after extending this chart over an even longer timeframe, the market cap of Lukoil versus the market price of oil does not meaningfully cross 10% (which is a discount of 90%) until the year 2020! However, from the early 1995 to mid-1996 time period, Lukoil does go from trading around a 98% discount to a 91 or 92% discount.

All in all, with the limited information we have, I think the most reasonable conclusion is that Li made his initial investment in Lukoil somewhere in early 1995 to mid-1996 when the stock was trading around $3 billion to $5 billion in market cap and $0.30 to $0.50 per proven barrel of oil and gas reserves, and he sold it somewhere around mid-1997 to mid-1998, in the region of $12 billion to $20 billion of market cap and $1.25 to $2.00 per proven barrel of reserves. (Recall his comments from earlier, that he sold “two years after” he first bought it and that the $2.00 price per proven barrel of oil no longer looked protected.)

With those crude, round numbers, his investment would have made him anywhere from 2.5 to 6.6 times his money in just over two years of time.

Li Lu first got interested in investing after attending a lecture by Warren Buffett, who was invited to the school to speak, in 1993. (It is possible the exact date was October 27.) At the time of his investment in Lukoil, he may still have been a student at Columbia University, from which he graduated in 1996. He worked at the investment bank Donaldson, Lufkin & Jenrette for about one year before founding Himalaya Capital in 1997. It was likely right at the start of his work at Himalaya that he sold his stake in Lukoil (and any other Russian oil and gas companies he may have bought).

I mention this as a brief aside because it may suggest something about Li’s boldness of character. After first learning about investing just two or three years back, he had the temerity to both do the work on a foreign investment in an emerging democracy and to pull the trigger.

How Cheap Is Cheap Enough?

Li talks about the dramatic cheapness of Lukoil and other Russian stocks at the time, and he was right to some extent. But that cheapness had its limits. Below, I show the price of Lukoil’s stock from 1993 to 2021. I also show a variation of the chart with Lukoil’s market cap versus the value of its proven oil reserves (a measure of Lukoil’s “cheapness”).

The charts paint a picture that is difficult to rectify: For virtually the entire period from 1993 to 2021, Lukoil appeared to be cheap, trading at a market cap that almost never valued the entire company greater than 8% of the value of its proven oil and gas in the ground. Exxon (and later Exxon-Mobil), by comparison, averaged a market cap of 34% of the value of its reserves from 1993 to 2021.

So, at all points, an investor might have thought that Lukoil was cheap. And yes, buying the company’s stock in 1995 and holding it for two years, like Li, would have produced a great return. Even holding it for 10 years, from, say, June 1995 to June 2005 would have produced an annualized return (excluding dividends) of 21%, as the stock went from $5.21 to $34.75.

However, the next 10 years, through June 2015, would have only produced an annualized return of only 3%, despite the company appearing cheap in June 2005, when its market value was only 4.7% of the value of its reserves.

As Much As Possible, Seek a Catalyst

What are we to think about this? How are we to know, for future investment opportunities, when apparent cheapness is “real” and when it’s not?

This case study was particularly enjoyable for me because the lessons are so difficult to tease out. Simply buying Lukoil stock at any point in its history because it was cheap relative to other companies around the world would have been a mixed bag. Buying in the 1990’s or early 2000’s would likely have worked out great. Buying in the late 2000’s or the 2010’s would likely have been poor. At all times, Lukoil looked cheap versus Exxon and other western oil companies.

It is very difficult to know how to think about this issue, but one thing to keep in mind is the timing of Li’s investment. In the early to mid 90’s, Russia was emerging from communism and still getting accustomed to the cultural shift toward capitalism and democracy. One could argue that, although corruption was still rampant, the prevailing winds were blowing in the direction of a country getting more used to democracy and slowly reaping the benefits of capitalist markets. These trends could serve as a gradual but important kind of catalyst to close the gap between price and value. In Russia, for example, these changes would slowly lead to more Western investors participating in Russian markets through the 1990s and 2000s.

But it’s important to realize too that the lack of such change (or timing) could make for a difficult investing situation, whereby an investor thinks a stock is cheap by some measure but that situation sticks around for many years.

So one takeaway from Li’s investment is that extreme cheapness is a great thing to hunt for, but seek to have it come along with a changing situation or an outright catalyst.

Summary and Takeaways:

• Li’s investment in Russian oil and gas companies in the 1990’s was a situation where the stocks were obviously cheap relative to the value of their assets and relative to other companies around the world.

• Dramatic changes, like the shift from communism to liberal democracy in Russia, often come with extreme undervaluations.

• It is very difficult and perhaps impossible to know just how much discount the market will demand of a given situation or investment. As much as possible, look for undervaluations that come with a naturally changing situation or an outright catalyst.

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In Part One of our case study of Li Lu’s investment in Russia, we discussed the the fall of communism, the government plan to privatize Russian businesses, and the voucher system that was used to convey interests in those businesses to private citizens.

Now, I would like to focus on one of the two companies mentioned by Li to try to get a more specific sense of what he saw at the time. That company is Lukoil. A good part of this case study will be focused on attempting to recreate basic information from the time, like Lukoil equity pricing and company fundamentals, since it is very difficult to get any good information about Russian stocks from that period.

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The History of Lukoil and Early Information Advantages

Lukoil was formed in 1991 with the merger of three companies, the Langepas Oil Company, Urai, and Kogalym (the “Luk” in Lukoil)1, and in November 1992, Boris Yeltsin officially designated Lukoil one of three integrated holding companies2. In those early days of the company’s formation and Russian market privatization, the trading of stocks was in its infancy and systems were rudimentary:3

The lack of good trading infrastructure is relevant for our case study today. Early trading prices for Lukoil are not available in any records I checked, which may be due to the disorganized nature of trading in those days. The first trading price I was able to find for the stock was January 12, 1996 from Bloomberg.

The same goes for information about company financials or any supplemental information. In fact, it was so difficult to obtain basic information about Russian companies in the early 90’s that it was cited by some investors as a distinct advantage. From David Hoffman’s The Oligarchs:4

The earliest annual report I was able to find for Lukoil was from the year 1996. It is from that report that I obtained the total for the company’s share count and for the company’s proven oil reserves that I will use in the analysis below.

Do The Legwork Others Won’t

The lack of financial and pricing information available raises a critical point about Li’s investment in Lukoil: it shows what it takes to invest well.

In the early and mid 1990’s, Li Lu was a student at Columbia University. If simply finding information about Russian companies was as difficult as it seems, especially for a student in New York like Li, it speaks to the extreme level of dedication and commitment he must have had in pursuing an investment like this.

Some very interesting and compelling investment opportunities come with the need to do “frontier”-type of work. (See also Li’s willingness in his investment in Timberland to travel to the hometown synagogue of the managing family to get to know them.) In the case of Lukoil, Li would have needed to figure out how to simply obtain basic information about the company and also how to execute a purchase of Lukoil’s stock.5

Recreating Lukoil’s Market Price History

Let’s imagine what Li might have seen in those early years of Lukoil’s formation and trading, recreating the company’s market cap and market price from those years, even if we can only do so crudely.

Since the first trading price of the stock I was able to find was January 12, 1996, I will stitch together an effective “Lukoil market price” for the stock prior to that date from a few data sources. It won’t exactly match the pricing traded by Russian stockbrokers from those early years, but it should be close enough for us to see how this investment unfolded.

1. From 1992 to December 1993, I used the pricing for vouchers we saw in Part One of this article. That figure is reproduced below. However, I could find no information about the outcome or pricing of Lukoil’s first privatization auction in April 1994.

   But some sources did report the results of the Gazprom auction as valuing the entire company at $228mn. Gazprom’s auction took place between April 1994 and June 1, 19946. And just a few years later, in 1996, Gazprom was trading at $1.775bn of market cap (versus $3.073bn for Lukoil)7.

   In determining the effective “voucher-price” of Lukoil, I used the assumption that Lukoil’s market cap coming out of auction was equal to the same ratio of 1.73 times that of Gazprom. It is very crude, and it shouldn’t be relied on for anything more than what we are doing here: trying to get a feel for roughly how this investment opportunity progressed in the early 90’s.

2. Credit Suisse created and maintained a valuable index of the Russian stock market called the ROS index, which tracked 30 Russian stocks (one of which was Lukoil). From December 1993 to January 1996, I make the assumption that Lukoil’s stock price tracks the ROS index exactly. This assumption is crude too, but the correlation between the two after 1996 is very high, so, again, this recreation should give a pretty good feel for what Lukoil’s stock price was doing during this period.

3. From January 1996 onward, I use Lukoil’s stock price from Bloomberg.

Finally, I am going to make two more crude assumptions.

1. Lukoil’s oil reserves. In his talk, Li does not discuss the earnings of Lukoil at all. In fact, he only mentions one metric that indicated how severely undervalued Lukoil was at the time: the number of barrels of proven oil reserves on the company’s balance sheet.

   Finding this figure was difficult, but I was able to discover one annual report of the company’s from those early years, the annual report for 1996. In that report, the company lists its total proven oil reserves in Russia as 10.5 billion barrels of oil and 2.150 trillion cubic feet of natural gas8, for a total of 10.9 billion barrels of oil equivalent. While these reserves will change each year as the company taps those reserves and discovers new reserves, we will use it through 1998 as a fixed value in order to recreate the metric Li spoke about. I was able to find annual reports from 1998 onwards, so any reserve figures from those years will be accurate.

2. Lukoil’s share count. In the same vein, I could find no sources that gave specific share counts for Lukoil’s common stock in the early years. So, I use the total from the 1996 annual report (714,563,255 total shares), assume that figure is fixed through 1998, and use it to calculate Lukoil’s market cap from its stock price.9 Again, I was able to find annual reports from 1998 onwards and have used share count figures for those years.

With the details out of the way, here is my recreated chart of Lukoil’s stock price (or its voucher-equivalent) from 1992 to 1999, made from the above data sources.10

The chart above makes the extreme undervaluation of Lukoil plain in absolute terms. To further drive home just how cheap Lukoil was relative to the rest of the world, consider how it stacked up against a major Western peer.

Lukoil versus Exxon

Lukoil was cheap in those days, but how cheap was it? Let’s take a look at the valuation of Lukoil versus that of another leading oil company at the time, Exxon.

While Lukoil’s trading prices implied a market cap of 20 cents to 50 cents per barrel of proven oil and gas reserves around the time of Li’s purchase, Exxon’s valuation implied a market cap around $6 to $8 per barrel. In other words, Lukoil was trading about 5% the value of Exxon on a reserve basis ($0.35 divided by $7). At the time, the price per barrel of crude oil on world markets was around $20.

Seeing the market cap of Lukoil at such a big discount from the market price of oil during that period (and versus other oil and gas companies as well) makes an investment in the company seem like a no-brainer. And according to Li’s comments in his speech, at the time, he regarded it as such.

But it is impossible to go back in time and truly recreate how any of us would have reacted at the time. To further explore that, let’s discuss the arguments against an investment in Lukoil.

Giving Weight to Arguments Against Russian Investments

To avoid looking at the past through rose-colored glasses, let’s explore some of the arguments against Russian stocks at the time.

Argument #1: Russian companies needed too much capital

At the time of Li’s investment, in the early 1990’s, Russia was still recovering from the collapse of communism, and it was widely thought that Russian companies needed a lot of capital to modernize after underinvestment in the years prior.11

Moreover, these concerns seemed to be more than just academic. In fact, Russian oil production was suffering declines in the early 1990’s:12

Argument #2: Rampant inflation

Another argument against any equity investment in Russia was that inflation was rampant in the country at that time. I spoke about this in Part One of this article. Prior to the fall of communism, the prices of many goods and services were set by the state. Starting in 1989 and in a few stages in the years following, Russian leaders slowly freed prices from government control. The effect was a massive inflation that gripped the country in the 1990’s, as shown in the table below.13

For me, this argument is an easier one to rectify than the first. Here, I’m reminded of Mohnish Pabrai’s investment in the Turkish company Reysas in 2019. Reysas owns warehouses in Turkey that are leased to large multi-national corporations.

At the time, Pabrai was concerned about the rampant inflation (both current and future) in Turkey, but rightly reasoned that a company that controls valuable and irreplaceable assets as part of its business should be able to raise prices to keep pace with inflation (or better). He was right, and, for Li’s investment, Lukoil’s proven oil reserves have a similar aspect.

Argument #3: Rampant corruption

This one is easy for a Westerner to understand today, and it is difficult to rectify. At the time, and despite its moving toward more democratic politics, Russia had a reputation for corruption. Perhaps nowhere was this more evident than in the “loans for shares” scandals that pervaded Russia’s privatization charge.14

The loans for shares program was emblematic of how much corruption was at play in Russia at the time, and the scheme helped fuel the subsequent rise of the Russian oligarchs. To give a more concrete feel for some of the undervaluations that resulted from the scheme, 5% of Lukoil was sold in these schemes for $35mn to $45mn, when the value for 5% of the company that was implied from stock market trades was $180mn.

Argument #4: Russia was cheap, and it should have been.

This argument goes along with #3: There is good reason for the cheapness of Russian stocks. Corruption puts the rule of law at risk, particularly property laws around equity ownership. As in the loans for shares deal, there was no guarantee that further portions of Lukoil wouldn’t be sold for large discounts, effectively diluting existing owners and raising their (per barrel) cost of ownership. Moreover, investing as a Westerner in a country that just came out of a Cold War with the US would have raised serious questions about the risk of the Russian government being antagonistic toward Western ownership.

Next week, in Part Three, the final installment of our case study, we’ll see how Li weighed these arguments, what he ultimately decided, and piece together his investment and just how lucrative it was.

References

1. Capitalism Russian-Style by Thane Gustafson (1999)

2. Wheel of Fortune by Thane Gustafson (2012)

3. Kremlin Capitalism by Joseph K. Blasi, Maya Kroumova, and Douglas Kruse (1997).

4. The Oligarchs by David Hoffman (2001).

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He mentions a very interesting investment that he made in the 1990’s in at least two Russian companies, during the time the country was emerging from communist rule and undergoing the privatization of its government-owned assets. Li begins with a summary:

As some of you might know, in the early 90’s, Russia went through shock therapy and went into a free market almost overnight. In a short period of time they privatized some of the most prized state assets, including Lukoil and Gazprom... And it was so short [a period of time] that most people didn’t really understand what it was all about. A lot of the people who worked in the companies and also other citizens were given a certificate that they could convert into stock ownership, but most people really didn’t know what it was, so to anybody who came along and offered them real cash [for the certificates], they would just freely give [the certificates] away. As a result, [the certificates], at one point, were trading at extraordinarily low prices...

The price of oil... was 20 dollars per barrel on the open market, [and Lukoil or similar firms were trading at market caps as low as] about 10 to 20 cents per barrel of proven oil on the balance sheet... It was ridiculous. At that point in time, I thought “now that’s a margin of safety”, even considering the political situation in Russia.

The Fall of Communism and the Plan to Privatize Russia

Li is referring to the period of time after the fall of communism in Eastern Europe, stretching from the revolutions of 1989 and the fall of the Berlin Wall on November 9 of that year, to the formal dissolution of the Soviet Union on December 26, 1991.

The revolutions of 1989 saw the adoption of liberal democratic policies, governments, and economic structures across central and eastern Europe in countries like Poland, East Germany, Bulgaria, Czechoslovakia, and Romania. In the Soviet Union, such principles were also taking hold and ultimately led to dramatic changes in 1991.

The more progressive Boris Yeltsin was elected as the first President of Russia in June of that year, and an unsuccessful coup attempt was launched in August against Mikhail Gorbachev, whose policies of glastnost and perestroika were perceived as too progressive for staunch Soviets. After the failed coup, the pace of reform increased, and the final step in the Soviet Union’s dissolution occurred in December when the Supreme Soviet ratified the Belavezha Accords.

During and following these events, Yeltsin and the new Russian government moved rapidly to establish principles and structures around a new economic model for Russia. Among the most important decisions was what to do with the thousands of Russian businesses that had been nationalized ever since the October Revolution of 1917 long ago.

To solve the problem, the State Committee on the Management of State Property (GKI) was created, and Anatoly Chubais was charged with heading it in October 1991. Chubais championed and shepherded Russian privatization from planning to realization, through a very turbulent time for the Russian economy, and the appeasement of a host of stakeholders who each had their own interests, from the politicians to the managers of the businesses themselves to their employees and to ordinary Russian citizens.

Ultimately, Chubais and his team landed on a system of vouchers for privatizing Russian businesses.

The Voucher System

The voucher system worked as follows.

Starting in October 1992, each Russian citizen would be given a paper voucher that could be used, in government-organized auctions, to purchase a portion of a Russian business. 147 million vouchers would be printed, one for each Russian citizen, and distributed until January 1993 via local branches of the State Savings Bank. To obtain the vouchers, a citizen needed only to pay a nominal fee of 25 rubles (equivalent to 10 cents US).

We’ll discuss exactly how a person could turn their voucher into a share in a Russian business later. But first, let’s consider the broad facts and what that meant about the value of Russian companies.

By January, 144 million of the vouchers had been picked up and were circulating in public.

Importantly, the vouchers were freely tradable, which could help poorer Russian citizens monetize their vouchers if they chose to (and many did), and free tradability helped attract larger pools of capital that were needed in privatizing the economy.

Once Russian citizens had their vouchers, they could either hold them and use them at the auctions or they could trade them immediately for cash, typically on the streets of Russia.1 As soon as the vouchers began trading, it was apparent that they were trading for very low prices.

That statement is a critical point in this case study.

Sometimes, in studying the past, we deceive ourselves by oversimplifying the situation or misreporting or misremembering facts. But in the case of Russian privatization, there are a host of reports, some of which I will discuss, that make it clear just how cheap Russian assets were and how it could have been clear even to people with only modest experience in finance and investing. The situation in Russia at the time was enormously complicated, yes, but, in those early days, the discounted prices of businesses was extreme enough to offset tremendous risks.

Russian Vouchers Were Very Cheap

Just how cheap were Russian businesses and assets at the time?

Consider the following chart from the great book Privatizing Russia by Maxim Boycko, Andrei Schleifer, and Robert Vishny, who report the trading price of vouchers from October 1992 to July 1994.2

As the chart shows, from 1992 to 1994, these vouchers were trading on the streets of Russia for anywhere from 5 to 25 USD each.

With some simple work, we can ascertain what these voucher prices implied for the value of Russian businesses, and it is astounding.

144 million privatization vouchers were distributed to Russian citizens. These vouchers were mandated by the government to be converted into the ownership of 29% of all businesses in the country. (In order to garner support for the privatization program, appease the other stakeholders who had control over Russian businesses, the remaining 71% of ownership was to be distributed to company managers and employees and retained by the Russian government. By June 1994, the vouchers accounted for on average 20% ownership of those companies auctioned, not 29%).3

Using a generous value of $20 per voucher, that implies the entirety of Russian businesses was worth $14.4bn at the time (equal to $20 x 144,000,000 vouchers / 20%). As if such an extreme undervaluation needs a comparison, the market cap of Exxon alone, a single US company, at its stock price low in 1993 was $71.7bn.

For another comparison, the market cap of all publicly listed US companies was $5.2tn in 1993.4 So, the opportunity to own Russian privatization vouchers, which would become an ownership stake in one or many Russian businesses, could have been had, between 1992 and 1994, at prices that valued all Russian businesses at 0.28% of all American businesses.

Why Were The Vouchers So Cheap?

Why were the vouchers trading at such incredibly low values? There were several reasons, and I will highlight three of them.

High Russian Inflation

First, inflation was rampant in Russia at that time. Prior to the fall of communism, the prices of many goods and services were set by the state. Starting in 1989 and in a few stages in the years following, Russian leaders slowly freed prices from government control. The effect was a massive inflation that gripped the country in the 1990’s, as shown in the table below.5

Many Russian citizens chose to sell their vouchers after receiving them, which is perhaps not surprising given the level of inflation. The average citizen may have appreciated having any amount of cash now in the face of prices that might be higher the next day.

Vouchers Were Complex for Ordinary Citizens

Second, and perhaps most obviously, the primary owners of the vouchers were ordinary Russian citizens. Now, the voucher auctions were designed to be as simple as possible, to the point where a citizen did not even need to know anything about a company to participate. (So as not to deter the flow of the article, I describe the mechanics of the Russian privatization program and the auction mechanics only in two footnotes below.67)

However, I suspect it is likely that, even with a simple voucher auction design, many citizens simply did not trouble themselves with trying to understand how to bid in the auction process. Moreover, with the Soviet Union recently dissolved, the average citizens’ opinion of Russian government procedure may have been sour. Many probably assumed the voucher auctions would never come to fruition, prompting many citizens to sell the vouchers for cash instead of holding them.

The Vouchers Had A Face Value of 10,000 Rubles

Finally, and for interesting reasons, the vouchers were given a “face value” of 10,000 rubles (approximately 25 USD as of the end of 1992, albeit highly volatile). Why? Boycko, Shleifer, and Vishny8 describe two reasons:

1. Having a face value printed on the vouchers gave the vouchers the feeling of a monetary gift to the people from the government, and helped create support for the fledgling program.

2. The denomination of the vouchers in a currency was purposely designed by pro-privatization government officials to make the government commit to the program. Had the vouchers been denominated using points, for example, it would have been easier for a future government committee to cancel the privatization program later on. But since the vouchers felt like real money, canceling or rescinding them would be very difficult.

The apparent effect of that 10,000 ruble face value (again, about 25 USD as of late 1992) on the trading price cannot be overstated.

It inadvertently created an anchor around which the vouchers traded. That anchor served to keep voucher prices low for virtually the entire time they were outstanding through June 1994 and created the opportunity that Li was talking about in Lukoil (and virtually every other Russian business at the time).

Cheap Russian Businesses Attracted Western Investors

The extremely low prices for Russian businesses implied by the voucher prices held sway for a few years and, indeed, throughout virtually the entire time the vouchers auctions were taking place. From December 1992 to June 1994, 15,052 Russian businesses were taken private, in whole or in part, almost all of them at prices that were incredibly low compared to their counterparts in other countries.9

Boycko, Shleifer, and Vishny describe two of the bargains:

1. VAZ, the auto maker of the popular Lada cars, came out of its auction with a total market value of $45 million. As a point of comparison, in 1991, Fiat reportedly offered the Russian government $2 billion for the company.

2. Gazprom, the gigantic Russian natural gas monopoly, emerged from its auction with a market value of $228 million. This was roughly 1/1000th the value of put on the company by foreign investment banks, presumably by comparing it to other natural gas companies around the world.

So, in those early years from 1992 to some time in 1994, Russian voucher prices and the market values of companies coming out of auctions and their subsequent traded stock prices were extremely low.

The most active foreign investment bank by far at the time appears to have been Credit Suisse First Boston, in large part through the efforts of its president Hans-Joerg Rudloff, who hired the very active deputy Boris Jordan and his teammate Steven Jennings. The two were exploring privatization opportunities for CSFB in Russia at the time and supporting the Russian government in its efforts. Prior to 1994, foreign interest in Russian privatization and investing was nil:10

Bill Browder was working for Salomon Brothers at the time and suffering from the same disinterest that Jordan at CSFB was:11

This lack of interest was surprising to foreigners on the ground in 1992 and 1993, but it all started to change in the spring of 1994. Around that time, investing in emerging markets was becoming hot. Also, The Economist published an important article in May of that year, entitled Sale of the Century.12 The article highlighted the cheapness I mentioned above:

At the time, the article created a stir, and it caught the attention of foreign investors:13

Russia Was Cheap But It Was Incredibly Volatile

I mention this turning point in 1994 in the attitudes around foreign investment in Russia because it highlights just how difficult it is to recreate the investment as Li saw it at the time. When Li discusses Lukoil and Gazprom, he doesn’t mention exactly when he made his investment. And Russian equity prices were so volatile in the 1990’s that understanding exactly when an investment was made could change the potential return by several multiples.

1994, for example, was an incredibly volatile year. The ROS index of 30 Russian stocks (created by CSFB) surged from 116 at the start of the year to a peak of 1,669 in September of that year. Yes, the index was up 1,338% in nine months. That is not a typo. It later dropped to a low of 443 in April 1995.

The End of The Voucher Period and The Start of Russian Stock Trading

So, 1994 was an important year for Russian privatization as an investment. It marks the end of the “voucher period” when Russian vouchers were trading at absurdly low prices and marks the deeper involvement of foreign investors (and the re-pricing and volatility that came with them). It is the time when the price of Russian businesses went from absurdly low to merely very low.

This is important to understand because it makes recreating Li’s exact investment returns virtually impossible. But we can still ascertain what he generally saw in the investment and learn some lessons about extreme opportunities. For example, Li’s commentary in his speech that Lukoil was trading at “10 cents to 20 cents” per barrel of oil reserves on the balance sheet, is consistent with the market cap of the company implied from voucher prices. We’ll see more of this in the next part.

The first period of Russian privatization, of vouchers and voucher auctions, provided astounding opportunities for (very) enterprising investors to invest in Russian businesses at dramatically low prices.

Next week, in Part Two of this case study, we will explore the mid-1990’s period when Russian stocks began trading, we’ll focus on one company in particular (Lukoil) and recreate its market valuations during that period, and we’ll discuss the real risks in investing in Russia at the time.

References

(1) Privatizing Russia by Maxim Boycko, Andrei Schleifer, and Robert Vishny (1995).

(2) The Oligarchs by David Hoffman (2001).

(3) Kremlin Capitalism by Joseph K. Blasi, Maya Kroumova, and Douglas Kruse (1997).

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I first learned about Duca through the excellent blog A Letter A Day by Kevin Gee. Kevin posted the transcript of an interview that Duca gave in 2023 in which he discusses his investment philosophy. In the interview, he stresses the importance of concentration in producing outsized investment returns and also emphasizes that there are a limited number of truly exceptional companies out there.

In driving home the latter point, Duca mentions a research study by Hendrik Bessembinder from Arizona State University. The study is called Do Stocks Outperform Treasury Bills?, and it was first posted on SSRN in 2017.

Bessembinder studied 25,332 companies over the 90-year period from 1926 to 2016, and he reported the dollar wealth generated by those companies.1 He found a few startling takeaways.

Only 4.3% of stocks produce dramatic outperformance

Most surprising of all, perhaps, is that the vast majority of dollar returns over 90 years was produced by a very small minority of companies. Of the 25,332 companies in the study, only 1,092 of them (4.3%) produced all of the net gains when compared to a competing investment in one-month Treasury bills.2 In other words, we can divide the stocks into three groups:

1. Those that produced dramatic outperformance vs Treasuries (1,092 stocks or 4.3% of stocks),

2. those that produced only modest outperformance (9,579 stocks or 37.8% of stocks), and

3. those that underperformed Treasuries (14,661 stocks or 57.9% of stocks).

Duca’s point in referencing the study is that, if one is going to engage in individual stock investing, he had better do everything he can to be invested in that small minority of companies and stocks that lead to dramatic returns (those in bucket number one). Otherwise, he is at risk of producing only modest outperformance for all the work he will be doing, or worse, selecting stocks in bucket number three.

Most stocks do not even outperform Treasuries in their lives

Bucket number three highlights a second surprising takeaway from the study: the majority of companies did not even outperform Treasuries over their lifetimes. That result flies in the face of one typical understanding of equity returns: that equity investors will outperform Treasuries by virtue of “taking on risk”.

While it is true that a well-diversified equity investor would outperform Treasuries over the 90-year period of the study, Bessembinder shows that an investor who seeks to select single stocks will underperform even Treasuries with the majority of his stock selections. Even worse than that, more than half of the stocks in the study produce lifetime returns that are outright negative.

It is only a minority of companies and stocks that vastly outperform, and one can think of those stocks as being the source of all the outperformance that equities generate over Treasuries. This phenomenon of massive outperformance from a small minority of companies is known as skewness of returns and it is well-known among equity investing researchers.

The purported benefits of diversification

Skewness is often pointed to as a reason for equity investors to be diversified. The logic is as follows. If so many stocks underperform even Treasuries, and so few dramatically outperform, then shouldn’t one ought to select a wide variety of stocks in order to minimize the chances of being in the bad bucket number three and maximize the chances of selecting one of the big winners?

Bessembinder advocates “yes” and highlights this benefit to diversification in his paper by constructing random portfolios consisting of various numbers of stocks (shown below) which turn over their holdings every month. The results show the protection from diversifying to more and more stocks: diversified portfolios are better able to avoid poor results.

The drawbacks of diversification

So why does Duca seem to take the opposite view, stressing the importance of concentration in his interview?

Well, the typical plea to seek diversification is sound advice for index investors who want to achieve market-like returns, but I believe (and so does Duca) that it is unsound for any active stock-picking investor who seeks to dramatically outperform.3

Bessembinder’s mock portfolios are selected randomly and mechanically and do not reveal the biggest danger that diversification introduces: the fact that no portfolio manager can know 25 positions as well as he knows five positions. As a result, when the price of one of those 25 selections begins to fall, he will be more likely to take the opinion of Mr. Market and jettison the position, rather than exploit Mr. Market’s mania and hold on or purchase more.

This is why many great investors stress concentration with only a small amount of diversification. Selecting a small enough number of stocks, like three to five or possible a few more, seems to strike the right balance between protecting oneself against ruin on one side and against not really knowing what you own on the other. As Buffett and Munger were fond of saying, “three wonderful businesses is more than you need in this life to do very well.”

…Within Berkshire, I could pick out three of our businesses. And I would be very happy if they were the only businesses we owned… three wonderful businesses is more than you need in this life to do very well.

I mean, if you look at how the fortunes were built in this country, they weren’t built out of a portfolio of fifty companies. They were built by someone who identified with a wonderful business… there aren’t fifty Coca-Colas [an example of a great business].

- Warren Buffett, Berkshire Hathaway 1996 annual meeting

That is why Duca stresses concentration.

Investment managers are incentivized to diversify

Moreover, the academic logic about the benefits of diversification persists in part because the investment management industry is incentivized to follow it. If an institutional manager is paid a percentage of assets under management, like many are, that payment incentivizes diversification so he or she may decrease the risk of ruin, stay in the game, and earn the fees as long as possible, all at the expense of any significant outperformance for their clients.

So, Bessembinder’s study reveals the first reason that most active portfolio managers underperform their index: most individual stocks underperform too. But it doesn’t say anything about the second reason: if one diversifies too much, one will not know any of his positions very well, and, as a result, he may fall prey to following Mr. Market.4

The chart below is from S&P Global’s SPIVA research and shows the degree of underperformance by US large-cap equity funds after fees. Over the past three years, for example, over 80% of fund managers underperformed their benchmark.

Instead of seeking diversification, and as difficult as it may be, the active stock-picker looking to dramatically outperform would be better served concentrating his effort on turning over as many rocks as he can and acting much more deliberately, only when he finds one of the few, rare, great companies (or opportunities) and investing heavily in it.

The greatest companies

In his report, Bessembinder publishes a list of the top 50 companies that have produced the largest dollar returns over the 90 years of the study through 2016. I show the top ten below. The company at the top of the list, Exxon Mobil, generated $1.0 trillion of wealth, meaning that a hypothetical investment equal to the company’s market cap in 1926 would have generated $1.0 trillion more than the equivalent investment in one-month Treasuries through 2016.

As you can see in the last columns of the table, six of the top ten companies on the list have generated their wealth over the entire 90 year duration of the study. (The remaining four needed less time than that to generate such wealth). Generally speaking, more time in existence means more dollar profits accumulated by the firms.

Before I discuss some of the results shown above, there is an important point to make. Bessembinder’s study is so popular that he has published four subsequent updates to the 2016 data at the ASU website, with the latest version from 2025.

Because of the tremendous run that technology stocks have had over the past nine years (and longer), the table above has changed dramatically. See the 2025 version below.

There are a few points to make here.

1. Staggering value produced

First, the amount of dollar wealth created by the largest firms in just the past nine years alone dwarfs that produced by previous US stalwarts. The wealth figures in Figure 5 are measured in trillions of dollars, while those in Figure 4 are hundreds of billions. Naturally, the past nine years have been fantastic for holders of large tech stocks.

2. Compounded returns

The companies on the 2016 list produced large dollar amounts of wealth, but the level of annualized returns they produced is what I would call very good but not extraordinary. (Microsoft is an exception, with a 25.02% annualized return.) This is especially true for those companies that produced their dollar returns over the full 90-year duration of the study. Simply put, it is very, very hard to maintain extraordinary rates of return for very long times. Take the top company on the list for example, Exxon Mobil. Over the course of 90 years, the company produced just over $1 trillion of wealth and an annualized return of 11.94%. That compares to a return for the S&P 500 of 9.9% per year. The dollar amount of wealth produced by Exxon Mobil is astounding, but the level of annualized returns is not near the astounding levels we typically associate with great investors or great investments.

However, the companies on the 2025 list in Figure 5 produced not just huge dollar amounts of wealth, but also did so while producing extraordinary annualized returns (Exxon Mobil being the exception). This may be a function of the fact that technology stocks have been in an extended golden era, or it may be because the economics of many of these firms are quite different than the businesses in the 2016 list. They are generally less capital-intensive and some of them have near-zero marginal production costs, making them very valuable. Alphabet is a good example of that, and it has produced $3.5 trillion of wealth and a stunning 25.27% annualized return over its 21 years of life through 2025.

3. Return inconsistency

For most of these great companies on either of Bessembinder’s lists, they likely did not produce consistent returns for their entire duration. Exxon Mobil produced 11.94% per year over 90 years, but for the past 20 years, from July 2005 to July 2025, the stock only returned 6.7% per year (compared to 10.5% for the S&P 500). And for the 20 years prior to that, from July 1985 to July 2005, the stock returned 15.2% (compared to 12.3% for the S&P 500).

Even Nvidia, the stock story of the decade, which produced $4.5 trillion of wealth and a mind-boggling 37.08% annualized return over its 26 years through 2025, wallowed in underperformance for much of its life. For the 10 years between December 31, 2001 and the same date in 2011, the stock produced a negative annualized return of -4.83%.

Such inconsistency in outperformance should serve as a caution to investors that “great companies” may not be great investments for the entirety of their lives.

In a coming article, I will dive more into great companies with great investment returns using another Bessembinder study. Instead of focusing on dollar-based returns, we’ll discuss the level of annualized returns that are typical of great investments. The goal will be to develop a sense for what levels of returns might constitute astounding performance and just how difficult that might be to achieve over a certain period of time.

Summary

There are three big takeaways from Bessembinder’s fantastic work.

1. Only a small minority of (great) companies produced all of the net gains versus Treasuries over the long term.

2. The majority of companies did not even outperform Treasuries over their lifetimes.

3. Diversification is critical if you want to realize market returns, but it is deadly if you want to produce massive outperformance.

For any individual investor seeking to produce stunning returns, Bessembinder’s study should serve as a reminder of that it is rare to find great companies and great investments. I must be prepared to search through and study many duds before finding one worthy of the punch card.

In Part One, I laid out the challenges facing Tenneco Automotive in late 2001: a crippling debt load, a recession, and a business that had been turned inside out by five years of spinoffs and business sales. It looked like a company heading toward bankruptcy. So what compelled Charlie Munger to invest?

Was there anything positive about Tenneco’s business?

Given all the challenges I discussed last week, Tenneco’s situation seemed pretty dire to the casual observer in 2001 (and even to many financial analysts). However, beneath all these challenges, there were some positive points about the company, each of which were evident with a careful reading of the company’s annual and quarterly reports.

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Positive point #1: Tenneco had great brands and a broad customer base

Tenneco produced auto products in two business segments: Emission Control and Ride Control. In both of those business segments, it had brand names with an excellent reputation and market share. Their leading position is backed up by disclosures in the 2000 annual report:

Moreover, Tenneco’s list of original equipment manufacturers was large, including just about every major auto maker in the world. And the largest automaker (GM) accounted for only 16.6% of the company’s sales, indicating the sales were nicely diversified.

Munger understood the great reputation of Tenneco’s products, as indicated by his brief comments at the Daily Journal meeting, when he stated:

I kind of knew based on experience how sticky some of that auto secondary market was, and how many old cars needed Monroe shock absorbers.

I think this point is critical to understanding Munger’s willingness to purchase these securities. Since customers loved and needed Tenneco’s products, the company still had fundamental value as an ongoing concern. We will see how pivotal this was in assessing the company’s likelihood to pull out of its debt problem.

Positive Point #2: Tenneco’s business was fundamentally healthy and profitable, apart from its large debt load

As indicated in Figure 4 last week (and as suggested by the company’s brand strength), Tenneco’s business was fundamentally profitable before accounting for the large interest payments on its debt.

Figure 8 below reproduces the abbreviated income statement from last week, this time stopping at EBIT and the EBIT margin. While the EBIT margin was low, especially compared to the company’s prior pre-spinoff years, Tenneco was still profitable before the large interest payments on its debt.

Moreover, even though sales were flagging as a result of the recession, the competitive nature and long lead times in the auto business meant that Tenneco’s management had a good idea about its order book for the coming two to three years, and those numbers revealed that the decline in sales, at least for the OEM segment, seemed to be abating by 2002. From the Q3 2001 10-Q report:

Positive Point #3: Management was pursuing aggressive cost controls post-spinoffs

Importantly, and perhaps underappreciated by the market, Tenneco was still in the midst of a major transition in its business. It had gone through five major spinoffs or sales of business units since 1993, it was facing its first recession since that time, and it was coping with all the debt it was saddled with after those spinoffs.

But digging in a bit to the company’s annual and quarterly reports makes it clear that management was keenly focused on right-sizing company expenses and running a more efficient organization. This is from the 2000 annual report:

So, as of the end of 2000, management expected to generate a total of $92 million of savings by right-sizing its workforce and by adopting more efficient processes and practices.

In fact, it was already becoming evident by Q3 of 2001 that those efforts were working better than expected. Figure 10 below (which is Figure 8 reproduced) shows annualized operating costs (plus DD&A) that were $104mn lower than those for the year 2000. And those lower operating costs boosted EBIT by 32% to $152mn.

Not only was the cost cutting working, it was having a large impact on earnings before interest.

The Pro Forma Tenneco

To drive the last two positive points home, let’s imagine a pro forma income statement that accounts for both these cost cutting measures and the forecasted increase in OEM sales (using management’s OEM forecast for 2004). That pro forma income statement is shown below, next to the Q3 2001 (annualized) figures and the year 2000 figures for comparison.1

As you can see, it seems plausible that Tenneco could once again become a profitable company. Perhaps more importantly, Tenneco seemed poised to almost double its EBIT from $115mn in the year 2000 to a pro forma $214mn.

Big deal. What about all the debt?

Of course, all this says nothing about paying down the extraordinary debt load the company was burdened with. However, I think these positive points are ultimately what caused Munger to believe that the company’s bonds, around a price of 35, and the company’s stock, around a price of $1.55 per share and a market cap of only $59mn, were way too cheap. For reference, the entire enterprise value of the company was $1.1bn, a figure I arrive at by conservatively assuming that the company’s debt is valued at par (apart from the 11 5/8% bonds, which I value at 35 cents).

I think Munger saw a very difficult financial situation for the company, and he probably acknowledged that a further, prolonged downturn in the economy and/or a group of unfriendly bank lenders could have pushed the company into bankruptcy. And in bankruptcy, in the wrong economic environment, it was quite possible that his debt and equity got wiped out.

The fact that Munger did not invest fully in Tenneco’s equity, which was more likely to be wiped out in bankruptcy, and chose to split his investment between bonds and equity, shows that he realized this was a possibility.

But more likely, by his judgment, the company could survive a recessionary environment (perhaps by delaying repayment on its debt through the use of its revolver for awhile and continuing to cut costs if the environment got worse). And yet, the pricing of the equity (at a market cap of $59mn) and the debt (at a price of 35 cents) was awarding almost no probability to a recovery.

Bankruptcy game theory

Now, here is the real kicker.

I think Munger likely reasoned about how a potential bankruptcy might play out, and I think this was the most important point of all, prompting him to make his investment.

If Tenneco was forced into bankruptcy, its lenders would then have to decide on the best course of action that might get them a full recovery on their lending amounts. The total amount of long-term debt outstanding was $989mn plus the $500mn of subordinate bonds which Munger would invest in.

Tenneco’s lenders would rightly ask themselves: How are we best off to recover our $989mn?

1. We could force a liquidation of the business and attempt to be paid in full. That would involve a few years of wind-down work, staggered employee layoffs and plant and equipment sales, along with the severance and interim operating costs that come along with it. Plus, we would also need to engage in a process to sell the Walker and Monroe brands, two of the most valuable assets the company had.

Or...

2. We could effectively realize the value of those brands by recapitalizing the company and operating as usual. One way to do that might be to forgive Tenneco’s debt completely, take an equity stake in the new company without debt, and then sell the equity in the new company to make ourselves whole on the lending amounts.2

Munger may have realized that option number 2 (or some variant of it) looked pretty attractive from the perspective of the bankers, especially compared to the more cumbersome option 1.

Once again, the strength of Tenneco’s brands, as evidenced by the healthy operating profit they generated, may partly be what Munger was communicating when he spoke positively about them: “I... knew based on experience how sticky some of that auto secondary market was”. It may also have been part of the reason that Tenneco’s CFO, Mark McCollum, suggested in another article3 that delaying loan repayments by using capacity on the company’s revolving line of credit might be an appealing course of action to their lender, Chase Bank, for the time being:

Investors are worried whether Chase [Bank] would approve, and how the company will come up the money it needs going forward, said Peters.

McCollum said Chase, whose name is on the revolver, as well as the term loan, would not be opposed to such an “in one pocket, out the other” scenario.

“Are they [Chase] going to be happy? No. But they realize that it’s not a bad answer,” he said. Tenneco has $357 million left on the revolver.

Munger’s investment decision and outcome

In the end, Munger decided that the pricing of Tenneco’s 11 5/8% bonds (at 35) and its stock (around $1.55 and a market cap of $59mn) was accounting for too severe a set of outcomes and not enough for what was likely to happen based on (1) the strength of Tenneco’s brands, (2) management’s right-sizing initiatives, and (3) the likely game theory with Tenneco’s lenders.

We know he purchased the bonds and stock around those levels, and we know, from his comments, that his bonds were called away from him and that he “sold [his] stock at 15”.

The chart below shows that Munger likely held his investment for three years until December 2004. Tenneco’s 11 5/8% bonds were called on December 20, 2004 at a price of 105.81, and its stock on that date closed at $16.44, close to Munger’s report of $15.

How much did Munger invest and make?

We also know that Munger made “$80mn” on the investment. But we don’t know specifically how much he invested in either of the securities. Let’s speculate on that for some fun.

The table below backs into rounded amounts that Munger is likely to have invested in each class of security, assuming:

1. he purchased the securities around the prices listed above,

2. the bonds were called from him at 105.81 in December 2004 and he sold the stock at $15 at that time as well, and

3. he made approximately $80mn on the trade in full, including bond coupon payments.

We don’t know how much he invested in each class, so I show the outcome of the trade if he put 25%, 50%, and 75% of his investable capital in each class. Corporate bond markets are typically much less liquid than equity markets. So, in practice, Munger may have simply had approximately $14mn to invest, bought as many bonds as were available, and then put the rest into Tenneco’s stock.

Assuming Munger invested somewhere between 25% and 75% in Tenneco’s bonds (and stock), he likely made anywhere from 4.5 times to 7.2 times on his investment in three years, from December 2001 to the time the bonds were called in December 2004 (and when he likely sold his stock as well). Those returns imply an annualized return of 65% to 93%.

Summary and takeaways

I think there is one clear takeaway from Munger’s Tenneco investment.

When you encounter a company with a quality, in-demand product and/or a great brand, and that company is suffering, look twice.

Tenneco manufactured a quality and beloved product, but it was being punished by the market because of the 2001 recession and a huge debt load from five past spinoffs and business sales.

But the recession’s impact appeared overblown, and we were able to see this with a detailed reading of the K’s and Q’s. Management was making great progress on a large cost-cutting initiative, and they had a book of orders that implied sales would be rising again.

The bankruptcy issues were scarier, perhaps, and the lesson there even more important. If a company has “hidden” assets, like a beloved product and/or a great brand (and could have a healthy business but for its debt), put yourself in the shoes of the lenders and ask “what is the best move for them?”

Postscript

In Munger’s discussion of the $80 million he made in the Tenneco investment, he also mentions that he “took the $80 million and gave it to Li Lu, who turned it into 4 or 5 hundred million dollars”.

In his foreword to Poor Charlie’s Almanack, from 2010, entitled “My Teacher: Charlie Munger”, Li mentions that Charlie first invested money with him in 2004, which lines up nicely with the timeframes presented above.

In 2004, Mr. Munger became my investment partner and has since become my lifelong mentor and friend — an opportunity I would have never dared to dream about.

2

Obviously, this is not a small matter. And I am dramatically simplifying the thought process here by saying that the lenders could ”forgive all the debt” (including that owned by bondholders). But I’m doing so to illustrate the point. Whether the newly imagined company had no debt or $500mn in debt (or an amount in between), it would be dramatically healthier, with an equity valuation that should reflect that.

That would be a much better path for a bank lender (and for bondholders) than liquidating the company. Ultimately, It’s that economic interest that should bring a bank lender and bondholders to the negotiating table. (And a shrewd investor would understand this and make an investment in anticipation of it being the best outcome.)

To allay a lingering doubt about the risk of a company liquidation, I’ve reproduced Tenneco’s balance sheet from Q3 2001 which shows that the company had $242mn of book value; the point here is that it would not be obvious to a bank lender that a liquidation of the company (after all costs) would provide enough proceeds to fully pay back $968mn of loan debt. That supports the allure of the equity recapitalization idea.