Untangling Skill and Luck

(Image:  Zen Buddha Silence by Marilyn Barbone.)           

January 13, 2019

Michael Mauboussin wrote a great book called The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing (Harvard Business Press, 2012).  

Here’s an outline for this blog post:

  • Understand were you are on the skill-luck continuum
  • Assess sample size, significance, and swans
  • Always consider a null hypothesis
  • Think carefully about feedback and rewards
  • Make use of counterfactuals
  • Develop aids to guide and improve your skill
  • Have a plan for strategic interactions
  • Make reversion to the mean work for you
  • Know your limitations



If an activity is mostly skill or mostly luck, it’s generally easy to classify it as such.  But many activities are somewhere in-between the two extremes, and it’s often hard to say where it falls on the continuum between pure skill and pure luck.

An activity dominated by skill means that results can be predicted reasonably well.  (You do need to consider the rate at which skill changes, though.)  A useful statistic is one that is persistent—the current outcome is highly correlated with the previous outcome.

An activity dominated by luck means you need a very large sample to detect the influence of skill.  The current outcome is not correlated with the previous outcome.

Obviously the location of an activity on the continuum gives us guidance on how much reversion to the mean is needed in making a prediction.  In an activity that is mostly skill, the best estimate for the next outcome is the current outcome.  In an activity that is mostly luck, the best guess for the next outcome is close to the base rate (the long-term average), i.e., nearly a full reversion to the mean.

Our minds by nature usually fail to regress to the mean as much as we should.  That’s because System 1—the automatic, intuitive part of our brain—invents coherent stories based on causality.  This worked fine during most of our evolutionary history.  But when luck plays a significant role, there has to be substantial reversion to the mean when predicting the next outcome.



Even trained scientists have a tendency to believe that a small sample of a population is representative of the whole population.  But a small sample can deviate meaningfully from the larger population.

If an activity is mostly skill, then a small sample will be representative of the larger population from which it is drawn.  If an activity is mostly luck, then a small sample can be significantly different from the larger population.  A small sample is not reliable when an activity is mostly luck—we need a large sample in this case in order to glean information.

In business, it would be an error to create a sample of all the companies that used a risky strategy and won, without also taking into account all the companies that used the same strategy and lost.  A narrow sample of just the winners would obviously be a biased view of the strategy’s quality.

Also be careful not to confuse statistical significance with economic significance.  Mauboussin quotes Deirdre McCloskey and Stephen Ziliak: “Tell me the oomph of your coefficient; and do not confuse it with mere statistical significance.”

Lastly, it’s important to keep in mind that some business strategies can produce a long series of small gains, followed by a huge loss.  Most of the large U.S. banks pursued such a strategy from 2003-2007.  It would obviously be a big mistake to conclude that a long series of small gains is safe if in reality it is not.

Another example of ignoring black swans is Long-Term Capital Management.  The fund’s actual trades were making about 1% per year.  But LTCM argued that these trades had infintessimally small risk, and so they levered the trades at approximately 40:1.  Many banks didn’t charge LTCM anything for the loan because LTCM was so highly regarded at the time, having a couple of Nobel Prize winners, etc.  Then a black swan arrived—the Asian financial crisis in 1998.  LTCM’s trades went against them, and because of the astronomically high leverage, the fund imploded.



Always compare the outcomes to what would have been generated under the null hypothesis.  Many streaks can easily be explained by luck alone.

Mauboussin gives the example of various streaks of funds beating the market.  Andrew Mauboussin and Sam Arbesman did a study on this.  They assumed that the probability a given fund would beat the S&P 500 Index was equal to the fraction of active funds that beat the index during a given year.  For example, 52 percent of funds beat the S&P 500 in 1993, so the null model assigns the same percentage probability that any given fund would beat the market in that year.  Mauboussin and Arbesman then ran ten thousand random simulations.

They determined that, under the null model—pure luck and no skill—146.9 funds would have a 5-year market-beating streak, 53.6 funds would have a 6-year streak, 21.4 funds would have a 7-year streak, 7.6 funds would have an 8-year streak, and 3.0 funds would have a 9-year streak.  They compared these figures to the actual empirical frequencies:  206 funds had 5-year streaks, 119 had 6-year streaks, 75 had 7-year streaks, 23 had 8-year streaks, and 28 had 9-year streaks.

So there were many more streaks in the empirical data than the null model generated.  This meant that some of those streaks involved the existence of skill.



Everybody wants to improve.  The keys to improving performance include high-quality feedback and proper rewards.

Only a small percentage of people achieve expertise through deliberate practice.  Most people hit a performance plateau and are satisfied to stay there.  Of course, for many activities—like driving—that’s perfectly fine.

The deliberate practice required to develop true expertise involves a great deal of hard and tedious work.  It is not pleasant.  It requires thousands of hours of very focused effort.  And there must be a lot of timely and accurate feedback in order for someone to keep improving and eventually attain expertise.

Even if you’re not pursuing expertise, the keys to improvement are still focused practice and high-quality feedback.

In activities where skill plays a significant role, actual performance is a reasonable measure of progress.  Where luck plays a strong role, the focus must be on the process.  Over shorter periods of time—more specifically, over a relatively small number of trials—a good process can lead to bad outcomes, and a bad process can lead to good outcomes.  But over time, with a large number of trials, a good process will yield good outcomes overall.

The investment industry struggles in this area.  When a strategy does well over a short period of time, quite often it is marketed and new investors flood in.  When a strategy does poorly over a short period of time, very often investors leave.  Most of the time, these strategies mean revert, so that the funds that just did well do poorly and the funds that just did poorly do well.

Another area that’s gone off-track is rewards for executives.  Stock options have become a primary means of rewarding executives.  But the payoff from a stock option involves a huge amount of randomness.  In the decade of the 1990’s, even poor-performing companies saw their stocks increase a great deal.  In the decade of the 2000’s, many high-performing companies saw their stocks stay relatively flat.  So stock options on the whole have not distinguished between skill and luck.

A solution would involve having the stock be measured relative to an index or relative to an appropriate peer group.  Also, the payoff from options could happen over longer periods of time.

Lastly, although executives—like the CEO—are much more skillful than their junior colleagues, often executive success depends to a large extent on luck while the success of those lower down can be attributed almost entirely to skill.  For instance, the overall success of a company may only have a 0.3 correlation with the skill of the CEO.  And yet the CEO would be paid as if the company’s success was highly correlated with his or her skill.



Once we know what happened in history, hindsight bias naturally overcomes us and we forget how unpredictable the world looked beforehand.  We come up with reasons to explain past outcomes.  The reasons we invent typically make it seem as if the outcomes were inevitable when they may have been anything but.

Mauboussin says a good way to avoid hindsight bias is to engage in counterfactual thinking—a careful consideration of what could have happened but didn’t.

Mauboussin gives an example in Chapter 6 of the book: MusicLab.  Fourteen thousand people were randomly divided into 8 groups—each 10% of the total number of people—and one independent group—20% of the total number of people.  There were forty-eight songs from unknown bands.  In the independent group, each person could listen to each song and then decide to download it based on that alone.  In the other 8 groups, for each song, a person would see how many other people in his or her group had already downloaded the song.

You could get a reasonable estimate for the “objective quality” of a song by looking at how the independent group rated them.

But in the 8 “social influence” groups, strange things happened based purely on luck—or which songs were downloaded early on and which were not.  For instance, a song “Lockdown” was rated twenty-sixth in the independent group.  But it was the number-one hit in one of the social influence worlds and number forty in another.

In brief, to maintain an open mind about the future, it is very helpful to maintain an open mind about the past.  We have to work hard to overcome our natural tendency to view what happened as having been inevitable.  System 1 always creates a story based on causality—System 1 wants to explain simply what happened and close the case.

If we do the Rain Dance and it rains, then to the human brain, it looks like the dance caused the rain.

But when we engage System 2 (the logical, mathematical part of our brain)—which requires conscious effort—we can come to realize that the Rain Dance didn’t cause the rain.



Depending on where an activity lies on the pure luck to pure skill continuum, there are different ways to improve skill.

When luck predominates, to improve our skill we have to focus on learning the process for making good decisions.  A good process must be well grounded in three areas:

  • analytical
  • psychological
  • organizational

In picking an undervalued stock, the analytical part means finding a discrepancy between price and value.

The psychological part of a good process entails an identification of the chief cognitive biases, and techniques to mitigate the influence of these cognitive biases.  For example, we all tend to be wildly overconfident when we make predictions.  System 1 automatically makes predictions all the time.  Usually this is fine.  But when the prediction involves a probabilistic area of life—such as an economy, a stock market, or a political situation—System 1 makes errors systematically.  In these cases, it is essential to engage System 2 in careful statistical thinking.

The organizational part of a good process should align the interests of principals and agents—for instance, shareholders (principals) and executives (agents).  If the executives own a large chunk of stock, then their interests are much more aligned with shareholder interests.

Now consider the middle of the continuum between luck and skill.  In this area, a checklist can be very useful.  A doctor caring for a patient is focused on the primary problem and can easily forget about the simple steps required to minimize infections.  Following the suggestion of Peter Pronovost, many hospitals have introduced simple checklists.  Thousands of lives and hundreds of millions of dollars have been saved, as the checklists have significantly reduced infections and deaths related to infections.

A checklist can also help in a stressful situation.  The chemicals of stress disrupt the functioning of the frontal lobes—the seat of reason.  So a READ-DO checklist gets you to take the concrete, important steps even when you’re not thinking clearly.

Writes Mauboussin:

Checklists have never been shown to hurt performance in any field, and they have helped results in a great many instances.

Finally, anyone serious about improving their performance should write down—if possible—the basis for every decision and then measure honestly how each decision turned out.  This careful measurement is the foundation for continual improvement.

The last category involves activities that are mostly skill.  The key to improvement is deliberate practice and good feedback.  A good coach can be a great help.

Even experts benefit from a good coach.  Feedback is the single most powerful way to improve skill.  Being open to honest feedback is difficult because it means being willing to admit where we need to change.

Mauboussin concludes:

One simple and inexpensive technique for getting feedback is to keep a journal that tracks your decisions.  Whenever you make a decision, write down what you decided, how you came to that decision, and what you expect to happen.  Then, when the results of that decision are clear, write them down and compare them with what you thought would happen.  The journal won’t lie.  You’ll see when you’re wrong.  Change your behavior accordingly.



The weaker side won more conflicts in the twentieth century than in the nineteenth.  This is because the underdogs learned not to go toe-to-toe with a stronger foe.  Instead, the underdogs pursued alternative tactics, like guerrilla warfare.  If you’re an underdog, complicate the game by injecting more luck.

Initially weaker companies almost never succeed by taking on established companies in their core markets.  But, by pursuing disruptive innovation—as described by Professor Clayton Christensen—weaker companies can overcome stronger companies.  The weaker companies pursue what is initially a low-margin part of the market.  The stronger companies have no incentive to invest in low-margin innovation when they have healthy margins in more established areas.  But over time, the low-margin technology improves to the point where demand for it increases and profit margins typically follow.  By then, the younger companies are already ahead by a few of years, and the more established companies usually are unable to catch up.



Mauboussin writes:

We are all in the business of forecasting.

Reversion to the mean is difficult for our brains to understand.  As noted, System 1 always invents a cause for everything that happens.  But often there is no specific cause.

Mauboussin cites an example given by Daniel Kahneman: Julie is a senior in college who read fluently when she was four years old.  Estimate her GPA.

People often guess a GPA of around 3.7.  Most people assume that being precocious is correlated with doing well in college.  But it turns out that reading at a young age is not related to doing well in college.  That means the best guess for the GPA would be much closer to the average.

Mauboussin adds:

Reversion to the mean is most pronounced at the extremes, so the first lesson is to recognize that when you see extremely good or bad results, they are unlikely to continue that way.  This doesn’t mean that good results will necessarily be followed by bad results, or vice versa, but rather that the next thing that happens will probably be closer to the average of all things that happen.



There is always a great deal that we simply don’t know and can’t know.  We must develop and maintain a healthy sense of humility.

Predictions are often difficult in many situations.  The sample size and the length of time over which you measure are essential.  And you need valid data.

Moreover, things can change.  If fiscal policy has become much more stimulative than it used to be, then bear markets may—or may not—be shallower and shorter.  And stocks may generally be higher than previously, as Ben Graham pointed out in a 1963 lecture, “Securities in an Insecure World”: http://jasonzweig.com/wp-content/uploads/2015/04/BG-speech-SF-1963.pdf

If monetary policy is much more stimulative than before—including a great deal of money-printing and zero or negative interest rates—then the long-term average of stock prices could conceivably make another jump higher.

The two fundamental changes just mentioned are part of why most great value investors never try to time the market.  As Buffett has said:

  • Forecasts may tell you a great deal about the forecaster;  they tell you nothing about the future.
  • I make no effort to predict the course of general business or the stock market.  Period.
  • I don’t invest a dime based on macro forecasts.

Henry Singleton—who has one of the best capital allocation records of all time—perhaps put it best:

I don’t believe all this nonsense about market timing.  Just buy very good value and when the market is ready that value will be recognized.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.

If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com


Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Bad Blood

(Image: Zen Buddha Silence by Marilyn Barbone)

December 16,2018

Bad Blood: Secrets and Lies in a Silicon Valley Startup, by John Carreyrou, is hands-down one of the best business books I’ve ever read.  (It’s up there with Business Adventures, by John Brooks, and Shoe Dog, by Phil Knight.)  The book tells the story of the rise and fall of Theranos. 

In brief, here’s why it’s such a great book: Carreyrou was the investigative reporter who broke the Theranos story in 2015.  Carreyrou interviewed 150 people and withstood enormous pressure from the company’s charismatic CEO and her attorneys—led by one of the best and most feared lawyers in the country.  Other key whistle-blowers also withstood great pressure.  Many of the facts of the story are unbelievable.  And finally, Carreyrou does an outstanding job telling the story.

Theranos was a company founded by Stanford dropout Elizabeth Holmes when she was just 19 years old.  She claimed that she had invented a semi-portable device that could do every kind of blood test using only a tiny drop of blood obtained by a pin prick to the end of a finger.  Holmes declared that you could get the results in a few hours and at a much lower price than what other labs charged.

Had Theranos’s technology worked, it would have been revolutionary.  The only problem: it never came close to working.  There are different kinds of blood tests that require different laboratory instruments.  If you do one kind of blood test on a tiny sample, there isn’t enough blood left to do the other kinds of blood tests.

But Holmes believed in her vision so much, and she was such a charismatic and brilliant saleswoman, that she raised close to $1 billion dollars from investors.  This included $700 million in late 2013.  How?  See this CNN Business interview (Sept. 20, 2018): https://www.youtube.com/watch?v=BXfw-S62ISE

As Carreyrou explains to Julia Chatterley in the CNN Business interview: Holmes launched the purportedly innovative technology in Walgreens stores in California and Arizona.  In addition, when seeking investors, she focused on the family offices of billionaires while avoiding investors with any sophistication related to next-gen diagnostics.  When the less sophisticated investors learned that Theranos was giving blood tests in Walgreens stores, they assumed that its technology must be real.

Theranos offered 250 blood tests.  Unbeknownst to investors and to Theranos’s business partners—Walgreens and Safeway—240 of these tests were actually done on Siemens machines.  Theranos would collect tiny blood samples from finger pricks and then dilute them so that the Siemens machine could analyze them.  (This also required modifications to the Siemens machines that Theranos engineers had figured out.)

Only 10 of the 250 blood tests offered by Theranos were done on the company’s machine, the Edison.  Moreover, the Edison was shockingly unreliable.  Ultimately, a million blood tests done by Edison machines were voided.

Here is the outline for this blog post.  (The outline does not include the Prologue and the Epilogue, which I also touch on.)

  1. A Purposeful Life
  2. The Gluebot
  3. Apply Envy
  4. Goodbye East Paly
  5. The Childhood Neighbor
  6. Sunny
  7. Dr. J
  8. The miniLab
  9. The Wellness Play
  10. “Who is LTC Shoemaker?”
  11. Lighting a Fuisz
  12. Ian Gibbons
  13. Chiat/Day
  14. Going Live
  15. Unicorn
  16. The Grandson
  17. Fame
  18. The Hippocratic Oath
  19. The Tip
  20. The Ambush
  21. Trade Secrets
  22. La Mattanza
  23. Damage Control
  24. The Empress Has No Clothes



November 17, 2006. Henry Mosley, Theranos’s chief financial officer.  Good news from Tim Kemp: Elizabeth Holmes, the twenty-two year old founder, had shown off the company’s system to executives at Novartis, a European drug giant. She had told Kemp, “It was perfect!”

Carreyrou writes:

This was a pivotal moment for Theranos.  The three-year-old startup had progressed from an ambitious idea Holmes had dreamed up in her Stanford dorm room to an actual product a huge multinational corporation was interested in using.

Mosley was a veteran of Silicon Valley.  Carreyrou again:

What had drawn Mosley to Theranos was the talent and experience gathered around Elizabeth.  She might be young, but she was surrounded by an all-star cast.  The chairman of her board was Donald L. Lucas, the venture capitalist who had groomed billionaire software entrepreneur Larry Ellison and helped him take Oracle Corporation public in the mid-1980s. Lucas and Ellison had both put some of their own money into Theranos.

Another board member with a sterling reputation was Channing Robertson, the associate dean of Stanford’s School of Engineering. Robertson was one of the stars of the Stanford faculty… Based on the few interactions Mosley had had with him, it was clear Robertson thought the world of Elizabeth.

Carreyrou says that Theranos also had a strong management team, which impressed Mosley.  Furthermore, Mosley understood that the market Theranos was targeting was huge.Pharmaceutical companies spent tens of billions of dollars on clinical trials to test new drugs each year.  If Theranos could make itself indispensable to them and capture a fraction of that spending, it could make a killing.

Carreyrou notes that Elizabeth had asked Mosley for some financial projections, which he provided. Elizabeth asked him to revise the projections upward.  Mosley was a bit uncomfortable, but he knew it was a part of the game new tech startups played to attract VC money.

Something wasn’t right, though.  Although Elizabeth was enthusiastic about the presentation to Novartis, some of her colleagues seemed downcast.  With some digging, Mosley found out the problem from Shaunak, a fellow employee. Theranos’s blood-testing system was unreliable. This was the first Mosley heard about the issue.

Well, there was a reason it always seemed to work, Shaunak said.  The image on the computer screen showing the blood and settling into he little wells was real.  But you never knew whether you were going to get a result or not.  So they’d recorded a result from one of the times it worked. It was that recorded result that was displayed at the end of each demo.

Mosley was stunned.  He thought the result were extracted in real time from the blood inside the cartridge.  That was certainly what the investors he brought by were led to believe.  What Shaunak had just described sounded like a sham. It was OK to be optimistic and aspirational when you pitched investors, but there was a line not to cross.  And this, in Mosley’s view, crossed.

Later, Mosley politely raised the issue with Elizabeth.  Mosley said they couldn’t keep fooling investors.  Elizabeth’s expression immediately became hostile.  She told Mosley he wasn’t a team played and said he should leave immediately.  Elizabeth had fired him.



Elizabeth wanted to be an entrepreneur at a young age.  Carreyrou:

When she was seven, she set out to design a time machine and filled up a notebook with detailed engineering drawings.

When she was nine or ten, one of her relatives asked her at a family gathering the question every boy and girl is asked sooner or later: “What do you want to do when you grow up?”

Without skipping a beat, Elizabeth replied, “I want to be a billionaire.”

These weren’t the idle words of a child. Elizabeth uttered them with he utmost seriousness and determination, according to a family member who witnessed the scene.

Carreyrou explains that Elizabeth’s parents encouraged her ambition based on a distinguished family history.  She descended from Charles Louis Fleischmann on her father’s side.  Fleischmann was a Hungarian immigrant who created the Fleischmann Yeast Company, which was remarkably successful.  The Fleischmanns were one of the wealthiest families in America at the beginning of the twentieth century. 

Bettie Fleischmann, Charles’s daughter, married her father’s Danish physician, Dr. Christian Holmes. He was Elizabeth’s great-great-grandfather.

Aided by the political and business connections of his wife’s wealthy family, Dr. Holmes established Cincinnati General Hospital and the University of Cincinnati’s medical school.  So the case could be made—and it would in fact be made to the venture capitalists clustered on Sand Hill Road near the Stanford University campus—that Elizabeth didn’t just inherit entrepreneurial genes, but medical ones too.

Elizabeth’s mother, Noel, also had notable family background.  Noel’s father was a West Point graduate who became a high-ranking Pentagon official who oversaw the shift from draft-based military to an all-volunteer force in the early 1970s.  The Daoust line could be traced back to one of Napoleon’s top field generals.

Chris Holmes also made sure to teach his daughter about the failings of his father and grandfather. They had cycled through marriages and struggled with alcoholism while they squandered the family fortune. Elizabeth later explained that she learned about greatness, but also about what happens if you don’t have a high purpose—your character and qualify of life suffered.

When Elizabeth was a kid, she liked to play monopoly with her cousins and brother.  She was intensely competitive.  She got furious when she lost and at least a few times ran right through a screen on the front door of the condo owned by her aunt and uncle.

Elizabeth became a straight-A student in high school by working hard and sacrificing sleep.  Stanford was the natural choice for someone interested in computers and science who wanted to be an entrepreneur.  She was accepted to Stanford as a President’s Scholar in the spring of 2002.

Carreyrou explains how Elizabeth got interested in biotechnology:

Her father had drilled into her the notion that she should live a purposeful life.  During his career in public service, Chris Holmes had overseen humanitarian efforts like the 1980 Mariel boatlift, in which more than one hundred thousand Cubans and Haitians migrated to the United States.  There were pictures around the house of him provided disaster relief in war-torn countries.  The message Elizabeth took away from them is that if she wanted to truly leave her mark on the world, she would need to accomplish something that furthered the greater good, not just become rich.  Biotechnology offered the prospect of achieving both.  She chose to study chemical engineering, a field that provided a natural gateway to the industry.

Elizabeth took Introduction to Chemical Engineering from star faculty member Channing Robertson. She also convinced him to let her work in his lab.  She had a boyfriend for a time, but broke up telling him that she was starting a company and wouldn’t have any time to date.

After her freshman year, Elizabeth had a summer internship at the Genome Institute of Singapore.  Earlier that year (2003), severe acute respiratory syndrome (SARS) had hit Asia.  Elizabeth’s job was testing patient specimens gathered using low-tech methods like syringes. She thought there was a better way. Carreyrou:

When she got back home to Houston, she sat down at her computer for five straight days, sleeping one or two hours a night and eating from trays of food her mother brought her.  Drawing from new technologies she had learned about during her internship and in Robertson’s classes, she wrote a patent application for an arm patch that would simultaneously diagnose medical conditions and treat them.

Robertson was impressed, saying:

“She had somehow been able to take and synthesis these pieces of science and engineering and technology that I had never thought of.”

Robertson urged Elizabeth to follow her dream.  So she did: she launched a startup, tapping family connections to raise money.  By the end of 2006, she had raised almost $6 million. Her first employee was Shaunak Roy, who had a Ph.D. in chemical engineering.  Elizabeth had worked with Shaunak in Roberton’s lab.

Elizabeth and Shaunak dropped the patch idea and came up with a cartridge-and-reader system:

The patient would prick her finger to draw a small sample of blood and place it in a cartridge that looked like a thick credit card.  The cartridge would slot into a bigger machine called a reader.  Pumps inside the reader would push the blood through tiny channels in the cartridge and into little wells coated with proteins known as antibodies.  On its way to the wells, a filter would separate the blood’s solid elements, its red and white blood cells, from the plasma and let only the plasma through.  When the plasma came into contact with the antibodies, a chemical reaction would produce a signal that would be “read” by the reader and translated into a result.

Elizabeth envisioned placing the cartridges and readers in patient’s homes so that they could test their blood regularly.  A cellular antenna on the reader would send the test results to the computer of a patient’s doctor by way of a central server. This would allow the doctor to make adjustments to the patient’s medication quickly, rather than waiting for the patient to go get his blood tested at a blood-draw center or during his next office visit.

By late 2005, eighteen months after he’d come on board, Shaunak was beginning to feel like they were making progress.  The company had a prototype, dubbed the Theranos 1.0, and had grown to two dozen employees.  It also had a business model it hoped would quickly generate revenues: it planned to license its blood-testing technology to pharmaceutical companies to help them catch adverse drug reactions during clinical trials.



Edmund Ku was a talented engineer with a reputation for fixing tough problems.  When Ku interviewed with Elizabeth Holmes in early 2006, he felt inspired by her vision.

Elizabeth cited the fact that an estimated one hundred thousand Americans died each year from adverse drug reactions.  Theranos would eliminate all those deaths, she said. It would quite literally save lives.

Ed’s job would be to turn the Theranos 1.0 prototype into a product that could be commercialized.  It soon became clear to Ed that this would be the most difficult engineering challenge he had faced.  The main challenge was that Elizabeth required that they use only a drop of blood pricked from the end of a finger.

Her obsession with miniaturization extended to the cartridge. She wanted it to fit in the palm of a hand, further complicating Ed’s task.  He and his team spent months reengineering it, but they never reached a point where they could reliably reproduce the same test results from the same blood samples.

The quantity of blood they were allowed to work with was so small that it had to bediluted with a saline solution to create more volume.  That made what would otherwise have been relatively routine chemistry work a lot more challenging.

Adding another level of complexity, blood and saline weren’t the only fluids that had to flow through the cartridge.  The reactions that occurred when the blood reached the little wells required chemicals known as reagents.  Those were stored in separate chambers. 

All these fluids needed to flow through the cartridge in a meticulously choreographed sequence, so the cartridge contained little valves that opened and shut at precise intervals.  Ed and his engineers tinkered with the design and the timing of the valves and the speed at which the various fluids were pumped through the cartridge.

Another problem was preventing all those fluids from leaking and contaminating one another.

Meanwhile, having burned through its first $6 million, Theranos raised another $9 million.  A separate group of biochemists worked on the chemistry work. But Elizabeth kept the two groups from commuting with one another.  She preferred to be the only one who could seethe whole system.  This was far from ideal.  Ed couldn’t tell if problems they were trying to solve were caused by microfluidics, which was their focus, or chemistry, which the other group was responsible for.

One evening, Elizabeth told Ed that progress wasn’t fast enough.  She wanted the engineering department to run twenty-four hours a day.  Ed disagreed.

Ed noticed a quote cut out from an article sitting on Elizabeth’s desk.  It was from Channing Robertson:

“You start to realize you are looking in the eyes of another Bill Gates, or Steve Jobs.”


That was a high bar to set for herself, Ed thought. Then again, if there was anyone who could clear it, it might just be this young woman.  Ed had never encountered anyone as driven and relentless. She slept four hours a night and popped chocolate-coated coffee beans throughout the day to inject herself with caffeine.  He tried to tell her to get more sleep and to live a healthier lifestyle, but she brushed him off.

Around that time, Elizabeth was meeting regularly with the venture capitalist Don Lucas and also (less regularly) with Larry Ellison.  Lucas and Ellison had both invested in the recent Series B round that raised $9 million. Carreyrou comments:

Ellison might be one of the richest people in the world, with a net worth of some $25 billion, but he wasn’t necessarily the ideal role model.  In Oracle’s early years, he had famously exaggerated his database software’s capabilities and shipped versions of it crawling with bugs.  That’s not something you could do with a medical device.

Since Ed had refused to make his engineering group work 24/7, Elizabeth had cooled towards him.  Soon she had hired a rival engineering group. Ed’s group was put in competition with this new group.

Elizabeth had persuaded Pfizer to try the Theranos system in a pilot project in Tennessee.  The Theranos 1.0 devices would be put in people’s homes and they would test their blood every day.  Results would be sent wirelessly to the Theranos’s office in California, where they would be analyzed and then sent to Pfizer.  The bugs would have to be fixed before then.  Ed accompanied Elizabeth to Tennessee to start training doctors and patients on how to use the system.

When they got to Tennessee, the cartridges and the readers they’d brought weren’t functioning properly, so Ed had to spend the night disassembling and reassembling them on his bed in his hotel room.  He managed to get them working well enough by morning that they were able to draw blood samples from two patients and a half dozen doctors and nurses at a local oncology clinic.

The patients looked very sick.  Ed learned that they were dying of cancer.  They were taking drugs designed to slow the growth of their tumors, which might buy them a few more months to live.

Elizabeth declared the trip a success, but Ed thought it was too soon to use Theranos 1.0 in a patient study—especially on terminal cancer patients.


In August 2007, Elizabeth had everyone in the company gather.  Standing next to Elizabeth was Michael Esquivel, a lawyer.  Equivel announced that the company was suing three former employees—Michael O’Connell,Chris Todd, and John Howard—for stealing intellectual property.  Current employees were not to have any contact with these individuals.  And all documents and emails had to be preserved. Moreover, the FBI had been called for assistance.

O’Connell held a postdoctorate in nanotechnology from Stanford.  He thought he had solved the microfluidic problems of the Theranos system. O’Connell convinced Todd to form a company with him—Avidnostics.  O’Connell also spoke with Howard, who helped but decided not to join the company.

Elizabeth had always been very concerned about proprietary information getting out.  She required employees—as well as any who entered the Theranos office or did business withi t—to sign nondisclosure agreements.

Meanwhile, the engineering teams vied to be first to solve the problems with Theranos 1.0.  Tony Nugent,an Irishman, was the head of the team competing with Ed’s team.

Tony decided that part of the Theranos value proposition should be to automate all the steps that bench chemists followed when they tested blood in a laboratory.  In order to automate, Tony needed a robot.  But he didn’t want to waste time building one from scratch, so he ordered a three-thousand-dollar glue-dispensing robot from a company in New Jersey called Fisnar.  It became the heart of the new Theranos system.

Soon Tony and team had built a smaller version of the robot that fit inside an aluminum box slightly smaller than a desktop computer tower.  Eventually they got the robot to follow the same steps a human chemist would.

First, it grabbed one of the two pipette tips and used it to aspirate the blood and mix it with diluents contained in the cartridge’s other tubes.  Then it grabbed the other pipette tip and aspirated the diluted blood with it. This second tip was coated with antibodies, which attached themselves to the molecule of interest, creating a microscopic sandwich.

Therobot’s last step was to aspirate reagents from yet another tube in the cartridge.  When the reagents came into contact with the microscopic sandwiches, a chemical reaction occurred that emitted a light signal.  An instrument inside the reader called a photomultiplier tube then translated the light signal into an electric current.

The molecule’s concentration in the blood—what the test sought to measure—could be inferred from the power of the electrical current, which was proportional to the intensity of the light.

This blood-testing technique was known as chemiluminescent immunoassay.  (In laboratory speak, the word “assay” is synonymous with “blood test.”)  The technique was not new: it had been pioneered in the early 1980s by a professor at Cardiff University.  But Tony had automated it inside a machine that, though bigger than the toaster-size Theranos 1.0, was still small enough to make Elizabeth’s vision of placing it in patients’ homes possible.  And it only required about 50 microliters of blood.  That was more than 10 microliters Elizabeth initially insisted upon, but it still amounted to just a drop.

Once they had a functioning prototype—it worked much better than the system Ed was working on—Elizabeth suggested they call it the Edison (since everything else had failed). Elizabeth decided to use the Edison instead of the microfluidic system.  Carreyrou points out the irony of this decision, given that the company had just filed a lawsuit to protect the intellectual property associated with the microfluidic system.  Soon thereafter, Ed and his team were let go.

Carreyrou continues:

Shaunak followed Ed out the door two weeks later, albeit on friendlier terms.  The Edison was at its core a converted glue robot and that was a pretty big step down from the lofty vision Elizebeth had originally sold him on.  He was also unsettled by the constant stuff turnover and the lawsuit hysteria.

Although Elizabeth was excited about the Edison, it was a long way from a finished product.



Elizabeth worshipped Steve Jobs and Apple.  In the summer of 2007, she started recruiting employees of Apple.  Ana Arriola, a product designer who worked on the iPhone, was one such recruit.

…Elizabeth told Ana she envisioned building a disease map of each person through Theranos’s blood tests.  The company would then be able to reverse engineer illnesses like cancer with mathematical models that would crunch the blood data and predict the evolution of tumors.

Ana and (later) her wife Corrine were impressed enough that Ana decided to leave behind fifteen thousand Apple shares.  She was hired as Theranos’s chief design officer.  Elizabeth wanted a software touchscreen like the iPhone’s for the Edison.  And she wanted a sleek outer case.

Since fans like Channing Robertson and Don Lucas were starting to compare Elizabeth to Steve Jobs, Ana thought she should look the part.  Soon Elizabeth was wearing a black turtleneck and black slacks most of the time.

Elizebeth’s idealism seemed like a good thing.  But there continued to be other aspects of working at Theranos that seemed stifling (to say the least).  Different groups were prevented from sharing information and working together. Moreover, employees knew they were being spied on—including what they did on their computer and what they did on Facebook. 

Also, one of Elizabeth’s assistants kept track of how many hours each employee worked.  Elizabeth had dinner catered—it arrived at 8 or 8:30 each night—in order to encourage people to put in more hours.

Finally, people were constantly getting fired from Theranos.

One person Elizabeth recruited to Theranos was Avie Tevanian.  Avie was one of Steve Job’s closest friends.  Avie had worked with Jobs and NeXT,and then went with Jobs to Apple in 1997. Avie was the head of software engineering.  After an arduous decade, Avie retired.  Elizabeth convinced Avie to join the Theranos board.  Avie invested $1.5 million into the company in the 2006 offering.

The first couple of board meetings Avie attended had been relatively uneventful, but, by the third one, he’d begun to notice a pattern.  Elizabeth would present increasingly rosy projections based on the deals she said Theranos was negotiating with pharmaceutical companies, but the revenues wouldn’t materialize.  It didn’t help that Henry Mosley, the chief financial officer, had been fired soon after Avie became a director.  At the last board meeting he’d attended, Avie had asked more pointed questions about the pharmaceutical deals and been told they were held up in legal review.  When he’d asked to see the contracts, Elizabeth had said she didn’t have any copies readily available.

There were also repeated delays with the product’s rollout and the explanation for what needed to be fixed kept changing. Avie didn’t pretend to understand the science of blood-testing; his expertise was software.  But if the Theranos system was in the final stages of fine-tuning as he’d been told, how could a completely different technical issue be the new holdup every quarter?  That didn’t sound to him like a product that was on the cusp of commercialization.

Avie started asking more questions at the board meetings.  Soon thereafter, Don Lucas contacted Avie and informed him that Elizabeth was upset with his behavior and wanted him to leave the board.  Avie was surprised because he was just doing his duty as a board member.  Avie decided to look at all the material he’d been given over the previous year, including investment material. 

As he read them over, he realized that everything about the company had changed in the space of a year, including Elizabeth’s entire executive team.  Don needed to see these, he thought.

Ana Arriola was also growing concerned.  One morning, Ana brought up a question to Elizabeth.  Given that the technology wasn’t working, why not pause the Tennessee study in order to fix the bugs first?  They could also restart the study later once the product was functional.  Elizabeth replied that Pfizer and every other big pharma company wanted her blood-testing system and Theranos was going to be a great company.  Then Elizabeth suggested to Ana that she might be happier elsewhere. 

Ana knew it wasn’t right to use an unreliable blood-test system in the Tennessee study.  Later that same day, she resigned.

When Avie showed the material he’d gathered to Don, Don suggested to Avie that he resign.  Avie was surprised that Don didn’t seem interested in the material.  But Avie realized that he’d retired from Apple for good reason (to spend more time with his family).  He didn’t need extra aggravation.  So he told Don he would resign.

Don then brought up one more thing to Avie.  Shaunak Roy was leaving and was selling his shares to Elizabeth.  She needed the board to waive the company’s rights to repurchase the stock.  Avie didn’t think that was a good idea.  Don then said he wanted Avie to waive his own right as a board member to purchase the stock.

Avie was starting to get upset.  He told Don to have Theranos’s general, Michael Esquivel, to send him the information. After reading it, Avie thought it was clear that he could be some of the stock.  Avie decided to do so and informed Esquivel.  That prompted an argument.

At 11:17 p.m. on Christmas Eve, Esquivel sent Avie an email accusing him of acting in “bad faith” and warned him that Theranos was giving serious consideration to suing him for breach of his fiduciary duties as a board member and for public disparagement of the company.

Avie was astonished.  Not only had he done no such things, in all his years in Silicon Valley he had never come close to being threatened with a lawsuit.  All over the Valley, he was known as a nice guy.  A teddy bear.  He didn’t have any enemies.  What was going on here? 

Avie spoke with a friend who was a lawyer, who asked Avie if, given what he now knew, he really wanted to buy more shares in the company.  No, thought Avie.  But he did write a parting letter to Don summarizing his concerns.  The letter concluded:

“I do hope you will fully inform the rest of the Board as to what happened here.  They deserve to know that by not going along 100% ‘with the program’ they risk retribution from the Company/Elizabeth.”



In early 2008, Theranos moved to a new location on Hillview Avenue in Palo Alto.  It was a drastic improvement over their previous location in East Palo Alto.  That area—east of Highway 101 (Bayshore Freeway)—was much poorer and had once been the country’s murder capital.

Matt Bissel, head of IT, was in charge of the move.  At 4 o’clock in the afternoon the day before the movers were scheduled to come, Matt was pulled into a conference room.  Elizabeth was on the line from Switzerland.  She told Matt she’d just learned that Theranos would be charged an extra month’s rent if they waited until tomorrow.  She told Matt to call the moving company immediately to see if they could do it.  No way. But Elizabeth kept pushing. Someone pointed out that the blood samples wouldn’t be kept at the right temperature if they were moved immediately. Elizabeth said they could put them in refrigerated trucks.

Finally, Matt got Elizabeth to slow down after pointing out that they would still have to do an inspection with state officials to prove that they had properly disposed of any hazardous materials.  That meant no new tenant could move in until then.

Matt greatly admired Elizabeth as one of the smartest people he’d ever met, and as an energizing leader. But he was starting to grow worried about some aspects of the company.

One aspect of Matt’s job had become increasingly distasteful to him.  Elizabeth demanded absolute loyalty from her employees and if she sensed that she no longer had it from someone, she could turn on them in a flash.  In Matt’s two and a half years at Theranos, he had seen her fire some thirty people, not counting the twenty or so employees who lost their jobs at the same time as Ed Ku when the microfluidic platform was abandoned.

Every time Elizabeth fired someone, Matt had to assist with terminating the employee…In some instances, she asked him to build a dossier on the person that she could use for leverage.

Matt was bothered in particular about how John Howard was treated.

When Matt reviewed all the evidence assembled for the Michael O’Connell lawsuit, he didn’t see anything proving that Howard had done anything wrong.  He’d had contact with O’Connell but he’d declined to join his company.  Yet Elizabeth insisted on connecting the dots in a certain way and suing him too, even though Howard been one of the first people to help her when she dropped out of Stanford, letting her use the basement of his house in Saratoga for experiments in the company’s early days.

Matt decided it was a good time to launch his own IT company.  When he informed Elizabeth, she couldn’t believe it.  She offered him a raise and a promotion, but he turned her down. Then she grew very cold.  She offered one of Matt’s colleagues, Ed Ruiz, Matt’s position if he would look through Matt’s filed and emails.  Ed was good friends with Matt and refused. (There was nothing to find anyway.) A few months after Matt left, Ed decided to work for Matt’s new company.

Meanwhile, Aaron Moore and Mike Bauerly wanted to test two ofthe Edison prototypes built by Tony Nugent and Dave Nelson.  This was informal “human factors” research to see how people reacted.

Aaron took photos with his digital camera to document what they were doing.  The Eve Behar cases weren’t ready yet, so the devices had a primitive look.  Their temporary cases were made from gray aluminum plates bolted together.  The front plate tilted upward like a cat door to let the cartridge in.  A rudimentary software interface sat atop the cat door at an angle.  Inside, the robotic arm made loud, grinding sounds.  Sometimes, it would crash against the cartridge and the pipette tips would snap off.  The overall impression was that of an eighth-grade science project.

Aaron and Mike visited their friends’ offices to do the tests.

As the day progressed, it became apparent that one pinprick often wasn’t enough to get the job done.  Transferring the blood to the cartridge wasn’t the easiest of procedures. The person had to swab his finger with alcohol, prick it with the lancet, apply the transfer pen to the blood that bubbled up from the finger to aspirate it, and then press on the transfer pen’s plunger to expel the blood into the cartridge.  Few people got it right on their first try.  Aaron and Mike kept having to ask their test subjects to prick themselves multiple times.  It got messy. There was blood everywhere.

This confirmed Aaron was worried about: A fifty-five-year-old patient in his or her home was going to have trouble.  Aaron passed on his concerns to Tony and Elizabeth, but they didn’t think it was important.  Aaron was getting disillusioned.

A bit later, Todd Surdey was hired to run sales and marketing.  One of Todd’s two subordinates was on the East Coast: Susan DGiaimo.  Susan had accompanied Elizabeth on quite a few sales pitches to drug makers.  Susan had been uncomfortable about Elizabeth’s very lofty promises.

Todd asked Susan about Elizabeth’s revenue projections.  Susan replied that they were vastly overinflated.

Moreover, no significant revenues would materialize unless Theranos proved to each partner that its blood system worked.  To that effect, each deal provided for an initial tryout, a so-called validation phase…

The 2007 study in Tennessee was the validation phase of the Pfizer contract.  Its objective was to prove that Theranos could help Pfizer gauge cancer patients’ response to drugs by measuring the blood concentration of three proteins the body produces in excess when tumors grow.  If Theranos failed to establish any correlation between the patients’ protein levels and the drugs, Pfizer could end their partnership and any revenue forecast Elizabeth had extrapolated from the deal would turn out to be fiction.

Susan also shared with Todd that she had never seen any validation data.  And when she went on demonstrations with Elizabeth, the devices often malfunctioned. A case in point was the one they’d just conducted at Novartis.  After the first Novartis demo in late 2006 during which Tim Kemp had beamed a fabricated result from California to Switzerland, Elizabeth had continued to court the drug maker and had arranged a second visit to its headquarters in January 2008.

The night before that second meeting, Susan and Elizabeth had pricked their fingers for two hours in a hotel in Zurich to try to establish some consistency in the test results they were getting, to no avail. When they showed up at Novartis’s Basel offices the next morning, it got worse: all three Edison readers produced error messages in front of a room full of Swiss executives.  Susan was mortified, but Elizabeth kept her composure and blamed a minor technical glitch.

Based on the intel he was getting from Susan and from other employees in Palo Alto, Todd became convinced that Theranos’s board was being misled about the company’s finances and the state of its technology.

Todd brought his concerns to Michael Esquivel, the company’s general counsel.  Michael had been harboring his own suspicions.  In March 2008, Todd and Michael approached Tom Brodeen, a Theranos board member.  Since he was relatively new, he said they should raise their concerns with Don Lucas, the board’s chairman.  So they did.

This time, Don Lucas had to take the matter seriously.

Lucas convened an emergency meeting of the board in his office on Sand HillRoad.  Elizabeth was asked to wait outside the door while the other directors—Lucas, Brodeen, Channing Robertson, and Peter Thomas, the founder of an early stage venture capital firm called ATAventures—conferred inside.

After some discussion, the four men reached a consensus: they would remove Elizabeth as CEO.  She had proven herself to young and inexperienced for the job.  Tom Brodeen would step in to lead the company for a temporary period until a more permanent replacement could be found. They called in Elizabeth to confront her with what they had learned and inform her of their decision.

But then something extraordinary happened.

Over the course of the next two hours, Elizabeth convinced them to change their minds.  She told them she recognized there were issues with her management and promised to change.  She would be more transparent and responsive going forward.  It wouldn’t happen again.

A few weeks later, Elizabeth fired Todd and Michael.  Soon thereafter, Justin Maxwell, a friend of Aaron and Mike’s, decided to resign.  His resignation email included this:

believe in the people who disagree with you… Lying is a disgusting habit, and it flows through the conversations here like its our own currency.  The cultural disease here is what we should be curing… I mean no ill will towards you, since you believe in what I was doing and hoped I would succeed at Theranos.

A few months later, Aaron Moore and Mike Bauerly resigned.



Richard Fuisz was a medical inventor and entrepreneur.  He was following what Elizabeth was doing at Theranos.  The Fuisz and Holmes families had been friends for two decades.

Elizabeth’s mother, Noel, and Richard’s wife, Lorraine had developed a close friendship.  But the husbands weren’t as close.  This may have been because Chris Holmes was on a government salary, while Richard Fuisz was a successful businessman who liked to flaunt it.

Money was indeed a sore point in the Holmes household.  Chris’s grandfather, Christian Holmes II, had depleted his share of the Fleischmann fortune by living a lavish and hedonistic lifestyle on an island in Hawaii, and Chris’s father, Christian III, had frittered away what was left during an unsuccessful career in the oil business.

Carreyrou later explains:

Richard Fuisz was a vain and prideful man.  The thought that the daughter of longtime friends and former neighbors would launch a company in his area of expertise and that they wouldn’t ask for his help or even consult him deeply offended him. 

Carreyrou again:

Fuisz had a history of taking slights personally and bearing grudges.  The lengths he was willing to go to get even with people he perceived to have crossed him is best illustrated by his long and protracted feud with Vernon Loucks, the CEO of hospital supplies maker Baxter International.

Fuisz traveled frequently to the Middle East in the 1970s and early 1980s because it was the biggest market for his medical film business, Medcom.  On one of these trips, he ran into Loucks.  Over dinner, Loucks offered to buy Medcom for $53 million.  Fuisz agreed. 

Fuisz was supposed to be head of the new Baxter subsidiary for three years, but Loucks dismissed him after the acquisition closed.  Fuisz sued Baxter for wrongful termination,asserting that Loucks fired him for refusing to pay a $2.2 million bribe to a Saudi firm to remove Baxter from an Arab blacklist of companies doing business with Israel.  Carreyrou:

The two sides reached a  1986, under which Baxter agreed to pay Fuisz $800,000.  That wasn’t the end of it, however.  When Fuisz flew to Baxter’s Deerfield, Illinois, headquarters to sign the settlement, Loucks refused to shake his hand, angering Fuisz and putting him back on the warpath.

In 1989, Baxter was taken off the Arab boycott list, giving Fuisz an opening to seek his revenge.  He was leading a double life as an undercover CIA agent by then, having volunteered his services to the agency a few years earlier after coming across one of its ads in the classified pages of the Washington Post.

Fuisz’s work for the CIA involved setting up dummy corporations throughout the Middle East that employed agency assets, giving them a non-embassy cover to operate outside the scrutiny of local intelligence services.  One of the companies supplied oil-rig operators to the national oil company of Syria,where he was particularly well-connected.

Fuisz suspected Baxter had gotten itself back in Arab countries’ good graces through chicanery and set out to prove it using his Syrian connections. He sent a female operative he’d recruited to obtain a memorandum kept on file in the offices of the Arab League committee in Damascus that was in charge of enforcing the boycott.  It showed that Baxter had provided the committee detailed documentation about its recent sale of an Israeli plant and promised it wouldn’t make new investments in Israel or sell the country new technologies.  This put Baxter in violation of a U.S. anti-boycott law, enacted in 1977, that forbade American companies from participating in any foreign boycott or supplying blacklist officials any information that demonstrated cooperation with the boycott.

Fuisz sent a copy of the memo to Baxter’s board of directors and another copy to the Wall Street Journal.  The Journal published a front-page story.  Fuisz then was able to get copies of letters Baxter’s general counsel had written to a general in the Syrian army.  These letters confirmed the memo.

The revelations led the Justice Department to open an investigation.  In March 1993, Baxter was forced to plead guilty to a felony charge of violating the anti-boycott law and to pay $6.6 million in civil and criminal fines.  The company was suspended from new federal contracts for four months and barred from doing business in Syria and Saudi Arabia for two years.  The reputational damage also cost it a $50 million contract with a big hospital group.

Fuisz was upset, however, that Loucks still remained CEO.  So he came up with another attack.  Loucks was a Yale alumnus and served as trustee of Yale Corporation, the university’s governing body.  He also chaired the university’s fund-raising campaign.  Commencement ceremonies were coming up that May.

Through his son Joe, who had graduated from Yale the year before, Fuisz got in touch with a student named Ben Gordon, who was the president of Yale Friends of Israel association.  Together, they organized a graduation day protest featuring “Loucks Is Bad for Yale” signs and leaflets.  The crowning flourish was a turboprop plane Fuisz hired to fly over the campus trailing a banner that read, “Resign Loucks.”

Three months later, Loucks stepped down as Yale trustee.

All of that said, Fuisz’s initial interest in Theranos’s technology came more from opportunism than any desire for revenge.  Fuisz had made quite a bit of money by patenting inventions he thought other companies would want at some point.  Carreyrou:

One of his most lucrative plays involved repurposing a cotton candy spinner to turn drugs into fast-dissolving capsules.  The idea came to him when he took his daughter to a country fair in Pennsylvania in the early 1990s.  He later sold the public corporation he formed to house the technology to a Canadian pharmaceutical company for $154 million and personally pocketed $30 million from the deal.

Fuisz listened to an interview Elizabeth did for NPR’s “Biotech Nation,” in May 2005.  In that interview, Elizabeth explained how her blood-test system could be used for at-home monitoring of adverse reactions to drugs.

…But as a trained physician, he also spotted a potential weakness he could exploit.  If patients were going to test their blood at home with the Theranos device to monitor how they were tolerating the drugs they were taking, there needed to be a built-in mechanism that would alert their doctors when the results came back abnormal.

He saw a chance to patent that missing element, figuring there was money to be made down the road, whether from Theranos or someone else.  His thirty-five years of experience patenting medical inventions told him such a patent might eventually command up to $4 million for an exclusive license.

Fuisz filed a fourteen-page patent application with he U.S. Patent and Trademark office on April 24, 2006. It didn’t claim to invent new technology, but to combine existing technologies—wireless data transmission, computer chips, and bar codes—into a physician alert mechanism that could be part of at-home blood-testing devices.  The application said clearly that it was  targeting the company Theranos.

Meanwhile, for other reasons, the Fuisz and Holmes families grew apart.  By the time Elizabeth became aware of Richard Fuisz’s patent, the two families were no longer on speaking terms.



Chelsea Burkett and Elizabeth had been friends at Stanford.  Elizabeth recruited Chelsea to Theranos.  Chelsea found Elizabeth to be very persuasive:

She had this intense way of looking at you while she spoke that made you believe in her and want to follow her.

About the same time Chelsea joined Theranos, Ramesh “Sunny” Balwani came on board as a senior Theranos executive.  All that Chelsea knew was that Sunny was Elizabeth’s boyfriend and that they were living together in a Palo Alto apartment.  Sunny immediately asserted himself and seemed omnipresent.

Sunny was a force of nature, and not in a good way.  Though only about five foot five and portly, he made up for his diminutive stature with an aggressive, in-your-face management style.  His thick eyebrows and almost-shaped eyes, set above a mouth that drooped at the edges and a square chin, projected an air of menace.  He was haughty and demeaning towards employees, barking orders and dressing people down.

Chelsea took an immediate dislike to him even though he made an effort to be nicer to her in deference to her friendship with Elizabeth.  She didn’t understand what her friend saw in this man, who was nearly two decades older than she was and lacking in the most basic grace and manners.  All her instincts told her Sunny was bad news, but Elizabeth seemed to have the utmost confidence in him.

Elizabeth and Sunny had met in Beijing when Elizabeth was in her third year of a Stanford program that taught students Mandarin.  Apparently, Elizabeth had been bullied by some of the students and Sunny came to her defense.

Sunny was born and raised in Pakistan.  He pursued his undergraduate studies in the U.S.  Then he worked for a decade as a software engineer for Lotus and Microsoft.  In 1999, Sunny joined CommerceBid.com, which was developing software that would have suppliers bid against one another in an auction.  The goal was to achieve economies of scale and lower prices.

In November 1999, a few months after Sunny joined CommerceBid as president and chief technology officer, the company was acquired for $232 million in cash and stock.  Carreyrou:

It was a breathtaking price for a company that had just three clients testing its software and barely any revenues.  As the company’s second-highest-ranking executive, Sunny pocketed more than $40 million.  His timing was perfect.  Five months later, the dot-com bubble popped and the stock market came crashing down. Commerce One [the company that acquired CommerceBid] eventually filed for bankruptcy.

Yet Sunny didn’t see himself as lucky.  In his mind, he was a gifted businessman and the Commerce One windfall was a validation of his talent.  When Elizabeth met him a few years later, she had no reason to question that.  She was an impressionable eighteen-year-old girl who saw in Sunny what she wanted to become: a successful and wealthy entrepreneur.  He became her mentor, the person who would teach her about business in Silicon Valley.

In 2004, the IRS forced Sunny to pay millions in back taxes after he had tried to use a tax shelter. Sunny liked to flaunt his wealth. He drove a black Lamborghini Gallardo and a black Porsche 911.  Carreyrou writes:

He wore white designer shirts with puffy sleaves, acid-washed jeans, and blue Gucci loafers.  His shirts’ top three buttons were always undone, causing his chest hair to spill out and revealing a thin gold chain around his neck.  A pungent scent of cologne emanated from his at all times.  Combined with the flashy cars, the overall impression was of someone heading out to a nightclub rather than to the office.

Sunny was supposed to be an expert in software.  He even bragged that he’d written a million lines of code.  Some employees thought that was an absurd claim.  (Microsoft software engineers had written the Windows operating system at a rate of one thousand lines of code per year, notes Carreyrou.)

Carreyrou adds:

There was also the murky question of what she told the board about their relationship.  When Elizabeth informed Tony that Sunny was joining the company, Tony asked her point-blank whether they were still a couple.  She responded that the relationship was over.  Going forward, it was strictly business, she said. But that would prove not to be true.

Carreyrou continues:

When Elizabeth pitched pharmaceutical executives now, she told them that Theranos would forecast how patients would react to the drugs they were taking.  Patients’ test results would be input into a proprietary computer program the company had developed.  As more results got fed into the program, its ability to predict how markers in the blood were likely to change during treatment would become better and better, she said.

It sounded cutting-edge, but there was a catch: the blood-test results had to be reliable for the computer program’s predictions to have any value… Theranos was supposed to help Centocor [in Antwerp, Belgium] to assess how patients were responding to an asthma drug by measuring a biomarker in their blood called allergen-specific immunoglobulin E, or IgE, but the Theranos devices seemed very buggy to Chelsea.  There were frequent mechanical failures.  The cartridges either wouldn’t slot into the readers properly or something inside the readers would malfunction.  Even when the devices didn’t break down, it could be a challenge coaxing any kind of output from them.

Sunny always blamed the wireless connection.  That was true sometimes, but here were other things that could interfere.  Nearly all blood tests require some dilution, but too much dilution made it harder for Theranos to get accurate results.

The amount of dilution the Theranos system required was greater than usual because of the small size of the blood samples Elizabeth insisted on.

Furthermore, to function properly, the Edisons required the ambient temperature to be exactly 34 degrees Celsius. Two 11-volt heaters built into the reader tried to maintain that temperature during a blood test.  But in colder settings, including some hospitals in Europe, the temperature couldn’t be maintained.

Meanwhile, Pfizer had ended its collaboration with Theranos because it was not impressed by the results of the Tennessee validation study.

The study had failed to show any clear link between drops in the patients’ protein levels and the administration of the antitumor drugs.  And the report had copped to some of the same snafus Chelsea was now witnessing in Belgium, such as mechanical failures and wireless transmission errors.

When Chelsea returned from her three-week trip to Europe, she found that Elizabeth and Sunny were now focused on Mexico, where a swine flu epidemic had been raging.  Seth Michelson, Theranos’ chief scientific officer, had suggested an idea to Elizabeth.

Seth had told Elizabeth about a math model called SEIR (Susceptible, Exposed, Infected, and Resolved) that he thought could be adapted to predict where the swine flu virus would spread next.  For it to work, Theranos would need to test recently infected patients and input their blood-test results into the model.  That meant getting the Edison readers and cartridges to Mexico. Elizabeth envisioned putting them in the beds of pickup trucks and driving them to the Mexican villages on the front lines of the outbreak.

Because Chelsea was fluent in Spanish, she and Sunny were sent.  Elizabeth used her family connections in order to get authorization to use the experimental medical device in Mexico.

Once again, things did not go smoothly.  Frequently, the readers flashed error messages, or the result that came back from Palo Alto was negative for the virus when it should have been positive.  Some of the readers didn’t work at all.  And Sunny continued to blame the wireless transmission.

Chelsea grew frustrated and miserable.  She questioned what she was even doing there.  Gary Frenzel and some of the other Theranos scientists had told her that the best way to diagnose H1N1, as the swine flu virus was called, was with a nasal swab and that testing for it in blood was a questionable utility.  She’d raised this point with Elizabeth before leaving, but Elizabeth had brushed it off. “Don’t listen to them,” she’d said of the scientists.  “They’re always complaining.”

At the time, Theranos was struggling financially:

The $15 million Theranos had raised in its first two funding rounds was long gone and the company had already burned through the $32 million Henry Mosley had been instrumental in bringing in during its Series C round in late 2006.  The company was being kept afloat by a loan Sunny had personally guaranteed.

Meanwhile, Sunny was also traveling to Thailand to set up another swine flu testing outpost.  The epidemic had spread to Asia, and the country was one of the region’s hardest hit with tens  of cases and more than two hundred deaths.  But unlike in Mexico, it wasn’t clear that Theranos’s activities in Thailand were sanctioned by local authorities.  Rumors were circulating among employees that Sunny’s connections there were shady and that he was paying bribes to obtain blood samples from infected patients. When a colleague of Chelsea’s in the client solutions group named Stefan Hristu quit immediately upon returning from a trip to Thailand with Sunny in January 2010, many took it to mean the rumors were true.

On the whole, Sunny had created a culture of fear with his bullying behavior.  The high rate of firings continued, and Sunny had taken charge of it.  Remaining employees started to say, “Sunny disappeared him” whenever Sunny fired someone.

The scientists, especially, were afraid of Sunny. One of the only ones who stood up to him was Seth Michelson.  A few days before Christmas, Seth had gone out and purchased polo shirts for his group. Their color matched the green of the company logo and they had the words “Theranos Biomath” emblazoned on them. Seth thought it was a nice team-building gesture and paid for it out of his own pocket.

When Sunny saw the polos, he got angry.  He didn’t like that he hasn’t been consulted and he argued that Seth’s gift to his team made the other managers look bad. Earlier in his career, Seth had worked at Roche, the big Swiss drug maker, where he’d been in charge of seventy people and an annual budget of $25 million.  He decided he wasn’t going to let Sunny lecture him about management. He pushed back and they got into a yelling match.

Soon thereafter, Seth found another job at Genomic Health in Redwood City.  When he went to give his resignation letter to Elizabeth, Sunny was there.  He read the letter and threw it in Seth’s face, shouting, “I won’t accept this!”

Seth shouted back: “I have news for you, sir: in 1863, President Lincoln freed the slaves!”

Sunny’s response was to throw him out of the building. It was weeks before Seth was able to retrieve his math books, scientific journals, and the pictures of his wife on his desk.  He had to enlist the company’s new lawyer, Jodi Sutton, and a security guard to help him pack his things late on a weeknight when Sunny wasn’t around.

Sunny also got into a yelling match with Tony Nugent.  Chelsea attempted to get through to Elizabeth about Sunny, but she was unable to.

Chelsea wanted to quit, but still wasn’t sure.  Then one day the Stanford student with the family connections to Mexico stopped with his father, who was dealing with a cancer scare of some sort.   Elizabeth and Sunny persuaded him to allow Theranos to test his blood for cancer biomarkers.

Chelsea was appalled.  The validation study in Belgium and the experiments in Mexico and Thailand were one thing.  Those were supposed to be for research purposes only and to have no bearing on the way patients were treated.  But by encouraging someone to rely on a Theranos blood test to make an important medical decision was something else altogether.  Chelsea found it reckless and irresponsible.

She became further alarmed when not long afterward Sunny and Elizabeth began circulating copies of the requisition forms doctors used to order blood tests from laboratories and speaking excitedly about the great opportunities that layin consumer testing.

I’m done, Chelsea thought to herself.  This has crossed too many lines.


Chelsea also worried about Elizabeth.  In her relentless drive to be a successful startup founder, she had built a bubble around herself that was cutting her off from reality.  And the only person she was letting inside was a terrible influence.  How could her friend not see that?



Dr. J was Jay Rosen’s nickname.  Rosen is a doctor who is a member of Walgreen’s innovation team, whose goal is to find ideas and technologies that could create growth.

In January 2010, Theranos approached Walgreen’s with an email stating that it had developed small devices capable of running any blood test from a few drops pricked from a finger in real time and for less than half the cost of traditional laboratories.  Two months later, Elizabeth and Sunny traveled to Walgreen’s headquarters in the Chicago suburb of Deerfield, Illinois, and gave a presentation to a group of Walgreen executives.  Dr. J, who flew up from Pennsylvania for the meeting, instantly recognized the potential for the Theranos technology.  Bringing the startup’s machines inside Walgreens stores could open up a big new revenue stream for the retailer and be the game changer it had been looking for, he believed.

…The picture Elizabeth presented at the meeting of making blood tests less painful and more widely available so they could become an early warning system against disease deeply resonated with him.

On August 24, 2010, a Walgreens delegation arrived at the Theranos office in Palo Alto for a two-day meeting.  Kevin Hunter was the leader of a small lab consulting firm Colaborate.  Walgreens had hired him to evaluate and launch a partnership it was setting up with the startup.  Hunter’s father, grandfather, and great-grandfather had all been pharmacists.

Walgreens and Theranos had signed a preliminary contract.  Walgreens would prepurchase up to $50 million worth of Theranos cartridges and loan the startup $25 million.  If the pilot went well, the companies would expand their partnership nationwide.

Hunter asked to see the lab, but Elizabeth said later if there was time.  Hunter asked again.  Elizabeth pulled Dr. J aside.  Then Dr. J informed Hunter that they wouldn’t see the lab yet.

Theranos had told Walgreens it had a commercially ready laboratory and had provided it with a list of 192 different blood tests it said its proprietary devices could handle.  In reality, although there was a lab downstairs, it was just an R&D lab where Gary Frenzel and his team of biochemists conducted their research. Moreover, half of the tests on the list couldn’t be performed as chemiluminescent immunoassays, the testing technique the Edison system relied on.  These required different testing methods beyond the Edison’s scope.

Carreyrou writes:

Hunter was beginning to grow suspicious.  With her black turtleneck, her deep voice, and the green kale shakes she sipped on all day, Elizabeth was going to great lengths to emulate Steve Jobs, but she didn’t seem to have a solid understanding of what distinguished different types of blood tests.  Theranos had also failed to deliver on his two basic requests: to let him see its lab and to demonstrate a live vitamin D test on its device. Hunter’s plan had been to have Theranos test his and Dr. J’s blood, then get retested at Stanford Hospital that evening and compare results.  He’d even arranged for a pathologist to be on standby at the hospital to write the order and draw their blood.  But Elizabeth claimed she’d been given too little notice even though he’d made the request two weeks ago.

Despite Hunter’s suspicions, Dr. J and the Walgreens CFO, Wade Miquelon, continued to be big fans of Elizabeth.

In September 2010, Elizabeth and Sunny met with Walgreens executives at the company’s headquarters in Deerfield.  Elizabeth and Sunny suggested they do blood tests on the executives.  Hunter wasn’t at the meeting, but he heard about the blood tests later.  He thought it was a good opportunity to see how the technology performed.

Hunter asked about the blood-test results a few days later on the weekly video conference call the companies were using as their primary mode of communication.  Elizabeth responded that Theranos could only release the results to a doctor.  Dr J…reminded everyone that he was a trained physician, so why didn’t Theranos go ahead and send him the results?  They agreed that Sunny would follow up separately with him.

A month passed and still no results.

There was another issue, too. Theranos had suddenly changed its regulatory strategy.  Initially Theranos said the blood tests would qualify as “waived” under the Clinical Laboratory Improvement Amendments, a 1988 federal law that covered laboratories.

CLIA-waved tests usually involved simply laboratory procedures that the Food and Drug Administration had cleared for home use.

Now, Theranos was changing its tune and saying the tests it would be offering in Walgreens stores were “laboratory-developed tests.”  It was a big difference: laboratory-developed tests lay in a gray zone between the FDA and another federal health regulator,the Centers for Medicare and Medicaid Services. CMS, as the latter agency was known, exercised oversight of clinical laboratories under CLIA, while the FDA regulated the diagnostic equipment that laboratories bought and used for their testing. But no one closely regulated tests that labs fashioned with their own methods.  Elizabeth and Sunny had a testy exchange with Hunter over the significance of the change.  They maintained that all the big laboratory companies mostly used laboratory-developed tests, which Hunter knew not to be true.

Hunter argued that it was now even more important to make sure Theranos’s tests were accurate.  He suggested a fifty-patient study, which he could easily arrange.  Hunter noticed that Elizabeth became defense immediately.  She said they didn’t want to do it “at this time,” and she quickly changed the subject.

After they hung up, Hunter took aside Renaat Van den Hooff, who was in charge of the pilot on the Walgreens side, and told him something just wasn’t right.  The red flags were piling up.  First, Elizabeth had denied him access to their lab.  Then she’d rejected his proposal to embed someone with them in Palo Alto.  And now she was refusing to do a simple comparison study.  To top it all off, Theranos had drawn the blood of the president of Walgreen’s pharmacy business,one of the company’s most senior executives, and failed to give him a test result!

Van den Hooff told Hunter:

“We can’t not pursue this.  We can’t risk a scenario where CVS has a deal with them in six months and it ends up being real.”

Almost everything Walgreens did was done with its rival CVS in mind.

Theranos had cleverly played on this insecurity. As a result, Walgreens suffered from a severe case of FoMO—the fear of missing out.

There were two more things Theranos claimed were proof that its technology works.  First, there was clinical trial work Theranos had done with pharmaceutical companies.  Hunter had called the pharmaceutical companies, but hadn’t been able to reach anyone who could verify Theranos’s claims.  Second, Dr. J had commissioned Johns Hopkins University’s medical school to do a review of Theranos’s technology.

Hunter asked to see the Johns Hopkins review.  It was a two-page document.

When Hunter was done reading it, he almost laughed. It was a letter dated April 27, 2010, summarizing a meeting Elizabeth and Sunny had had with Dr. J and five university representatives on the Hopkins campus in Baltimore.  It stated that they had shown the Hopkins team “proprietary data on test performance” and that Hopkins had deemed the technology “novel and sound.”  But it also made clear that the university had conducted no independent verification of its own.  In fact, the letter included a disclaimer at the bottom of the second page: “The materials provided in no way signify an endorsement by Johns Hopkins Medicine to any product or service.”

In addition to Walgreens, Theranos also tried to get Safeway as a partner.  Elizabeth convinced Safeway’s CEO, Steve Burd, to do a deal.  Safeway loaned Theranos $30 million.  Safeway also committed to a massive renovation project of its stores, creating new clinics where customers could have their blood tested on Theranos devices.  Burd saw Elizabeth as a genius.

In early 2011, Hunter was informed that Elizabeth and Sunny no longer wanted him on the calls or in meetings between Theranos and Walgreens.  Hunter asked why Walgreens was paying him $25,000 a month to look out for the interests if he couldn’t do his job, which includes asking tough questions? 



Elizabeth had told Walgreens and Safeway that Theranos’s technology could perform hundreds of tests on small blood samples. 

The truth was that the Edison system could only do immunoassays, a type of test that uses antibodies to measure substances in the blood.  Immunoassays included some commonly ordered lab tests such as tests to measure vitamin D or to detect prostrate cancer.  But many other routine blood tests, ranging from cholesterol to blood sugar, required completely different laboratory techniques.

Elizabeth needed a new device, one that could perform more than just one class of test.  In November 2010, she hired a young engineer named Kent Frankovich and put him in charge of designing it.

Kent had just earned a master’s degree in mechanical engineering from Stanford.  Prior to that,he’d worked for two years at NASA’s Jet Propulsion Laboratory in Pasadena,where he’d helped construct Curiosity, the Mars rover.  Kent recruited a friend—Greg Baney—from NASA to Theranos.

Carreyrou notes that for several months, Kent and Greg were Elizabeth’s favorite employees.  She joined their brainstorming sessions and offered some suggestions about what robotic systems they should consider.  Elizabeth called the new system the “miniLab.” 

Because the miniLab would be in people’s homes, it had to be small.

This posed engineering challenges because, in order to run all the tests she wanted,the miniLab would need to have many more components than the Edison.  In addition to Edison’s photomultiplier tube, the new device would need to cram three other laboratory instruments in one small space: a spectrophotometer, a cytometer, and an isothermal amplifier.

None of these were new inventions…

Laboratories all over the world had been using these instruments for decades.  In other words, Theranos wasn’t pioneering any new ways to test blood.  Rather, the miniLab’s value would lie in the miniaturization of existing lab technology.  While that might not amount to groundbreaking science, it made sense in the context of Elizabeth’s vision of taking blood testing out of central laboratories and bringing it to drugstores, supermarkets, and, eventually, people’s homes.

To be sure, there were already portable blood analyzers on the market.  One of them, a device that looked like a small ATM called the Piccolo Express, could perform thirty-one different blood tests and produce results in as little as twelve minutes.  It required only three or four drops of blood for a panel of a half dozen commonly ordered tests.  However, neither the Piccolo nor other existing portable analyzers could do the entire range of laboratory tests.  In Elizabeth’s mind, that was going to be the miniLab’s selling point.

Greg thought they should take off-the-shelf components and get the overall system working first before miniaturizing it.  Trying to miniaturize before having a working prototype didn’t make sense.  But Elizabeth wouldn’t hear of it.

In the spring of 2011, Elizabeth hired her younger brother, Christian.  Although two years out of college—Duke University—and with no clear qualifications to work at a blood diagnostics company, what mattered to Elizabeth was that she could trust her brother.  Christian soon recruited five fraternity brothers: Jeff Blickman, Nick Menchel, Dan Edlin, Sani Hadziahmetovic, and MaxFosque.  The became known inside Theranosas “the Frat Pack.”

Like Christian, none of the other Duke boys had any experience or training relevant to blood testing or medical devices, but their friendship with Elizabeth’s brother vaulted them above most other employees in the company hierarchy.

Meanwhile, Greg had brought several of his own friends, Jordan Carr, Ted Pasco, and Trey Howard.

Jordan, Trey,and Ted were all assigned to the product management group with Christian and his friends, but they weren’t granted the same level of access to sensitive information.  Many of the hush-hush meetings Elizabeth and Sunny held to strategize about the Walgreens and Safeway partnerships were off limits to them, whereas Christian and his fraternity brothers were invited in.

At the holiday party in December 2011, Elizabeth gave a speech which included the following:

“The miniLab is the most important thing humanity has ever built.  If you don’t believe this is the case, you should leave now.  Everyone needs to work as hard as humanly possible to deliver it.”

By this point, Greg had decided to leave Theranos in two months.  He had become disillusioned:

The miniLab Greg was helping build with a prototype, nothing more.  It needed to be tested thoroughly and fine-tuned, which would require time.  A lot of time.  Most companies went through three cycles of prototyping before they went to market with a product.  But Sunny was already placing orders for components to build one hundred miniLabs, based on a first, untested prototype.  It was as if Boeing built one plane and, without doing a single flight test, told airline passengers, “Hop aboard.”

One problem that would require a great deal of testing wasthermal.  Packing many instrumentstogether in a small space led to unpredicted variations in temperature.



Safeway’s business was struggling and CEO Steve Burd  on an earnings call for buying back stock in order to boost earnings per share.  Burd responded that the company was about to do well, so buying back shares was the right move.  Burd elaborated by saying that the company was planning a significant “wellness play.” Analysts inferred that Safeway had a secret plan to ignite growth.

Burd had high hopes for the venture.  He’d ordered the remodeling of more than half of Safeway’s seventeen hundred stores to make room for upscale clinics with deluxe carpeting, custom wood cabinetry, granite countertops, and flat-screen TVs.  Per Theranos’s instructions, they were to be called wellness centers and had to look “better than a spa.”  Although Safeway was shouldering the entire cost of the $350 million renovation on its own, Burd expected it to more than pay for itself once the new clinics started offering the startup’s novel blood tests.

…[Burd]was starry-eyed about the young Stanford dropout and her revolutionary technology, which fit so perfectly with his passion for preventative healthcare.

Elizabeth had a direct line to Burd and answered only to him… He usually held his deputies and the company’s business partners to firm deadlines, but he allowed Elizabeth to miss one after the other.

In early 2012, the companies had agreed that Theranos would be in charge of blood testing at a Safeway employee health clinic on its corporate campus in Pleasanton.

Safeway’s first chief medical officer was Kent Bradley.  Bradley attended West Point and then the armed forces’ medical school in Bethesda, Maryland.  Then he served the U.S. Army for seventeen years before Safeway hired him.  Bradley looked forward to seeing the Theranos system in action.

However, he was surprised to learn that Theranos wasn’t planning on putting any of its devices in the Pleasanton clinic. Instead, it had stationed two phlebotomists there to draw blood, and the samples they collected were couriered across San Francisco Bay to Palo Alto for testing.  He also noticed that the phlebotomists were drawing blood from every employee twice, once with a lancet applied to the index finger and a second time the old-fashioned way with a hypodermic needle inserted in the arm. Why the need for venipunctures—the medical term for needle draws—if the Theranos finger-stock technology was fully developed and ready to be rolled out to consumers, he wondered.

Bradley’s suspicions were further aroused by the amount of time it took to get results back.  His understanding had been that the tests were supposed to be quasi-instantaneous, but some Safeway employees were having to wait as long as two weeks to receive their results.  And not every test was performed by Theranos itself.  Even though the startup had not said anything about outsourcing some of the testing, Bradley discovered that it was farming out some tests to a big reference laboratory in Salt Lake City called ARUP.

What really set off Bradley’s alarm bells, though, was when some otherwise healthy employees started coming to him with concerns about abnormal test results.  As a precaution, he sent them to get retested at a Quest or LabCorp location.  Each time, the new set of tests came back normal, suggesting the Theranos results were off…

Bradley put together a detailed analysis of the discrepancies.  Some of the differences between the Theranos values and the values from the other labs were disturbingly large.  When the Theranos values did match those of the other labs, they tended to be for tests performed by ARUP.

Bradley ended up taking his concerns to Burd, but Burd assured the doctor that Theranos’s technology had been tested and was reliable.

Theranos had a temporary lab in East Meadow Circle in Palo Alto.  The lab had gotten a certificate saying it was in compliance with CLIA—the federal law that governed clinical laboratories.  But such certificates were easy to obtain.

Although the ultimate enforcer of CLIA was the Centers for Medicare and Medicaid Services, the federal agency delegated most routine lab inspections to states.  In California, they were handled by the state department of health’s Laboratory Field Services division, which an audit had shown to be badly undefunded and struggling to fulfill its oversight responsibilities.

The East Meadows Circle lab didn’t contain a single Theranos proprietary device.  The miniLab was still being developed and was a long way from being ready for patient testing.  Instead, the lab had more than a dozen commercial blood and body-fluid analyzers made by companies such as Chicago-based Abbott Laboratories, Germany’s Siemens, and Italy’s DiaSorin.  Arne Gelb, a pathologist, ran the lab.  A handful of clinical laboratory scientists (CLSs) helped Arne.

One CLS named Kosal Lim was poorly trained and sloppy.  An experienced colleague, Diana Dupuy, believed Lim was harming the accuracy of the test results.

To Dupuy, Lim’s blunders were inexcusable. They included ignoring manufacturers’ instructions for how to handle reagents; putting expired reagents in the same refrigerator as current ones; running patient tests on lab equipment that hadn’t been calibrated; improperly performing quality-control runs on an analyzer; doing tasks he hadn’t been trained to do; and contaminating a bottle of Wright’s stain, a mixture of dyes used to differentiate blood cell types.

Dupuy documented Lim’s mistakes in regular emails to Arne and to Sunny, often including photos.

Dupuy also had concerns about the competence of the two phlebotomists Theranos had stationed in Pleasanton.  Blood is typically spun down in a centrifuge before it’s tested to separate its plasma from the patient’s blood cells.  The phlebotomists hadn’t been trained to use the centrifuge they’d been given and they didn’t know how long or at what speed to spin down patients’ blood.  When they arrived in Palo Alto, the plasma samples were often polluted with particulate matter.  She also discovered that many of the blood-drawing tubes Theranos was using were expired, making the anticoagulant in them ineffective and compromising the integrity of the specimens.

Dupuy was sent to Delaware to train on a new Siemens analyzer Theranos bought.  When she got back to the lab, it was spotless.

Sunny, who appeared to have been waiting for her, summoned her into a meeting room.  In an intimidating tone, he informed her that he had taken a tour of the lab in her absence and found not a single one of her complaints to be justified.

Sunny promptly fired her. He rehired her based on Arne’s recommendation.  Then Sunny fired Dupuy again several weeks later.  She was immediately escorted from the building without a chance to grab her personal belongings.  Dupuy sent an email to Sunny—and copied Elizabeth—which included the following:

I was warned by more than 5 people that you are a loose cannon and it all depends on your mood as to what will trigger you to explode.  I was also told that anytime someone deals with you it’s never a good outcome for that person.

The CLIA lab is in trouble with Kosal running the show and no one watching him or Arne.  You have a mediocre Lab Director taking up for a sub-par CLS for whatever reason.  I fully guarantee that Kosal will certainly make a huge mistake one day in the lab that will adversely affect patient results. I actually think he has already done this on several accounts but has put the blame on the reagents.  Just as you stated everything he touches is a disaster!

I only hope that somehow I bring awareness to you that you have created a work environment where people hide things from you out of fear.  You cannot run a company through fear and intimidation… it will only work for a period of time before it collapses.

As for the Safeway partnership, Theranos kept pushing back the date for the launch.  Burd had to keep telling analysts and investors on each quarterly earnings call that the new program was just about to launch, only to have it be delayed again.  Safeway’s finance department forecast revenues of $250 million, which was aggressive. The revenues hadn’t materialized, however, and Safeway had spent $350 million just to build the wellness centers. Safeway’s board was starting to get upset.  Although Burd had done an excellent job during his first decade as CEO, the second decade hadn’t been very good.  The costs and delays associated with the wellness centers prompted the board to ask Burd to retire.  He agreed.

Safeway then had to contact Sunny or the Frat Pack if they wanted to communicate with Theranos. Sunny always acted upset as if his time was too valuable, as if Theranos’s technology was a massive innovation requiring a huge time commitment.  Safeway executives were very upset about Sunny’s attitude.  But they still worried that they might miss out, so they didn’t walk away from the partnership.



Lieutenant Colonel David Shoemaker was part of a small military delegation meeting in Palo Alto in November 2011 to bless Theranos’s  deploy its devices in the Afghan war theatre.  Only, instead of blessing the proposal, LTC Shoemaker told Elizabeth that there were various regulations her approach would fail to meet.

The idea of using Theranos devices on the battlefield had germinated the previous August when Elizabeth had met James Mattis, head of the U.S. Central Command, at the Marines’ Memorial Club in San Francisco. Elizabeth’s impromptu pitch about how her novel way of testing blood from just a finger prick could help diagnose and treat wounded soldiers faster,and potentially save lives, had found a receptive audience in the four-star general.  Jim “Mad Dog” Mattis was fiercely protective of his troops, which made him one of the most popular commanders in the U.S. military.  The hard-charging general was open to pursuing any technology that might keep his men safer as they fought the Taliban in the interminable, atrocity-marred war in Afghanistan.

This type of request had to go through the army’s medical department.  Shoemaker’s job was to makes sure the armyfollowed all laws and regulations when it tested medical devices.  With regard to Theranos, the company would have to get approval from the FDA at a minimum.

Elizabeth disagreed forcefully, citing advice Theranos received from its lawyers.  She was so defensive and obstinate that Shoemaker quickly realized that prolonging the argument would be a waste of time.  She clearly didn’t want to hear anything that contradicted her point of view.  Ashe looked around the table, he noted that she had brought no regulatory affairs expert to the meeting.  He suspected the company didn’t even employ one.  If he was right about that, it was an incredibly naïve way of operating.  Health care was the most highly regulated industry in the country, and for good reason: the lives of patients were at stake.

Soon thereafter. Gary Yamamoto, a veteran field inspector in CMS’s regional office in San Francisco, was sent to exam Theranos’s lab.

Yes, Elizabeth had met with the army officer, but she had never told him Theranos intended to deploy its blood-testing machines far and wide under the cover of a single CLIA certificate.

Yamamoto asked why Theranos had applied for a CLIA certificate.

Sunny responded that the company wanted to learn a about how labs worked and what better way to do that than to operate one itself?  Yamamoto found that answer fishy and borderline nonsensical.  He asked to see their lab.

Carreyrou continues:

It looked like any other lab.  No sign of any special or novel blood-testing technology. When he pointed this out, Sunny said the Theranos devices were still under development and the company had no plans to deploy them without FDA clearance—flatly contradicting what Elizabeth had told Shoemaker on not one but two occasions.  Yamamoto wasn’t sure what to believe.  Why would the army officer have made all that stuff up?

…If Theranos intended to eventually roll its devices out to other locations, those places would need CLIA certificates too. Either that or, better yet, the devices themselves would need to be approved by the FDA.

Elizabeth immediately sent an email to General Mattis accusing Shoemaker of giving “blatantly false information” to the FDA and CMS about Theranos.  Mattis was furious and wanted to get to the bottom of things ASAP.  A colleague of Shoemaker’s forwarded the emails, including Mattis’s responses, to Shoemaker.  Shoemaker got worried about what Mattis would do.

Shoemaker met with Mattis to answer the general’s questions.  Once Mattis learned more about the rules and regulations governing the situation—the medical devices couldn’t be tested on human subjects without FDA approval except under very strict conditions—he was reasonable.  In the meantime, they could conduct a “limited objective experiment” using leftover de-identified blood samples from soldiers.

Although Theranos had the green light to run the “limited objective experiment,” for some reason it never proceeded to do so.



On October 29, 2011, Richard Fuisz was served a set of papers.  It was a lawsuit filed by Theranos in federal court in San Francisco alleging that Fuisz had conspired with his sons from his first marriage, Joe and John Fuisz, to steal confidential patent information to develop a rival patent. The suit alleged that the theft had been done by John Fuisz while he was employed at Theranos’s former patent counsel, McDermott Will & Emery.

Fuisz and his sons were angered by the suit, but they weren’t overly worried about it at first.  They were confident in the knowledge that its allegations were false.

Carreyrou writes:

John had no reason to wish Elizabeth or her family ill; on the contrary.  When he was in his early twenties, Chris Holmes had written him a letter of recommendation that helped him gain admission to Catholic University’s law school. Later, John’s first wife had gotten to know Noel Holmes through Lorraine Fuisz and become friendly with her.  Noel had even dropped by their house when John’s first son was born to bring the baby a gift.

Moreover, Richard and John Fuisz weren’t close.  John thought his father was an overbearing megalomaniac and tried to keep their interactions to a bare minimum.  In 2004, he’d even dropped him as a McDermott client because he was being difficult and slow to pay his bills.  The notion that John had willingly jeopardized his legal career to steal information for his father betrayed a fundamental misunderstanding of their frosty relationship.

But Elizabeth was understandably furious at Richard Fuisz.  The patent application he had filed in April 2006 had matured into U.S. Patent 7,824,612 in November 2010 and now stood in the way of her vision of putting the Theranos device in people’s homes.  If that vision was someday realized, she would have to license the bar code mechanism Fuisz had thought up to alert doctors to patients’ abnormal blood-test results.  Fuisz had rubbed that fact in her face the day his patent was issued by sending a Fuisz pharma press release to info@theranos.com, the email address the company provided on its website for general queries.  Rather than give in to what she saw as blackmail, Elizabeth had decided to steamroll her old neighbor by hiring one of the country’s best and most feared attorneys to go after him.

The Justice Department had hired David Boies to handle its antitrust suit against Microsoft.  Boies won a resounding victory in that case, which helped him rise to national prominence.  Just before Theranos sued, all three Fuiszes—Richard, John, and Joe—could tell that they were under surveillance by private investigators.

Boies’s use of private investigators wasn’t an intimidation tactic, it was the product of a singular paranoia that shaped Elizabeth and Sunny’s view of the world.  That paranoia centered on the belief that the lab industry’s two dominant players, Quest Diagnostics and Laboratory Corporation of America, would stop at nothing to undermine Theranos and its technology.  When Boies had first been approached about representing Theranos by Larry Ellison and another investor, it was that overarching concern that had been communicated to him.  In other words, Boies’s assignment wasn’t just to sue Fuisz, it was to investigate whether he was in league with Quest and LabCorp.  The reality was that Theranos was on neither company’s radar at that stage and that, as colorful and filled with intrigue as Fuisz’s life had been, he had no connection to them whatsoever.

Boies didn’t have any evidence whatsoever that John Fuisz had done what Theranos alleged.  Nonetheless, Boies intended to use several things from John’s past to create doubt in a judge or jury.  Potentially the most damaging thing Boies wanted to use was that McDermott had made John resign in 2009 after he had an argument with the firm’s other partners.  John insisted the firm discontinue its reliance on a forged document in a case before the International Trade Commission in which McDermott was representing a Chinese state-owned company against the U.S. government’s Office of Unfair Import Investigations.  McDermott leaders agreed to withdraw the document,but that decision significantly weakened the Chinese client’s defense.  Senior partners got upset about it.  They argued that there had been several incidents when John didn’t behave as a partner should. One incident was a complaint a client had made—this was Elizabeth’s September 2008 complaint about Richard Fuisz’s patent.

Eventually John was beyond furious.  He had launched his own practice after leaving McDermott.  The Theranos allegations had caused him to lose several clients.  Moreover, opposing counsel mentioned the allegations in order to tar John. Finally, his wife had been diagnosed with vasa previa—a pregnancy complication where the fetus’s blood vessels are dangerously exposed.  This added to John’s stress.

John always had a short fuse. During the deposition by Boies’s partners, John was combative and ornery.  He used foul language while threatening to harass Elizabeth “till she dies, absolutely.”

In the meantime, Richard and Joe Fuisz were worrying about how expensive the litigation was getting. Also, they knew they were up against one of the most expensive lawyers in the world: David Boies, who was reported to make $10 million a year.  But they didn’t know that Boies had agreed to accept stock in Theranos in place of his usual fees.  Partly out of concern for his investment, Boies began attending all of the company’s board meetings in early 2013.

Richard Fuisz examined Theranos’s patents.  He noticed that the name Ian Gibbons often appeared.  Gibbons was British and had a Ph.D. in biochemistry from Cambridge.  Fuisz suspected that Gibbons and other Theranos employees with advanced degrees had done most of the technical work related to Theranos’s patents.



Elizabeth hired Ian Gibbons on the recommendation of her Stanford mentor, Channing Robertson.

Ian fit the stereotype of the nerdy scientists to a T.  He wore a beard and glasses and hiked his pants way above his waist.  He could spend hours on end analyzing data and took copious notes documenting everything he did at work.  This meticulousness carried over to his leisure time: he was an avid reader and kept a list of every single book he’dread.  It included Marcel Proust’s seven-volume opus, Remembrance of Things Past, which he reread more than once.

Ian met his wife Rochelle at Berkeley in the 1970s.  He was doing a postdoctorate fellowship in molecular biology, while Rochelle was doing graduate research.  They didn’t have children.  But they loved their dogs Chloe and Lucy, and their cat Livia, named after the wife of the Roman emperor Augustus.  Ian also enjoyed going to the opera and photography.  He altered photos for fun.

Ian’s specialty was immunoassays.  He was passionate about the science of bloodtesting.  He also enjoyed teaching it.  Early on at Theranos, he would give small lectures to the rest of the staff.

Ian insisted that the blood tests they designed be as accurate in Theranos devices as they did on the lab bench.  Because this was rarely the case, Ian was quite frustrated.

He and Tony Nugent butted heads over this issue during the development of the Edison. As admirable as Ian’s exacting standards were, Tony felt that all he did was complain and that he never offered any solutions.

Ian also had issues with Elizabeth’s management, especially the way she siloed the groups off from one another and discouraged them from communicating.  The reason she and Sunny invoked for this way of operating was that Theranos was “in stealth mode,” but it made no sense to Ian.  At the other diagnostics companies where he had worked, there had always been cross-functional teams with representatives from the chemistry, engineering,manufacturing, quality control, and regulatory departments working toward a common objective.  That was how you got everyone on the same page, solved problems, and met deadlines.

Elizabeth’s loose relationship with the truth was another point of contention. Ian had heard her tell outright lies more than once and, after five years of working with her, he no longer trusted anything she said, especially when she made representations to employees or outsiders about the readiness of the company’s technology.

Ian complained confidentially to his friend Channing Robertson.  But Robertson turned around and told Elizabeth all that Ian said.  Elizabeth fired him.  Sunny called the next day because several colleagues urged Elizabeth to reconsider.  Ian was brought back but he was no longer head of general chemistry.  Instead, he was a technical consultant. 

Ian wasn’t the only employee being sidelined at that point.  It seemed that the old guard was being mothballed in favor of new recruits.  Nonetheless, Ian took it hard.

One day, Tony and Ian—who’d both been marginalized—got to talking.  Tony suggested that perhaps the company was merely a vehicle for Elizabeth and Sunny’s romance and that none of the work they didn’t actually mattered.  Ian agreed, saying, “It’s a folie a deux.”  Tony looked up the definition of that expression, which seemed accurate to him: “The presence of the same or similar delusional ideas in two persons closely associated with one another.”

Ian kept working closely with Paul Patel, who had replaced Ian.  Paul had enormous respect for Ian and continued treating him as an equal, consulting him on everything.  However, Paul avoided conflict and was more willing than Ian to compromise with the engineers while building the miniLab.  Ian wouldn’t compromise and got upset.  Paul frequently had to calm him down over the phone at night. Ian told Paul to abide by his convictions and never lose sight of concern for the patient.

Sunny put Samartha Anekal, who had a Ph.D. in chemical engineering, in charge of integrating the parts of the miniLab.  Sam struck some as a yes-man who simply did what Sunny told him to do.

As these things were unfolding, Ian had gotten clinically depressed—except he hadn’t been diagnosed as such.  He started drinking heavily in the evenings.  Rochelle was grieving for her mother, who had just passed away, and didn’t notice how depressed Ian was getting.

Theranos told Ian he’d been subpoenaed to testify in the Fuisz case.  Because Rochelle had done work as a patent attorney, Ian asked her to look the Theranos’s patents. 

While doing so, she noticed that Elizabreth’s name was on all the company’s patents, often in first place in the list of inventors.  When Ian told her that Elizabeth’s scientific contribution had been negligible, Rochelle warned him that the patents could be invalidated if this was ever exposed.  That only served to make him more agitated.

On May 15, he called to set up a meeting with Elizabeth.  After an appointment was set for the next day, Ian started worrying that Elizabeth would fire him.  The same day, the Theranos lawyer David Doyle told Ian that Fuizs’s lawyers—after trying for weeks to get the Boies Schiller attorneys to propose a date for Ian’s deposition—required Ian to appear at their offices in Campbell, California, on May 17.

The morning of May 16, Ian’s wife discovered that he’d taken enough acetaminophen to kill a horse.  He was pronounced dead on May 23.  Theranos had virtually no response. 

Although Tony Nugent and Ian had fought all the time, Tony felt bad about the lack of empathy for someone who had given a decade of his life to the company. Tony downloaded a list of Ian’s patents and created an email, including a photo of Ian, which Tony sent to two dozen colleagues who’d worked with him.



Chait/Day was working on a secretmarketing campaign for Theranos.  Patrick O’Neill, the creative director of the company’s Los Angeles’ office, was in charge.

Elizabeth had chosen Chiat/Day because it was the agency that represented Apple for many years, creating its iconic 1984 Macintosh ad and later its “Think Different” campaign in the late 1990s.  She’d even tried to convince Lee Clow, the creative genius behind those ads, to come out of retirement to work for her.  Clow politely referred her back to the agency, where she had immediately connected with Patrick.

Patrick was drawn in by Elizabeth’s extreme determination to do something great.  The Theranos mission to give people pain-free,low-cost health care was inspiring.  Advertisers don’t often get a chance to work on something that can make the world better, observes Carreyrou.

Part of the campaign included pictures of patients—played by models—of all different ages, genders, and ethnicities. 

The message was that Theranos’s blood-testing technology would help everyone.

Carreyrou again:

Real blood tended to turn purple after awhile when it was exposed to air, so they filled one of the nanotainters with fake Halloween blood and took pictures of it against a white background.  Patrick then made a photo montage showing it balancing on the tip of a finger.  As he’d anticipated, it made for an arresting visual. Mike Yagi tried out different slogans to go with it, eventually settling on two that Elizabeth really liked: “One tiny drop changes everything” and “The lab test, reinvented.”…

Patrick also worked with Elizabeth on a newcompany logo.  Elizabeth believed in the Flower of Life, a geometric pattern of intersecting circles within a larger circle that pagans once considered the visual expression of the life that runs through all sentient beings.

Although Patrick was enthused, his colleague Stan Fiorito was more circumspect.  He thought something about Sunny was strange.  He kept using software engineering jargon in weekly meeting even though it has zero applicability to the marketing discussions.  Also, Theranos was paying Chiat/Day $6 million a year.  Where was it getting the money for this?  Elizabeth stated several times that the army was using Theranos technology on the battlefield in Afghanistan.  She claimed it was saving soldiers’lives.  Perhaps Theranos was funded by the Pentagon, thought Stan.  At least that would help explain the extreme secrecy the company insisted upon.

Besides Mike Yagi, Stan supervised Kate Wolff and Mike Pedito.  Kate and Mikewere no-nonsense people and they began to wonder about Theranos.

Elizabeth wanted the website and all the various marketing materials to feature bold, affirmative statements.  One was that Theranos could run “over 800 tests”on a drop of blood.  Another was that its technology was more accurate than traditional lab testing.  She also wanted to say that Theranos test results were ready in less than thirty minutes and that its tests were “approved by FDA” and “endorsed by key medical centers” such as the Mayo Clinic and the University of California, San Francisco’s medical school, using the FDA, Mayo Clinic, and UCSF logos.

When she inquired about the basis for the claim about Theranos’s superior accuracy, Kate learned that it was extrapolated from a study that had concluded that 93 percent of lab mistakes were due to human error.  Theranos argued that, since its testing process was fully automated inside its device, that was grounds enough to say that it was more accurate than other labs.  Kate thought that was a big leap in logic and said so.  After all, there were laws against misleading advertising.

Mike agreed with Kate.

Elizabeth had mentioned a report several hundred pages long supporting Theranos’s scientific claims.  Kate and Mike repeatedly asked to see it, but Theranos wouldn’t produce it.  Instead,the company sent them a password-protected file containing what it said were excerpts from the report.  It stated that the Johns Hopkins University School of Medicine had conducted due diligence on the Theranos technology and found it “novel and sound” and capable of “accurately”running “a wide range of routine and special assays.”

Those quotes weren’t from any lengthy report, however.  They were from the two-page summary of Elizabeth and Sunny’s meeting with five Hopkins officials in April 2010.  As it had done with Walgreens, Theranos was again using that meeting to claim that its system had been independently evaluated.  But that simply wasn’t true.  Bill Clarke, the director of clinical toxicology at the Johns Hopkins Hospital and one of three university scientists who attended the 2010 meeting, had asked Elizabeth to ship one of her devices to his lab so he could put it through its paces and compare its performance to the equipment he normally used.  She had indicated she would but had never followed through.  Kate and Mike didn’t know any of this, but the fact that Theranos refused to show them the full report made them suspicious.

To learn how to market to doctors, Chiat/Day suggested doing focus group interviews with a few physicians.  Theranos agreed as long as it was very secret.  Kate asked her wife, Tracy, chief resident at Los Angeles County General, to participate.  Tracy agreed. During a phone interview, Tracy asked a few questions that no one at Theranos seemed to be able to answer. Tracy told Kate that she doubted the company had any new technology.  She also doubted you could get enough blood from a finger to run tests accurately.

The evening before the marketing campaign was going to launch, Elizabeth set up an emergency conference call.  She systematically dialed back the language that would be used.  “Welcome toa revolution in lab testing” was changed to “Welcome to Theranos.”  “Faster results.  Faster answers” became “Fast results.  Fast answers.”  “A tiny drop is all it takes” was now “A few drops is all it takes.”  “Goodbye, big bad needle” (which referred only to finger-stick draws) was replaced with “Instead of a huge needle, we can use a tiny finger stick or collect a micro-sample from a venous draw.”

Not everyone at Chiat/Day was skeptical, however.  Patrick thought Theranos could become his own big legacy, just as Apple had been for Lee Clow.



Alan Beam decided to become a doctor because his conservative Jewish parents thought that only law, medicine, or business was an appropriate career choice. While attending Mount Sinai’s School of Medicine, he didn’t like the crazy hours or the sights and smells of the hospital ward.  Instead, he got interested in laboratory science.  He pursued postdoctoral studies in virology and a residency in clinical pathology at Brigham and Women’s Hospital in Boston.

In the summer of 2012, having recently read Walter Isaacson’s biography of Steve Jobs—which greatly inspired Alan—he wanted to move to the San Francisco Bay Area.  He ended up being hired as laboratory directory as Theranos.  He didn’t start until April 2013 because it took eight months before he got his California medical license.

After starting, Alan became concerned about low morale in the lab:

Its members were downright despondent.  During Alan’s first week on the job, Sunny summarily fired one of the CLSs.  The poor fellow was frog-marched out by security in front of everyone.  Alan got the distinct impression it wasn’t the first time something like that had happened.  No wonder people’s spirits were low, he thought.

The lab Alan inherited was divided into two parts: a room on the building’s second floor that was filled with commercial diagnostic equipment, and a second room beneath it where research was being conducted.  The upstairs room was the CLIA-certified part of the lab, the one Alan was responsible for.  Sunny and Elizabeth viewed its conventional machines as dinosaurs that would soon be rendered extinct by Theranos’s revolutionary technology, so they called it “Jurassic Park.” They called the downstairs room “Normandy” in reference to the D-day landings during during World War II.  The proprietary Theranos devices it contained would take the lab industry by storm,like the Allied troops who braved hails of machine-gun fire on Normandy’s beaches to liberate Europe from Nazi occupation.

Alan liked the bravado at first.  But then he learned Paul Patel—the biochemist leading the development of blood tests for Theranos’s new device (now called the “4S” instead of the miniLab)—that he and his team were still developing its assays on lab plates on the bench.  Alan asked Paul about it and Paul said the new Theranos box wasn’t working.

By the summer of 2013, the 4S had been under development for more than two and a half years.  But it still had a long list of problems.  Carreyrou writes:

The biggest problem of all was the dysfunctional corporate culture in which it was being developed.  Elizabeth and Sunny regarded anyone who raised a concern or an objection as a cynic and a naysayer.  Employees who persisted in doing so were usually marginalized or fired, while sycophants were promoted.  Sunny had elevated a group of ingratiating Indians to key positions…

For the dozens of Indians Theranos employed,the fear of being fired was more than just the dread of losing a paycheck.  Most were on H-1B visas and dependent on their continued employment at the company to remain in the country.  With a despotic boss like Sunny holding their fates in his hands, it was akin to indentured servitude.  Sunny, in fact, had the master-servant mentality common among an older generation of Indian businessmen.  Employees were his minions.  He expected them to be at his disposal at all hours of the day or night and on weekends. He checked the security logs every morning to see when they badged in and out…

With time, some employees grew less afraid of him and devised ways to manage him, as it dawned on them that they were dealing with an erratic man-child of limited intellect and an even more limited attention span.

Some of the problems were because Elizabeth was fixated on certain things.  For instance, she thought the 4S—aka the miniLab—was a consumer device like an iPhone, and therefore it had to be small and pretty.  She still hoped these devices would be in people’s homes someday.

Another difficulty stemmed from Elizabeth’s insistence that the miniLab be capable of performing the four major classes of blood tests: immunoassays, general chemistry assays, hematology assays, and assays that relied on the amplification of DNA. The only known approach that would permit combining all of them in one desktop machine was to use robots wielding pipettes.  But this approach had an inherent flaw: overtime, a pipette’s accuracy drifts… While pipette drift was something that ailed all blood analyzers that relied on pipetting systems, the phenomenon was particularly pronounced on the miniLab. Its pipettes had to be recalibrated every two to three months, and the recalibration process put the device out of commission for five days.

Another serious weakness of the miniLab was that it could process only one blood sample at a time.  Commercial machines—which were bulky—could process hundreds of samples at the same time.

If the Theranos wellness centers attracted a lot of patients, the miniLab’s low throughput would cause long wait times, which was clearly inconsistent with the company’s promise of fast test results.

Someone suggested putting six miniLabs on top of one another—sharing one cytometer.  They adopted a computer term to name it: the“six-blade.”  But they overlooked a basic issue: temperature.  Some types of blood test require a very specific temperature. Because heat rises, the miniLabs near the top wouldn’t function.

There were other problems, too.  Many of them were fixable but would require a relatively long time.  Carreyrou explains:

Less than three years was not a lot of time to develop and perfect a complex medical device… The company was still several years away from having a viable product that could be used on patients.

However, as Elizabeth saw it, she didn’t have several years.  Twelve months earlier, on June 5, 2012, she’d designed a new contract with Walgreens that committed Theranos to launch its blood-testing services in some of the chain’s stores by February 1, 2013, in exchange for a $100 million “innovation fee” and an additional $40 million loan.

Theranos had missed that deadline—another postponement in what from Walgreens’s perspective had been three years of delays.  With Steve Burd’s retirement, the Safeway partnership was already falling apart, and if she waited  , Elizabeth risked losing Walgreens too. She was determined to launch in Walgreens stores by September, come hell or high water.

Since the miniLab was in no state to be deployed, Elizabeth and Sunny decided to dust off the Edison and launch with the older device.  That, in turn, led to another fateful decision—the decision to cheat.

Daniel Young, head of Theranos’s biomath team, and Xinwei Gong (who went by Sam), told Alan Beam that he and Sam were going to tinker with the ADVIA, one of the lab’s commercial analyzers.  It weighed 1,320 pounds and was made by Siemens Healthcare.  Since the Edison could only do immunoassays, Alan grasped why Daniel and Sam were going to try to use the ADVIA, which specialized in general chemistry assays.  As Carreyrou describes it:

One of the panels of blood tests most commonly ordered by physicians was known as the “chem 18” panel.  Its components, which ranged from tests to measure electrolytes sodium, potassium, and chloride to tests used to monitor patients’ kidney and liver function, were all general chemistry assays.  Launching in Walgreens stores with a menu of blood tests that didn’t include these tests would have been pointless.  They accounted for about two-thirds of doctors’ orders.

But the ADVIA was designed to handle a larger quantity of blood than you could obtain by pricking a finger.  So Daniel and Sam thought up a series of steps to adapt the Siemens analyzer to smaller samples.  Chief among these was the use of a big robotic liquid handler called the Tecan to dilute the little blood samples collected in the nanotainters with a saline solution.  Another was the transfer the diluted blood into custom-designed cups half the size of the ones that normally went into the ADVIA.

Because they were working with small blood samples, Daniel and Sam concluded that they would have to dilute the blood not once, but twice.  Alan knew this was a bad idea:

Any lab director worth his salt knew that the more you tampered with a blood sample, the more room you introduced for error.

Moreover, this double dilution lowered the concentration of the analytes in the blood samples to levels that were below the ADVIA’s FDA-sanctioned analytic measurement range. In other words, it meant using the machine in a way that neither the manufacturer nor its regulator approved of. To get the final patient result, one had to multiply the diluted result by the same factor the blood had been diluted by, not knowing whether the diluted result was even reliable.  Daniel and Sam were nonetheless proud of what they’d accomplished.  At heart, both were engineers for whom patient care was an abstract concept.  If their tinkering turned out to have adverse consequences, they weren’t the ones who would be held personally responsible. It was Alan’s name, not theirs, that was on the CLIA certificate.

Anjali Laghari was in charge of the immunoassay group.  She’d worked with Ian Gibbons for a decade.  Anjali had spent years trying to get the Edison working, but the device still had a high error rate.

When Anjali started hearing that Theranos was “going live,” she grew very concerned.  She emailed Elizabeth and Sunny to remind them about he high error rates for some blood tests run on the Edison.

Neither Elizabeth nor Daniel acknowledged her email.  After eight years at the company, Anjali felt she was at an ethical crossroads.  To still be working out the kinds in the product was one thing when you were in R&D mode and testing blood volunteered by employees and their family members, but going live in Walgreens stores meant exposing the general population to what was essentially a big unauthorized research experiment.  That was something she couldn’t live with.  She decided to resign.

Elizabeth wanted to persuade Anjali to stay.  Anjali asked Elizabeth why they should rush to launch before their technology was ready?  

“Because when I promise something to a customer, I deliver.”

Elizabeth Holmes

Anjali questioned this line of thought.  The customers were really mattered were the patients who ordered blood tests, believing that the tests were a reliable basis for medical decisions.

After Anjali resigned, her deputy Tina Noyes resigned.

The resignations infuriated Elizabeth and Sunny.  The following day they summoned the staff for an all-hands meeting in the cafeteria… Still visibly angry, Elizabeth told the gathered employees that she was building religion.  If there were any among them who didn’t believe, they should leave.  Sunny put it more blatantly: anyone not prepared to show complete devotion and unmitigated loyalty to the company should “get the fuck out.”



Elizabeth had met the great statesman George Shultz a couple of years before 2013. She impressed him and won his support. Based on this connection, Elizabeth had been able to engineer a very favorable piece in the Wall Street Journal.  The article was published September 7, 2013, just as Theranos was going to launch its blood-testing services.  Carreyrou says of the article:

Drawing blood the traditional way with a needle in the arm was likened to vampirism… Theranos’s processes, by contrast,were described as requiring “only microscopic blood volumes” and as “faster, cheaper, and more accurate than the conventional methods.”  The brilliant young Stanford dropout behind the breakthrough invention was anointed “the next Steve Jobs or Bill Gates” by no less than former secretary of state George Shultz, the man many credited with winning the cold war, in a quote at the end of the article.

Elizabeth planned to use the misleading article and the Walgreens launch as a basis for a new fundraising campaign.

Donald A. Lucas, son of legendary venture capitalist Donald L. Lucas, called Mike Barsanti.  Don and Mike had been friendly since they attended Santa Clara University in the 1980s.  Don proceeded to pitch Mike on Theranos.

Mike had first heard about Elizabeth seven years earlier.  Mike had been interested then, but Don hadn’t been. 

[Back in 2006, Mike] asked Don why the firm wasn’t taking a flyer on [Elizabeth] like his father had.  Don had replied that after careful consideration he’s decided against it.  Elizabeth was all over the place, she wasn’t focused, his father couldn’t control her even though he chaired her board, and Don didn’t like or trust her, Mike recalled his friend telling him.

In 2013, Mike asked Don what had changed.

Don explained excitedly that Theranos had come a long way since then.  The company was about to announce the launch of its innovative finger-stick tests in one of the country’s largest retail chains.  And that wasn’t all, he said.  The Theranos devices were also being used by the U.S. military.

“Did you know they’re in the back of Humvees in Iraq?” he asked Mike.


If all this were true, they were impressive developments, Mike thought.

…Intent on seizing what he saw as a great opportunity, the Lucas Venture Group was raising money for two new funds, Don told Mike.  One of them was a traditional venture fund that would invest in several companies, including Theranos.  The second would be exclusively devoted to Theranos.  Did Mike want in?  If so, time was short.

Mike got an email on September 9, 2013, discussing the “Theranos-time sensitive” opportunity.  The Lucas Venture group would get a discounted price, which valued the firm at $6 billion. Don mentioned that Theranos had “signed contracts and partnerships with very large retailers and drug stores as well as various pharmaceutical companies, HMO’s, insurance agencies, hospitals, clinics, and various government agencies.”  Don also said that the company had been “cash flow positive since 2006.”

Theranos seemed to be another “unicorn.”  Unicorns like Uber had been able to raise massive amounts of money while still remaining private companies, allowing them to avoid the pressures and scrutiny of going public.

Christopher James and Brian Grossman ran the hedge fund Partner Fund Management, which had $4 billion under management.  James and Grossman saw the Wall Street Journal article about Theranos and were interested.  They reached out to Elizabeth and went to meet with her on December 15, 2013.

During that first meeting, Elizabeth and Sunny told their guests that Theranos’s proprietary finger-stick technology could perform blood tests covering 1,000 of the 1,300 codes laboratories used to bill Medicare and private health insurers, according to a lawsuit Partner Fund later filed against the company.  (Many blood tests involve several billing codes, so the actual number of tests represented by those thousand codes was in the low hundreds.)

At a second meeting three weeks later, they showed them a Powerpoint presentation containing scatter plots purporting to compare test data from Theranos’s proprietary analyzers to data from conventional lab machines.  Each plot showed data points tightly clustered around a straight line that rose up diagonally from the horizontal x-axis.  This indicated that Theranos’s tests results were almost perfectly correlated with those of the conventional machines.  In other words, its technology was as accurate as traditional testing.  The rub was that much of the data in the charts wasn’t from the miniLab or even from the Edison.  It was from other commercial blood analyzers Theranos had purchased, including one manufactured by a company located an hour north of Palo Alto called Bio-Rad.

Sunny also told James and Grossman that Theranos had developed about three hundred different blood tests, ranging from commonly ordered tests to measure glucose, electrolytes, and kidney function to more esoteric cancer-detection tests.  He boasted that Theranos could perform 98 percent of them on tiny blood samples pricked from a finger and that, within six months, it would be able to do all of them that way.  These three hundred tests represented 99 to 99.9 percent of all laboratory requests, and Theranos had submitted every single one of them to the FDA for approval, he said.

Sunny and Elizabeth’s boldest claim was that the Theranos system was capable of running seventy different blood tests simultaneously on a single finger-stick sample and that it would soon be able to run even more.  The ability to perform so many tests on just a drop or two of blood was something of a Holy Grail in the field of microfluidics.

There were some basic problems with trying to run many tests on small samples of blood.  If you used a micro blood sample to do an immunoassay, then there usually wasn’t for the different set of lab techniques a general chemistry or hematology assay required.  Another fundamental problem was that in transferring a small sample to a microfluidic chip, some blood was lost.  This doesn’t matter for large blood samples, but it can be a crucial problem for small blood samples.  Yet Elizabeth and Sunny implied that they had solved these and other difficulties.

James and Grossman not only liked the presentations by Elizabeth and Sunny; they also were impressed by Theranos’s board of directors.  In addition to Shultz and General Mattis, the board now had Henry Kissinger, William Perry (former secretary of defense), Sam Nunn, and former navy admiral Gary Roughead.  Like Shultz, all of these board members were fellows at the Hoover Institution at Stanford.

Sunny sent the hedge fund managers a spreadsheet with financial projections.

It forecast gross profits of $165 million on revenues of $261 million in 2014 and gross profits of $1.08 billion on revenues of $1.68 billion in 2015.  Little did they know that Sunny had fabricated these numbers from whole cloth.  Theranos hadn’t had a real chief financial officer since Elizabeth had fired Henry Mosley in 2006.

Partner Fund invested $96 million.  This valued Theranos at $9 billion, which put Elizabeth’s net worth at almost $5 billion.



Carreyrou writes this chapter about Tyler Shultz, the grandon of George Shultz:

Tyler had first met Elizabeth in late 2011 when he’d dropped by his grandfather George’s house near the Stanford campus.  He was a junior then, majoring in mechanical engineering.  Elizabeth’s vision of instant and painless tests run on drops of blood collected from fingertips had struck an immediate chord with him.  After interning at Theranos that summer, he’d changed his major to biology and applied for a full-time position at the company.

Tyler became friends with Erika Cheung.

Their job on the immunoassay team was to help run experiments to verify the accuracy of blood tests on Theranos’s Edison devices before they were deployed in the lab for use on patients.  This verification process was known as “assay validation.”


One type of experiment he and Erika were tasked with doing involved retesting blood samples on the Edisons over and over to measure how much their results varied. The data collected were used to calculate each Edison’s blood test’s coefficient of variation, or CV.  A testis generally considered precise if its CV is less than 10 percent.  To Tyler’s dismay, data runs that didn’t achieve low enough CVs were simply discarded and the experiments repeated until the desired number was reached.  It was as if you flipped a coin enough times to get ten heads in a row and then declared that the coin always returned heads. Even with the “good” data runs, Tyler and Erika noticed that some values were deemed outliers and deleted.  When Erika asked the group’s more senior scientists how they defined an outlier, no one could give her a straight answer. Erika and Tyler might be young and inexperienced, but they both knew that cherry-picking data wasn’t good science. Nor were they the only ones who had concerns about these practices.

Tyler and colleagues tested 247 blood samples on Edison for syphilis, 66 of which were known to be positive.  The devices correctly identified only 65 percent of the sample on the first run, and 80 percent on the second run.

Yet, in its validation report, Theranos stated that its syphilis test had a sensitivity of 95 percent.

There were other tests where Tyler and Erika thought Theranos was being misleading.  For instance, a blood sample would be tested for vitamin D on an analyzer made by the Italian company DiaSorin.  It might show a vitamin D concentration of 20 nanograms per milliliter—a normal result for a healthy patient.  When Erika tested the sample on the Edison,the result was 10 or 20 nanograms per milliliter—indicating a vitamin D deficiency.  Nonetheless, the Edison was cleared for use in the clinical lab on live patient samples, writes Carreyrou.

In November 2013, while workingin the clinical lab, Erika received a patient order from the Walgreens store inPalo Alto.  As was standard practice, first she did a quality-control check. That involves testing a sample where you already know the concentration of the analyte.

If the result obtained is two standard deviations higher or lower than the known value, the quality-control check is usually deemed to have failed.

Erik’a first quality-control check failed.  She ran it again and that one failed as well.  Because it was during Thanksgiving, no one Erika normally reported to was around.  Erika sent an email to the company’s emergency help line.

Sam Anekal, Suraj Saksena, and Daniel Young responded to her email with various suggestions, but nothing they proposed worked.  After awhile an employee named Uyen Do from the research-and-development side came down and took a look at the quality-control readings.

Twelve values had been generated, six during each quality-control test.

Without bothering to explain her rationale to Erika, Do deleted two of those twelve values, declaring them outliers.  She then went ahead and tested the patient sample and sent out a result.

This wasn’t how you were supposed to handle repeat quality-control failures. Normally, two such failures in a row would have been cause to take the devices off-line and recalibrate them. Moreover, Do wasn’t even authorized to be in the clinical lab.  Unlike Erika, she didn’t have a CLS license and had no standing to process patient samples. The episode left Erika shaken.

Tyler Shultz moved to the production team in early 2014.  This put him back near Erika and other colleagues from the clinical lab.

Tyler learned from Erika and others that the Edisons were frequently flunking quality-control checks and that Sunny was pressuring lab personnel to ignore the failures and to test patient samples on the devices anyway.

Tyler asked Elizabeth about validation reports, and she suggested he speak with Daniel Young.  Tyler asked Daniel about CV values: Why were so many data runs discarded when the resulting CV was too high?   Daniel told him that he was making the mistake of taking into account all six values generating by the Edison during a test.  Young said that only the median value mattered.  It was obvious to Tyler that if the Edison’s results were accurate, such data contortions—and the associated dishonesty—wouldn’t be needed in the first place.

Furthermore, all clinical laboratories undergo “proficiency testing” three times a year.

During its first two years of operation, the Theranos lab had always tested proficiency-testing samples on commercial analyzers.  But since it was now using the Edisons for some patient tests, Alan Beam and his new lab codirector had been curious to see how the devices fared in the exercise.  Beam and the new codirector, Mark Pandori, had ordered Erika and other lab associates to split the proficiency-testing samples and run one part on the Edisons and the other part on the lab’s Siemens and DiaSorin analyzers for comparison. The Edison results had differed markedly from the Siemens and DiaSorin ones, especially for vitamin D.

When Sunny had learned of their little experiment, he’d hit the roof.  Not only had he put an immediate end to it, he had made them report only the Siemens and DiaSorin results.  There was a lot of chatter in the lab that the Edison results should have been the ones reported.  Tyler had looked up the CLIA regulations and they seemed to bear that out…

Tyler told Daniel he didn’t see how what Theranos had done could be legal.  Daniel’s response followed a tortuous logic.  He said a laboratory’s proficiency-testing results were assessed by comparing them to its peers’results, which wasn’t possible in Theranos’s case because its technology was unique and had no peer group.  As a result, the only way to do an apples-to-apples comparison was by using the same conventional methods as other laboratories. Besides, proficiency-testing rules were extremely complicated, he argued.  Tyler could rest assured that no laws had been broken.  Tyler didn’t buy it.

In March 2014, using an alias, Tyler emailed the New York health department because it ran one of the proficiency-testing programs in which Theranos had participated.  Without revealing the name of the company in question, he asked about Theranos’s approach.  He got confirmation that Theranos’s practices were “a form of PT cheating” and were “in violation of the state and federal requirements.”  Tyler was given a choice:reveal the name of the company or file an anonymous complaint with New York State’s Laboratory Investigative Unit. He chose the second option.

Tyler told his famous grandfather George about his concerns.  He said,moreover, that he was going to resign.  George asked him to give Elizabeth a chance to respond.  Tyler agreed. Elizabeth was too busy to meet in person, so Tyler sent her a detailed email.  He didn’t hear anything for a few days.

When the response finally arrived, it didn’t come from Elizabeth.  It came from Sunny.  And it was withering.  In a point-by-point rebuttal that was longer than Tyler’s original email, Sunny belittled everything from his grasp of statistics to his knowledge of laboratory science.

On the topic of proficiency testing, Sunny wrote:

“That reckless comment and accusation about the integrity of our company, its leadership and its core team members based on absolute ignorance is so insulting to me that had any other person made the sestatements, we would have held them accountable in the strongest way.  The only reason I have taken so much time away from work to address this personally is because you are Mr. Shultz’s grandson…

I have now spent an extraordinary amount of time postponing critical business matters to investigate your assertions—the only email on this topic I want to see from you going forward is an apology that I’ll pass on to other people including Daniel here.”

Tyler replied to Sunny with a one-sentence email saying he was resigning.  Before he even got to his car, Tyler’s mother called and blurted, “Stop whatever you’re about to do!”  Tyler explained that he had already resigned.

“That’s not what I mean.  I just got off the phone with your grandfather.  He said Elizabeth called him and told him that if you insist on carrying out your vendetta against her, you will lose.”

Tyler was dumbfounded.  Elizabeth was threatening him through his family, using his grandfather to deliver the message.

Tyler went to the Hoover Institution to meet with his grandfather. George listened to what Tyler had to say.  Finally, George told his grandson that he thought he was wrong in this case.

In the meantime, a patient order for a hepatitis C test had reached the lab and Erika refused to run it on the Edisons, writes Carreyrou.  The reagents for the hepatitis C test were expired.  Also,the Edisons hadn’t been recalibrated in awhile. Erika and a coworker decided to use commercially available hepatitis kits called OraQuick HCV.  The worked until they ran out.  They tried to order more, but Sunny had gotten upset and tried to block it.  Sunny also learned that it was Erika who had given Tyler the proficiency-testing results. Sunny asked Erika to meet with him and then told her, “You need to tell me if you want to work here or not.”

Erika went to meet Tyler, who suggested that she join him for dinner at his grandfather’s house.  Perhaps have two people with similar experiences would be more persuasive.  Unfortunately,while Charlotte, George’s wife, seemed receptive and incredulous, George wasn’t buying it.

Tyler had noticed how much he doted on Elizabeth.  His relationship with her seemed closer than their own.  Tyler also knew that his grandfather was passionate about science.  Scientific progress would make the world a better place and save it from such perils as pandemics and climate change, he often told his grandson.  This passion seemed to make him unable to let go of the promise of Theranos.

George said a top surgeon in New York had told him the company was gong to revolutionize the field of surgery and this was someone his good friend Henry Kissinger considered to be the smartest man alive.  And according to Elizabeth, Theranos’s devices were already being used in medevac helicopters and hospital operating rooms, so they must be working.

Tyler and Erika tried to tell him that couldn’t possibly be true given that the devices were barely working within the walls of Theranos.  But it was clear they weren’t making any headway.  George  to put the company behind them and to move on with their lives. 

The next morning Erika quit Theranos.



After Theranos sued Richard Fuisz, Richard and Joe Fuisz resolved to fight it to the very end.  However, after they’d spent more than $2 million on their defense and after they realized how outgunned they were by Theranos’s lawyers—led by David Boies—they decided it would be better to settle.

It amounted to a complete capitulation on the Fuiszes’ part.  Elizabeth had won.

At a meeting with Boies, the two sides drafted the settlement agreement. Then Richard and Joe signed.

…Richard Fuisz looked utterly defeated.  The proud and pugnacious former CIA agentbroke down and sobbed.

Roger Parloff, Fortune magazine’s legal correspondent, saw an article about the case involving Theranos and the Fuiszes.  Parloff called Dawn Schneider, Boies’s long-term public relations representative. She offered to meet Parloff at his office.  On the walk across Midtown, Schneider thought that a better story to write about was Theranos and its brilliant young founder.  When she arrived at Parloff’s office, she told him about Theranos and said, “this is the greatest company you’ve never heard of.”

Parloff went to Palo Alto do meet with Elizabeth.

…what Elizabeth told Parloff she’d achieved seemed genuinely innovative and impressive. As she and Sunny had stated to Partner fund, she told him the Theranos analyzer could perform as many as seventy different blood tests from one tiny finger-stick draw and she led him to believe that the more than two hundred tests on its menu were all finger-stick tests done with proprietary technology.  Since he didn’t have the expertise to vet her scientific claims, Parloff interviewed the prominent members of her board of directors and effectively relied on them as character witnesses… All of the vouched for Elizabeth emphatically. Shultz and Mattis were particularly effusive.

“Everywhere you look with this young lady,there’s a purity of motivation,” Shultz told him.  “I mean she is really trying to make the world better, and this is her way of doing it.”

Mattis went out his way to praise her integrity.  “She has probably one of the most mature and well-honed sense of ethics—personal ethics, managerial ethics, business ethics, medical ethics that I’ve ever heard articulated,” the retired general gushed.

Parloff’s cover story for Fortune magazine was published June 12, 2014.  Elizabeth instantly became a star.  Forbes then ran its own piece.

Two months later she graced one of the covers of the magazine’s annual Forbes 400 issue on the richest people in America.  More fawning stories followed in USA Today, Inc., Fast Company, and Glamour, along with segments on NPR, Fox Business, CNBC, CNN, and CBS News.  With the explosion of media coverage came invitations to numerous conferences and a cascade of accolades.  Elizabeth became the youngest person to win the Horatio Alger award.  Time magazine her one of the one hundred most influential people in the world. President Obama appointed her a U.S. ambassador for global entrepreneurship, and Harvard Medical School invited her to join its prestigious board of fellows.

Carreyrou continues:

As much as she courted the attention, Elizabeth’s sudden fame wasn’t entirely her doing… In Elizabeth Holmes, the Valley had its first female billionaire tech founder.

Still, there was something unusual in the way Elizabeth embraced the limelight. She behaved more like a movie star than an entrepreneur, basking in the public adulation she was receiving.  Each week brought a new media interview or conference appearance.  Other well-known startup founders gave interviews and made public appearances too but with nowhere near the same frequency.  The image of the reclusive, ascetic young woman Parloff had been sold on had overnight given way to that of the ubiquitous celebrity.

Elizabeth excelled at delivering a heartwarming message that Theranos’s convenient blood tests could be used to catch diseases early so that no one would have to say goodbye to loved ones too soon, notes Carreyrou.  She soon started adding a new personal detail to her interviews and presentations: her uncle had died of cancer.

It was true that Elizabeth’s uncle, Ron Dietz, had died eighteen months earlier from skin cancer that had metastasized and spread to his brain.  But what she omitted to disclose was that she had never been close to him.  To family members who knew the reality of their relationship, using his death to promote her company felt phony and exploitative.

Of course, at that time, most people who heard Elizabeth in an interview or presentation didn’t know about the lies she was telling.  But she was a great salesperson.  Elizabeth told one story about a little girl who got stuck repeatedly because the nurse couldn’t find the vein.  Another story was about cancer patients depressed because of how much blood they had to give.

Patrick O’Neill, from TBWA/Chiat/Day, was Theranos’s chief creative officer.  He was raising Elizabeth’s profile and perfecting her image.

To Patrick, making Elizabeth the face of Theranos made perfect sense.  She was the company’s most powerful marketing tool. Her story was intoxicating. Everyone wanted to believe in it, including the numerous young girls who were sending her letters and emails.  It wasn’t a cynical calculus on his part: Patrick was one of her biggest believers.  He had no knowledge of the shenanigans in the lab and didn’t pretend to understand the science of blood testing.  As far as he was concerned, the fairy tale was real.

With over five hundred employees, Theranos had to move to a new location.  Patrick designed Elizabeth’s new office:

Elizabeth’s new corner office was designed to look like the Oval Office.  Patrick ordered a custom-made desk that was as deep as the president’s at its center but had rounded edges.  In front of it, he arranged two sofas and two armchairs around a table, replicating the White House layout.  At Elizabeth’s insistence, the office’s big windows were made of bulletproof glass.



Alan Beam had become disillusioned:

For his first few months as laboratory director, he’s clung to the belief that the company was going to transform  with its technology.  But the past year’s events had shattered any illusion of that.  He now felt like a pawn in a dangerous  played with patients, investors, and regulators.  At one point, he’d had to talk Sunny and Elizabeth out of running HIV tests on diluted finger-stick samples.  Unreliable potassium and cholesterol results were bad enough.  False HIV results would have been disastrous.

Two of Alan’s colleagues had recently resigned out of disagreement with what they viewed as blatantly dishonest company policies.

One day Alan was talking with Curtis Schneider, one of the smartest people at Theranos, with a Ph.D. in inorganic chemistry and having spent four years as a postdoctoral scholar at Caltech. 

He told Curtis about the lab’s quality-control data and how it was being kept from him. And he confided something else: the company was cheating on its proficiency testing.  In case Curtis hadn’t registered the implication of what he’d just said, he spelled it out: Theranos was breaking the law.

A few weeks later, Christian Holmes contacted Alan.

Christian wanted Alan to handle yet another doctor’s complaint.  Alan had field dozens of them since the company had gone live with its tests the previous fall.  Time and time again, he’d been asked to convince physicians that blood-test results he had no confidence in were sound and accurate.  He decided he couldn’t do it anymore.  His conscience wouldn’t allow him to.

He told Christian no and emailed Sunny and Elizabeth to inform them that he was resigning and to ask them to immediately take his name off the lab’s CLIA license.

December 15, 2014, there another article about Theranos in the New Yorker.  Adam Clapper, a pathologist in Columbia Missouri, who writes a blog about the industry Pathology Blawg, noticed the article.  He was very skeptical about Theranos.  Joe Fuisz noticed the article and told his father about it.  Richard read the article and got in touch with Adam. Adam felt initially there he would need more proof.

A few days later, Richard noticed that someone named Alan Beam had looked at his LinkedIn profile.  Richard saw that Alan had been laboratory at Theranos.  So he sent him an InMail,thinking it was worth a shot.  Alan got back to him.

Alan called and said to Richard, “You and I took the Hippocratic Oath, which is to first do no harm.  Theranos is putting people in harm’s way.”  Alan filled him in on all the details. 

Richard told Adam about what he’d learned from Alan.  Adam agreed that the information changed everything. However, he was worried about the legal liability of going against a $9 million Silicon Valley company with a litigious history and represented by David Boies.  That said, Adam knew an investigative reporter at the Wall Street Journal.  John Carreyrou.



Adam called John Carreyrou at the Wall Street Journal. Carreyrou says that even though nine times out of ten, tips don’t workout, he always listened because you never knew. Also, he happened to have just finished a year-long investigation in Medicare fraud and he was looking for his next story.

February 26, 2015, Carreyrou reached Alan Beam.  Alan agreed to talk as long as his identity was kept confidential.

…the Theranos devices didn’t work.  They were called Edisons, he said, and they were error-prone.  They constantly failed quality-control.  Furthermore, Theranos used them for only a small number of tests.  It performed most of its tests on commercially available instruments and diluted the blood samples.

…Theranos didn’t want people to know its technology was limited, so it had contrived away of running small finger-stick samples on conventional machines.  This involved diluting the finger-stick samples to make them bigger.  The problem, he said, was that when you diluted the samples, you lowered the concentration of analytes in the blood to a level the conventional machines could no longer measure accurately.

He said he had tried to delay the launch of Theranos’s blood tests in Walgreens stores and had warned Holmes that the lab’s sodium and potassium results were completely unreliable… I was barely getting my head around these revelations when Alan mentioned something called proficiency testing.  He was adamant that Theranos was breaking federal proficiency-testing rules.

There was more:

Alan also said that Holmes was evangelical about revolutionizing blood testing but that her knowledge base on science and medicine was poor, confirming my instincts.  He said she wasn’t the onerunning Theranos day-to-day.  A man named Sunny Balwani was.  Alan didn’t mince his words about Balwani: he was a dishonest bully who managed through intimidation.  Then he dropped another bombshell: Holmes and Balwani were romantically involved.

It’s not that there were rules against such a romantic involvement in the Silicon Valley startup world. Rather, it’s that Elizabeth was hiding the relationship from her board.  What other information might she be keeping from her board?

Alan told Carreyrou how he had brought up his concerns with Holmes and Balwani a number of times, but Balwani would either rebuff him or put him off, writes Carreyrou. 

Alan was most worried about potential harm to patients:

He described the two nightmare scenarios false blood-test results could lead to.  A false positive might cause a patient to have an unnecessary medical procedure.  But a false negative was worse: a patient with a serious condition that went undiagnosed could die.

Carreyrou experienced the familiar rush of a big reporting breakthrough, but he knew that he needed to get corroboration.  He proceeded to speak with others who had been associated with Theranos and who were willing to talk—some on the condition of anonymity.  A good start.  However, getting documentary evidence was “the gold standard for these types of stories.”  This would be harder.

Carreyrou spoke with Alan again.

Our conversation shifted to proficiency testing. Alan explained how Theranos was gaming it and he told me which commercial analyzers it used fort he majority of its blood tests.  Both were made by Siemens… He revealed something else that hadn’t come up in our first call: Theranos’s lab was divided into two parts.  One contained the commercial analyzers and the other the Edison devices.  During her inspection of the lab, a state inspector had been shown only the part with the commercial analyzers.  Alan felt she’d been deceived.

He also mentioned that Theranos was working on a newer-generation device code-named 4S that was supposed to supplant the Edison and do a broader variety of blood tests, but it didn’t work at all and was never deployed in the lab.  Diluting finger-stick samples and running them on Siemens machines was supposed to be a temporary solution, but it had become a permanent one because the 4S had turned into a fiasco.

It was all beginning to make sense: Holmes and her company had overpromised and then cut corners when they couldn’t deliver. It was one thing to do that with software or a smartphone app, but doing it with a medical product that people relied on to make important health decisions was unconscionable.

Carreyrou reached out to twenty former and current Theranos employees.  Many didn’t respond.  Those Carreyrou got on the phone said they’d signed strict confidentiality agreements. They were worried about being sued.

Carreyrou’s initial conversations with Alan and two others had been “on deep background,” which meant Carreyrou could use what they said but had to keep their identities confidential. Subsequently, he spoke with a former high-ranking employee “off the record.”  This meant that Carreyrou couldn’t make use of any information from that conversation. But Carreyrou did learn corroborating information even though it was off the record.  This further bolstered his confidence.

Carreyrou knew he needed proof that Theranos was delivering inaccurate blood-test results.  He discovered a doctor, Nicole Sundene, who had much such a complaint on Yelp.  Carreyrou met with Dr. Sundene, who told him about the experience of one of her patients, Maureen Glunz.

The lab report she’d received from Theranos had shown abnormally elevated results for calcium, protein, glucose, and three liver enzymes… Dr. Sundene had worried she might be on the cusp of a stroke and sent her straight to the hospital.  Glunz had spent four hours in the emergency room on the eve of Thanksgiving while doctors ran a battery of tests on her,including a CT scan.  She’d been discharged after a new set of blood tests performed by the hospital’s lab came back normal.  That hadn’t been the end of it, however.  As a precaution, she’d undergone two MRIs during the ensuing week…

When I met with Dr. Sundene at her office, I learned that Glunz wasn’t the only patient whose results she found suspect.  She told me more than a dozen of her patients had tested suspiciously high for potassium and calcium and she doubted the accuracy of those results as well.  She had written Theranos a letter to complain but the company hadn’t even acknowledged it.

Carreyrou met a Dr. Adrienne Stewart who told him about two of her patients who’d gotten incorrect results from Theranos.  One patient had to delay a long-planned trip to Ireland because an incorrect result from Theranos suggested she could have deep vein thrombosis.  A second set of tests from another lab turned out to be normal. Also, ultrasound of the patient’s legs didn’t reveal anything.

Another of Dr. Stewart patients had gotten a test result from Theranos indicating a high TSH value.

The patient was already on thyroid medication and the result suggested that he dose needed to be raised.  Before she did anything, Dr. Stewart sent the patient to get retested at Sonora Quest, a joint venture of Quest and the hospital system Banner Health.  The Sonora Quest result came back normal.  Had she trusted the Theranos result and increased the patient’s medication dosage, the outcome could have been disastrous, Dr. Stewart said.  The patient was pregnant.  Increasing her dosage would have made her levels of thyroid hormone too high and put her pregnancy at risk.

Carreyrou also met with Dr. Gary Betz.  He had a patient on medication to reduce blood pressure.  High potassium was one potential side effect of the medication, so Dr. Betz monitored it.  A Theranos test showed that his patient had an almost critical level of potassium.  A nurse sent Dr. Bet’z patient back to get retested.  But the phlebotomist was unable to complete the test despite three attempts to draw blood. Dr. Betz was very upset because if the initial test was accurate, an immediate change in the patient’s treatment was crucial.  He sent his patient to get tested as SonoraQuest.  The result came back normal.

As an experiment, Carreyrou and Dr. Sundene had each gotten their blood tested by Theranos and by another lab.  Carreyrou:

Theranos had flagged three of my values as abnormally high and one as abnormally low.  Yet on LabCorp’s report, all four of those values showed up as normal. Meanwhile, LabCorp had flagged both my total cholesterol and LDL cholesterol as high, while the Theranos described the first as “desirable” and the second as “near optimal.”

Those differences were mild compared to a whopper Dr. Sundene had found in her results.  According to Theranos, the amount of cortisol in her blood was less than one microgram per deciliter.  A value that low was usually associated with Addison’s disease, a dangerous condition characterized by extreme fatigue and low blood pressure that could result in death if it went untreated.  Her LabCorp report, however, showed a cortisol level of 18.8, micrograms per deciliter, which was within the normal range for healthy patients.  Dr. Sundene had no doubt which of the two values was the correct one.

Carreyrou mentions a “No surprise” rule they have at the Wall Street Journal.

We never went to press with a story without informing the story subject of every single piece of information we had gathered in our reporting and giving them ample time and opportunity to address and rebut everything.

Carreyrou met with Erica Cheung.

She said Theranos should never have gone live testing patient samples.  The company routinely ignored quality-control failures and test errors and showed a complete disregard for the well-being of patients, she said.  In the end, she had resigned because she was sickened by what she had become a party to, she told me.

Carreyrou also met with Tyler Shultz, who gave him a detailed account of his experiences with Theranos. Finally, Carreyrou met with Rochelle Gibbons, the widow of Ian Gibbons.

I flew back to New York the next day confident that I’d reached a critical mass in my reporting and that it wouldn’t be too long before I could publish.  But that was underestimating whom I was up against.



On May 27, 2015, Tyler went to his parents’ house for dinner,as he tried to do every two weeks.  His father, looking worried, asked Tyler if he’d spoken with an investigative journalist from the Wall Street Journal.  Yes, said Tyler.  His father: “Are you kidding me?  How stupid could you be?  Well, they know.”

His father told him that his grandfather George had called.  George said if Tyler wanted to get out of a “world of trouble,” he would have to meet with Theranos’s lawyers the next day and sign something.  Tyler called his grandfather and arranged to meet him later that night.

Carreyrou had sent a list of seven areas he wanted to discuss with Elizabeth to Matthew Traub, a representative of Theranos.  Included in one section was coefficient of variation for one of the blood tests.  It happened to be a number that Tyler had calculated.  It was because of that number that Elizabeth had been able to tie Tyler to the investigative reporter.

However, the number Elizabeth tied to Tyler could have come from anyone.  When Tyler met with his grandfather, he categorically denied speaking with any reporter.  George told Tyler:  “We’re doing this for you.  Elizabeth says your career will be over if the article is published.”

Tyler summarized all the issues he had raised earlier regarding Theranos.  But his grandfather still didn’t agree with Tyler’s views.  George told his grandson that there was a one-page document Theranos wanted him to sign swearing confidentiality going forward. Theranos argued that the Wall Street Journal article would include trade secrets of the company.  Tyler said he would consider signing the document if the company would stop bothering him. George then told Tyler that there were two Theranos lawyers upstairs.

Tyler felt betrayed because he had specifically asked to meet his grandfather with no lawyers.  His grandmother Charlotte told Tyler that she was questioning whether Theranos had a functioning product and that Henry Kissinger was also skeptical and wanted out.

The two lawyers, Mike Brill and Meredith Dearborn, were partners at Boies, Schiller & Flexner. Brille told Tyler he had identified him as a source for the Journal article.

He handed him three documents: a temporary restraining order, a notice to appear in court two days later, and a letter stating Theranos had reason to believe Tyler had violated his confidentiality obligations and was prepared to file suit against him.

Brille pressed Tyler to admit that he had spoken with a reporter.  Tyler kept denying it.  Brille kept pushing and pushing and pushing.  Finally, Tyler said the conversation needed to end.  His grandfather jumped in and defended Tyler and escorted the lawyers out of the house. 

[George] called Holmes and told her this was not what they had agreed upon.  She had sent over a prosecutor rather than someone who was willing to have a civilized conversation.  Tyler was ready to go to court the next day, he warned her.

George and Elizabeth reached a compromise.  They would meet again at George’s house the following morning.  Tyler would look at the one-page document.  George asked Elizabeth to send a different lawyer.

The next morning, Tyler wasn’t surprised to see Brille again.  Brille had new documents. 

One of them was an affidavit stating that Tyler had never spoken to any third parties about Theranos and that he pledged to give the names of every current and former employee who he knew had talked to the Journal. Brille asked Tyler to sign the affidavit.  Tyler refused.

George asked Tyler what it would take for him to sign it.  Tyler said Theranos would have to agree not to sue him.  George wrote the requirement on the affidavit.  Then he and Brille went into another room to talk.

In the interim, Tyler decided he wasn’t going to sign anything.  After speaking with two lawyers soon thereafter, Tyler stuck with his decision.  Brille had been threatening to sue immediately, but then told Tyler’s lawyer that they were going to delay the lawsuit in order to try to reach some agreement.

Tyler—through his lawyer—began exchanging drafts of the affidavit with Brille.  Tyler tried to make concessions in order to reach some agreement.  For instance, he agreed to be called a junior employee who couldn’t have known what he was talking about when it come to proficiency testing, assay validation, and lab operations. But Theranos kept pushing Tyler to name the Journal’s other sources.  He refused.

As the stalemate dragged on, Boies Schiller resorted to the bare-knuckle tactics it had become notorious for.  Brille let it be known that if Tyler didn’t sign the affidavit and name the Journal‘s sources, the firm would make sure to bankrupt his entire family when it took him to court.  Tyler also received a tip that he was being surveilled by private investigators.

Tyler got a lawyer for his parents.  That way Tyler and his parents could communicate through attorneys and those conversations would be protected by attorney-client privilege.

This led to an incident that rattled both Tyler and his parents.  Hours after his parents’ new lawyer met with them for the first time, her car was broken into and her briefcase containing her notes from the meeting was stolen.



A Theranos delegation met Carreyrou at the offices of the Journal. David Boies came with Mike Brille, Meredith Dearborn, and Heather King, who was now general counsel for Theranos. Matthew Traub was there.  The only Theranos executive was Daniel Young.

Carreyrou brought along Mike Siconolfi, head of the Journal’s investigations team, and Jay Conti, the deputy general counsel of the Journal’sparent company.

Carreyrou had sent eighty questions, at Traub’s request, as a basis for the discussion.  King began the meeting by saying they were going to refute the “false premises” assumed by the questions.  The lawyers tried to intimidate Carreyrou.  King warned: “We do not consent to your publication of our trade secrets.”

Carreyrou wasn’t going to be intimidated.  He retorted: “We do not consent to waiving our journalistic privileges.”

King became more conciliatory as they agreed to start going through the questions one at a time.  Daniel Young was the only there who could answer them.

After Young acknowledged that Theranos owned commercial blood analyzers, which he claimed the company used only for comparison purposes, rather than for delivering patient results, I asked if one of them was the Siemens ADVIA.  He declined to comment, citing trade secrets.  I then asked whether Theranos ran small finger-stick samples on the Siemens ADVIA with a special dilution protocol.  He again invoked trade secrets to avoid answering the question but argued that diluting blood samples was common in the lab industry.

Carreyrou pointed out that if they weren’t prepared to answer such basic questions that were at the heart of his story, what was the point ofmeeting?  Eventually Boies got angry and criticized Carreyrou’s reporting methods, saying he asked loaded questions to doctors.  Much more back-and-forth ensued between members of the Theranos delegation and Carreyrou, Siconolfi, and Conti.

How could anything involving a commercial analyzer manufactured by a third party possibly be deemed a Theranos trade secret? I asked.  Brille replied unconvincingly that the distinction wasn’t as possible as I made it out to be.

Turning to the Edison, Carreyrou asked how many blood tests it performs.  The answer was that it was a trade secret.

I felt like I was watching a live performance of the Theater of the Absurd.

…It was frustrating but also a sign that I was on the right track. They wouldn’t be stonewalling if they had nothing to hide.

For four more hours, the meeting went on like this.  Young did answer a few questions.

He acknowledged problems with Theranos’s potassium test but claimed they had quickly been solved and none of the faulty results had been released to any patients.  Alan Beam had told me otherwise, so I suspected Young was lying about that. Young also confirmed that Theranos conducted proficiency testing differently than most laboratories but argued this was justified by the uniqueness of its technology. 

A few days later, Theranos threatened Erika Cheung with a lawsuit and also started started threatening Alan Beam again.  However, Alan had consulted a lawyer and felt less vulnerable to Theranos’s intimidation tactics.

Boies sent a twenty-three page letter to the Journal threatening a lawsuit if the paper published a story that defamed Theranos or revealed any of its trade secrets.  Boies attacked Carreyrou’s journalistic integrity.

His main evidence to back up that argument was signed statements Theranos had obtained from two of the other doctors I had spoken two claiming I had mischaracterized what they had told me and hadn’t made clear to them that I might use the information in a published article.  The doctors were Lauren Beardsley and Saman Rezaie…

The truth was that I hadn’t planned on using the patient case Dr. Beardsley and Rezaie had told me about because it was a secondhand account.  The patient in question was being treated by another doctor in their practice who had declined to speak to me.  But, while their signed statements in no way weakened my story, the likelihood that they had caved to the company’s pressure worried me.

Meanwhile, Dr. Stewart reassured Carreyrou that she was standing up for patients and for the integrity of lab testing.  She wouldn’t be pressured.  Balwani later told her that if the Journal article was published with Dr.Stewart in the story, her name would be dragged through the mud.  When Carreyrou spoke with Dr. Stewart, she asked him please not to use her name in the story.



Roger Parloff of Fortune still believed in Theranos.  During  interview with Elizabeth for a second article he was working on, he asked about an Ebola test Theranos had been developing.

Given that an Ebola epidemic had been raging in West Africa for more than a year, Parloff thought a rapid finger-stick test to detect the deadly virus could be of great use to public health authorities and had been interested in writing about it.  Holmes said she expected to obtain emergency-use authorization for the test shortly and invited him to come see a live demonstration of it at Boies Schiller’s Manhattan offices.

Parloff arrived at the offices, and they told him they wanted to do two tests, one for Ebola and the other to measure potassium.  They pricked his finger twice.

Parloff wondered fleetingly why one of the devices couldn’t simultaneously perform both tests from a single blood sample but decided not to press the issue.

For some reason, the results of the tests were delayed.  An indicator of the machine’s progress seemed to be moving very slowly.

Balwani had tasked a Theranos software engineer named Michael Craig to write an application for the miniLab’s software that masked test malfunctions.  When something went wrong insider the machine, the app kicked in and prevented an error message from appearing on the digital display.  Instead, the screen showed the test’s progress slowing to a crawl.


In the absence of real validation data, Holmes used these demos to convince board members, prospective investors, and journalists that the miniLab was a finished working product.  Michael Craig’s app wasn’t the only subterfuge used to maintain the illusion. During demos at headquarters, employees would make a show of placing the finger-stick sample of a visiting VIP in the miniLab, wait until the visitor had left the room, and then take the sample out and bring it to a lab associate, who would run it on one of the modified commercial analyzers.

Parloff had no idea he’d been duped.

Back in California, Holmes had invited Vice President Joe Biden to visit the company’s facilities.

Holmes and Balwani wanted to impress the vice president with a vision of a cutting-edge, completely automated laboratory. So instead of showing him the actual lab, they created a fake one.

Carreyrou writes:

A few days later, on July 28, I opened that morning’s edition of the Journal and nearly spit out my coffee: as I was leafing through the paper’s first section, I stumbled across an op-ed written by Elizabeth Holmes crowing about Theranos’s herpes-test approval and calling for all lab tests to be reviewed by the FDA. She’d been denying me an interview for months, her lawyers had been stonewalling and threatening my sources, and here she was using my own newspaper’s opinion pages to perpetuate the myth that she was regulators’ best friend.

Of course, because the firewall between the Journal’s news and editorial side, Paul Gigot and his staff had no idea what Carreyrou was working on.  Nonetheless, Carreyrou was annoyed because it seemed like Holmes was trying to make it more difficult for the paper to publish Carreyrou’s investigation.

Carreyrou went to speak with his editor, Mike Siconolfi, hoping they could speed up the publication of his Theranos article.  But Mike, who was Italian American, urged patience and then asked Carreyrou, “Did I ever tell you about la mattanza?”  La mattanza was an ancient Sicilian ritual in which fishermen waded into the Mediterranean Sea with clubs and spears. Then they stood perfectly still for hours until the fish no longer noticed them.  Someone would give the signal and the fishermen would strike.



Soon after Carreyrou started investigating Theranos, the company completed another round of fund-raising. They raised $430 million, $125 million of which came from Rupert Murdoch, who controlled News Corporation, the parent company of the Journal.

He was won over by Holmes’s charisma and vision but also by the financial projections she gave him.  The investment packet she sent forecast $330 million in profits on revenues of $1 billion in 2015 and $505 million in profits on revenues of $2 billion in 2016.  These numbers made what was now a $10 million valuation seem cheap.

Murdoch also derived comfort from some of the other reputable investors he heard Theranos had lined up.  They included Cox Enterprises, the Atlanta-based, family-owned conglomerate whose chairman, Jim Kennedy, he was friendly with, and the Waltons of Walmart fame.  Other big-name investors he didn’t know about ranged from Bob Kraft, owner of the New England Patriots, to Mexican billionaire Carlos Slim and John Elkann, the Italian industrialist who controlled Fiat Chrystler Automobiles.

On two separate occasions when Holmes met with Murdoch, she brought up Carreyrou’s story, saying it was false and would damage Theranos.  Both times, Murdoch maintained that he trusted the Journal’s editors to handle the matter fairly.

Meanwhile, Theranos continued to try to intimidate Carreyrou’ssources.  For instance, two patients who had appointments with Dr. Sundene fabricated negative stories and posted them on Yelp.  Dr. Sundene had to hire an attorney to get Yelp to remove the bad reviews.

The Journal finally published Carreyrou’s on the front page on Thursday, October 15, 2015.

The headline,“A Prized Startup Struggles,” was understated but the article itself was devastating.  In addition to revealing that Theranos ran all but a small fraction of its tests on conventional machines and laying bare its proficiency-testing shenanigans and its dilution of finger-stick samples, it raised serious questions about the accuracy of its own devices.  It ended with a quote from Maureen Glunz saying that “trial and error on people” was “not OK,” bringing home what I felt was the most important point: the medical danger to which the company had exposed patients.

Thestory sparked a firestorm…

Other news organization picked up the story and produced critical pieces.  In Silicon Valley,everyone was talking about the Theranos story. Some, including venture capitalist Marc Andreesen, defended Theranos.  Others revealed that they had had their doubts for some time:

Why had Holmes always been so secretive about her technology? Why had she never recruited a board member with even basic knowledge of blood science?  And why hadn’t a single venture capital firm with expertise in health care put money into the company?

Many others didn’t know what to believe.

Carreyrou writes:

We knew that the battle was far from over and that Theranos and Boies would be coming at us hard in the coming days and weeks. Whether my reporting stood up to their attacks would largely depend on what actions, if any, regulators took.

Carreyrou was trying to speak with his source at the FDA and finally reached him:

On deep background, he confirmed to me that the FDA had recently conducted a surprise inspection of Theranos’s facilities in Newark and Palo Alto. Dealing a severe blow to the company, the agency had declared its nanotainter an uncleared medical device and forbid it from continuing to use it, he said.

He explained that the FDA had targeted the little tube because, as a medical device, it clearly fell under its jurisdiction and gave it the most solid legal cover to take action against the company.  But the underlying reason for the inspection had been the poor clinical data Theranos had submitted to the agency in an effort to get it to approve its tests.  When the inspectors failed to find any better data on-site, the decision had been made to shut down the company’s finger-stick testing by taking away the nanotainter, he said.  That wasn’t all: he said the Centers for Medicare and Medicaid Services had also just launched its own inspection of Theranos.

Holmes tried to jump ahead of the story by stating that the nanotainter withdrawal was a voluntary decision.

We quickly published by follow-up piece online. Setting the record straight, it revealed that the FDA had forced the company to stop testing blood drawn from patients’ fingers and declared its nanotainter an “unapproved medical device.” The story made the front page of the paper’s print edition he next morning, providing more fuel to what was now a full-blown scandal.

Holmes called a meeting of all company employees.

Striking a defiant tone, she told the assembled staff that the two articles the Journal had published were filled with falsehoods seeded by disgruntled former employees and competitors.  This sort of thing was bound to happen when you were working to disrupt a huge industry with powerful incumbents who wanted to see you fail, she said.  Calling the Journal a “tabloid,” she vowed to take the fight to the paper.

A senior hardware engineer asked Balwani to lead them in a chant.  A few months earlier, they’d done a certain chant directed at Quest and LabCorp. Everyone remember this chant.

Balwani was glad to lead the chant again.  Several hundred employees chanted:

“Fuck you, Carrey-rou!  Fuck you, Carrey-rou!”

The following week, the Journalwas hosting the WSJ D.Live conference at which Holmes was scheduled to be interviewed. 

Holmes came out swinging from the start.  That was no surprise: we had expected her to be combative.  What we hadn’t fully anticipated was her willingness to tell bald-faced lies in a public forum.  Not just once, but again and again during the half-hour interview.  In addition to continuing to insist that the nanotainter withdrawal had been voluntary, she said the Edison devices referred to in my stories were an old technology that Theranos hadn’t used in years.  She also denied that the company had ever used commercial lab equipment for finger-stick tests.  And she claimed that the way Theranos conducted proficiency-testing was not only perfectly legal, it has the express blessing of regulators.

The biggest lie, to my mind, was her categorical denial that Theranos diluted finger-stick samples before running them on commercial machines.

By this point, several prominent Silicon Valley figures were publicly criticizing the company. John-Louis Gassee published a blog post in which he mentioned pointedly different blood-test results he received from Theranos and Stanford Hospital.  He wrote Holmes asking about the discrepancy,but never got a reply.

Shultz, Kissnger, Sam Nunn, and other ex-statesmen left the Theranos board and instead formed a board of counselors. David Boies joined the Theranos board.

Within days, the Journal received a letter from Heather King demanding a retraction of the main points of the two articles, calling them “libelous assertions.”  David Boies stated that a defamation suit was likely.  The Journal received another letter demanding that it retain all documents concerning Theranos.

But if Theranos thought this saber rattling would make us stand down, it was mistaken.  Over the next three weeks, we published four more articles.  They revealed that Walgreens had halted a planned nationwide expansion of Theranos wellness centers, that Theranos had tried to sell more shares at a higher valuation days before my first story was published, that its lab was operating without a real director, and that Safeway had walked away from their previously undisclosed partnership over concerns about its testing.

In an interview with Bloomberg Businessweek, Holmes said she was the victim of sexism.

In the same story, her old Stanford professor, Channing Robertson, dismissed questions about he accuracy of Theranos’s testing as absurd, saying the company would have to be “certifiable” to go to market with a product that people’s lives depended on knowing that it was unreliable.  He also maintained that Holmes was a once-in-a-generation genius, comparing her to Newton, Einstein, Mozart, and Leonardo da Vinci.

Carreyrou comments:

There was only one way the charade would end and that was if CMS, the chief regulatory of clinical laboratories, too strong action against the company.  I needed to find out what had come of that second regulatory inspection.



Based on a complaint from Erika Cheung, a veteran CMS field inspector, Gary Yamamoto and his colleague Sarah Bennett made a surprise inspection of Theranos’s lab.  Yamamoto and Bennett planned to spend two days, but there were so many issues that they asked for more time.  Balwani asked if they could return in two months and they agreed.

In late 2015 and early 2016, Carreyrou tried to find out about the second inspection conducted by Yamamoto and Bennett.  Finally he learned that the CMS inspectors had found “serious deficiencies.”

How serious became clear a few days later when the agency released a letter it had sent the company saying they posed “immediate jeopardy to patient health and safety.”  The letter gave the company ten days to come up with a credible correction plan and warned that failing to come back into compliance quickly could cause the lab to lose its federal certification.

This was major.  The overseer of clinical laboratories in the United States had not only confirmed that there were significant problems with Theranos’s blood tests, it had deemed the problems grave enough to put patients in immediate danger.  Suddenly, Heather King’s written retraction demands, which had been arriving like clockwork after each story we published, stopped.

However, Theranos continued to minimize the seriousness of the situation.  In a statement, it claimed to have already addressed many of the deficiencies and that the inspection findings didn’t reflect the current state of the Newark lab.  It also claimed that the problems were confined to the way the lab was run and had no bearing on the soundness of its proprietary technology.  It was impossible to disprove these claims without access to the inspection report. CMS usually made such documents public a few weeks after sending them to the offending laboratory, but Theranos was invoking trade secrets to demand that it be kept confidential…

Carreyrou filed a Freedom of Information Act request to try to force CMS to release the inspection report.

But Heather King continued to urge the agency not to make the report public without extensive redactions, claiming that doing so would expose valuable trade secrets.  It was the first time the owner of a laboratory under the threat of sanctions had demanded redactions to an inspection report, and CMS seemed unsure how to proceed.

Carreyrou finally got his hands on a copy of the CMS report.

For one thing, it proved that Holmes had lied at the Journal’s tech conference the previous fall: the proprietary devices Theranos used in the lab were indeed called “Edison,” and the report showed it had used them for only twelve of the 250 tests on its menu.  Every other test had been run on commercial analyzers.

More important, the inspection report showed, citing the lab’s own data, that the Edisons produced wildly erratic results. During one month, they had failed quality-control checks nearly a third of the time.  One of the blood tests run on the Edisons, a test to measure a hormone that affects testosterone levels, had failed quality control an astounding 87 percent of the time.  And test, to help detect prostrate cancer, had failed 22 percent of its quality-control checks.  In comparison runs using the same blood samples, the Edisons had produced results that differed from those of conventional machines by as much as 146 percent.  And just as Tyler Shultz had contended, the devices couldn’t reproduce their own results. And Edison test to measure vitamin B12 had a coefficient of variation that ranged from 34 to 48 percent, far exceeding the 2 or 3 percent common for the test at most labs.

As for the lab itself, it was a mess: the company had allowed unqualified personnel to handle patient samples, it had stored blood at the wrong temperatures, it had let reagents expire, and it had failed to inform patients of flawed test results, among many other lapses.


The coup de grace came a few days later when we obtained a new letter CMS had sent to Theranos.  It said the company had failed to correct forty-three of the forty-five deficiencies the inspectors had cited it for and threatened to ban Holmes from the blood-testing business for two years.

Carreyrou met up with Tyler Shultz.  Carreyrou points out that Tyler never buckled even though he was under enormous pressure. Moreover, his parents spent over $400,000 on legal fees.  Were it not for Tyler’s courage, Carreyrou acknowledges that he might never have gotten his first Theranos article published.  In addition, Tyler continued to be estranged from his grandfather, who continued to believe Elizabeth and not Tyler.

Not long after this meeting between Tyler and Carreyrou, Theranos contacted Tyler’s lawyers and said they knew about the meeting.  Because neither one of them had told anyone about the meeting, they realized they were under surveillance and being followed.  (Alan Beam and Erika Cheung were probably also under surveillance.)  At this juncture, Tyler wasn’t too worried, joking that next time he might take a selfie of himself and Carreyrou and sent it to Holmes “to save her the trouble of hiring PIs.”

Soon thereafter, there was more bad news for Theranos.  Carreyrou:

…we reported that Theranos had voided tens of thousands of blood-test results, including two years’ worth of Edison tests, in an effort to come back into compliance and avoid the CMS ban.  In other words, it had effectively admitted to the agency that not a single one of the blood tests run on its proprietary devices could be relied upon.  Once again, Holmes had hoped to keep the voided tests secret, but I found out about them from my new source, the one who had leaked to me CMS’s letter threatening to ban Holmes from the lab industry.  In Chicago, executives at Walgreens were astonished to learn of the scale of the test voidings.  The pharmacy chain had been trying to get answers from Theranos about the impact on its customers for months.  On June 12, 2016, it terminated the companies’partnership and shut down all the wellness centers located in its stores.

In another crippling blow, CMS followed through on its threat to ban Holmes and her company from the lab business in early July.  More ominously, Theranos was now the subject of a criminal investigation by the U.S. Attorney’s Office in San Francisco and of a parallel civil probe by the Securities and Exchange Commission. 

Many investors in Theranos were fed up:

Partner Fund, the San Francisco hedge fund that had invested closet to $100 million in the company in early 2014, sued Holmes, Balwani, and the company in Delaware’s Court of Chancery, alleging that they had deceived it with “a series of lies,material misstatements, and omissions.” Another set of investors led by the retired banker Robert Coleman filed a separate lawsuit in federal court in San Francisco.  It also alleged securities fraud and sought class-action status.

Most of the other investors opted against litigation, settling instead for a grand of extra shares in exchange for a promise not to sue.  One notable exception was Rupert Murdoch.  The media mogul sold his stock back to Theranos for one dollar so he could claim a big tax write-off on his other earnings.  With a fortune estimated at $12 billion, Murdoch could afford to lose more than a $100 million on a bad investment.


Walgreens, which had sunk a total of $140 million into Theranos, filed its own lawsuit against the company, accusing it of failing to meet the “most basic quality standards and legal requirements” of the companies’ contract.  “The fundamental premise of the parties’contract—like any endeavor involving human health—was to help people, and not to harm them,” the drugstore chain wrote in its complaint.

Carreyrou concludes the chapter:

The number of test results Theranos voided or corrected in California and Arizona eventually reached nearly 1 million.  The harm done to patients from all those faulty tests is hard to determine.  Ten patients have filed lawsuits alleging consumer fraud and medical battery.  One of them alleges that Theranos’s blood tests failed to detect his heart disease,leading him to suffer a preventable heart attack.  The suits have been consolidated into a putative class action in federal court in Arizona.  Whether the plaintiffs are able to prove injury in court remains to be seen.

One thing is certain: the chances that people would have died from missed diagnoses or wrong medical treatments would have risen expontentially if the company had expanded its blood-testing services to Walgreen’s 8,134 other U.S. stores as it was on the cusp of doing when Pathology Blawg’s Adam Clapper reached out to me.



Theranos settled the Partners Fund case for $43 million, and it settled the Walgreens lawsuit for more than $25 million.  On March 14, 2018, the Securities and Exchange Commission charged Theranos, Holmes, and Balwani with conducting “an elaborate, years-long fraud.”

To resolve the agency’s civil charges, Holmes was forced to relinquish her voting control over the company, give back a big chunk of her stock, and pay a$500,000 penalty.  She also greed to be barred from being an officer or director in a public company for ten years.  Unable to reach a settlement with Balwani, the SEC sued him in federal court in California. In the meantime, the criminal investigation continued to gather steam.  As of this writing, criminal indictments of both Holmes and Balwani on charges of lying to investors and federal officials seem a distinct possibility.

It’s one thing for a software or hardware company to overhype the arrival of its technology years before the product was ready.  The term “vaporware” describes this kind of software or hardware.  Microsoft, Apple,and Oracle were all accused of this at one point, observes Carreyrou.

But it’s crucial to bear in mind that Theranos wasn’t a tech company in the traditional sense.  It was first and foremost a health-care company.  It’s product wasn’t software but a medical device that analyzed people’s blood.  As Holmes herself liked to point out in media interviews and public appearances at the height of her fame, doctors base 70 percent of their treatment decisions on lab results.  They rely on lab equipment to work as advertised.  Otherwise, patient health is jeopardized.

So howwas Holmes able to rationalize gambling with people’s lives?

Carreyrou ends the book:

A sociopath is often described as someone with little or no conscience.  I’ll leave it to the psychologists to decide whether Holmes fits the clinical profile, but there’s no question that her moral compass was badly askew.  I’m fairly certain she didn’t initially set out to defraud investors and put patients in harm’s way when she dropped out of Stanford fifteen years ago.  By all accounts, she had a vision that she genuinely believed in and threw herself into realizing.  But in her all-consuming quest to be the second coming of Steve Jobs amid the gold rush of the “unicorn” boom, there came a point when she stopped listening to sound advice and began to cut corners.  Her ambition was voracious and it brooked no interference.  If there was collateral damage on her way to riches and fame, so be it.


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Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Seeking Wisdom

(Image:  Zen Buddha Silence by Marilyn Barbone)

December 2, 2018

In his pursuit of wisdom, Peter Bevelin was inspired by Charlie Munger’s idea:

I believe in the discipline of mastering the best of what other people have ever figured out.

Bevelin was also influenced by Munger’s statement that Charles Darwin was one of the best thinkers who ever lived.  Despite the fact that many others had much higher IQ’s.  Bevelin:

Darwin’s lesson is that even people who aren’t geniuses can outthink the rest of mankind if they develop certain thinking habits.

(Photo by Maull and Polyblank (1855), via Wikimedia Commons)

In the spirit of Darwin and Munger, and with the goal of gaining a better understanding of human behavior, Bevelin read books in biology, psychology, neuroscience, physics, and mathematics.  Bevelin took extensive notes.  The result is the book, Seeking Wisdom: From Darwin to Munger.

Here’s the outline:


  • Our anatomy sets the limits for our behavior
  • Evolution selected the connections  that produce useful behavior for survival and reproduction
  • Adaptive behavior for survival and reproduction


  • Misjudgments explained by psychology
  • Psychological reasons for mistakes


  • Systems thinking
  • Scale and limits
  • Causes
  • Numbers and their meaning
  • Probabilities and number of possible outcomes
  • Scenarios
  • Coincidences and miracles
  • Reliability of case evidence
  • Misrepresentative evidence


  • Models of reality
  • Meaning
  • Simplification
  • Rules and filters
  • Goals
  • Alternatives
  • Consequences
  • Quantification
  • Evidence
  • Backward thinking
  • Risk
  • Attitudes

(Photo by Nick Webb)


Part One:  What Influences Our Thinking


Bevelin quotes Nobel Laureate Dr. Gerald Edelman:

The brain is the most complicated material object in the known universe.  If you attempted to count the number of connections, one per second, in the mantle of the brain (the cerebral cortex), you would finish counting 32 million years later.  But that is not the whole story.  The way the brain is connected—its neuroanatomical pattern—is enormously intricate.  Within this anatomy a remarkable set of dynamic events take place in hundredths of a second and the number of levels controlling these events, from molecules to behavior, is quite large.

Neurons can send signals—electrochemical pulses—to specific target cells over long distances.  These signals are sent by axons, thin fibers that extend from neurons to other parts of the brain.  Axons can be quite long.

(Illustration by ustas)

Some neurons emit electrochemical pulses constantly while other neurons are quiet most of the time.  A single axon can have several thousand synaptic connections.  When an electrochemical pulse travels along an axon and reaches a synapse, it causes a neurotransmitter (a chemical) to be released.

The human brain contains approximately 100 trillion synapses.  From wikipedia:

The functions of these synapses are very diverse: some are excitatory (exciting the target cell); others are inhibitory; others work by activating second messenger systems that change the internal chemistry of their target cells in complex ways.  A large number of synapses are dynamically modifiable; that is, they are capable of changing strength in a way that is controlled by the patterns of signals that pass through them.  It is widely believed that activity-dependent modification of synapses is the brain’s primary mechanism for learning and memory.

Most of the space in the brain is taken up by axons, which are often bundled together in what are called nerve fiber tracts.  A myelinated axon is wrapped in a fatty insulating sheath of myelin, which serves to greatly increase the speed of signal propagation.  (There are also unmyelinated axons).  Myelin is white, making parts of the brain filled exclusively with nerve fibers appear as light-colored white matter, in contrast to the darker-colored grey matter that marks areas with high densities of neuron cell bodies.

Genes, life experiences, and randomness determine how neurons connect.

Also, everything that happens in the brain involves many areas at once (the left brain versus right brain distinction is not strictly accurate).  This is part of why the brain is so flexible.  There are different ways for the brain to achieve the same result.



Bevelin writes:

If certain connections help us interact with our environment, we use them more often than connections that don’t help us.  Since we use them more often, they become strengthened.

Evolution has given us preferences that help us classify what is good or bad.  When these values are satisfied (causing either pleasure or less pain) through the interaction with our environment, these neural connections are strengthened.  These values are reinforced over time because they give humans advantages for survival and reproduction in dealing with their environment.

(Illustration by goce risteski)

If a certain behavior is rewarding, the neural connections associated with that behavior get strengthened.  The next time the same situation is encountered, we feel motivated to respond in the way that we’ve learned brings pleasure (or reduces pain).  Bevelin:

We do things that we associate with pleasure and avoid things that we associate with pain.




The consequences of our actions reinforce certain behavior.  If the consequences were rewarding, our behavior is likely to be repeated.  What we consider rewarding is individual specific.  Rewards can be anything from health, money, job, reputation, family, status, or power.  In all of these activities, we do what works.  This is how we adapt.  The environment selects our future behavior.

Illustration by kalpis

Especially in a random environment like the stock market, it can be difficult to figure out what works and what doesn’t.  We may make a good decision based on the odds, but get a poor outcome.  Or we may make a bad decision based on the odds, but get a good outcome.  Only over the course of many decisions can we tell if our investment process is probably working.


Part Two:  The Psychology of Misjudgments


Illustration by intheskies

Bevelin lists 28 reasons for misjudgments and mistakes:

  1. Bias from mere association—automatically connecting a stimulus with pain or pleasure; including liking or disliking something associated with something bad or good.  Includes seeing situations as identical because they seem similar.  Also bias from Persian Messenger Syndrome—not wanting to be the carrier of bad news.
  2. Underestimating the power of incentives (rewards and punishment)—people repeat actions that result in rewards and avoid actions that they are punished for.
  3. Underestimating bias from own self-interest and incentives.
  4. Self-serving bias—overly positive view of our abilities and future.  Includes over-optimism.
  5. Self-deception and denial—distortion of reality to reduce pain or increase pleasure.  Includes wishful thinking.
  6. Bias from consistency tendency—being consistent with our prior commitments and ideas even when acting against our best interest or in the face of disconfirming evidence.  Includes Confirmation Bias—looking for evidence that confirms our actions and beliefs and ignoring or distorting disconfirming evidence.
  7. Bias from deprival syndrome—strongly reacting (including desiring and valuing more) when something we like and have (or almost have) is (or threatens to be) taken away or “lost.”  Includes desiring and valuing more what we can’t have or what is (or threatens to be) less available.
  8. Status quo bias and do-nothing syndrome—keeping things the way they are.  Includes minimizing effort and a preference for default options.
  9. Impatience—valuing the present more highly than the future.
  10. Bias from envy and jealousy.
  11. Distortion by contrast comparison—judging and perceiving the absolute magnitude of something not by itself but based only on its difference to something else presented closely in time or space or to some earlier adaptation level.  Also underestimating the consequences over time of gradual changes.
  12. The anchoring effect—People tend to use any random number as a baseline for estimating an unknown quantity, despite the fact that the unknown quantity is totally unrelated to the random number.  (People also overweigh initial information that is non-quantitative.)
  13. Over-influence by vivid or the most recent information.
  14. Omission and abstract blindness—only seeing stimuli we encounter or that grabs our attention, and neglecting important missing information or the abstract.  Includes inattentional blindness.
  15. Bias from reciprocation tendency—repaying in kind what others have done for or to us like favors, concessions, information, and attitudes.
  16. Bias from over-influence by liking tendency—believing, trusting, and agreeing with people we know and like.  Includes bias from over-desire for liking and social acceptance and for avoiding social disapproval.  Also bias from disliking—our tendency to avoid and disagree with people we don’t like.
  17. Bias from over-influence by social proof—imitating the behavior of many others or similar others.  Includes crowd folly.
  18. Bias from over-influence by authority—trusting and obeying a perceived authority or expert.
  19. The Narrative Fallacy (Bevelin uses the term “Sensemaking”)—constructing explanations that fit an outcome.  Includes being too quick in drawing conclusions.  Also Hindsight Bias: Thinking events that have happened were more predictable than they were.
  20. Reason-respecting—complying with requests merely because we’ve been given a reason.  Includes underestimating the power in giving people reasons.
  21. Believing first and doubting later—believing what is not true, especially when distracted.
  22. Memory limitations—remembering selectively and wrong.  Includes influence by suggestions.
  23. Do-something syndrome—acting without a sensible reason.
  24. Mental confusion from say-something syndrome—feeling a need to say something when we have nothing to say.
  25. Emotional arousal—making hasty judgments under the influence of intense emotions.  Includes exaggerating the emotional impact of future events.
  26. Mental confusion from stress.
  27. Mental confusion from physical or psychological pain, and the influence of chemicalsa li.
  28. Bias from over-influence by the combined effect of many psychological tendencies operating together.



Bevelin notes that his explanations for the 28 reasons for misjudgments is based on work by Charles Munger, Robert Cialdini, Richard Thaler, Robyn Dawes, Daniel Gilbert, Daniel Kahneman, and Amos Tversky.  All are psychologists except for Thaler (economist) and Munger (investor).

1. Mere Association


Association can influence the immune system.  One experiment studied food aversion in mice.  Mice got saccharin-flavored water (saccharin has incentive value due to its sweet taste) along with a nausea-producing drug.  Would the mice show signs of nausea the next time they got saccharin water alone?  Yes, but the mice also developed infections.  It was known that the drug in addition to producing nausea, weakened the immune system, but why would saccharin alone have this effect?  The mere paring of the saccharin with the drug caused the mouse immune system to learn the association.  Therefore, every time the mouse encountered the saccharin, its immune system weakened making the mouse more vulnerable to infections.

If someone brings us bad news, we tend to associate that person with the bad news—and dislike them—even if the person didn’t cause the bad news.

2. Incentives (Reward and Punishment)

Incentives are extremely important.   Charlie Munger:

I think I’ve been in the top 5% of my age cohort all my life in understanding the power of incentives, and all my life I’ve underestimated it.  Never a year passes that I don’t get some surprise that pushes my limit a little farther.

Munger again:

From all business, my favorite case on incentives is Federal Express.  The heart and soul of their system—which creates the integrity of the product—is having all their airplanes come to one place in the middle of the night and shift all the packages from plane to plane.  If there are delays, the whole operation can’t deliver a product full of integrity to Federal Express customers.  And it was always screwed up.  They could never get it done on time.  They tried everything—moral suasion, threats, you name it.  And nothing worked.  Finally, somebody got the idea to pay all these people not so much an hour, but so much a shift—and when it’s all done, they can all go home.  Well, their problems cleared up over night.

People can learn the wrong incentives in a random environment like the stock market.  A good decision based on the odds may yield a bad result, while a bad decision based on the odds may yield a good result.  People tend to become overly optimistic after a success (even if it was good luck) and overly pessimistic after a failure (even if it was bad luck).

3. Self-interest and Incentives

“Never ask the barber if you need a haircut.”

Munger has commented that commissioned sales people, consultants, and lawyers have a tendency to serve the transaction rather than the truth.  Many others—including bankers and doctors—are in the same category.  Bevelin quotes the American actor Walter Matthau:

“My doctor gave me six months to live.  When I told him I couldn’t pay the bill, he gave me six more months.”

If they make unprofitable loans, bankers may be rewarded for many years while the consequences of the bad loans may not occur for a long time.

When designing a system, careful attention must be paid to incentives.  Bevelin notes that a new program was put in place in New Orleans: districts that showed improvement in crime statistics would receive rewards, while districts that didn’t faced cutbacks and firings.  As a result, in one district, nearly half of all serious crimes were re-classified as minor offences and never fully investigated.

4. Self-serving Tendencies and Overoptimism 

We tend to overestimate our abilities and future prospects when we are knowledgeable on a subject, feel in control, or after we’ve been successful.

Bevelin again:

When we fail, we blame external circumstances or bad luck.  When others are successful, we tend to credit their success to luck and blame their failures on foolishness.  When our investments turn into losers, we had bad luck.  When they turn into winners, we are geniuses.  This way we draw the wrong conclusions and don’t learn from our mistakes.  We also underestimate luck and randomness in outcomes.

5. Self-deception and Denial

Munger likes to quote Demosthenes:

Nothing is easier than self-deceit.  For what each man wishes, that he also believes to be true.

People have a strong tendency to believe what they want to believe.  People prefer comforting illusions to painful truths.

Richard Feynman:

The first principle is that you must not fool yourself—and you are the easiest person to fool.

6. Consistency


Once we’ve made a commitment—a promise, a choice, taken a stand, invested time, money, or effort—we want to remain consistent.  We want to feel that we’ve made the right decision.  And the more we have invested in our behavior the harder it is to change.

The more time, money, effort, and pain we invest in something, the more difficulty we have at recognizing a mistaken commitment.  We don’t want to face the prospect of a big mistake.

For instance, as the Vietnam War became more and more a colossal mistake, key leaders found it more and more difficult to recognize the mistake and walk away.  The U.S. could have walked away years earlier than it did, which would have saved a great deal of money and thousands of lives.

Bevelin quotes Warren Buffett:

What the human being is best at doing is interpreting all new information so that their prior conclusions remain intact.

Even scientists, whose job is to be as objective as possible, have a hard time changing their minds after they’ve accepted the existing theory for a long time.  Physicist Max Planck:

A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it.

7. Deprival Syndrome


When something we like is (or threatens to be) taken away, we often value it higher.  Take away people’s freedom, status, reputation, money, or anything they value, and they get upset… The more we like what is taken away or the larger the commitment we’ve made, the more upset we become.  This can create hatreds, revolts, violence, and retaliations.

Fearing deprival, people will be overly conservative or will engage in cover-ups.

A good value investor is wrong roughly 40 percent of the time.  However, due to deprival syndrome and loss aversion—the pain of a loss is about 2 to 2.5 times greater than the pleasure of an equivalent gain—investors have a hard time admitting their mistakes and moving on.  Admitting a mistake means accepting a loss of money and also recognizing our own fallibility.

Furthermore, deprival syndrome makes us keep trying something if we’ve just experienced a series of near misses.  We feel that “we were so close” to getting some reward that we can’t give up now, even if the reward may not be worth the expected cost.

Finally, the harder it is to get something, the  more value we tend to place on it.

8. Status Quo and Do-Nothing Syndrome

We feel worse about a harm or loss if it results from our action than if it results from our inaction.  We prefer the default option—what is selected automatically unless we change it.  However, as Bevelin points out, doing nothing is still a decision and the cost of doing nothing could be greater than the cost of taking an action.

In countries where being an organ donor is the default choice, people strongly prefer to be organ donors.  But in countries where not being an organ donor is the default choice, people prefer not to be organ donors.  In each case, most people simply go with the default option—the status quo.  But society is better off if most people are organ donors.

9. Impatience

We value the present more than the future.  We often seek pleasure today at the cost of a potentially better future.  It’s important to understand that pain and sacrifice today—if done for the right reasons—can lead to greater happiness in the future.

10. Envy and Jealousy

Charlie Munger and Warren Buffett often point out that envy is a stupid sin because—unlike other sins like gluttony—there’s no upside.  Also, jealousy is among the top three motives for murder.

It’s best to set goals and work towards them without comparing ourselves to others.  Partly by chance, there are always some people doing better and some people doing worse.

11. Contrast Comparison

The classic demonstration of contrast comparison is to stick one hand in cold water and the other hand in warm water.  Then put both hands in a buck with room temperature water.  Your cold hand will feel warm while your warm hand will feel cold.

Bevelin writes:

We judge stimuli by differences and changes and not absolute magnitudes.  For example, we evaluate stimuli like temperature, loudness, brightness, health, status, or prices based on their contrast or difference from a reference point (the prior or concurrent stimuli or what we have become used to).  This reference point changes with new experiences and context.

How we value things depends on what we compare them with.

Salespeople, after selling the main item, often try to sell add-ons, which seem cheap by comparison.  If you buy a car for $50,000, then adding an extra $1,000 for leather doesn’t seem like much.  If you buy a computer for $1,500, then adding an extra $50 seems inconsequential.

Bevelin observes:

The same thing may appear attractive when compared to less attractive things and unattractive when compared to more attractive things.  For example, studies show that a person of average attractiveness is seen as less attractive when compared to more attractive others.

One trick some real estate agents use is to show the client a terrible house at an absurdly high price first, and then show them a merely mediocre house at a somewhat high price.  The agent often makes the sale.

Munger has remarked that some people enter into a bad marriage because their previous marriage was terrible.  These folks make the mistake of thinking that what is better based on their own limited experience is the same as what is better based on the experience of many different people.

Another issue is that something can gradually get much worse over time, but we don’t notice it because each increment is small.  It’s like the frog in water where the water is slowly brought to the boiling point.  For instance, the behavior of some people may get worse and worse and worse.  But we fail to notice because the change is too gradual.

12. Anchoring

The anchoring effect:  People tend to use any random number as a baseline for estimating an unknown quantity, despite the fact that the unknown quantity is totally unrelated to the random number.  (People also overweigh initial information that is non-quantitative.)

Daniel Kahneman and Amos Tversky did one experiment where they spun a wheel of fortune, but they had secretly programmed the wheel so that it would stop on 10 or 65.   After the wheel stopped, participants were asked to estimate the percentage of African countries in the UN.   Participants who saw “10” on the wheel guessed 25% on average, while participants who saw “65” on the wheel guessed 45% on average, a huge difference.

Behavioral finance expert James Montier has run his own experiment on anchoring.   People are asked to write down the last four digits of their phone number.   Then they are asked whether the number of doctors in their capital city is higher or lower than the last four digits of their phone number.   Results:  Those whose last four digits were greater than 7000 on average report 6762 doctors, while those with telephone numbers below 2000 arrived at an average 2270 doctors.  (James Montier, Behavioural Investing, Wiley 2007, page 120)

Those are just two experiments out of many.  The anchoring effect is “one of the most reliable and robust results of experimental psychology,” says Kahneman.  Furthermore, Montier observes that the anchoring effect is one reason why people cling to financial forecasts, despite the fact that most financial forecasts are either wrong, useless, or impossible to time.

When faced with the unknown, people will grasp onto almost anything.  So it is little wonder that an investor will cling to forecasts, despite their uselessness. 

13. Vividness and Recency

Bevelin explains:

The more dramatic, salient, personal, entertaining, or emotional some information, event, or experience is, the more influenced we are.  For example, the easier it is to imagine an event, the more likely we are to think that it will happen.

We are easily influenced when we are told stories because we relate to stories better than to logic or fact.  We love to be entertained.  Information we receive directly, through our eyes or ears has more impact than information that may have more evidential value.  A vivid description from a friend or family member is more believable than true evidence.  Statistical data is often overlooked.  Studies show that jurors are influenced by vivid descriptions.  Lawyers try to present dramatic and memorable testimony.

The media capitalizes on negative events—especially if they are vivid—because negative news sells.  For instance, even though the odds of being in a plane crash are infinitesimally low—one in 11 million—people become very fearful when a plane crash is reported in the news.  Many people continue to think that a car is safer than a plane, but you are over 2,000 times more likely to be in a car crash than a plane crash.  (The odds of being in a car crash are one in 5,000.)

14. Omission and Abstract Blindness

We see the available information.  We don’t see what isn’t reported.  Missing information doesn’t draw our attention.  We tend not to think about other possibilities, alternatives, explanations, outcomes, or attributes.  When we try to find out if one thing causes another, we only see what happened, not what didn’t happen.  We see when a procedure works, not when it doesn’t work.  When we use checklists to find out possible reasons for why something doesn’t work, we often don’t see that what is not on the list in the first place may be the reason for the problem.

Often we don’t see things right in front of us if our attention is focused elsewhere.

15. Reciprocation


The automatic tendency of humans to reciprocate both favors and disfavors has long been noticed as it is in apes, monkeys, dogs, and many less cognitively gifted animals.  The tendency facilitates group cooperation for the benefit of members.

Unfortunately, hostility can get extreme.  But we have the ability to train ourselves.  Munger:

The standard antidote to one’s overactive hostility is to train oneself to defer reaction.  As my smart friend Tom Murphy so frequently says, ‘You can always tell the man off tomorrow, if it is such a good idea.’

Munger then notes that the tendency to reciprocate favor for favor is also very intense.  On the whole, Munger argues, the reciprocation tendency is a positive:

Overall, both inside and outside religions, it seems clear to me that Reciprocation Tendency’s constructive contributions to man far outweigh its destructive effects…

And the very best part of human life probably lies in relationships of affection wherein parties are more interested in pleasing than being pleased—a not uncommon outcome in display of reciprocate-favor tendency.

Guilt is also a net positive, asserts Munger:

…To the extent the feeling of guilt has an evolutionary base, I believe the most plausible cause is the mental conflict triggered in one direction by reciprocate-favor tendency and in the opposite direction by reward superresponse tendency pushing one to enjoy one hundred percent of some good thing… And if you, like me… believe that, averaged out, feelings of guilt do more good than harm, you may join in my special gratitude for reciprocate-favor tendency, no matter how unpleasant you find feelings of guilt.

16. Liking and Disliking


One very practical consequence of Liking/Loving Tendency is that it acts as a conditioning device that makes the liker or lover tend (1) to ignore faults of, and comply with wishes of, the object of his affection, (2) to favor people, products, and actions merely associated with the object of his affection [this is also due to Bias from Mere Association] and (3) to distort other facts to facilitate love.

We’re naturally biased, so we have to be careful in some situations.

On the other hand, Munger points out that loving admirable persons and ideas can be very beneficial.

…a man who is so constructed that he loves admirable persons and ideas with a special intensity has a huge advantage in life.  This blessing came to both Buffett and myself in large measure, sometimes from the same persons and ideas.  One common, beneficial example for us both was Warren’s uncle, Fred Buffett, who cheerfully did the endless grocery-store work that Warren and I ended up admiring from a safe distance.  Even now, after I have known so many other people, I doubt if it is possible to be a nicer man than Fred Buffett was, and he changed me for the better.

Warren Buffett:

If you tell me who your heroes are, I’ll tell you how you’re gonna turn out.  It’s really important in life to have the right heroes.  I’ve been very lucky in that I’ve probably had a dozen or so major heroes.  And none of them have ever let me down.  You want to hang around with people that are better than you are.  You will move in the direction of the crowd that you associate with.

Disliking: Munger notes that Switzerland and the United States have clever political arrangements to “channel” the hatreds and dislikings of individuals and groups into nonlethal patterns including elections.

But the dislikings and hatreds never go away completely…  And we also get the extreme popularity of very negative political advertising in the United States.

Munger explains:

Disliking/Hating Tendency also acts as a conditioning device that makes the disliker/hater tend to (1) ignore virtues in the object of dislike, (2) dislike people, products, and actions merely associated with the object of dislike, and (3) distort other facts to facilitate hatred.

Distortion of that kind is often so extreme that miscognition is shockingly large…

17. Social Proof

Munger comments:

The otherwise complex behavior of man is much simplified when he automatically thinks and does what he observes to be thought and done around him.  And such followership often works fine…

Psychology professors love Social-Proof Tendency because in their experiments it causes ridiculous results.  For instance, if a professor arranges for some stranger to enter an elevator wherein ten ‘compliance practitioners’ are all standing so that they face the rear of the elevator, the stranger will often turn around and do the same.

Of course, like the other tendencies, Social Proof has an evolutionary basis.  If the crowd was running in one direction, typically your best response was to follow.

But, in today’s world, simply copying others often doesn’t make sense.  Munger:

And in the highest reaches of business, it is not at all uncommon to find leaders who display followership akin to that of teenagers.  If one oil company foolishly buys a mine, other oil companies often quickly join in buying mines.  So also if the purchased company makes fertilizer.  Both of these oil company buying fads actually bloomed, with bad results.

Of course, it is difficult to identify and correctly weigh all the possible ways to deploy the cash flow of an oil company.  So oil company executives, like everyone else, have made many bad decisions that were triggered by discomfort from doubt.  Going along with social proof provided by the action of other oil companies ends this discomfort in a natural way.

Munger points out that Social Proof can sometimes be constructive:

Because both bad and good behavior are made contagious by Social-Proof Tendency, it is highly important that human societies (1) stop any bad behavior before it spreads and (2) foster and display all good behavior.

It’s vital for investors to be able to think independently.  As Ben Graham says:

You are neither right nor wrong because the crowd disagrees with you.  You are right because your data and reasoning are right.

18. Authority

A disturbingly significant portion of copilots will not correct obvious errors made by the pilot during simulation exercises.  There are also real world examples of copilots crashing planes because they followed the pilot mindlessly.  Munger states:

…Such cases are also given attention in the simulator training of copilots who have to learn to ignore certain really foolish orders from boss pilots because boss pilots will sometimes err disastrously.  Even after going through such a training regime, however, copilots in simulator exercises will too often allow the simulated plane to crash because of some extreme and perfectly obvious simulated error of the chief pilot.

Psychologist Stanley Milgram wanted to understand why so many seemingly normal and decent people engaged in horrific, unspeakable acts during World War II.  Munger:

[Milgram] decided to do an experiment to determine exactly how far authority figures could lead ordinary people into gross misbehavior.  In this experiment, a man posing as an authority figure, namely a professor governing a respectable experiment, was able to trick a great many ordinary people into giving what they had every reason to believe were massive electric shocks that inflicted heavy torture on innocent fellow citizens…

Almost any intelligent person with my checklist of psychological tendencies in his hand would, by simply going down the checklist, have seen that Milgram’s experiment involved about six powerful psychological tendencies acting in confluence to bring about his extreme experimental result.  For instance, the person pushing Milgram’s shock lever was given much social proof from presence of inactive bystanders whose silence communicated that his behavior was okay…

Bevelin quotes the British novelist and scientist Charles Percy Snow:

When you think of the long and gloomy history of man, you will find more hideous crimes have been committed in the name of obedience than have ever been committed in the name of rebellion.

19. The Narrative Fallacy (Sensemaking)

(Bevelin uses the term “sensemaking,” but “narrative fallacy” is better, in my view.)  In The Black Swan, Nassim Taleb writes the following about the narrative fallacy:

The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship, upon them.  Explanations bind facts together.  They make them all the more easily remembered;  they help them make more sense.  Where this propensity can go wrong is when it increases our impression of understanding.

The narrative fallacy is central to many of the biases and misjudgments mentioned by Charlie Munger.  (In his great book, Thinking, Fast and Slow, Daniel Kahneman discusses the narrative fallacy as a central cognitive bias.)  The human brain, whether using System 1 (intuition) or System 2 (logic), always looks for or creates logical coherence among random data.  Often System 1 is right when it assumes causality; thus, System 1 is generally helpful, thanks to evolution.  Furthermore, System 2, by searching for underlying causes or coherence, has, through careful application of the scientific method over centuries, developed a highly useful set of scientific laws by which to explain and predict various phenomena.

The trouble comes when the data or phenomena in question are highly random—or inherently unpredictable (at least for the time being).  In these areas, System 1 makes predictions that are often very wrong.  And even System 2 assumes necessary logical connections when there may not be any—at least, none that can be discovered for some time.

Note:  The eighteenth century Scottish philosopher (and psychologist) David Hume was one of the first to clearly recognize the human brain’s insistence on always assuming necessary logical connections in any set of data or phenomena.

If our goal is to explain certain phenomena scientifically, then we have to develop a testable hypothesis about what will happen (or what will happen with probability x) under specific, relevant conditions.  If our hypothesis can’t accurately predict what will happen under specific, relevant conditions, then our hypothesis is not a valid scientific explanation.

20. Reason-respecting

We are more likely to comply with a request if people give us a reason—even if we don’t understand the reason or if it’s wrong.  In one experiment, a person approaches people standing in line waiting to use a copy machine and says, “Excuse me, I have 5 pages.  May I use the Xerox machine because I have to make some copies?”  Nearly everyone agreed.

Bevelin notes that often the word “because” is enough to convince someone, even if no actual reason is given.

21. Believe First and Doubt Later

We are not natural skeptics.  We find it easy to believe but difficult to doubt.  Doubting is active and takes effort.

Bevelin continues:

Studies show that in order to understand some information, we must first accept it as true… We first believe all information we understand and only afterwards and with effort do we evaluate, and if necessary, un-believe it.

Distraction, fatigue, and stress tend to make us less likely to think things through and more likely to believe something that we normally might doubt.

When it comes to detecting lies, many (if not most) people are only slightly better than chance.  Bevelin quotes Michel de Montaigne:

If falsehood, like truth, had only one face, we would be in better shape.  For we would take as certain the opposite of what the liar said.  But the reverse of truth has a hundred thousand shapes and a limitless field.

22. Memory Limitations


Our memory is selective.  We remember certain things and distort or forget others.  Every time we recall an event, we reconstruct our memories.  We only remember fragments of our real past experiences.  Fragments influenced by what we have learned, our experiences, beliefs, mood, expectations, stress, and biases.

We remember things that are dramatic, fearful, emotional, or vivid.  But when it comes to learning in general—as opposed to remembering—we learn better when we’re in a positive mood.

Human memory is flawed to the point that eyewitness identification evidence has been a significant cause of wrongful convictions.  Moreover, leading and suggestive questions can cause misidentification.  Bevelin:

Studies show that it is easy to get a witness to believe they saw something when they didn’t.  Merely let some time pass between their observation and the questioning.  Then give them false or emotional information about the event.

23. Do-something Syndrome

Activity is not the same thing as results.  Most people feel impelled by boredom or hubris to be active.  But many things are not worth doing.

If we’re long-term investors, then nearly all of the time the best thing for us to do is nothing at all (other than learn).  This is especially true if we’re tired, stressed, or emotional.

24. Say-something Syndrome

Many people have a hard time either saying nothing or saying, “I don’t know.”  But it’s better for us to say nothing if we have nothing to say.  It’s better to admit “I don’t know” rather than pretend to know.

25. Emotions

Bevelin writes:

We saw under loss aversion and deprival that we put a higher value on things we already own than on the same things if we don’t own them.  Sadness reverses this effect, making us willing to accept less money to sell something than we would pay to buy it.

It’s also worth repeating: If we feel emotional, it’s best to defer important decisions whenever possible.

26. Stress

A study showed that business executives who are committed to their work and who have a positive attitude towards challenges—viewing them as opportunities for growth—do not get sick from stress.  Business executives who lack such commitment or who lack a positive attitude towards challenges are more likely to get sick from stress.

Stress itself is essential to life.  We need challenges.  What harms us is not stress but distress—unnecessary anxiety and unhelpful trains of thought.  Bevelin quotes the stoic philosopher Epictetus:

Happiness and freedom begin with a clear understanding of one principle: Some things are within our control, and some things are not.  It is only after you have faced up to this fundamental rule and learned to distinguish between what you can and can’t control that inner tranquility and outer effectiveness become possible.

27. Pain and Chemicals

People struggle to think clearly when they are in pain or when they’re drunk or high.

Munger argues that if we want to live a good life, first we should list the things that can ruin a life.  Alcohol and drugs are near the top of the list.  Self-pity and a poor mental attitude will also be on that list.  We can’t control everything that happens, but we can always control our mental attitude.  As the Austrian psychiatrist and Holocaust survivor Viktor Frankl said:

Everything can be taken from a man but one thing: the last of the human freedoms—to choose one’s attitude in any given set of circumstances, to choose one’s own way.

28. Multiple Tendencies

Often multiple psychological tendencies operate at the same time.  Bevelin gives an example where the CEO makes a decision and expects the board of directors to go along without any real questions.  Bevelin explains:

Apart from incentive-caused bias, liking, and social approval, what are some other tendencies that operate here?  Authority—the CEO is the authority figure whom directors tend to trust and obey.  He may also make it difficult for those who question him.  Social proof—the CEO is doing dumb things but no one else is objecting so all directors collectively stay quiet—silence equals consent; illusions of the group as invulnerable and group pressure (loyalty) may also contribute.  Reciprocation—unwelcome information is withheld since the CEO is raising the director fees, giving them perks, taking them on trips or letting them use the corporate jet.  Association and Persian Messenger Syndrome—a single director doesn’t want to be the carrier of bad news.  Self-serving tendencies and optimism—feelings of confidence and optimism: many boards also select new directors who are much like themselves; that share similar ideological viewpoints.  Deprival—directors don’t want to lose income and status.  Respecting reasons no matter how illogical—the CEO gives them reasons.  Believing first and doubting later—believing what the CEO says even if not true, especially when distracted.  Consistency—directors want to be consistent with earlier decisions—dumb or not.


Part Three:  The Physics and Mathematics of Misjudgments


  • Failing to consider that actions have both intended and unintended consequences.  Includes failing to consider secondary and higher order consequences and inevitable implications.
  • Failing to consider the whole system in which actions and reactions take place, the important factors that make up the system, their relationships and effects of changes on system outcome.
  • Failing to consider the likely reaction of others—what is best to do may depend on what others do.
  • Failing to consider the implications of winning a bid—overestimating value and paying too much.
  • Overestimating predictive ability or using unknowable factors in making predictions.



  • Failing to consider that changes in size or time influence form, function, and behavior.
  • Failing to consider breakpoints, critical thresholds, or limits.
  • Failing to consider constraints—that a system’s performance is constrained by its weakest link.



  • Not understanding what causes desired results.
  • Believing cause resembles its effect—that a big effect must have a big or complicated cause.
  • Underestimating the influence of randomness in bad or good outcomes.
  • Mistaking an effect for its cause.  Includes failing to consider that many effects may originate from one common root cause.
  • Attributing outcome to a single cause when there are multiple causes.
  • Mistaking correlation for cause.
  • Failing to consider that an outcome may be consistent with alternative explanations.
  • Drawing conclusions about causes from selective data.  Includes identifying the wrong cause because it seems the obvious one based on a single observed effect.  Also failing to consider information or evidence that is missing.
  • Not comparing the difference in conditions, behavior, and factors between negative and positive outcomes in similar situations when explaining an outcome.



  • Looking at isolated numbers—failing to consider relationships and magnitudes.  Includes not using basic math to count and quantify.  Also not differentiating between relative and absolute risk.
  • Underestimating the effect of exponential growth.
  • Underestimating the time value of money.



  • Underestimating risk exposure in situations where relative frequency (or comparable data) and/or magnitude of consequences is unknown or changing over time.
  • Underestimating the number of possible outcomes for unwanted events.  Includes underestimating the probability and severity of rate or extreme events.
  • Overestimating the chance of rare but widely publicized and highly emotional events and underestimating the chance of common but less publicized events.
  • Failing to consider both probabilities and consequences (expected value).
  • Believing events where chance plays a role are self-correcting—that previous outcomes of independent events have predictive value in determining future outcomes.
  • Believing one can control the outcome of events where chance is involved.
  • Judging financial decisions by evaluating gains and losses instead of final state of wealth and personal value.
  • Failing to consider the consequences of being wrong.



  • Overestimating the probability of scenarios where all of a series of steps must be achieved for a wanted outcome.  Also underestimating opportunities for failure and what normally happens in similar situations.
  • Underestimating the probability of systems failure—scenarios composed of many parts where system failure can happen one way or another.  Includes failing to consider that time horizon changes probabilities.  Also assuming independence when it is not present and/or assuming events are equally likely when they are not.
  • Not adding a factor of safety for known and unknown risks.  Size of factor depends on the consequences of failure, how well the risks are understood, systems characteristics, and degree of control.



  • Underestimating that surprises and improbable events happen, somewhere, sometime, to someone, if they have enough opportunities (large enough size or time) to happen.
  • Looking for meaning, searching for causes, and making up patterns for chance events, especially events that have emotional implications.
  • Failing to consider cases involving the absence of a cause or effect.



  • Overweighing individual case evidence and under-weighing the prior probability (probability estimate of an event before considering new evidence that might change it) considering for example, the base rate (relative frequency of an attribute or event in a representative comparison group), or evidence from many similar cases.  Includes failing to consider the probability of a random match, and the probability of a false positive and a false negative.  Also failing to consider a relevant comparison population that bears the characteristic we are seeking.



  • Failing to consider changes in factors, context, or conditions when using past evidence to predict likely future outcomes.  Includes not searching for explanations to why a past outcome happened, what is required to make the past record continue, and what forces can change it.
  • Overestimating evidence from a single case or small or unrepresentative samples.
  • Underestimating the influence of chance in performance (success and failure)
  • Only seeing positive outcomes—paying little or no attention to negative outcomes and prior probabilities.
  • Failing to consider variability of outcomes and their frequency.
  • Failing to consider regression—in any series of events where chance is involved, unique outcomes tend to regress back to the average outcome.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC

Buffett’s Best: Microcap Cigar Butts

(Image:  Zen Buddha Silence by Marilyn Barbone)

November 25, 2018

Warren Buffett, the world’s greatest investor, earned the highest returns of his career from microcap cigar butts.  Buffett wrote in the 2014 Berkshire Letter:

My cigar-butt strategy worked very well while I was managing small sums.  Indeed, the many dozens of free puffs I obtained in the 1950’s made the decade by far the best of my life for both relative and absolute performance.

Even then, however, I made a few exceptions to cigar butts, the most important being GEICO.  Thanks to a 1951 conversation I had with Lorimer Davidson, a wonderful man who later became CEO of the company, I learned that GEICO was a terrific business and promptly put 65% of my $9,800 net worth into its shares.  Most of my gains in those early years, though, came from investments in mediocre companies that traded at bargain prices.  Ben Graham had taught me that technique, and it worked.

But a major weakness in this approach gradually became apparent:  Cigar-butt investing was scalable only to a point.  With large sums, it would never work well…

Before Buffett led Berkshire Hathaway, he managed an investment partnership from 1957 to 1970 called Buffett Partnership Ltd. (BPL).  While running BPL, Buffett wrote letters to limited partners filled with insights (and humor) about investing and business.  Jeremy C. Miller has written a great book— Warren Buffett’s Ground Rules (Harper, 2016)—summarizing the lessons from Buffett’s partnership letters.

This blog post considers a few topics related to microcap cigar butts:

  • Net Nets
  • Dempster: The Asset Conversion Play
  • Liquidation Value or Earnings Power?
  • Mean Reversion for Cigar Butts
  • Focused vs. Statistical
  • The Rewards of Psychological Discomfort
  • Conclusion



Here Miller quotes the November 1966 letter, in which Buffett writes about valuing the partnership’s controlling ownership position in a cigar-butt stock:

…Wide changes in the market valuations accorded stocks at some point obviously find reflection in the valuation of businesses, although this factor is of much less importance when asset factors (particularly when current assets are significant) overshadow earnings power considerations in the valuation process…

Ben Graham’s primary cigar-butt method was net nets.  Take net current asset value minus ALL liabilities, and then only buy the stock at 2/3 (or less) of that level.  If you buy a basket (at least 20-30) of such stocks, then given enough time (at least a few years), you’re virtually certain to get good investment results, predominantly far in excess of the broad market.

A typical net-net stock might have $30 million in cash, with no debt, but have a market capitalization of $20 million.  Assume there are 10 million shares outstanding.  That means the company has $3/share in net cash, with no debt.  But you can buy part ownership of this business by paying only $2/share.  That’s ridiculously cheap.  If the price remained near those levels, you could effectively buy $1 million in cash for $667,000—and repeat the exercise many times.

Of course, a company that cheap almost certainly has problems and may be losing money.  But every business on the planet, at any given time, is in either one of two states:  it is having problems, or it will be having problems.  When problems come—whether company-specific, industry-driven, or macro-related—that often causes a stock to get very cheap.

The key question is whether the problems are temporary or permanent.  Statistically speaking, many of the problems are temporary when viewed over the subsequent 3 to 5 years.  The typical net-net stock is so extremely cheap relative to net tangible assets that usually something changes for the better—whether it’s a change by management, or a change from the outside (or both).  Most net nets are not liquidated, and even those that are still bring a profit in many cases.

The net-net approach is one of the highest-returning investment strategies ever devised.  That’s not a surprise because net nets, by definition, are absurdly cheap on the whole, often trading below net cash—cash in the bank minus ALL liabilities.

Buffett called Graham’s net-net method the cigar-butt approach:

…I call it the cigar-butt approach to investing.  You walk down the street and you look around for a cigar butt someplace.  Finally you see one and it is soggy and kind of repulsive, but there is one puff left in it.  So you pick it up and the puff is free – it is a cigar butt stock.  You get one free puff on it and then you throw it away and try another one.  It is not elegant.  But it works.  Those are low return businesses.

Link: http://intelligentinvestorclub.com/downloads/Warren-Buffett-Florida-Speech.pdf

(Photo by Sky Sirasitwattana)

When running BPL, Buffett would go through thousands of pages of Moody’s Manuals (and other such sources) to locate just one or a handful of microcap stocks trading at less than liquidation value.  Other leading value investors have also used this technique.  This includes Charlie Munger (early in his career), Walter Schloss, John Neff, Peter Cundill, and Marty Whitman, to name a few.

The cigar-butt approach is also called deep value investing.  This normally means finding a stock that is available below liquidation value, or at least below net tangible book value.

When applying the cigar-butt method, you can either do it as a statistical group approach, or you can do it in a focused manner.  Walter Schloss achieved one of the best long-term track records of all time—near 21% annually (gross) for 47 years—using a statistical group approach to cigar butts.  Schloss typically had a hundred stocks in his portfolio, most of which were trading below tangible book value.

At the other extreme, Warren Buffett—when running BPL—used a focused approach to cigar butts.  Dempster is a good example, which Miller explores in detail in his book.



Dempster was a tiny micro cap, a family-owned company in Beatrice, Nebraska, that manufactured windmills and farm equipment.  Buffett slowly bought shares in the company over the course of five years.

(Photo by Digikhmer)

Dempster had a market cap of $1.6 million, about $13.3 million in today’s dollars, says Miller.

  • Note:  A market cap of $13.3 million is in the $10 to $25 million range—among the tiniest micro caps—which is avoided by nearly all investors, including professional microcap investors.

Buffett’s average price paid for Dempster was $28/share.  Buffett’s estimate of liquidation value early on was near $35/share, which is intentionally conservative.  Miller quotes one of Buffett’s letters:

The estimated value should not be what we hope it would be worth, or what it might be worth to an eager buyer, etc., but what I would estimate our interest would bring if sold under current conditions in a reasonably short period of time.

To estimate liquidation value, Buffett followed Graham’s method, as Miller explains:

  • cash, being liquid, doesn’t need a haircut
  • accounts receivable are valued at 85 cents on the dollar
  • inventory, carried on the books at cost, is marked down to 65 cents on the dollar
  • prepaid expenses and “other” are valued at 25 cents on the dollar
  • long-term assets, generally less liquid, are valued using estimated auction values

Buffett’s conservative estimate of liquidation value for Dempster was $35/share, or $2.2 million for the whole company.  Recall that Buffett paid an average price of $28/share—quite a cheap price.

Even though the assets were clearly there, Dempster had problems.  Stocks generally don’t get that cheap unless there are major problems.  In Dempster’s case, inventories were far too high and rising fast.  Buffett tried to get existing management to make needed improvements.  But eventually Buffett had to throw them out.  Then the company’s bank was threatening to seize the collateral on the loan.  Fortunately, Charlie Munger—who later became Buffett’s business partner—recommended a turnaround specialist, Harry Bottle.  Miller:

Harry did such an outstanding job whipping the company into shape that Buffett, in the next year’s letter, named him “man of the year.”  Not only did he reduce inventories from $4 million to $1 million, alleviating the concerns of the bank (whose loan was quickly repaid), he also cut administrative and selling expenses in half and closed five unprofitable branches.  With the help of Buffett and Munger, Dempster also raised prices on their used equipment up to 500% with little impact to sales volume or resistance from customers, all of which worked in combination to restore a healthy economic return in the business.

Miller explains that Buffett rationally focused on maximizing the return on capital:

Buffett was wired differently, and he achieves better results in part because he invests using an absolute scale.  With Dempster he wasn’t at all bogged down with all the emotional baggage of being a veteran of the windmill business.  He was in it to produce the highest rate of return on the capital he had tied up in the assets of the business.  This absolute scale allowed him to see that the fix for Dempster would come by not reinvesting back into windmills.  He immediately stopped the company from putting more capital in and started taking the capital out.

With profits and proceeds raised from converting inventory and other assets to cash, Buffett started buying stocks he liked.  In essence, he was converting capital that was previously utilized in a bad (low-return) business, windmills, to capital that could be utilized in a good (high-return) business, securities.

Bottle, Buffett, and Munger maximized the value of Dempster’s assets.  Buffett took the further step of not reinvesting cash in a low-return business, but instead investing in high-return stocks.  In the end, on its investment of $28/share, BPL realized a net gain of $45 per share.  This is a gain of a bit more than 160% on what was a very large position for BPL—one-fifth of the portfolio.  Had the company been shut down by the bank, or simply burned through its assets, the return after paying $28/share could have been nothing or even negative.

Miller nicely summarizes the lessons of Buffett’s asset conversion play:

Buffett teaches investors to think of stocks as a conduit through which they can own their share of the assets that make up a business.  The value of that business will be determined by one of two methods: (1) what the assets are worth if sold, or (2) the level of profits in relation to the value of assets required in producing them.  This is true for each and every business and they are interrelated…

Operationally, a business can be improved in only three ways: (1) increase the level of sales; (2) reduce costs as a percent of sales; (3) reduce assets as a percentage of sales.  The other factors, (4) increase leverage or (5) lower the tax rate, are the financial drivers of business value.  These are the only ways a business can make itself more valuable.

Buffett “pulled all the levers” at Dempster…



For most of the cigar butts that Buffett bought for BPL, he used Graham’s net-net method of buying at a discount to liquidation value, conservatively estimated.  However, you can find deep value stocks—cigar butts—on the basis of other low “price-to-a-fundamental” ratio’s, such as low P/E or low EV/EBITDA.  Even Buffett, when he was managing BPL, used a low P/E in some cases to identify cigar butts.  (See an example below: Western Insurance Securities.)

Tobias Carlisle and Wes Gray tested various measures of cheapness from 1964 to 2011.  Quantitative Value (Wiley, 2012)—an excellent book—summarizes their results.  James P. O’Shaughnessy has conducted one of the broadest arrays of statistical backtests.  See his results in What Works on Wall Street (McGraw-Hill, 4th edition, 2012), a terrific book.

(Illustration by Maxim Popov)

  • Carlisle and Gray found that low EV/EBIT was the best-performing measure of cheapness from 1964 to 2011.  It even outperformed composite measures.
  • O’Shaughnessy learned that low EV/EBITDA was the best-performing individual measure of cheapness from 1964 to 2009.
  • But O’Shaughnessy also discovered that a composite measure—combining low P/B, P/E, P/S, P/CF, and EV/EBITDA—outperformed low EV/EBITDA.

Assuming relatively similar levels of performance, a composite measure is arguably better because it tends to be more consistent over time.  There are periods when a given individual metric might not work well.  The composite measure will tend to smooth over such periods.  Besides, O’Shaughnessy found that a composite measure led to the best performance from 1964 to 2009.

Carlisle and Gray, as well as O’Shaughnessy, didn’t include Graham’s net-net method in their reported results.  Carlisle wrote another book, Deep Value (Wiley, 2014)—which is fascinating—in which he summarizes several tests of net nets:

  • Henry Oppenheimer found that net nets returned 29.4% per year versus 11.5% per year for the market from 1970 to 1983.
  • Carlisle—with Jeffrey Oxman and Sunil Mohanty—tested net nets from 1983 to 2008.  They discovered that the annual returns for net nets averaged 35.3% versus 12.9% for the market and 18.4% for a Small Firm Index.
  • A study of the Japanese market from 1975 to 1988 uncovered that net nets outperformed the market by about 13% per year.
  • An examination of the London Stock Exchange from 1981 to 2005 established that net nets outperformed the market by 19.7% per year.
  • Finally, James Montier analyzed all developed markets globally from 1985 to 2007.  He learned that net nets averaged 35% per year versus 17% for the developed markets on the whole.

Given these outstanding returns, why didn’t Carlisle and Gray, as well as O’Shaughnessy, consider net nets?  Primarily because many net nets are especially tiny microcap stocks.  For example, in his study, Montier found that the median market capitalization for net nets was $21 million.  Even the majority of professionally managed microcap funds do not consider stocks this tiny.

  • Recall that Dempster had a market cap of $1.6 million, or about $13.3 million in today’s dollars.
  • Unlike the majority of microcap funds, the Boole Microcap Fund does consider microcap stocks in the $10 to $25 million market cap range.

In 1999, Buffett commented that he could get 50% per year by investing in microcap cigar butts.  He was later asked about this comment in 2005, and he replied:

Yes, I would still say the same thing today.  In fact, we are still earning those types of returns on some of our smaller investments.  The best decade was the 1950s;  I was earning 50% plus returns with small amounts of capital.  I would do the same thing today with smaller amounts.  It would perhaps even be easier to make that much money in today’s environment because information is easier to access.  You have to turn over a lot of rocks to find those little anomalies.  You have to find the companies that are off the map—way off the map.  You may find local companies that have nothing wrong with them at all.  A company that I found, Western Insurance Securities, was trading for $3/share when it was earning $20/share!!  I tried to buy up as much of it as possible.  No one will tell you about these businesses.  You have to find them.

Although the majority of microcap cigar butts Buffett invested in were cheap relative to liquidation value—cheap on the basis of net tangible assets—Buffett clearly found some cigar butts on the basis of a low P/E.  Western Insurance Securities is a good example.  It had a P/E of 0.15.



Warren Buffett commented on high quality companies versus statistically cheap companies in his October 1967 letter to partners:

The evaluation of securities and businesses for investment purposes has always involved a mixture of qualitative and quantitative factors.  At the one extreme, the analyst exclusively oriented to qualitative factors would say, “Buy the right company (with the right prospects, inherent industry conditions, management, etc.) and the price will take care of itself.”  On the other hand, the quantitative spokesman would say, “Buy at the right price and the company (and stock) will take care of itself.”  As is so often the pleasant result in the securities world, money can be made with either approach.  And, of course, any analyst combines the two to some extent—his classification in either school would depend on the relative weight he assigns to the various factors and not to his consideration of one group of factors to the exclusion of the other group.

Interestingly enough, although I consider myself to be primarily in the quantitative school… the really sensational ideas I have had over the years have been heavily weighted toward the qualitative side where I have had a “high-probability insight”.  This is what causes the cash register to really sing.  However, it is an infrequent occurrence, as insights usually are, and, of course, no insight is required on the quantitative side—the figures should hit you over the head with a baseball bat.  So the really big money tends to be made by investors who are right on qualitative decisions but, at least in my opinion, the more sure money tends to be made on the obvious quantitative decisions.

Buffett and Munger acquired See’s Candies for Berkshire Hathaway in 1972.  See’s Candies is the quintessential high quality company because of its sustainably high ROIC (return on invested capital) of over 100%.

Truly high quality companies—like See’s—are very rare and difficult to find.  Cigar butts are much easier to find by comparison.

Furthermore, it’s important to understand that Buffett got around 50% annual returns from cigar butts because he took a focused approach, like BPL’s 20% position in Dempster.

The vast majority of investors, if using a cigar-butt approach like net nets, should implement a group—or statistical—approach, and regularly buy and hold a basket of cigar butts (at least 20-30).  This typically won’t produce 50% annual returns.  But net nets, as a group, clearly have produced very high returns, often 30%+ annually.  To do this today, you’d have to look globally.

As an alternative to net nets, you could implement a group approach using one of O’Shaughnessy’s composite measures—such as low P/B, P/E, P/S, P/CF, EV/EBITDA.  Applying this to micro caps can produce 15-20% annual returns.  Still excellent results.  And much easier to apply consistently.

You may think that you can find some high quality companies.  But that’s not enough.  You have to find a high quality company that can maintain its competitive position and high ROIC.  And it has to be available at a reasonable price.

Most high quality companies are trading at very high prices, to the extent that you can’t do better than the market by investing in them.  In fact, often the prices are so high that you’ll probably do worse than the market.

Consider this observation by Charlie Munger:

The model I like to sort of simplify the notion of what goes o­n in a market for common stocks is the pari-mutuel system at the racetrack.  If you stop to think about it, a pari-mutuel system is a market.  Everybody goes there and bets and the odds change based o­n what’s bet.  That’s what happens in the stock market.

Any damn fool can see that a horse carrying a light weight with a wonderful win rate and a good post position etc., etc. is way more likely to win than a horse with a terrible record and extra weight and so o­n and so on.  But if you look at the odds, the bad horse pays 100 to 1, whereas the good horse pays 3 to 2.  Then it’s not clear which is statistically the best bet using the mathematics of Fermat and Pascal.  The prices have changed in such a way that it’s very hard to beat the system.

(Illustration by Nadoelopisat)

A horse with a great record (etc.) is much more likely to win than a horse with a terrible record.  But—whether betting on horses or betting on stocks—you don’t get paid for identifying winners.  You get paid for identifying mispricings.

The statistical evidence is overwhelming that if you systematically buy stocks at low multiples—P/B, P/E, P/S, P/CF, EV/EBITDA, etc.—you’ll almost certainly do better than the market over the long haul.

A deep value (cigar-butt) approach has always worked, given enough time.  Betting on “the losers” has always worked eventually, whereas betting on “the winners” hardly ever works.

Classic academic studies showing “the losers” doing far better than “the winners” over subsequent 3- to 5-year periods:

That’s not to say deep value investing is easy.  When you put together a basket of statistically cheap companies, you’re buying stocks that are widely hated or neglected.  You have to endure loneliness and looking foolish.  Some people can do it, but it’s important to know yourself before using a deep value strategy.

In general, we extrapolate the poor performance of cheap stocks and the good performance of expensive stocks too far into the future.  This is the mistake of ignoring mean reversion.

When you find a group of companies that have been doing poorly for at least several years, those conditions typically do not persist.  Instead, there tends to be mean reversion, or a return to “more normal” levels of revenues, earnings, or cash flows.

Similarly for a group of companies that have been doing exceedingly well.  Those conditions also do not continue in general.  There tends to be mean reversion, but in this case the mean—the average or “normal” conditions—is below recent activity levels.

Here’s Ben Graham explaining mean reversion:

It is natural to assume that industries which have fared worse than the average are “unfavorably situated” and therefore to be avoided.  The converse would be assumed, of course, for those with superior records.  But this conclusion may often prove quite erroneous.  Abnormally good or abnormally bad conditions do not last forever.  This is true of general business but of particular industries as well.  Corrective forces are usually set in motion which tend to restore profits where they have disappeared or to reduce them where they are excessive in relation to capital.

With his taste for literature, Graham put the following quote from Horace’s Ars Poetica at the beginning of Security Analysis—the bible for value investors:

Many shall be restored that now are fallen and many shall fall than now are in honor.

Tobias Carlisle, while discussing mean reversion in Deep Value, smartly (and humorously) included this image of Albrecht Durer’s Wheel of Fortune:

(Albrecht Durer’s Wheel of Fortune from Sebastien Brant’s Ship of Fools (1494) via Wikimedia Commons)



We’ve already seen that there are two basic ways to do cigar-butt investing: focused vs. statistical (group).

Ben Graham usually preferred the statistical (group) approach.  Near the beginning of the Great Depression, Graham’s managed accounts lost more than 80 percent.  Furthermore, the economy and the stock market took a long time to recover.  As a result, Graham had a strong tendency towards conservatism in investing.  This is likely part of why he preferred the statistical approach to net nets.  By buying a basket of net nets (at least 20-30), the investor is virtually certain to get the statistical results of the group over time, which are broadly excellent.

Graham also was a polymath of sorts.  He had wide-ranging intellectual interests.  Because he knew net nets as a group would do quite well over the long term, he wasn’t inclined to spend much time analyzing individual net nets.  Instead, he spent time on his other interests.

Warren Buffett was Graham’s best student.  Buffett was the only student ever to be awarded an A+ in Graham’s class at Columbia University.  Unlike Graham, Buffett has always had an extraordinary focus on business and investing.  After spending many years learning everything about virtually every public company, Buffett took a focused approach to net nets.  He found the ones that were the cheapest and that seemed the surest.

Buffett has asserted that returns can be improved—and risk lowered—if you focus your investments only on those companies that are within your circle of competence—those companies that you can truly understand.  Buffett also maintains, however, that the vast majority of investors should simply invest in index funds: http://boolefund.com/warren-buffett-jack-bogle/

Regarding individual net nets, Graham admitted a danger:

Corporate gold dollars are now available in quantity at 50 cents and less—but they do have strings attached.  Although they belong to the stockholder, he doesn’t control them.  He may have to sit back and watch them dwindle and disappear as operating losses take their toll.  For that reason the public refuses to accept even the cash holdings of corporations at their face value.

Graham explained that net nets are cheap because they “almost always have an unsatisfactory trend in earnings.”  Graham:

If the profits had been increasing steadily it is obvious that the shares would not sell at so low a price.  The objection to buying these issues lies in the probability, or at least the possibility, that earnings will decline or losses continue, and that the resources will be dissipated and the intrinsic value ultimately become less than the price paid.

(Image by Preecha Israphiwat)

Value investor Seth Klarman warns:

As long as working capital is not overstated and operations are not rapidly consuming cash, a company could liquidate its assets, extinguish all liabilities, and still distribute proceeds in excess of the market price to investors.  Ongoing business losses can, however, quickly erode net-net working capital.  Investors must therefore always consider the state of a company’s current operations before buying.

Even Buffett—nearly two decades after closing BPL—wrote the following in his 1989 letter to Berkshire shareholders:

If you buy a stock at a sufficiently low price, there will usually be some hiccup in the fortunes of the business that gives you a chance to unload at a decent profit, even though the long-term performance of the business may be terrible.  I call this the “cigar butt” approach to investing.  A cigar butt found on the street that has only one puff left in it may not offer much of a smoke, but the “bargain purchase” will make that puff all profit.

Unless you are a liquidator, that kind of approach to buying businesses is foolish.  First, the original “bargain” price probably will not turn out to be such a steal after all.  In a difficult business, no sooner is one problem solved than another surfaces—never is there just one cockroach in the kitchen.  Second, any initial advantage you secure will be quickly eroded by the low return that the business earns.  For example, if you buy a business for $8 million that can be sold or liquidated for $10 million and promptly take either course, you can realize a high return.  But the investment will disappoint if the business is sold for $10 million in ten years and in the interim has annually earned and distributed only a few percent on cost…

Based on these objections, you might think that Buffett’s focused approach is better than the statistical (group) method.  That way, the investor can figure out which net nets are more likely to recover instead of burn through their assets and leave the investor with a low or negative return.

However, Graham’s response was that the statistical or group approach to net nets is highly profitable over time.  There is a wide range of potential outcomes for net nets, and many of those scenarios are good for the investor.  Therefore, while there are always some individual net nets that don’t work out, a group or basket of net nets is nearly certain to work well eventually.

Indeed, Graham’s application of a statistical net-net approach produced 20% annual returns over many decades.  Most backtests of net nets have tended to show annual returns of close to 30%.  In practice, while around 5 percent of net nets may suffer a terminal decline in stock price, a statistical group of net nets has done far better than the market and has experienced fewer down years.  Moreover, as Carlisle notes in Deep Value, very few net nets are actually liquidated or merged.  In the vast majority of cases, there is a change by management, a change from the outside, or both, in order to restore earnings to a level more in line with net asset value.  Mean reversion.



We noted earlier that it’s far more difficult to find a company like See’s Candies, at a reasonable price, than it is to find statistically cheap stocks.  Moreover, if you buy a basket of statistically cheap stocks, you don’t have to possess an ability to analyze individual businesses in great depth.

That said, in order to use a deep value strategy, you do have to be able to handle the psychological discomfort of being lonely and looking foolish.

(Illustration by Sangoiri)

John Mihaljevic, author of The Manual of Ideas (Wiley, 2013), writes:

Comfort can be expensive in investing.  Put differently, acceptance of discomfort can be rewarding, as equities that cause their owners discomfort frequently trade at exceptionally low valuations….

…Misery loves company, so it makes sense that rewards may await those willing to be miserable in solitude…

Mihaljevic explains:

If we owned nothing but a portfolio of Ben Graham-style bargain equities, we may become quite uncomfortable at times, especially if the market value of the portfolio declined precipitously.  We might look at the portfolio and conclude that every investment could be worth zero.  After all, we could have a mediocre business run by mediocre management, with assets that could be squandered.  Investing in deep value equities therefore requires faith in the law of large numbers—that historical experience of market-beating returns in deep value stocks and the fact that we own a diversified portfolio will combine to yield a satisfactory result over time.  This conceptually sound view becomes seriously challenged in times of distress…

Playing into the psychological discomfort of Graham-style equities is the tendency of such investments to exhibit strong asset value but inferior earnings or cash flows.  In a stressed situation, investors may doubt their investment theses to such an extent that they disregard the objectively appraised asset values.  After all—the reasoning of a scared investor might go—what is an asset really worth if it produces no cash flow?

Deep value investors often find some of the best investments in cyclical areas.  A company at a cyclical low may have multi-bagger potential—the prospect of returning 300-500% (or more) to the investor.

A good current example is Ensco plc (NYSE: ESV), an offshore oil driller.  Ensco is a leading offshore driller with a high-specification, globally diverse fleet.  The company also has one of the lowest cost structures, and relatively low debt levels (with the majority of debt due in 2024 or later).  In addition, Ensco has a long history of safety and operational excellence.  Ensco has been rated #1 for eight consecutive years in the leading independent customer satisfaction survey.

Intrinsic value scenarios for Ensco:

  • Low case: If oil prices languish below $60 (WTI) for the next 3 to 5 years, then Ensco will be a survivor, due to its large fleet, globally diverse customer base, industry leading performance, and well-capitalized position.  In this scenario, Ensco is likely worth at least $12 a share, over 90% higher than today’s $6.26.  (Current book value is $19.30 a share.)
  • Mid case: If oil prices are in a range of $65 to $85 over the next 3 to 5 years—which is likely based on long-term supply and demand—then Ensco is probably worth at least $25 a share, about 300% higher than today’s $6.26.
  • High case: If oil prices average $85 or more over the next 3 to 5 years, then Ensco could easily be worth $37 a share, over 490% higher than today’s $6.26.

Mihaljevic comments on a central challenge of deep value investing in cyclical companies:

The question of whether a company has entered permanent decline is anything but easy to answer, as virtually all companies appear to be in permanent decline when they hit a rock-bottom market quotation.  Even if a business has been cyclical in the past, analysts generally adopt a “this time is different” attitude.  As a pessimistic stock price inevitably influences the appraisal objectivity of most investors, it becomes exceedingly difficult to form a view strongly opposed to the prevailing consensus.

Consider the following industries that have been pronounced permanently impaired in the past, only to rebound strongly in subsequent years:  Following the financial crisis of 2008-2009, many analysts argued that the banking industry would be permanently negatively affected, as higher capital requirements and regulatory oversight would compress returns on equity.  The credit rating agencies were seen as impaired because the regulators would surely alter the business model of the industry for the worse following the failings of the rating agencies during the subprime mortgage bubble.  The homebuilding industry would fail to rebound as strongly as in the past, as overcapacity became chronic and home prices remained tethered to building costs.  The refining industry would suffer permanently lower margins, as those businesses were capital-intensive and driven by volatile commodity prices.

Are offshore oil drillers in a cyclical or a secular decline?  It’s likely that oil will return to $65-85 in the next 3 to 5 years.  But no one knows for sure.

Ongoing improvements in technology allow oil producers to get more oil—more cheaply—out of existing fields.  Also, growth in transport demand for oil will slow significantly at some point, due to ongoing improvements in fuel efficiency.  See: https://www.spe.org/en/jpt/jpt-article-detail/?art=3286

Transport demand is responsible for over 50% of daily oil consumption, and it’s inelastic—typically people have to get where they’re going, so they’re not very sensitive to fuel price increases.

But even if oil never returns to $65+, oil will be needed for many decades.  At least some offshore drilling will still be needed.

What’s great about an investment in Ensco is that even in worst case, the company will survive and the stock would likely be worth at least $12 a share, almost double today’s $6.26.  Recall that book value is $19.30 a share, and that the company has a low cost structure.  Also note that because of its safety, reliability, high-spec assets, and well-capitalized position, Ensco has continued to win a disproportionate share of new contracts.

If the worst-case scenario means that you’ll double your money—over a 3- to 5-year holding period—that’s an interesting investment.  And if the base case scenario means that you’ll quadruple your money (or better), well…


  • The Boole Fund had an investment in Atwood Oceanics.  Because Ensco acquired Atwood in 2017, the Boole Fund now own shares in Ensco.
  • The Boole Fund holds positions for 3 to 5 years.  The fund doesn’t sell an investment that is still cheap, even if the stock in question is no longer a micro cap.
  • On October 8, Ensco plc (ESV) and Rowan Companies plc (RDC) announced that they are merging in an all-stock transaction.  The new entity is probably even more undervalued than Ensco was prior to the announcement.  That’s based partly on projected cost savings of $150 million a year—which is credible based on track record.  In addition, besides being a leader in ultra-harsh and modern harsh environment jackups, Rowan has a groundbreaking partnership (ARO Drilling) with Saudi Aramco that will likely create billions of dollars in value for shareholders.



Buffett has made it clear, including in his 2014 letter to shareholders, that the best returns of his career came from investing in microcap cigar butts.  Most of these were mediocre businesses (or worse).  But they were ridiculously cheap.  And, in some cases like Dempster, Buffett was able to bring about needed improvements when required.

When Buffett wrote about buying wonderful businesses in his 1989 letter, that’s chiefly because investable assets at Berkshire Hathaway had grown far too large for microcap cigar butts.

Even in recent years, Buffett invested part of his personal portfolio in a group of cigar butts he found in South Korea.  So he’s never changed his view that an investor can get the highest returns from microcap cigar butts, either by using a statistical group approach or by using a more focused method.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Capitalism without Capital

(Image:  Zen Buddha Silence by Marilyn Barbone.)

November 11, 2018

Capitalism without Capital: The Rise of the Intangible Economy, by Jonathan Haskel and Stian Westlake, is an excellent book that everyone should read.

Historically most assets were tangible rather than intangible.  Houses, castles, temples, churches, farms, farm animals, equipment, horses, weapons, jewels, precious metals, art, etc.  These types of tangible assets tended to hold their value, and naturally they were included on accountants’ balance sheets.

(Photo by W. Scott McGill)

Intangible assets are different.  It’s harder to account for investing in intangibles.  But intangible investment is important.  Haskel and Westlake explain why:

Investment is what builds up capital, which, together with labor, constitutes the two measured inputs to production that power the economy, the sinews and joints that make the economy work.  Gross domestic product is defined as the sum of the value of consumption, investment, government spending, and net exports; of these four, investment is often the driver of booms and recessions, as it tends to rise and fall in response to monetary policy and business confidence.

The problem is that national statistical offices have, until very recently, measured only tangible investments.

The Dark Matter of Investment

In 2002 in Washington, at a meeting of the Conference on Research in Income and Wealth, economists considered investments people made in the “new economy.”  Carol Corrado and Dan Sichel of the US Federal Reserve Board and Charles Hulten of the University of Maryland developed a framework for thinking about different types of investments.

Haskel and Westlake mention Microsoft as an example.  In 2006, Microsoft’s market value was about $250 billion.  There was $70 billion in assets, $60 billion of which was cash and cash equivalents.  Plant and equipment totaled only $3 billion, 4 percent of Microsoft’s assets and 1 percent of its market value.  In a sense, Microsoft is a miracle:  capitalism without capital.

(Photo by tashatuvango)

Charles Hulten sought to explain Microsoft’s value by using intangible assets:

Examples include the ideas generated by Microsoft’s investments in R&D and product design, the value of its brands, its supply chains and internal structures, and the human capital built up by training.

Such intangible assets are similar to tangible assets in that the company had to spend time and money on them up-front, while the value to the company was delivered over time.

Why Intangible Investment is Different

Businesses change what they invest in all the time, so how is intangible investment different?  Haskel and Westlake:

Our central argument in this book is that there is something fundamentally different about intangible investment, and that understanding the steady move to intangible investment helps us understand some of the key issues facing us today:  innovation and growth, inequality, the role of management, and financial and policy reform.

We shall argue there are two big differences with intangible assets.  First, most measurement conventions ignore them.  There are some good reasons for this, but as intangibles have become more important, it means we are now trying to measure capitalism without counting all the capital.  Second, the basic economic properties of intangibles make an intangible-rich economy behave differently from a tangible-rich one.

Outline for this blog post:

Part I  The Rise of the Intangible Economy

  • Capital’s Vanishing Act:  The Rise of Intangible Investment
  • How to Measure Intangible Investment
  • What’s Different About Intangible Investment?  The Four S’s of Intangibles

Part II  The Consequences of the Rise of the Intangible Economy

  • Intangibles, Investment, Productivity, and Secular Stagnation
  • Intangibles and the Rise of Inequality
  • Infrastructure for Intangibles, and Intangible Infrastructure
  • The Challenge of Financing an Intangible Economy
  • Competing, Managing, and Investing in the Intangible Economy
  • Public Policy in an Intangible Economy:  Five Hard Questions


Part I  The Rise of the Intangible Economy


Investment has changed:

The type of investment that has risen inexorably is intangible: investment in ideas, in knowledge, in aesthetic content, in software, in brands, in networks and relationships.

Investment, assets, and capital all have multiple meanings.

For investment, Haskel and Westlake stick with the internationally agreed upon definition as given by the UN’s System of National Accounts:

Investment is what happens when a producer either acquires a fixed asset or spends resources (money, effort, raw materials) to improve it.

An asset is an economic resource that is expected to provide a benefit over a period of time.  A fixed asset is an asset that results from using up resources in the process of its production.

Spending resources:  To be an investment, the business doing the investing has to acquire the asset or pay some cost to produce it themselves.

Haskel and Westlake offer some examples of intangible investments:

Suppose a solar panel manufacturer researches and discovers a cheaper process for making photovoltaic cells:  it is incurring expense in the present to generate knowledge it expects to benefit from in the future.  Or consider a streaming music start-up that spends months designing and negotiating deals with record labels to allow it to use songs the record labels own—again, short-term expenditure to create longer-term gain.  Or imagine a training company pays for the long-term rights to run a popular psychometric test:  it too is investing.

(Photo by magele-picture)

Intangible investing results in intangible assets.  More examples of intangible investments:

  • Software
  • Databases
  • R&D
  • Mineral exploration
  • Creating entertainment, literary or artistic originals
  • Design
  • Training
  • Market research and branding
  • Business process re-engineering

Intangible Investment Has Steadily Grown

Supermarkets have developed complex pricing systems, more ambitious branding and marketing campaigns, and more detailed processes and systems (including better use of bar codes).  Moreover, as you might expect, tech firms make heavy use of intangible investments, as Haskel and Westlake explain:

Fast-growing tech companies are some of the most intangible-intensive of firms.  This is in part because software and data are intangibles, and the growing power of computers and telecommunications is increasing the scope of things that software can achieve.  But the process of “software eating the world,” in venture capitalist Marc Andreesen’s words, is not just about software:  it involves other intangibles in abundance.  Consider Apple’s designs and its unrivaled supply chain, which has helped it to bring elegant products to market quickly and in sufficient numbers to meet customer demand, or the networks of drivers and hosts that sharing-economy giants like Uber and AirBnB have developed, or Tesla’s manufacturing know-how.  Computers and the Internet are important drivers of this change in investment, but the change is long running and predates not only the World Wide Web but even the Internet and the PC.

By the mid-1990s, intangible investment in the United States exceeded tangible investment.  There is a similar pattern for the UK, Sweden, and Finland.  But tangible investment is still greater than intangible investment in Spain, Italy, Germany, Austria, Denmark, and the Netherlands.

Reasons for the Growth of Intangible Investment

Because the productivity of the manufacturing sector typically increases faster than that of the services sector, labor-intensive services gradually become more expensive compared to manufactured goods.  (This is called Baumol’s Cost Disease.)  This implies that intangible investing will grow faster than tangible investing over time.

Furthermore, new technology seems to create greater opportunities for businesses to invest productively in intangibles.  Haskel and Westlake give Uber as an example.  It would have been possible before computers and smartphones for Uber to develop its large network of drivers.  But smartphones—which connect people quickly, allow the rating of drivers, and make payment quick and easy—significantly boosted the return on investment for Uber.

It’s natural to wonder if computers are the cause of increased intangible investment.  Haskel and Westlake suggest that while computers may be a primary cause, they do not seem to be the only cause:

First of all, as we saw earlier, the rise of intangible investment began before the semiconductor revolution, in the 1940s and 1950s and perhaps before.  Second, while some intangibles like software and data strongly rely on computers, others do not:  brands, organizational development, and training, for example.  Finally, a number of writers in the innovation studies literature argue that it may be that it was the rise of intangibles that led to the development of modern IT as much as the other way around.



Productivity growth in the United States starting in the mid-1970s and throughout the 1980s seemed quite low.  Economists found this puzzling because computers seemed to be making a difference in a variety of areas.  Statistical agencies, led by the US Bureau of Economic Analysis (BEA), made two adjustments:

First, in the 1980s, in conjunction with IBM, the BEA started to produce indexes of computer prices that were quality adjusted.  This turned out to make a very big difference to measuring how much investment businesses were making in computer hardware.

In most cases—for products, for example—prices for the same good tend to rise gently in line with overall inflation.  But even if sticker prices for computers were rising, they were decidedly not the same good, since every dimension of their quality (speed, memory, and space) was improving incredibly.  So their “quality-adjusted” prices were, in fact, falling and falling very fast, meaning that the quality you could buy per dollar spent on computers was in fact rising very fast.

In the 1990s, statisticians looked at business spending that creates computer software.  Haskel and Westlake comment that banks are huge spenders on the creation of software (at one point, Citibank employed more programmers than Microsoft).  Software is an intangible good—knowledge written down in lines of code.

(Photo by Krisana Antharith)

By the early 2000s, many business economists realized that knowledge more generally is an intangible investment that should be included in GDP and productivity measures.  Gradually statistical offices began to incorporate various intangible investments into GDP statistics.  Haskel and Westlake:

And these changes added up.  In the United States, for example, the capitalization of software added about 1.1 percent to 1999 US GDP and R&D added 2.5 percent to 2012 GDP, with these numbers growing all the time…

What Sorts of Intangibles Are There?

Corrado, Hulten, and Sichel divided intangible investment into three broad types:

  • Computerized Information:  Software development;  Database development.
  • Innovative Property:  R&D;  Mineral exploration;  Creating entertainment and artistic originals;  Design and other product development costs.
  • Economic Competencies:  Training;  Market research and branding;  Business process re-engineering.

Right now, design and other product development costs are not included in official GDP measures.  Also not included:  training, market research and branding, and business process re-engineering.

Measuring Investment in Intangibles

Haskel and Westlake:

Measuring investment requires a number of steps.  First, we need to find out how much firms are spending on the intangible.  Second, in some cases, not all of that spending will be creating a long-lived asset… So we may have to adjust that spending to measure investment—that is, that part of spending creating a long-lived asset.  Third, we need to adjust that investment for inflation and quality change so we can compare investment in different periods when prices and quality are changing.

For most investment goods, national accountants simply send out a survey to companies asking them how much there are spending on each good.  It’s trickier, however, if it’s an intangible good that the company makes for itself, like writing its own software or doing its own R&D.  In this case, statisticians can figure out how much it costs a company—over and above wages—to produce the intangible good.  Statisticians also must estimate how much of that additional spending is an investment that will last for more than a year.  The third step is to adjust for inflation and quality changes.

To measure the intangible asset created by intangible investment, economists have to estimate depreciation.  Once you know the flow of intangible investment and you adjust for depreciation, you can then estimate the stock—the value of intangible assets in a given year.  For software, design, marketing, and training, depreciation is about 33 percent a year.  For R&D, depreciation is roughly 15 percent a year.  For entertainment and artistic originals and mineral exploration, depreciation is lower.



An intangible-rich economy has four characteristics—the four S’s—that distinguish it from a tangible-rich economy.  Intangible assets:

  • Are more likely to be scalable;
  • Their costs are more likely to be sunk;
  • They are inclined to have spillovers;
  • They tend to exhibit synergies with each other.


Why Are Intangibles Scalable?

Scalability derives from what economists call “non-rivalry” goods.  A rival good is like a loaf of bread.  Once one person eats the loaf of bread, no one else can eat that loaf.  In contrast, a non-rival good is not used up when one person uses it.  For instance, once a software program has been created, it can be reproduced an infinite number of times at almost no cost.  There’s virtually no limit to how many people can make use of that one software program.  Another example, given by Paul Romer—a pioneer of how economists think about economic growth—is oral rehydration therapy (ORT).  ORT is a simple treatment that has saved many lives in the developing world by stopping children’s deaths from diarrhea.  The idea of ORT can be used again and again—it’s never used up.

Note:  Scalability can really take off if there are “network effects.”  Haskel and Westlake mention networks like Uber drivers or Instagram users as examples.

(Illustration by Aquir)

Why Does Scalability Matter?

Haskel and Westlake say that we will see three unusual things happening in an economy where more investments are clearly scalable:

  • There will be some highly intangible-intensive businesses that have gotten very large.  Google, Microsoft, and Facebook are good examples.  Their software can be reproduced countless times at almost no cost.
  • Given the prospects of such large markets, ever more firms feel incentivized to go for it.
  • Businesses who compete with owners of scalable assets are in a tough position.  In markets with hugely scalable assets, the rewards for runners-up are often meager.


Why Are Intangibles Sunk Costs?

Intangible assets are much harder to sell than tangible assets.  If an intangible investment works, creating value for the company that made the investment, then there’s no issue.  However, if an intangible investment doesn’t work or the company wants to back out, it’s often hard to sell.  Specifically, if knowledge isn’t protected by intellectual property rights, it’s often impossible to sell.

(Image by OpturaDesign)

Why Does Sunkenness Matter?

Because intangible investments frequently involve unrecoverable costs, they can be difficult to finance, especially with debt.  There’s a reason why many small business loans require a lien on directors’ houses:  a house is a tangible asset with ascertainable value.

Moreover, people tend to fall for the sunk-cost fallacy, whereby they overvalue an intangible asset that hasn’t worked out because of the time, energy, and resources they’ve poured into it.  People are inclined to continue putting in more time and resources.  This may contribute to bubbles.


Why Do Intangibles Generate Spillovers?

Intangible investments can be used relatively easily by companies that didn’t make the investments.  Consider R&D.  Unless it is protected by patents, knowledge gained through R&D can be re-used again and again.  Haskel and Westlake remark:

Patents and copyrights are, on the whole, less secure and more subject to challenge than the title deeds to farmland or the ownership of a shipping container or a computer.

One reason is that property rights related to tangible assets have been around for thousands of years.

Why Do Spillovers Matter?

(Photo by Vs1489)

Haskel and Westlake remark that spillovers matter for three reasons:

  • First, in a world where companies can’t be sure they will obtain the benefits of their investments, we would expect them to invest less.
  • Second, there is a premium on the ability to manage spillovers:  companies that can make the most of their own investments in intangibles, or that are especially good at exploiting the spillovers from others’ investments, will do particularly well.
  • Third, spillovers affect the geography of modern economies.

The U.S. government funds 30 percent of the R&D that happens in the country.  It’s the classic answer to the issue of companies being unsure about the benefits of intangible investments they’re considering.  Public R&D is particularly important for basic research.

Haskel and Westlake:

Patent trolls and copyright lawsuits catch our attention because they are newsworthy, but other ways of capturing the spillovers of intangible investment are common—in fact, they’re part of the invisible fabric of everyday business life.  They often involve reciprocity rather than compulsion or legal threats.  Software developers use online repositories like GitHub to share code; being an active contributor and an effective user of GitHub is a badge of honor for some developers.  Firms sometimes pool their patents; they realize that the spillovers from each company’s technologies are valuable, and that enforcing everyone’s individual legal rights is not worth it.  (Indeed, the US government helped end the patent war between the Wright Brothers and Curtiss Aeroplane and Motor Company that was holding back the US aircraft industry in the 1910s by getting everyone to set up a patent pool, the Manufacturers Aircraft Association.)


Why Do Intangibles Exhibit Synergies?

Haskel and Westlake give the example of the microwave.  Near the end of World War II, Raytheon was mass-producing cavity magnetrons (similar to a vacuum tube), a crucial part of the radar defenses the British had invented.  A Raytheon engineer, Percy Spenser, realized the microwaves from magnetrons could heat food by creating electromagnetic fields in a box.

Haskel and Westlake write:

A few companies tried to sell domestic microwave ovens, but none were very successful.  Then, in the 1960s, Raytheon bought Amana, a white goods manufacturer, and combined their microwave expertise with Amana’s kitchen appliance knowledge to build a more successful product.  At the same time, Litton, another defense contractor, invented the modern microwave oven shape and tweaked the magnetron to make it safer.

In 1970 forty thousand microwaves were sold.  By 1975 it was a million.  What made this possible was the gradual accumulation of ideas and innovations.  The magnetron on its own wasn’t very useful to a customer, but combined with other incremental bits of R&D and the design and marketing ideas of Litton and Amana, it became a defining innovation of the late twentieth century.

The point of the microwave story is that intangible assets have synergies with one another.  Also, it’s hard to predict where innovations will come from or how they will combine.  In this example, military technology led to a kitchen appliance.

(Synergies in digital business, science, and technology:  Illustration by Agsandrew)

Intangible assets have synergies with tangible assets as well.  In the 1990s, productivity increased and at first people didn’t know why.  Haskel and Westlake explain:

In 2000 the McKinsey Global Institute analyzed the sources of this productivity increase.  Counterintuitively, they found that the bulk of it came from the way big chains retailers, in particular Walmart, were using computers and software to reorganize their supply chains, improve efficiency, and lower prices.  In a sense, it was a technological revolution.  But the gains were realized through organizational and business practice changes in a low-tech sector.  Or, to put it another way, there were big synergies between Walmart’s investment in computers and its investment in processes and supply chain development to make the most of the computers.

Why Do the Synergies of Intangible Assets Matter?

While spillovers cause firms to be protective of their intangible investments, synergies have the opposite effect and lead to open innovation.

In its simplest form, open innovation happens when a firm deliberately connects with and benefits from new ideas that arise outside the firm itself.  Cooking up ideas in a big corporate R&D lab is not open innovation; getting ideas by buying start-ups, partnering with academic researchers, or undertaking joint ventures with other companies is.

(Illustration by mindscanner)

Besides open innovation, there’s a second reason why synergies matter:

They also matter because they create an alternative way for firms to protect their intangible investments against competition:  by building synergistic clusters of intangible investments, rather than by protecting individual assets.


Part II  The Consequences of the Rise of the Intangible Economy


Two characteristics of secular stagnation are low investment and low interest rates.  Investment fell in the 1970s, recovered some in the mid-1980s, but fell sharply in the financial crisis (2008) and hasn’t recovered.

What’s puzzling is that investment hasn’t recovered despite low interest rates.  In the past, central banks relied on lowering rates to spur investment activity.  But that seems not to have worked this time.

(Illustration by ibreakstock)

One possible explanation is that technological progress has slowed.  Robert Gordon makes this argument in The Rise and Fall of American Growth (2016).  But technological progress is quite difficult to measure.

There are three more aspects to secular stagnation.

  • Corporate profits in the United States are higher than they’ve been for decades, and they seem to keep increasing.  Return on invested capital (ROIC) has grown significantly since the 1990s.
  • When it comes to both profitability and productivity, there is a growing gap between leaders and laggards.
  • Productivity growth has slowed due mostly to a decline in total factor productivity—workers are working less effectively with the capital they have.

Haskel and Westlake note that a good explanation for secular stagnation should explain four facts:

  • A fall in measured investment at the same time as a fall in interest rates
  • Strong profits
  • Increasingly unequal productivity and profits
  • Weak total factor productivity growth

Intangibles can help explain these facts.

Mismeasurement:  Intangibles and Apparently Low Investment

Intangible investment exceeds tangible investment in countries including the United States and the UK.  Are economies growing faster than reported because the value of intangibles is not being properly measured?  Haskel and Westlake show that including intangibles does not noticeably change investment/GDP.

Profits and Productivity Differences:  Scale, Spillovers, and the Incentives to Invest

Haskel and Westlake state:

…leading firms, which are confident of their ability to create scalable assets and to appropriate most of their benefits, will continue to invest (and enjoy a high rate of return on those investments); but laggard firms, expecting low private returns from their investments, will not.  In a world where there are a few leaders and many laggards, the net effect of this could be lower aggregate rates of investment, combined with high returns on those investments that do get made.

Spillovers:  Intangibles and Slowing TFP Growth A Lower Pace of Intangible Growth?

The slowdown in intangible investment since the financial crisis does seem to account for slowing TFP (Total Factor Productivity) growth, although the data are noisy and more exploration is needed.

Are Intangibles Generating Fewer Spillovers?

Lagging firms may be less able to absorb spillovers from leaders, possibly because leading firms can gain from synergies between different intangibles to a much greater extent than laggards.



In addition to inequality of income and inequality of wealth, there is also what Haskel and Westlake call “inequality of esteem.”  Some communities feel left-behind and overlooked by America’s prosperous coastal cities.

Standard explanations for inequality

One standard explanation for inequality is that new technologies replace workers, which causes wages to fall and profits to rise.

A second explanation relates to trade.  In the 1980s, before the collapse of the Soviet Union and before market reforms in China and India, the global economy had 1.46 billion workers.  Then in the 1990s, the number of workers doubled to 2.93 billion workers.  This puts pressure on lower-skilled workers in developed economies.  The flip side is that lower-skilled workers in China and India end up far better off than they were before.

A third explanation for inequality is that capital tends to accumulate.  Capital tends to grow faster than the economy—this is Thomas Piketty’s famous r > g inequality—which causes capital to build up over time.

(Illustration by manakil)

How Intangibles Affect Income, Wealth, and Esteem Inequality

Intangibles, Firms, and Income Inequality

The best firms—owning scalable intangibles and able to extract spillovers from other businesses—will be highly productive and profitable while their competitors will lose out.  But that doesn’t necessarily mean the best firms pays all their workers more.  To explain rising wage inequality, more is needed.

Who is Benefiting from Intangible-Based Firm Inequality?

“Superstars” benefit by being associated with exceptionally valuable intangibles that can scale massively.  Whereas in most markets a top worker could probably be replaced by two not-as-fast workers, this isn’t true for superstar markets:  you can’t replace the best opera singer or the best basketball player with two not-quite-as-good ones.  Tech billionaires also tend to be superstars with large equity stakes in companies they founded—companies that probably scaled massively.

However, senior managers have also done very well.  Haskel and Westlake explain why:

Intangible investment increases.  Because of its scalability and the benefits to companies that can appropriate intangible spillovers, leading companies pull ahead of laggards in terms of productivity, especially in the more intangible-intensive industries.  The employees of these highly productive companies benefit from higher wages.  Because intangibles are contestable, companies are especially eager to hire people who are good at contesting them—appropriating spillovers from other firms or identifying and maximizing synergies.

Why are CEOs at many companies being paid so much more than other workers?  One reason relates to a “fundamental attribution error” whereby people explain a good business outcome by referring to what is simple and salient—like the skill of the CEO—rather than by acknowledging complexity and the fact that luck typically plays a major role.  It’s also possible, say Haskel and Westlake, that shareholders—especially those who are most diversified—are not paying much attention to CEO pay.

Housing Prices, Cities, Intangibles, and Wealth Inequality

Intangibles can help explain wealth inequality.  First, intangibles tend to drive up property prices.  Second, the mobility of intangible capital means it’s harder to tax.

In a world where intangibles are becoming more abundant and a more important part of the way businesses create value, the benefits to exploiting spillovers and synergies increase.  And as these benefits increase, we would expect businesses and their employees to want to locate in diverse, growing cities where synergies and spillovers abound.

Haskel and Westlake summarize how intangibles impact long-run inequality:

  • First, inequality of income.  The synergies and spillovers that intangibles create increase inequality between competing companies, and this inequality leads to increasing differences in employee pay… In addition, managing intangibles requires particular skills and education, and people with these skills are clustering in high-paid jobs in intangible-intensive firms.  Finally, the growing economic importance of the kind of people who manage intangibles helps foster myths that can be used to justify excessive pay, especially for top managers.
  • Second, inequality of wealth.  Thriving cities are places where spillovers and synergies abound.  The rise of intangibles makes cities increasingly attractive places to be, driving up the prices of prime property.  This type of inflation has been shown to be one of the major causes of the increase in the wealth of the richest.  In addition, intangibles are often mobile; they can be shifted across firms and borders.  This makes capital more mobile, which makes it harder to tax.  Since capital is disproportionately owned by the rich, this makes redistributive taxation to reduce wealth inequality harder.
  • Finally, inequality of esteem.  There is some evidence that supporters of populist movements… are more likely to hold traditional views and to score low on tests for the psychological trait of openness to experience.



On the one hand, in order to thrive, the intangible economy needs new buildings in and around cities.  On the other hand, artistic and creative institutions are important for combinatorial innovation.  In the longer term, face-to-face interaction may eventually be phased out, but often these kinds of changes can take much longer than initially supposed.

(Illustration by Panimoni)

Haskel and Westlake comment:

The death of distance has failed to take place.  Indeed, the importance of spillovers and synergies has increased the importance of places where people come together to share ideas and the importance of the transport and social spaces that make cities work.

But the death of distance may have been postponed rather than cancelled.  Information technologies are slowly, gradually, replacing some aspects of face-to-face interaction.  This may be a slow-motion change, like the electrification of factories—if so, the importance of physical infrastructure will radically change.

Soft infrastructure will also matter increasingly.  The synergies between intangibles increase the importance of standards and norms, which together make up a kind of social infrastructure for intangible investment.  And standards and norms are underpinned by trust and social capital, which are particularly important in an intangible economy.



Banks are often criticized for not providing enough capital for businesses to succeed.  Equity markets are criticized for being too short-term and also too influential.  Managers seem to fixate more and more on shorter term stock prices.  Managers may cut R&D to try to please short-term investors.  Haskel and Westlake remark:

These concerns drive public policy across the developed world:  most governments to some extent subsidize or coerce banks to lend to businesses, and they give tax advantages to companies that finance using debt.  Many countries are considering measures to make equity investors take a longer-term perspective, such as imposing taxes on short-term shareholdings or changing financial reporting requirements.  And most governments have spent money trying to encourage alternative forms of financing, particularly venture capital (VC), which is regarded as providing a big potential source of business growth and national wealth.

Banking:  The Problem of Lending in a World of Intangibles

When a bank lends money to a business, the bank usually has some recourse to the assets of the business if the debt isn’t repaid.  However, intangible assets are typically much harder to value than tangible assets, and frequently intangible assets don’t have much value at all when a business fails.  Thus it is difficult for a bank to lend to a business whose assets are mostly intangible.

This is why industries with mostly tangible assets—like oil and gas producers—have high leverage (are funded more with debt than equity), while industries with mostly intangible assets—like software—have less debt and more equity.

One way to increase bank lending to businesses with more intangible assets is for the government to cofund or guarantee bank loans.  A second way is financial innovation, such as finding ways to value intangible assets—like patents—more accurately.  A third way to deal with the issue of lending against intangibles is to get businesses to rely more on equity than debt.

Haskel and Westlake on how equity markets impact intangible investing:

There is some evidence that markets are short-termist, to the extent that management can sometimes boost their company’s share price by cutting intangible investment to preserve or increase profits, or cut investment to buy back stock.  But it also seems that some of what is happening is a sharpening of managerial incentives:  publicly held companies whose managers own stock focus on types of intangible investment that are more likely to be successful.  And the extent of market myopia varies:  companies with more concentrated, sophisticated investors are less likely to feel pressure to cut intangible investment than those with dispersed, unsophisticated ones.

Why VC Works for Intangibles

(Photo by designer491)

Haskel and Westlake observe:

VC has several characteristics that make it especially well-suited to intangible-intensive businesses:  VC firms take equity stakes, not debt, because intangible-rich businesses are unlikely to be worth much if they fail—all those sunk investments.  Similarly, to satisfy their own investors, VC funds rely on home-run successes, made possible by the scalability of assets like Google’s algorithms, Uber’s driver network, or Genentech’s patents.  Third, VC is often sequential, with rounds of funding proceeding in stages.  This is a response to the inherent uncertainty of intangible investment.

Leading VC firms and their partners are well-connected and credible, which helps in building networks to exploit synergies.



Businesses look to improve their performance in a way that is sustainable.  How can this be done?  The advice has always been to build and maintain distinctive assets.  Tangible assets are usually not distinctive, or at least not for long.  Haskel and Westlake:

It’s much more likely that the types of intangible assets we have talked about in this book are going to be distinctive:  reputation, product design, trained employees providing customer service.  Indeed, perhaps the most distinctive asset will be the ability to weave all these assets together; so a particularly valuable intangible asset will be the organization itself.

When it comes to management, Haskel and Westlake suggest replacing the question, “What are managers for?” with a deeper question, “What’s the role of authority in an economy?”

Markets work with minimal government interference.  However, firms can do a better job than dispersed individuals at organizing certain activities.  Managers are people at firms who have authority.  This is usually more efficient:  managers tell employees what to do rather than discussing or arguing about every step.

But if management is largely just monitoring, and software can do the job of monitoring, then what is the role of managers in an intangible-intensive economy?  For one, note Haskel and Westlake, the stakes tend to be much higher in the intangible economy.  Moreover, in synergistic firms, only managers may understand the big picture.

How can managers build a good organization in an intangible-intensive firm?  Haskel and Westlake explain:

…if you are primarily a producer of intangible assets (writing software, doing design, producing research) you probably want to build an organization that allows information to flow, helps serendipitous interactions, and keeps the key talent.  That probably means allowing more autonomy, fewer targets, and more access to the boss, even if that is at the cost of influence activities.

Leadership is important in an intangible economy.

(Photo by Raywoo)

Having voluntary followers is really useful in an intangible economy.  A follower will stay loyal to the firm, which keeps the tacit intangible capital at the firm.  Better, if they are inspired by and empathize with the leader, they will cooperate with each other and feed information up to the leader.  This is why leadership is going to be so valued in an intangible economy.  It can at best replace, and likely mitigate, the costly and possibly distortive aspects of managing by authority.


How can an investor discern if a business is building intangible assets?  Can investors learn about intangibles from accounting data?

Accountants try to match revenues with costs.  If the company has a long-lived asset that produces revenues, then the company measures the annual cost by depreciation or amortization of that asset.

The other way to measure the cost of a long-lived asset is to expense the entire cost of creating the asset in the year in which the expenditures are made.  However, this can lead to distortions.  First, the costs in creating the asset can make profits in that year appear unusually low.  By the same logic, if the asset in question continues producing revenues, then in future years profits will appear unusually high.

In the case of intangible assets, if the asset is bought from outside the company, then it is capitalized (and annual expenses are calculated based on depreciation or amortization).  If the asset is created within the company, then the costs are recognized when they are spent (even if the asset is long-lived).

The result is that much intangible investment is hidden because it is expensed.  This is a challenge for investors because economies are coming to rely increasingly on intangible assets.  Book value—which is frequently based largely on tangible assets—is less relevant for a company that relies on intangible assets—especially if the company develops those assets internally.

What Should Investors Do?

The simplest solution for investors is to invest in low-cost broad market index funds.  In this way, the investor will benefit from companies that rely on intangible assets.

Because index funds outpace 90-95% of all active investors if you measure performance over several decades, it already makes excellent sense for many investors to invest in index funds.

Haskel and Westlake sum up the chapter:

The growth of intangible investment has significant implications for managers, but it will affect different firms in different ways.  Firms that produce intangible assets will want to maximize synergies, create opportunities to learn from the ideas of others (and appropriate the spillovers from others’ intangibles), and retain talent.  These workplaces may end up looking rather like the popular image of hip knowledge-based companies.  But companies that rely on exploiting existing intangible assets may look very different, especially where the intangible assets are organizational structure and processes.  These may be much more controlled environments—Amazon’s warehouses rather than its headquarters.  Leadership will be increasingly prized, to the extent that it allows firms to coordinate intangible investments in different areas and exploit their synergies.

Financial investors who can understand the complexity of intangible-rich firms will also do well.  The greater uncertainty of intangible assets and the decreasing usefulness of company accounts put a premium on good equity research and on insight into firm management.



Haskel and Westlake highlight five of the most important challenges in an intangible-rich economy:

  • First, intangibles tend to be contested:  it is hard to prove who owns them, and even then their benefits have a tendency to spill over to others.  Good intellectual property frameworks are important for an economy increasingly dependent on intangibles.
  • Second, in an intangible economy, synergies are very important. Combining different ideas and intangible assets is central to successful business innovation.  An important objective for policy makers is to create conditions for ideas to come together.
  • The third challenge relates to finance and investment.  Businesses and financial markets seem to underinvest in scalable, sunk intangible investments with a tendency to generate spillovers and synergies.  The current system of business finance exacerbates the problem.  A thriving intangible economy will significantly improve its financial system to make it easier for companies to invest in intangibles.
  • Fourth, it will probably be harder for most businesses to appropriate the benefits of capital investment in the economies of the future than in the tangible-rich economies we are familiar with.  Successful intangible-rich economies will have higher levels of public investment in intangibles.
  • Fifth, governments must work out how to deal with the dilemma of the particular type of inequality that intangibles seem to encourage.

(Illustration by Robert Wilson)

Clearer Rules and Norms about the Ownership of Intangibles

Stronger IP rights are not necessarily best because while they can increase incentive to invest, productivity gains are lowered.  Also, strengthening IP rights might accidentally favor incumbent rights-holders and patent trolls.

Clearer IP rights can be helpful, though.  They can reduce lawsuits that often end up in the notoriously troll-friendly Eastern District of Texas court.

Moreover, since intangible assets are often much more difficult to value than tangible assets, there are ways to help with this.  For instance, Ian Hargreaves in 2011 suggested that the UK have a Digital Copyright Exchange.  Another example is patent pools where firms coinvest in research and agree to share the resulting rights.

Helping Ideas Combine:  Maximizing the Benefits of Synergies

Good public policy should be just as assiduous about creating the conditions for knowledge to spread, mingle, and fructify as it is about creating property rights for those who invest in intangibles.

It should be easy to build new workplaces and homes in cities.  But simultaneously, cities have to be connected and livable.

A Financial Architecture for Intangible Investment

Governments should encourage new forms of debt that facilitate the ability to borrow against intangible assets.  Longer term, governments should help a shift from debt to equity financing.  Currently, debt is cheaper than equity due to the tax benefits of debt.  This must change, but it will be very difficult because vested interests still rely on debt.  Furthermore, new institutions will be required that provide equity financing to small and medium-size businesses.  Although these shifts will be challenging, the rewards will be ever greater, note Haskel and Westlake.

Solving the Intangible Investment Gap

Some large firms seem able to gain from both their own intangible investments and from intangible investments made by others.  These companies—like Google or Facebook—can be expected to continue making intangible investments.

Outside of these companies, the government and other public interest bodies (like large non-profit foundations) must make intangible investments.

The government is the investor of last resort.  Here are three practical tips given by Haskel and Westlake for government investment in intangibles:

  • Public R&D Funding.  This means the government spending more on university research, public research institutes, or research undertaken by businesses.  This type of government spending is not at all ideologically controversial and it can help a great deal over time.
  • Public Procurement.  When the US military funded the development of the semiconductor industry in the 1950s, they also acted as a lead customer.  This helped Texas Instruments and other firms not just to invest in R&D, but also to build the capacity to produce and sell chips.
  • Training and Education. Because it’s hard to predict what skills will be needed in 20 to 30 years, adult education may be a good area in which to invest.  This could also help with inequality to some extent.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Ten Attributes of Great Investors

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 28, 2018

Michael Mauboussin is the author of several excellent books, including More Than You Know and Think Twice.  I wrote about these books here:

He has also written numerous papers, including Thirty Years: Reflections on the Ten Attributes of Great Investorshttps://bit.ly/2zlaljc

When it comes to value investing, Mauboussin is one of the best writers in the world.  Mauboussin highlights market efficiency, competitive strategy analysis, valuation, and decision making as chief areas of focus for him the past couple of decades.  Mauboussin:

What we know about each of these areas today is substantially greater than what we did in 1986, and yet we have an enormous amount to learn.  As I like to tell my students, this is an exciting time to be an investor because much of what we teach in business schools is a work-in-progress.

(Image by magele-picture)

Here are the Ten Attributes of Great Investors:

  • Be numerate (and understand accounting).
  • Understand value (the present value of free cash flow).
  • Properly assess strategy (or how a business makes money).
  • Compare effectively (expectations versus fundamentals).
  • Think probabilistically (there are few sure things).
  • Update your views effectively (beliefs are hypotheses to be tested, not treasures to be protected).
  • Beware of behavioral biases (minimizing constraints to good thinking).
  • Know the difference between information and influence.
  • Position sizing (maximizing the payoff from edge).
  • Read (and keep an open mind).



Mauboussin notes that there are two goals when analyzing a company’s financial statements:

  • Translate the financial statements into free cash flow.
  • Determine how the competitive strategy of the company creates value.

The value of any business is the future free cash flow it will produce discounted back to the present.

(Photo by designer491)

Free cash flow is cash earnings minus investments that must be made to grow future earnings.  Free cash flow represents what owners of the business receive.  Warren Buffett refers to free cash flow as owner earnings.

Earnings alone cannot give you the value of a company.  You can grow earnings without growing value.  Whether earnings growth creates value depends on how much money the company invests to generate that growth.  If the ROIC (return on invested capital) of the company’s investment is below the cost of capital, then the resulting earnings growth destroys value rather than creates it.

After calculating free cash flow, the next goal in financial statement analysis is to figure out how the company’s strategy creates value.  For the company to create value, the ROIC must exceed the cost of capital.  Analyzing the company’s strategy means determining precisely how the company can get ROIC above the cost of capital.

Mauboussin writes that one way to analyze strategy is to compare two companies in the same business.  If you look at how the companies spend money, you can start to understand competitive positions.

Another way to grasp competitive position is by analyzing ROIC.

Photo by stanciuc

You can break ROIC into two parts:

  • profitability (net operating profit after tax / sales)
  • capital velocity (sales / invested capital)

Companies with high profitability but low capital velocity are using a differentiation strategy.  Their product is positioned in such a way that the business can earn high profit margins.  (For instance, a luxury jeweler.)

Companies with high capital velocity but low profitability have adopted a cost leadership strategy.  These businesses may have very thin profit margins, but they still generate high ROIC because their capital velocity is so high.  (Wal-Mart is a good example.)

Understanding how the company makes money can lead to insight about how long the company can maintain a high ROIC (if ROIC is high) or what the company must do to improve (if ROIC is low).




Great fundamental investors focus on understanding the magnitude and sustainability of free cash flow.  Factors that an investor must consider include where the industry is in its life cycle, a company’s competitive position within its industry, barriers to entry, the economics of the business, and management’s skill at allocating capital.

It’s worth repeating: The value of any business (or any financial asset) is the future free cash flow it will produce discounted back to the present.  Successful investors understand the variables that impact free cash flow.

Illustration by OpturaDesign



Mauboussin says this attribute has two elements:

  • How does the company make money?
  • Does the company have a sustainable competitive advantage, and if so, how durable is it?

To see how a business makes money, you have to figure out the basic unit of analysis.  Mauboussin points out that the basic unit of analysis for a retailer is store economics:  How much does it cost to build a store?  What revenues will it generate?  What are the profit margins?

Regarding sustainable competitive advantage, Warren Buffett famously said:

The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage.

If a company has a sustainable competitive advantage, then ROIC (return on invested capital) is above the cost of capital.  To assess the durability of that advantage, you have to analyze the industry and how the company fits in.  Looking at the five forces that determine industry attractiveness is a common step.  You should also examine potential threats from disruptive innovation.


Great investors can appreciate what differentiates a company that allows it to build an economic moat around its franchise that protects the business from competitors.  The size and longevity of the moat are significant inputs into any thoughtful valuation.

Bodiam Castle, Photo by valeryegorov

Buffett popularized the term economic moat to refer to a sustainable competitive advantage.  Here’s what Buffett said at the Berkshire annual meeting in 2000:

So we think in terms of that moat and the ability to keep its width and its impossibility of being crossed as the primary criterion of a great business.  And we tell our managers we want the moat widened every year.  That doesn’t necessarily mean the profit will be more this year than it was last year because it won’t be sometimes.  However, if the moat is widened every year, the business will do very well.




Perhaps the most important comparison an investor must make, and one that distinguishes average from great investors, is between fundamentals and expectations.  Fundamentals capture a sense of a company’s future financial performance.  Value drivers including sales growth, operating profit margins, investment needs, and return on investment shape fundamentals.  Expectations reflect the financial performance implied by the stock price.

Mauboussin mentions pari-mutuel betting, specifically horse racing.

(Photo by Elshaneo)

Fundamentals are how fast the horse will run, while expectations are the odds.

  • If a company has good fundamentals, but the stock price already reflects that, then you can’t expect to beat the market by investing in the stock.
  • If a company has bad fundamentals, but the stock price is overly pessimistic, then you can expect to beat the market by investing in the stock.

The best business in the world will not bring excess returns if the stock price already fully reflects the high quality of the business.  Similarly, a terrible business can produce excess returns if the stock price indicates that investors have overreacted.

To make money by investing in a stock, you have to have what great investor Michael Steinhardt calls a variant perception—a view at odds with the consensus view (as reflected in the stock price).  And you have to be right.

Mauboussin observes that humans are quick to compare but aren’t good at it.  This includes reasoning by analogy, e.g., asking whether a particular turnaround is similar to some other turnaround.  However, it’s usually better to figure out the base rate:  What percentage of all turnarounds succeed?  (Not a very high number, which is why Buffett quipped, “Turnarounds seldom turn.)

Another limitation of humans making comparisons is that people tend to see similarities when they’re looking for similarities, but they tend to see differences when they’re looking for differences.  For instance, Amos Tversky did an experiment in which the subjects were asked which countries are more similar, West Germany and East Germany, or Nepal and Ceylon?  Two-thirds answered West Germany and East Germany.  But then the subjects were asked which countries seemed more different.  Logic says that they would answer Nepal and Ceylon, but instead subjects again answered West Germany and East Germany.



Great investors are always seeking an edge, where the price of an asset misrepresents the probabilities or the outcomes.  By similar logic, great investors evaluate each investment decision based on the process used rather than based on the outcome.

  • A good investment decision is one that if repeatedly made would be profitable over time.
  • A bad investment decision is one that if repeatedly made would lead to losses over time.

However, a good decision will sometimes lead to a bad outcome, while a bad decision will sometimes lead to a good outcome.  Investing is similar to other forms of betting in that way.

Photo by annebel146

Furthermore, what matters is not how often an investor is right, but rather how much the investor makes when he is right versus how much he loses when he is wrong.  In other words, what matters is not batting average but slugging percentage.  This is hard to put into practice due to loss aversion—the fact that as humans we feel a loss at least twice as much as an equivalent gain.

There are three ways of determining probabilities.  Subjective probability is a number that corresponds with your state of knowledge or belief.  Mauboussin gives an example:  You might come up with a probability that two countries will go to war.  Propensity is usually based on the physical properties of the system.  If a six-sided die is a perfect cube, then you know that the odds of a particular side coming up must be one out of six.  Frequency is the third approach.  Frequency—also called the base rate—is measured by looking at the outcomes of a proper reference class.  How often will a fair coin land on heads?  If you gather all the records you can of a fair coin being tossed, you’ll find that it lands on heads 50 percent of the time.  (You could run your own trials, too, by tossing a fair coin thousands or millions of times.)

Often subjective probabilities are useful as long as you remain open to new information and properly adjust your probabilities based on that information.  (The proper way to update such beliefs is using Bayes’s theorem.)  Subjective probabilities are useful when there’s no clear reference class—no relevant base rate.

When you’re looking at corporate performance—like sales or profit growth—it’s usually best to look at frequencies, i.e., base rates.

An investment decision doesn’t have to be complicated.  In fact, most good investment decisions are simple.  Mauboussin quotes Warren Buffett:

Take the probability of loss times the amount of possible loss from the probability of gain times the amount of possible gain.  That is what we’re trying to do.  It’s imperfect, but that’s what it’s all about.

Buffett again:

Investing is simple, but not easy.



People have a strong preference for consistency when it comes to their own beliefs.  And they expect others to be consistent.  The problem is compounded by confirmation bias, the tendency to look for and see only information that confirms your beliefs, and the tendency to interpret ambiguous information in a way that supports your beliefs.  As long as you feel like your beliefs are consistent, you’ll feel comfortable and won’t challenge your beliefs.

Illustration by intheskies

Great investors seek data and arguments that challenge their views.  Great investors also update their beliefs when they come across evidence that suggests they should.  The proper way to update beliefs is using Bayes’s theorem.  To see Bayes’s theorem and also a clear explanation and example, see: http://boolefund.com/the-signal-and-the-noise/


The best investors among us recognize that the world changes constantly and that all of the views that we hold are tenuous.  They actively seek varied points of view and update their beliefs as new information dictates.  The consequence of updated views can be action: changing a portfolio stance or weightings within a portfolio.  Others, including your clients, may view this mental flexibility as unsettling.  But good thinking requires maintaining as accurate a view of the world as possible.




Keith Stanovich, a professor of psychology, likes to distinguish between intelligence quotient (IQ), which measures mental skills that are real and helpful in cognitive tasks, and rationality quotient (RQ), the ability to make good decisions.  His claim is that the overlap between these abilities is much lower than most people think.  Importantly, you can cultivate your RQ.

Rationality is only partly genetic.  You can train yourself to be more rational.

Great investors relentlessly train themselves to be as rational as possible.  Typically they keep an investment journal in which they write down the reasoning for every investment decision.  Later they look back on their decisions to analyze what they got right and where they went wrong.

Great investors also undertake a comprehensive study of cognitive biases.  For a list of cognitive biases, see these two blog posts:

It’s rarely enough just to know about cognitive biases.  Great investors take steps—like using a checklist—designed to mitigate the impact that innate cognitive biases have on investment decision-making.

Photo by Kenishirotie



A stock price generally represents the collective wisdom of investors about how a given company will perform in the future.  Most of the time, the crowd is more accurate than virtually any individual investor.

(Illustration by Marrishuanna)

However, periodically a stock price can get irrational.  (If this weren’t the case, great value investors could not exist.)  People regularly get carried away with some idea.  For instance, as Mauboussin notes, many investors got rich on paper by investing in dot-com stocks in the late 1990’s.  Investors who didn’t own dot-com stocks felt compelled to jump on board when they saw their neighbor getting rich (on paper).

Mauboussin mentions the threshold model from Mark Granovetter, a professor of sociology at Stanford University.  Mauboussin:

Imagine 100 potential rioters milling around in a public square.  Each individual has a “riot threshold,” the number of rioters that person would have to see in order to join the riot.  Say one person has a threshold of 0 (the instigator), one has a threshold of 1, one has a threshold of 2, and so on up to 99.  This uniform distribution of thresholds creates a domino effect and ensures that a riot will happen.  The instigator breaks a window with a rock, person one joins in, and then each individual piles on once the size of the riot reaches his or her threshold.  Substitute “buy dotcom stocks” for “join the riot” and you get the idea.

The point is that very few of the individuals, save the instigator, think that rioting is a good idea.  Most would probably shun rioting.  But once the number of others rioting reaches a threshold, they will jump in.  This is how the informational value of stocks is set aside and the influential component takes over.

Great investors are not influenced much at all by the behavior of other investors.  Great investors know that the collective wisdom reflected in a stock price is usually right, but sometimes wrong.  These investors can identify the occasional mispricing and then make an investment while ignoring the crowd.



Great investors patiently wait for situations where they have an edge, i.e., where the odds are in their favor.  Many investors understand the need for an edge.  However, fewer investors pay much attention to position sizing.

If you know the odds, there’s a formula—the Kelly criterion—that tells you exactly how much to bet in order to maximize your long-term returns.  The Kelly criterion can be written as follows:

  • F = p – [q/o]


  • F = Kelly criterion fraction of current capital to bet
  • o = Net odds, or dollars won per $1 bet if the bet wins (e.g., the bet may pay 5 to 1, meaning you win $5 per each $1 bet if the bet wins)
  • p = probability of winning
  • q = probability of losing = 1 – p

The Kelly criterion has a unique mathematical property: if you know the probability of winning and the net odds (payoff), then betting exactly the percentage determined by the Kelly criterion leads to the maximum long-term compounding of capital.  (This assumes that you’re going to make a long series of bets.)  Betting any percentage that is not equal to that given by the Kelly criterion will inevitably lead to lower compound growth over a long period of time.

Mauboussin adds:

Proper portfolio construction requires specifying a goal (maximize sum for one period or parlayed bets), identifying an opportunity set (lots of small edge or lumpy but large edge), and considering constraints (liquidity, drawdowns, leverage).   Answers to these questions suggest an appropriate policy regarding position sizing and portfolio construction.

In brief, most investors are ineffective at position sizing, but great investors are good at it.



Great investors generally read a ton.  They also read widely across many disciplines.  Moreover, as noted earlier, great investors seek to learn about the arguments of people who disagree with them.  Mauboussin:

Berkshire Hathaway’s Charlie Munger said that he really liked Albert Einstein’s point that “success comes from curiosity, concentration, perseverance and self-criticism. And by self-criticism, he meant the ability to change his mind so that he destroyed his own best-loved ideas.”  Reading is an activity that tends to foster all of those qualities.

(Photo by Lapandr)

Mauboussin continues:

Munger has also said, “In my whole life, I have known no wise people (over a broad subject matter area) who didn’t read all the time—none, zero.”  This may be hyperbolic, but seems to be true in the investment world as well.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

The Outsiders: Radically Rational CEOs

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 21, 2018

William Thorndike is the author of The Outsiders: Eight Unconventional CEOs and Their Radically Rational Blueprint for Success (Harvard Business Review Press, 2012).  It’s an excellent book profiling eight CEOs who compounded shareholder value at extraordinary rates over decades.

Through this book, value investors can improve their understanding of how to identify CEOs who maximize long-term returns to shareholders.  Also, investors can become better businesspeople, while businesspeople can become better investors.

I am a better investor because I am a businessman and a better businessman because I am an investor. – Warren Buffett

Thorndike explains that you only need three things to evaluate CEO performance:

  • the compound annual return to shareholders during his or her tenure
  • the return over the same period for peer companies
  • the return over the same period for the broader market (usually measured by the S&P 500)

Thorndike notes that 20 percent returns is one thing during a huge bull market—like 1982 to 1999.  It’s quite another thing if it occurs during a period when the overall market is flat—like 1966 to 1982—and when there are several bear markets.

Moreover, many industries will go out of favor periodically.  That’s why it’s important to compare the company’s performance to peers.

Thorndike mentions Henry Singleton as the quintessential outsider CEO.  Long before it was popular to repurchase stock, Singleton repurchased over 90% of Teledyne’s stock.  Also, he emphasized cash flow over earnings.  He never split the stock.  He didn’t give quarterly guidance.  He almost never spoke with analysts or journalists.  And he ran a radically decentralized organization.  Thorndike:

If you had invested a dollar with Singleton in 1963, by 1990, when he retired as chairman in the teeth of a severe bear market, it would have been worth $180.  That same dollar invested in a broad group of conglomerates would have been worth only $27, and $15 if invested in the S&P 500.  Remarkably, Singleton outperformed the index by over twelve times.

Thorndike observes that rational capital allocation was the key to Singleton’s success.  Thorndike writes:

Basically, CEOs have five essential choices for deploying capital—investing in existing operations, acquiring other businesses, issuing dividends, paying down debt, or repurchasing stock—and three alternatives for raising it—tapping internal cash flow, issuing debt, or raising equity.  Think of these options collectively as a tool kit.  Over the long term, returns for shareholders will be determined largely by the decisions a CEO makes in choosing which tools to use (and which to avoid) among these various options.  Stated simply, two companies with identical operating results and different approaches to allocating capital will derive two very different long-term outcomes for shareholders.

Warren Buffett has noted that most CEOs reach the top due to their skill in marketing, production, engineering, administration, or even institutional politics.  Thus most CEOs have not been prepared to allocate capital.

Thorndike also points out that the outsider CEOs were iconoclastic, independent thinkers.  But the outsider CEOs, while differing noticeably from industry norms, ended up being similar to one another.  Thorndike says that the outsider CEOs understood the following principles:

  • Capital allocation is a CEO’s most important job.
  • What counts in the long run is the increase in per share value, not overall growth or size.
  • Cash flow, not reported earnings, is what determines long-term value.
  • Decentralized organizations release entrepreneurial energy and keep both costs and ‘rancor’ down.
  • Independent thinking is essential to long-term success, and interactions with outside advisers (Wall Street, the press, etc.) can be distracting and time-consuming.
  • Sometimes the best investment opportunity is your own stock.
  • With acquisitions, patience is a vital… as is occasional boldness.

(Illustration by yiorgosgr)

Here are the sections in the blog post:

  • Introduction
  • Tom Murphy and Capital Cities Broadcasting
  • Henry Singleton and Teledyne
  • Bill Anders and General Dynamics
  • John Malone and TCI
  • Katharine Graham and The Washington Post Company
  • Bill Stiritz and Ralston Purina
  • Dick Smith and General Cinema
  • Warren Buffett and Berkshire Hathaway
  • Radical Rationality



Only two of the eight outsider CEOs had MBAs.  And, writes Thorndike, they did not attract or seek the spotlight:

As a group, they shared old-fashioned, premodern values including frugality, humility, independence, and an unusual combination of conservatism and boldness.  They typically worked out of bare-bones offices (of which they were inordinately proud), generally eschewed perks such as corporate plans, avoided the spotlight wherever possible, and rarely communicated with Wall Street or the business press.  They also actively avoided bankers and other advisers, preferring their own counsel and that of a select group around them.  Ben Franklin would have liked these guys.

Thorndike describes how the outsider CEOs were iconoclasts:

Like Singleton, these CEOs consistently made very different decisions than their peers did.  They were not, however, blindly contrarian.  Theirs was an intelligent iconoclasm informed by careful analysis and often expressed in unusual financial metrics that were distinctly different from industry or Wall Street conventions.

Thorndike compares the outsider CEOs to Billy Beane as described by Michael Lewis in Moneyball.  Beane’s team, despite having the second-lowest payroll in the league, made the playoffs in four of his first six years on the job.  Beane had discovered newand unorthodoxmetrics that were more correlated with team winning percentage.

Thorndike mentions a famous essay about Leo Tolstoy written by Isaiah Berlin.  Berlin distinguishes between a “fox” who knows many things and a “hedgehog” who knows one thing extremely well.  Thorndike continues:

Foxes… also have many attractive qualities, including an ability to make connections across fields and to innovate, and the CEOs in this book were definite foxes.  They had familiarity with other companies and industries and disciplines, and this ranginess translated into new perspectives, which in turn helped them to develop new approaches that eventually translated into exceptional results.

(Photo by mbridger68)



When Murphy became CEO of Capital Cities in 1966, CBS’ market capitalization was sixteen times than that of Capital Cities.  Thirty years later, Capital Cities was three times as valuable as CBS.  Warren Buffett has said that in 1966, it was like a rowboat (Capital Cities) against QE2 (CBS) in a trans-Atlantic race.  And the rowboat won decisively!

Bill Paley, who ran CBS, used the enormous cash flow from its network and broadcast operations and undertook an aggressive acquisition program of companies in entirely unrelated fields.  Paley simply tried to make CBS larger without paying attention to the return on invested capital (ROIC).

Without a sufficiently high ROIC, growth destroys shareholder value instead of creating it.  But, like Paley, many business leaders at the time sought growth for its own sake.  Even if growth destroys value (due to low ROIC), it does make the business larger, bringing greater benefits to the executives.

Murphy’s goal, on the other hand, was to make his company as valuable as possible.  This meant maximizing profitability and ROIC:

…Murphy’s goal was to make his company more valuable… Under Murphy and his lieutenant, Dan Burke, Capital Cities rejected diversification and instead created an unusually streamlined conglomerate that focused laser-like on the media businesses it knew well.  Murphy acquired more radio and TV stations, operated them superbly well, regularly repurchased his shares, and eventually acquired CBS’s rival broadcast network ABC.

(Capital Cities/ABC, Inc. logo, via Wikimedia Commons)

Burke excelled in operations, while Murphy excelled in making acquisitions.  Together, they were a great team—unmatched, according to Warren Buffett.  Burke said his ‘job was to create free cash flow and Murphy’s was to spend it.’

During the mid-1970s, there was an extended bear market.  Murphy aggressively repurchased shares, mostly at single-digit price-to-earnings (P/E) multiples.

Thorndike writes that in January 1986, Murphy bought the ABC Network and its related broadcasting assets for $3.5 billion with financing from his friend Warren Buffett.  Thorndike comments:

Burke and Murphy wasted little time in implementing Capital Cities’ lean, decentralized approach—immediately cutting unnecessary perks, such as the executive elevator and the private dining room, and moving quickly to eliminate redundant positions, laying off fifteen hundred employees in the first several months after the transaction closed.  They also consolidated offices and sold off unnecessary real estate, collecting $175 million for the headquarters building in midtown Manhattan…

In the nine years after the transaction, revenues and cash flows grew significantly in every major ABC business line, including the TV stations, the publishing assets, and ESPN.  Even the network, which had been in last place at the time of the acquisition, was ranked number one in prime time ratings and was more profitable than either CBS or NBC.

In 1993, Burke retired.  And in 1995, Murphy, at Buffett’s suggestion, met with Michael Eisner, the CEO of Disney.  Over a few days, Murphy sold Capital Cities/ABC to Disney for $19 billion, which was 13.5 times cash flow and 28 times net income.  Thorndike:

He left behind an ecstatic group of shareholders—if you had invested a dollar with Tom Murphy as he became CEO in 1966, that dollar would have been worth $204 by the time he sold the company to Disney.  That’s a remarkable 19.9 percent internal rate of return over twenty-nine years, significantly outpacing the 10.1 percent return for the S&P 500 and 13.2 percent return for an index of leading media companies over the same period.

Thorndike points out the decentralization was one the keys to success for Capital Cities.  There was a single paragraph on the inside cover of every Capital Cities annual report:

‘Decentralization is the cornerstone of our philosophy.  Our goal is to hire the best people we can and give them the responsibility and authority they need to perform their jobs.  All decisions are made at the local level… We expect our managers… to be forever cost conscious and to recognize and exploit sales potential.’

Headquarters had almost no staff.  There were no vice presidents in marketing, strategic planning, or human resources.  There was no corporate counsel and no public relations department.  The environment was ideal for entrepreneurial managers.  Costs were minimized at every level.

Burke developed an extremely detailed annual budgeting process for every operation.  Managers had to present operating and capital budgets for the coming year, and Burke (and his CFO, Ron Doerfler) went through the budgets line-by-line:

The budget sessions were not perfunctory and almost always produced material changes.  Particular attention was paid to capital expenditures and expenses.  Managers were expected to outperform their peers, and great attention was paid to margins, which Burke viewed as ‘a form of report card.’  Outside of these meetings, managers were left alone and sometimes went months without hearing from corporate.

High margins resulted not only from cost minimization, but also from Murphy and Burke’s focus on revenue growth and advertising market share.  They invested in their properties to ensure leadership in local markets.

When it came to acquisitions, Murphy was very patient and disciplined.  His benchmark ‘was a double-digit after-tax return over ten years without leverage.’  Murphy never won an auction as a result of his discipline.  Murphy also had a unique negotiating style.

Murphy thought that, in the best transactions, everyone comes away happy.  He believed in ‘leaving something on the table’ for the seller.  Murphy would often ask the seller what they thought the property was worth.  If Murphy thought the offer was fair, he would take it.  If he thought the offer was high, he would counter with his best price.  If the seller rejected his counter-offer, Murphy would walk away.  He thought this approach saved time and avoided unnecessary friction.

Thorndike concludes his discussion of Capital Cities:

Although the focus here is on quantifiable business performance, it is worth noting that Murphy built a universally admired company at Capital Cities with an exceptionally strong culture and esprit de corps (at least two different groups of executives still hold regular reunions).



Singleton earned bachelor’s, master’s, and PhD degrees in electrical engineering from MIT.  He programmed the first student computer at MIT.  He won the Putnam Medal as the top mathematics student in the country in 1939.  And he was 100 points away from being a chess grandmaster.

Singleton worked as a research engineer at North American Aviation and Hughes Aircraft in 1950.  Tex Thornton recruited him to Litton Industries in the late 1950s, where Singleton invented an inertial guidance system—still in use—for commercial and military aircraft.  By the end of the decade, Singleton had grown Litton’s Electronic Systems Group to be the company’s largest division with over $80 million in revenue.

Once he realized he wouldn’t succeed Thornton as CEO, Singleton left Litton and founded Teledyne with his colleague George Kozmetzky.  After acquiring three small electronics companies, Teledyne successfully bid for a large naval contract.  Teledyne became a public company in 1961.

(Photo of Teledyne logo by Piotr Trojanowski)

In the 1960’s, conglomerates had high price-to-earnings (P/E) ratios and were able to use their stock to buy operating companies at relatively low multiples.  Singleton took full advantage of this arbitrage opportunity.  From 1961 to 1969, he purchased 130 companies in industries from aviation electronics to specialty metals and insurance.  Thorndike elaborates:

Singleton’s approach to acquisitions, however, differed from that of other conglomerateurs.  He did not buy indiscriminately, avoiding turnaround situations, and focusing instead on profitable, growing companies with leading market positions, often in niche markets… Singleton was a very disciplined buyer, never paying more than twelve times earnings and purchasing most companies at significantly lower multiples.  This compares to the high P/E multiple on Teledyne’s stock, which ranged from a low of 20 to a high of 50 over this period.

In mid-1969, Teledyne was trading at a lower multiple, while acquisition prices were increasing.  So Singleton completely stopped acquiring companies.

Singleton ran a highly decentralized company.  Singleton also did not report earnings, but instead focused on free cash flow (FCF)—what Buffett calls owner earnings.  The value of any business is all future FCF discounted back to the present.

FCF = net income + DDA – capex

(There are also adjustments to FCF based on changes in working capital.  DDA is depreciation, depletion, and amortization.)

At Teledyne, bonus compensation for all business unit managers was based on the maximization of free cash flow.  Singleton—along with his roommate from the Naval Academy, George Roberts—worked to improve margins and significantly reduce working capital.  Return on assets at Teledyne was greater than 20 percent in the 1970s and 1980s.  Charlie Munger calls these results from Teledyne ‘miles higher than anybody else… utterly ridiculous.’  This high profitability generated a great deal of excess cash, which was sent to Singleton to allocate.

Starting in 1972, Singleton started buying back Teledyne stock because it was cheap.  During the next twelve years, Singleton repurchased over 90 percent of Teledyne’s stock.  Keep in mind that in the early 1970s, stock buybacks were seen as a lack of investment opportunity.  But Singleton realized buybacks were far more tax-efficient than dividends.  And buybacks done when the stock is noticeably cheap create much value.  Whenever the returns from a buyback seemed higher than any alternative use of cash, Singleton repurchased shares.  Singleton spent $2.5 billion on buybacks—an unbelievable amount at the time—at an average P/E multiple of 8.  (When Teledyne issued shares, the average P/E multiple was 25.)

In the insurance portfolios, Singleton invested 77 percent in equities, concentrated on just a few stocks.  His investments were in companies he knew well that had P/E ratios at or near record lows.

In 1986, Singleton started going in the opposite direction:  deconglomerating instead of conglomerating.  He was a pioneer of spinning off various divisions.  And in 1987, Singleton announced the first dividend.

From 1963 to 1990, when Singleton stepped down as chairman, Teledyne produced 20.4 percent compound annual returns versus 8.0 percent for the S&P 500 and 11.6 percent for other major conglomerates.  A dollar invested with Singleton in 1963 would have been worth $180.94 by 1990, nearly ninefold outperformance versus his peers and more than twelvefold outperformance versus the S&P 500.



In 1989, the Berlin Wall came down and the U.S. defense industry’s business model had to be significantly downsized.  The policy of Soviet containment had become obsolete almost overnight.

General Dynamics had a long history selling major weapons to the Pentagon, including the B-29 bomber, the F-16 fighter plane, submarines, and land vehicles (such as tanks).  The company had diversified into missiles and space systems, as well as nondefense business including Cessna commercial planes.

(General Dynamics logo, via Wikimedia Commons)

W(hen Bill Anders took over General Dynamics in January 1991, the company had $600 million in debt and negative cash flow.  Revenues were $10 billion, but the market capitalization was just $1 billion.  Many thought the company was headed into bankruptcy.  It was a turnaround situation.

Anders graduated from the Naval Academy in 1955 with an electrical engineering degree.  He was an airforce fighter pilot during the Cold War.  In 1963 he earned a master’s degree in nuclear engineering and was chosen to join NASA’s elite astronaut corps.  Thorndike writes:

As the lunar module pilot on the 1968 Apollo 8 mission, Anders took the now-iconic Earthrise photograph, which eventually appeared on the covers of Time, Life, and American Photography.

Anders was a major general when he left NASA.  He was made the first chairman of the Nuclear Regulatory Commission.  Then he served as ambassador to Norway.  After that, he worked at General Electric and was trained in their management approach.  In 1984, Anders was hired to run the commercial operations of Textron Corporation.  He was not impressed with the mediocre businesses and the bureaucratic culture.  In 1989, he was invited to join General Dynamics as vice-chairman for a year before becoming CEO.

Anders realized that the defense industry had a great deal of excess capacity after the end of the Cold War.  Following Welch’s approach, Anders concluded that General Dynamics should only be in businesses where it was number one or two.  General Dynamics would stick to businesses it knew well.  And it would exit businesses that didn’t meet these criteria.

Anders also wanted to change the culture.  Instead of an engineering focus on ‘larger, faster, more lethal’ weapons, Anders wanted a focus on metrics such as return on equity (ROE).  Anders concluded that maximizing shareholder returns should be the primary business goal.  To help streamline operations, Anders hired Jim Mellor as president and COO.  In the first half of 1991, Anders and Mellor replaced twenty-one of the top twenty-five executives.

Anders then proceeded to generate $5 billion in cash through the sales of noncore businesses and by a significant improvement in operations.  Anders and Mellor created a culture focused on maximizing shareholder returns.  Anders sold most of General Dynamics’ businesses.  He also sought to grow the company’s largest business units through acquisition.

When Anders went to acquire Lockheed’s smaller fighter plane division, he met with a surprise:  Lockheed’s CEO made a high counteroffer for General Dynamics’ F-16 business.  Because the fighter plane division was a core business for General Dynamics—not to mention that Anders was a fighter pilot and still loved to fly—this was a crucial moment for Anders.  He agreed to sell the business on the spot for a very high price of $1.5 billion.  Anders’ decision was rational in the context of maximizing shareholder returns.

With the cash pile growing, Anders next decided not to make additional acquisitions, but to return cash to shareholders.  First he declared three special dividends—which, because they were deemed ‘return of capital,’ were not subject to capital gains or ordinary income taxes.  Next, Anders announced an enormous $1 billion tender offer for 30 percent of the company’s stock.

A dollar invested when Anders took the helm would have been worth $30 seventeen years later.  That same dollar would have been worth $17 if invested in an index of peer companies and $6 if invested in the S&P.



While at McKinsey, John Malone came to realize how attractive the cable television business was.  Revenues were very predictable.  Taxes were low.  And the industry was growing very fast.  Malone decided to build a career in cable.

Malone’s father was a research engineer and his mother a former teacher.  Malone graduated from Yale with degrees in economics and electrical engineering.  Then Malone earned master’s and PhD degrees in operations research from Johns Hopkins.

Malone’s first job was at Bell Labs, the research arm of AT&T.  After a couple of years, he moved to McKinsey Consulting.  In 1970, a client, General Instrument, offered Malone the chance to run its cable television equipment division.  He jumped at the opportunity.

After a couple of years, Malone was sought by two of the largest cable companies, Warner Communications and Tele-Communications Inc. (TCI).  Malone chose TCI.  Although the salary would be 60 percent lower, he would get more equity at TCI.  Also, he and his wife preferred Denver to Manhattan.

(TCI logo, via Wikimedia Commons)

The industry had excellent tax characteristics:

Prudent cable operators could successfully shelter their cash flow from taxes by using debt to build new systems and by aggressively depreciating the costs of construction.  These substantial depreciation charges reduced taxable income as did the interest expense on the debt, with the result that well-run cable companies rarely showed net income, and as a result, rarely paid taxes, despite very healthy cash flows.  If an operator then used debt to buy or build additional systems and depreciated the newly acquired assets, he could continue to shelter his cash flow indefinitely.

Just after Malone took over as CEO of TCI in 1973, the 1973-1974 bear market left TCI in a dangerous position.  The company was on the edge of bankruptcy due to its very high debt levels.  Malone spent the next few years meeting with bankers and lenders to keep the company out of bankruptcy.  Also during this time, Malone instituted new discipline in operations, which resulted in a frugal, entrepreneurial culture.  Headquarters was austere.  Executives stayed together in motels while on the road.

Malone depended on COO J. C. Sparkman to oversee operations, while Malone focused on capital allocation.  TCI ended up having the highest margins in the industry as a result.  They earned a reputation for underpromising and overdelivering.

In 1977, the balance sheet was in much better shape.  Malone had learned that the key to creating value in cable television was financial leverage and leverage with suppliers (especially programmers).  Both types of leverage improved as the company became larger.  Malone had unwavering commitment to increasing the company’s size.

The largest cost in a cable television system is fees paid to programmers (HBO, MTV, ESPN, etc.).  Larger cable operators can negotiate lower programming costs per subscriber.  The more subscribers the cable company has, the lower its programming cost per subscriber.  This led to a virtuous cycle:

[If] you buy more systems, you lower your programming costs and increase your cash flow, which allows more financial leverage, which can then be used to buy more systems, which further improves your programming costs, and so on… no one else at the time pursued scale remotely as aggressively as Malone and TCI.

Malone also focused on minimizing reported earnings (and thus taxes).  At the time, this was highly unconventional since most companies focused on earnings per share.  TCI gained an important competitive advantage by minimizing earnings and taxes.  Terms like EBITDA were introduced by Malone.

Between 1973 and 1989, the company made 482 acquisitions.  The key was to maximize the number of subscribers.  (When TCI’s stock dropped, Malone repurchased shares.)

By the late 1970s and early 1980s, after the introduction of satellite-delivered channels such as HBO and MTV, cable television went from primarily rural customers to a new focus on urban markets.  The bidding for urban franchises quickly overheated.  Malone avoided the expensive urban franchise wars, and stayed focused on acquiring less expensive rural and suburban subscribers.  Thorndike:

When many of the early urban franchises collapsed under a combination of too much debt and uneconomic terms, Malone stepped forward and acquired control at a fraction of the original cost.

Malone also established various joint ventures, which led to a number of cable companies in which TCI held a minority stake.  Over time, Malone created a great deal of value for TCI by investing in young, talented entrepreneurs.

From 1973 to 1998, TCI shareholders enjoyed a compound annual return of 30.3 percent, compared to 20.4 percent for other publicly traded cable companies and 14.3 percent for the S&P 500.  A dollar invested in TCI at the beginning was worth over $900 by mid-1998.  The same dollar was worth $180 if invested in other publicly traded cable companies and $22 if invested in the S&P 500.

Malone never used spreadsheets.  He looked for no-brainers that could be understood with simple math.  Malone also delayed capital expenditures, generally until the economic viability of the investment had been proved.  When it came to acquisitions—of which there were many—Malone would only pay five times cash flow.



Katharine Graham was the daughter of financier Eugene Meyer.  In 1940, she married Philip Graham, a brilliant lawyer.  Meyer hired Philip Graham to run The Washington Post Company in 1946.  He did an excellent job until his tragic suicide in 1963.

(The Washington Post logo, via Wikimedia Commons)

Katharine was unexpectedly thrust into the CEO role.  At age forty-six, she had virtually no preparation for this role and she was naturally shy.  But she ended up doing an amazing job.  From 1971 to 1993, the compound annual return to shareholders was 22.3 percent versus 12.4 percent for peers and 7.4 percent for the S&P 500.  A dollar invested in the IPO was worth $89 by the time she retired, versus $5 for the S&P and $14 for her peer group.  These are remarkable margins of outperformance.

After a few years of settling into the new role, she began to take charge.  In 1967, she replaced longtime editor in chief Russ Wiggins with the brash Ben Bradlee, who was forty-four years old.

In 1971, she took the company public to raise capital for acquisitions.  This was what the board had recommended.  At the same time, the newspaper encountered the Pentagon Papers crisis.  The company was going to publish a highly controversial (and negative) internal Pentagon opinion of the war in Vietnam that a court had barred the New York Times from publishing.  The Nixon administration threatened to challenge the company’s broadcast licenses if it published the report:

Such a challenge would have scuttled the stock offering and threatened one of the company’s primary profit centers.  Graham, faced with unclear legal advice, had to make the decision entirely on her own.  She decided to go ahead and print the story, and the Post’s editorial reputation was made.  The Nixon administration did not challenge the TV licenses, and the offering, which raised $16 million, was a success.

In 1972, with Graham’s full support, the paper began in-depth investigations into the Republican campaign lapses that would eventually become the Watergate scandal.  Bradlee and two young investigative reporters, Carl Bernstein and Bob Woodward, led the coverage of Watergate, which culminated with Nixon’s resignation in the summer of 1974.  This led to a Pulitzer for the Post—one of an astonishing eighteen during Bradlee’s editorship—and established the paper as the only peer of the New York Times.  All during the investigation, the Nixon administration threatened Graham and the Post.  Graham firmly ignored them.

In 1974, an unknown investor eventually bought 13 percent of the paper’s shares.  The board advised Graham not to meet with him.  Graham ignored the advice and met the investor, whose name was Warren Buffett.  Buffett quickly became Graham’s business mentor.

In 1975, the paper faced a huge strike led by the pressmen’s union.  Graham, after consulting Buffett and the board, decided to fight the strike.  Graham, Bradlee, and a very small crew managed to get the paper published for 139 consecutive days.  Then the pressmen finally agreed to concessions.  These concessions led to significantly improved profitability for the paper.  It was also the first time a major city paper had broken a strike.

Also on advice from Buffett, Graham began aggressively buying back stock.  Over the next few years, she repurchased nearly 40 percent of the company’s stock at very low prices (relative to intrinsic value).  No other major papers did so.

In 1981, the Post’s rival, the Washington Star, ceased publication.  This allowed the Post to significantly increase circulation.  At the same time, Graham hired Dick Simmons as COO.  Simmons successfully lowered costs and improved profits.  Simmons also emphasized bonus compensation based on performance relative to peer newspapers.

In the early 1980s, the Post spent years not acquiring any companies, even though other major newspapers were making more deals than ever.  Graham was criticized, but stuck to her financial discipline.  In 1983, however, after extensive research, the Post bought cellular telephone businesses in six major markets.  In 1984, the Post acquired the Stanley Kaplan test prep business.  And in 1986, the paper bought Capital Cities’ cable television assets for $350 million.  All of these acquisitions would prove valuable for the Post in the future.

In 1988, Graham sold the paper’s telephone assets for $197 million, a very high return on investment.  Thorndike continues:

During the recession of the early 1990s, when her overleveraged peers were forced to the sidelines, the company became uncharacteristically acquisitive, taking advantage of dramatically lower prices to opportunistically purchase cable television systems, underperforming TV stations, and a few education businesses.

When Kay Graham stepped down as chairman in 1993, the Post Company was by far the most diversified among its major newspaper peers, earning almost half its revenues and profits from non-print sources.  This diversification would position the company for further outperformance under her son Donald’s leadership.



Bill Stiritz was at Ralston seventeen years before becoming CEO at age forty-seven.

This seemingly conventional background, however, masked a fiercely independent cast of mind that made him a highly effective, if unlikely, change agent.  When Stiritz assumed the CEO role, it would have been impossible to predict the radical transformation he would effect at Ralston and the broader influence it would have on his peers in the food and packaged goods industries.

(Purina logo, via Wikimedia Commons)

Stiritz attended the University of Arkansas for a year but then joined the navy for four years.  While in the navy, he developed his poker skills enough so that poker eventually would pay for his college tuition.  Stiritz completed his undergraduate degree at Northwestern, majoring in business.  (In his mid-thirties, he got a master’s degree in European history from Saint Louis University.)

Stiritz first worked at the Pillsbury Company as a field rep putting cereal on store shelves.  He was promoted to product manager and he learned about consumer packaged goods (CPG) marketing.  Wanting to understand advertising and media better, he started working two years later at the Gardner Advertising agency in St. Louis.  He focused on quantitative approaches to marketing such as the new Nielsen ratings service, which gave a detailed view of market share as a function of promotional spending.

In 1964, Stiritz joined Ralston Purina in the grocery products division (pet food and cereals).  He became general manager of the division in 1971.  While Stiritz was there, operating profits increased fiftyfold due to new product introductions and line extensions.  Thorndike:

Stiritz personally oversaw the introduction of Purina Puppy and Cat Chow, two of the most successful launches in the history of the pet food industry.  For a marketer, Stiritz was highly analytical, with a natural facility for numbers and a skeptical, almost prickly temperament.

Thorndike continues:

On assuming the CEO role in 1981, Stiritz wasted little time in aggressively restructuring the company.  He fully appreciated the exceptionally attractive economics of the company’s portfolio of consumer brands and promptly reorganized the company around these businesses, which he believed offered an attractive combination of high margins and low capital requirements.  He immediately began to remove the underpinnings of his predecessor’s strategy, and his first moves involved actively divesting businesses that did not meet his criteria for profitability and returns.

After a number of divestitures, Ralston was a pure branded products company.  In the early 1980s, Stiritz began repurchasing stock aggressively.  No other major branded products company was repurchasing stock at that time.

Stiritz then bought Continental Baking, the maker of Twinkies and Wonder Bread.  He expanded distribution, cut costs, introduced new products, and increased cash flow materially, creating much value for shareholders.

Then in 1986, Stiritz bought the Energizer Battery division from Union Carbide for $1.5 billion.  The business had been a neglected operation at Union Carbide.  Stiritz thought it was undermanaged and also part of a growing duopoly market.

By the late 1980s, almost 90 percent of Ralston’s revenues were from consumer packaged goods.  Pretax profit margins increased from 9 to 15 percent.  ROE went from 15 to 37 percent.  Since the share base was reduced by aggressive buybacks, earnings and cash flow per share increased dramatically.  Stiritz continued making very careful acquisitions and divestitures, with each decision based on an in-depth analysis of potential returns for shareholders.

Stiritz also began spinning off some businesses he thought were not receiving the attention they deserved—either internally or from Wall Street.  Spin-offs not only can highlight the value of certain business units.  Spin-offs also allow the deferral of capital gains taxes.

Finally, Stiritz sold Ralston itself to Nestle for $10.4 billion, or fourteen times cash flow.  This successfully concluded Stiritz’ career at Ralston.  A dollar invested with Stiritz when he became CEO was worth $57 nineteen years later.  The compound return was 20.0 percent versus 17.7 percent for peers and 14.7 percent for the S&P 500.

Stiritz didn’t like the false precision of detailed financial models.  Instead, he focused only on the few key variables that mattered, including growth and competitive dynamics.  When Ralston bought Energizer, Stiritz and his protégé Pat Mulcahy, along with a small group, took a look at Energizer’s books and then wrote down a simple, back of the envelope LBO model.  That was it.

Since selling Ralston, Stiritz has energetically managed an investment partnership made up primarily of his own capital.



In 1922, Phillip Smith borrowed money from friends and family, and opened a theater in Boston’s North End.  Over the next forty years, Smith built a successful chain of theaters.  In 1961, Phillip Smith took the company public to raise capital.  But in 1962, Smith passed away.  His son, Dick Smith, took over as CEO.  He was thirty-seven years old.

(General Cinema logo, via Wikimedia Commons)

Dick Smith demonstrated a high degree of patience in using the company’s cash flow to diversify away from the maturing drive-in movie business.

Smith would alternate long periods of inactivity with the occasional very large transaction.  During his tenure, he would make three significant acquisitions (one in the late 1960s, one in the mid-1980s, and one in the early 1990s) in unrelated businesses:  soft drink bottling (American Beverage Company), retailing (Carter Hawley Hale), and publishing (Harcourt Brace Jovanovich).  This series of transactions transformed the regional drive-in company into an enormously successful consumer conglomerate.

Dick Smith later sold businesses that he had earlier acquired.  His timing was extraordinarily good, with one sale in the late 1980s, one in 2003, and one in 2006.  Thorndike writes:

This accordion-like pattern of expansion and contraction, of diversification and divestiture, was highly unusual (although similar in some ways to Henry Singleton’s at Teledyne) and paid enormous benefits for General Cinema’s shareholders.

Smith graduated from Harvard with an engineering degree in 1946.  He worked as a naval engineer during World War II.  After the war, he didn’t want an MBA.  He wanted to join the family business.  In 1956, Dick Smith’s father made him a full partner.

Dick Smith recognized before most others that suburban theaters were benefitting from strong demographic trends.  This led him to develop two new practices.

First, it had been assumed that theater owners should own the underlying land.  But Smith realized that a theater in the right location could fairly quickly generate predictable cash flow.  So he pioneered lease financing for new theaters, which significantly reduced the upfront investment.

Second, he added more screens to each theater, thereby attracting more people, who in turn bought more high-margin concessions.

Throughout the 1960s and into the early 1970s, General Cinema was getting very high returns on its investment in new theaters.  But Smith realized that such growth was not likely to continue indefinitely.  He started searching for new businesses with better long-term prospects.

In 1968, Smith acquired the American Beverage Company (ABC), the largest, independent Pepsi bottler in the country.  Smith knew about the beverage business based on his experience with theater concessions.  Smith paid five times cash flow and it was a very large acquisition for General Cinema at the time.  Thorndike notes:

Smith had grown up in the bricks-and-mortar world of movie theaters, and ABC was his first exposure to the value of businesses with intangible assets, like beverage brands.  Smith grew to love the beverage business, which was an oligopoly with very high returns on capital and attractive long-term growth trends.  He particularly liked the dynamics within the Pepsi bottler universe, which was fragmented and had many second- and third-generation owners who were potential sellers (unlike the Coke system, which was dominated by a smaller number of large independents).  Because Pepsi was the number two brand, its franchises often traded at lower valuations than Coke’s.

ABC was a platform companyother companies could be added easily and efficiently.  Smith could buy new franchises at seemingly high multiples of the seller’s cash flow and then quickly reduce the effective price through reducing expenses, minimizing taxes, and improving marketing.  So Smith acquired other franchises.

Due to constant efforts to reduce costs by Smith and his team, ABC had industry-leading margins.  Soon thereafter, ABC invested $20 million to launch Sunkist.  In 1984, Smith sold Sunkist to Canada Dry for $87 million.

Smith sought another large business to purchase.  He made a number of smaller acquisitions in the broadcast media business.  But his price discipline prevented him from buying very much.

Eventually General Cinema bought Carter Hawley Hale (CHH), a retail conglomerate with several department store and specialty retail chains.  Woody Ives, General Cinema’s CFO, was able to negotiate attractive terms:

Ives negotiated a preferred security that guaranteed General Cinema a 10 percent return, allowed it to convert its interest into 40 percent of the common stock if the business performed well, and included a fixed-price option to buy Waldenbooks, a wholly owned subsidiary of CHH…

Eventually General Cinema would exchange its 40 percent ownership in CHH shares for a controlling 60 percent stake in the company’s specialty retail division, whose primary asset was the Neiman Marcus chain.  The long-term returns on the company’s CHH investment were an extraordinary 51.2 percent.  The CHH transaction moved General Cinema decisively into retailing, a new business whose attractive growth prospects were not correlated with either the beverage or the theater businesses.

In the late 1980s, Smith noticed that a newly energetic Coke was attacking Pepsi in local markets.  At the same time, beverage franchises were selling for much higher prices as their good economics were more widely recognized.  So Smith sold the bottling business in 1989 to Pepsi for a record price.  After the sale, General Cinema was sitting on $1 billion in cash.  Smith started looking for another diversifying acquisition.

It didn’t take him long to find one.  In 1991, after a tortuous eighteen-month process, Smith made his largest and last acquisition, buying publisher Harcourt Brace Jovanovich (HBJ) in a complex auction process and assembling General Cinema’s final third leg.  HBJ was a leading educational and scientific publisher that also owned a testing business and an outplacement firm.  Since the mid-1960s, the firm had been run as a personal fiefdom by CEO William Jovanovich.  In 1986, the company received a hostile takeover bid from the renegade British publisher Robert Maxwell, and in response Jovanovich had taken on large amounts of debt, sold off HBJ’s amusement park business, and made a large distribution to shareholders.

General Cinema management concluded, after examining the business, that HBJ would fit their acquisition criteria.  Moreover, General Cinema managers thought HBJ’s complex balance sheet would probably deter other buyers.  Thorndike writes:

After extensive negotiations with the company’s many debt holders, Smith agreed to purchase the company for $1.56 billion, which represented 62 percent of General Cinema’s enterprise value at the time—an enormous bet.  This price equaled a multiple of six times cash flow for HBJ’s core publishing assets, an attractive price relative to comparable transactions (Smith would eventually sell those businesses for eleven times cash flow).

Thorndike continues:

Following the HBJ acquisition in 1991, General Cinema spun off its mature theater business into a separate publicly traded entity, GC Companies (GCC), allowing management to focus its attention on the larger retail and publishing businesses.  Smith and his management team proceeded to operate both the retail and the publishing businesses over the next decade.  In 2003, Smith sold the HBJ publishing assets to Reed Elsevier, and in 2006 he sold Neiman Marcus, the last vestige of the General Cinema portfolio, to a consortium of private equity buyers.  Both transactions set valuation records within their industries, capping an extraordinary run for Smith and General Cinema shareholders.

From 1962 to 1991, Smith had generated 16.1 percent compound annual return versus 9 percent for the S&P 500 and 9.8 percent for GE.  A dollar invested with Dick Smith in 1962 would be worth $684 by 1991.  The same dollar would $43 if invested in the S&P and $60 if invested in GE.



Buffett was first attracted to the old textile mill Berkshire Hathaway because its price was cheap compared to book value.  Thorndike tells the story:

At the time, the company had only a weak market position in a brutally competitive commodity business (suit linings) and a mere $18 million in market capitalization.  From this undistinguished start, unprecedented returns followed;  and measured by long-term stock performance, the formerly crew-cut Nebraskan is simply on another planet from all other CEOs.  These otherworldly returns had their origin in that aging New England textile company, which today has a market capitalization of $140 billion and virtually the same number of shares.  Buffett bought his first share of Berkshire for $7;  today it trades for over $120,000 share.  [Value of Berkshire share as of 10/21/18:  $517.2 billion market capitalization, or $314,477 a share]

(Company logo, by Berkshire Hathaway Inc., via Wikimedia Commons)

Buffett was born in 1930 in Omaha, Nebraska.  His grandfather ran a well-known local grocery store.  His father was a stockbroker in downtown Omaha and later a congressman.  Starting at age six, Buffett started various entrepreneurial ventures.  He would buy a 6-pack of Coke for 25 cents and resell each one for 5 cents.  He later had several paper routes and then pinball machines, too.  Buffett attended Wharton, but didn’t feel he could learn much.  So he returned to Omaha and graduated from the University of Nebraska at age 20.

He’d always been interested in the stock market.  But it wasn’t until he was nineteen that he discovered The Intelligent Investor, by Benjamin Graham.  Buffett immediately realized that value investing—as explained by Graham in simple terms—was the key to making money in the stock market.

Buffett was rejected by Harvard Business School, which was a blessing in that Buffett attended Columbia University where Graham was teaching.  Buffett was the star in Graham’s class, getting the only A+ Graham ever gave in more than twenty years of teaching.  Others in that particular course said the class was often like a conversation between Graham and Buffett.

Buffett graduated from Columbia in 1952.  He applied to work for Graham, but Graham turned him down.  At the time, Jewish analysts were having a hard time finding work on Wall Street, so Graham only hired Jewish people.  Buffett returned to Omaha and worked as a stockbroker.

One idea Buffett had tried to pitch while he was a stockbroker was GEICO.  He realized that GEICO had a sustainable competitive advantage:  a permanently lower cost structure because GEICO sold car insurance direct, without agents or branches.  Buffett had trouble convincing clients to buy GEICO, but he himself loaded up in his own account.

Meanwhile, Buffett regularly mailed investment ideas to Graham.  After a couple of years, in 1954, Graham hired Buffett.

In 1956, Graham dissolved the partnership to focus on other interests.  Buffett returned to Omaha and launched a small investment partnership with $105,000 under management.  Buffett himself was worth $140,000 at the time (over $1 million today).

Over the next thirteen years, Buffett crushed the market averages.  Early on, he was applying Graham’s methods by buying stocks that were cheap relative to net asset value.  But in the mid-1960s, Buffett made two large investments—in American Express and Disney—that were based more on normalized earnings than net asset value.  This was the beginning of a transition Buffett made from buying statistically cheap cigar butts to buying higher quality companies.

  • Buffett referred to deep value opportunities—stocks bought far below net asset value—as cigar butts. Like a soggy cigar butt found on a street corner, a deep value investment would often give “one free puff.”  Such a cigar butt is disgusting, but that one puff is “all profit.”

Buffett started acquiring shares in Berkshire Hathaway—a cigar butt—in 1965.  In the late 1960s, Buffett was having trouble finding cheap stocks, so he closed down the Buffett partnership.

After getting control of Berkshire Hathaway, Buffett put in a new CEO, Ken Chace.  The company generated $14 million in cash as Chace reduced inventories and sold excess plants and equipment.  Buffett used most of this cash to acquire National Indemnity, a niche insurance company.  Buffett invested National Indemnity’s float quite well, buying other businesses like the Omaha Sun, a weekly newspaper, and a bank in Rockford, Illinois.

During this period, Buffett met Charlie Munger, another Omaha native who was then a brilliant lawyer in Los Angeles.  Buffett convinced Munger to run his own investment partnership, which he did with excellent results.  Later on, Munger became vice-chairman at Berkshire Hathaway.

Partly by reading the works of Phil Fisher, but more from Munger’s influence, Buffett realized that a wonderful company at a fair price was better than a fair company at a wonderful price.  A wonderful company would have a sustainably high ROIC, which meant that its intrinsic value would compound over time.  In order to estimate intrinsic value, Buffett now relied more on DCF (discounted cash flow) and private market value—methods well-suited to valuing good businesses (often at fair prices)—rather than an estimate of liquidation value—a method well-suited to valuing cigar butts (mediocre businesses at cheap prices).

In the 1970s, Buffett and Munger invested in See’s Candies and the Buffalo News.  And they bought large stock positions in the Washington Post, GEICO, and General Foods.

In the first half of the 1980s, Buffett bought the Nebraska Furniture Mart for $60 million and Scott Fetzer, a conglomerate of niche industrial businesses, for $315 million.  In 1986, Buffett invested $500 million helping his friend Tom Murphy, CEO of Capital Cities, acquire ABC.

Buffett then made no public market investments for several years.  Finally in 1989, Buffett announced that he invested $1.02 billion, a quarter of Berkshire’s investment portfolio, in Coca-Cola, paying five times book value and fifteen times earnings.  The return on this investment over the ensuing decade was 10x.

(Coca-Cola Company logo, via Wikimedia Commons)

Also in the late 1980s, Buffett invested in convertible preferred securities in Salomon Brothers, Gillette, US Airways, and Champion Industries.  The dividends were tax-advantaged, and he could convert to common stock if the companies did well.

In 1991, Salomon Brothers was in a major scandal based on fixing prices in government Treasury bill auctions.  Buffett ended up as interim CEO for nine months.  Buffett told Salomon employees:

“Lose money for the firm and I will be understanding.  Lose even a shred of reputation for the firm, and I will be ruthless.”

In 1996, Salomon was sold to Sandy Weill’s Travelers Corporation for $9 billion, which was a large return on investment for Berkshire.

In the early 1990s, Buffett invested—taking large positions—in Wells Fargo (1990), General Dynamics (1992), and American Express (1994).  In 1996, Berkshire acquired the half of GEICO it didn’t own.  Berkshire also purchased the reinsurer General Re in 1998 for $22 billion in Berkshire stock.

In the late 1990s and early 2000s, Buffett bought a string of private companies, including Shaw Carpets, Benjamin Moore Paints, and Clayton Homes.  He also invested in the electric utility industry through MidAmerican Energy.  In 2006, Berkshire announced its first international acquisition, a $5 billion investment in Iscar, an Israeli manufacturer of cutting tools and blades.

In early 2010, Berkshire purchased the nation’s largest railroad, the Burlington Northern Santa Fe, for $34.2 billion.

From June 1965, when Buffett assumed control of Berkshire, through 2011, the value of the company’s shares increased at a compound rate of 20.7 percent compared to 9.3 percent for the S&P 500.  A dollar invested in Berkshire was worth $6,265 forty-five years later.  The same dollar invested in the S&P 500 was worth $62.

The Nuts and Bolts

Having learned from Murphy, Buffett and Munger created Berkshire to be radically decentralized.  Business managers are given total autonomy over everything except large capital allocation decisions.  Buffett makes the capital allocation decisions, and Buffett is an even better investor than Henry Singleton.

Another key to Berkshire’s success is that the insurance and reinsurance operations are profitable over time, and meanwhile Buffett invests most of the float.  Effectively, the float has an extremely low cost (occasionally negative) because the insurance and reinsurance operations are profitable.  Buffett always reminds Berkshire shareholders that hiring Ajit Jain to run reinsurance was one of the best investments ever for Berkshire.

As mentioned, Buffett is in charge of capital allocation.  He is arguably the best investor ever based on the longevity of his phenomenal track record.

Buffett and Munger have always believed in concentrated portfolios.  It makes sense to take very large positions in your best ideas.  Buffett invested 40 percent of the Buffett partnership in American Express after the salad oil scandal in 1963.  In 1989, Buffett invested 25 percent of the Berkshire portfolio—$1.02 billion—in Coca-Cola.

Buffett and Munger still have a very concentrated portfolio.  But sheer size requires them to have more positions than before.  It also means that they can no longer look at most companies, which are too small to move the needle.

Buffett and Munger also believe in holding their positions for decades.  Over time, this saves a great deal of money by minimizing taxes and transaction costs.


Buffett’s approach to investor relations is also unique and homegrown.  Buffett estimates that the average CEO spends 20 percent of his time communicating with Wall Street.  In contrast, he spends no time with analysts, never attends investment conferences, and has never provided quarterly earnings guidance.  He prefers to communicate with his investors through detailed annual reports and meetings, both of which are unique.

… The annual reports and meetings reinforce a powerful culture that values frugality, independent thinking, and long-term stewardship.




You’re neither right nor wrong because other people agree with you.  You’re right because your facts are right and your reasoning is right—and that’s the only thing that makes you right.  And if your facts and reasoning are right, you don’t have to worry about anybody else. – Warren Buffett

Thorndike sums up the outsider’s mindset:

  • Always Do the Math
  • The Denominator Matters
  • A Feisty Independence
  • Charisma is Overrated
  • A Crocodile-Like Temperament That Mixes Patience with Occasional Bold Action
  • The Consistent Application of a Rational, Analytical Approach to Decisions Large and Small
  • A Long-Term Perspective

Always Do the Math

The outsider CEOs always focus on the ROIC for any potential investment.  They do the analysis themselves just using the key variables and without using a financial model.  Outsider CEOs realize that it’s the assumptions about the key variables that really matter.

The Denominator Matters

The outsider CEOs focus on maximizing value per share.  Thus, the focus is not only on maximizing the numerator—the value—but also on minimizing the denominator—the number of shares.  Outsider CEOs opportunistically repurchase shares when the shares are cheap.  And they are careful when they finance investment projects.

A Feisty Independence

The outsider CEOs all ran very decentralized organizations.  They gave people responsibility for their respective operations.  But outsider CEOs kept control over capital allocation decisions.  And when they did make decisions, outsider CEOs didn’t seek others’ opinions.  Instead, they liked to gather all the information, and then think and decide with as much independence and rationality as possible.

Charisma Is Overrated

The outsider CEOs tended to be humble and unpromotional.  They tried to spend the absolute minimum amount of time interacting with Wall Street.  Outsider CEOs did not offer quarterly guidance and they did not participate in Wall Street conferences.

A Crocodile-Like Temperament That Mixes Patience With Occasional Bold Action

The outsider CEOs were willing to wait very long periods of time for the right opportunity to emerge.

Like Katharine Graham, many of them created enormous shareholder value by simply avoiding overpriced ‘strategic’ acquisitions, staying on the sidelines during periods of acquisition feeding frenzy.

On the rare occasions when there was something to do, the outsider CEOs acted boldly and aggressively.  Tom Murphy made an acquisition of a company (ABC) larger than the one he managed (Capital Cities).  Henry Singleton repeatedly repurchased huge amounts of stock at cheap prices, eventually buying back over 90 percent of Teledyne’s shares.

The Consistent Application of a Rational, Analytical Approach to Decisions Large and Small

The total value that any company creates over time is the cumulative difference between ROIC and the cost of capital.  The outsider CEOs made every capital allocation decision in order to maximize ROIC over time, thereby maximizing long-term shareholder value.

These CEOs knew precisely what they were looking for, and so did their employees.  They didn’t overanalyze or overmodel, and they didn’t look to outside consultants or bankers to confirm their thinking—they pounced.

A Long-Term Perspective

The outsider CEOs would make investments in their business as long as they thought that it would contribute to maximizing long-term ROIC and long-term shareholder value.  The outsiders were always willing to take short-term pain for long-term gain:

[They] disdained dividends, made disciplined (occasionally large) acquisitions, used leverage selectively, bought back a lot of stock, minimized taxes, ran decentralized organizations, and focused on cash flow over reported net income.

Thorndike notes that the advantage the outsider CEOs had was temperament, not intellect (although they were all highly intelligent).  They understood that what mattered was rationality and patience.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Quantitative Deep Value Investing

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 14, 2018

Virtually all of the historical evidence shows that quantitative deep value investing—systematically buying stocks at low multiples (low P/B, P/E, P/S, P/CF, and EV/EBITDA)—does better than the market over time.

Deep value investing means investing in ugly stocks that are doing terribly—with low- or no-growth—and that are trading at low multiples.  Quantitative deep value investing means that the portfolio of deep value stocks is systematically constructed based solely on quantitative factors including cheapness.  (It’s a process that can easily be automated.)

One of the best papers on quantitative deep value investing is by Josef Lakonishok, Andrei Shleifer, and Robert Vishny (1994), “Contrarian Investment, Extrapolation, and Risk.”  Link: http://scholar.harvard.edu/files/shleifer/files/contrarianinvestment.pdf

Buffett has called deep value investing the cigar butt approach:

…You walk down the street and you look around for a cigar butt someplace.  Finally you see one and it is soggy and kind of repulsive, but there is one puff left in it.  So you pick it up and the puff is free—it is a cigar butt stock.  You get one free puff on it and then you throw it away and try another one.  It is not elegant.  But it works.  Those are low return businesses.

(Photo by Sensay)

Outline for this blog post:

  • Rare Temperament
  • Early Buffett: Deep Value Investor
  • Investors Much Prefer Income Over Assets
  • Companies at Cyclical Lows



Many value investors prefer to invest in higher-quality companies rather than deep value stocks.  A high-quality company has a sustainable competitive advantage that allows it to earn a high ROIC (return on invested capital) for a long time.  When you invest in such a company, you can simply hold the position for years as it compounds intrinsic value.  Assuming you’ve done your homework and gotten the initial buy decision right, you typically don’t have to worry much.

Investing in cigar butts (deep value stocks), however, means that you’re investing in many mediocre or bad businesses.  These are companies that have terrible recent performance.  Some of these businesses won’t survive over the longer term, although even the non-survivors often survive many years longer than is commonly supposed.

Deep value investing can work quite well, but it takes a certain temperament not to care about various forms of suffering—such as being isolated and looking foolish.  As Bryan Jacoboski puts it:

The very reason price and value diverge in predictable and exploitable ways is because people are emotional beings.  That’s why the distinguishing attribute among successful investors is temperament rather than brainpower, experience, or classroom training.  They have the ability to be rational when others are not.

(Photo by Nikki Zalewski)

In The Manual of Ideas (Wiley, 2013), John Mihaljevic explains the difficulty of deep value investing:

It turns out that Graham-style investing may be appropriate for a relatively small subset of the investment community, as it requires an unusual willingness to stand alone, persevere, and look foolish.

On more than one occasion, we have heard investors respond as follows to a deep value investment thesis: ‘The stock does look deeply undervalued, but I just can’t get comfortable with it.’  When pressed on the reasons for passing, many investors point to the uncertainty of the situation, the likelihood of negative news flow, or simply a bad gut feeling.  Most investors also find it less rewarding to communicate to their clients that they own a company that has been in the news for the wrong reasons.

Comfort can be expensive in investing.  Put differently, acceptance of discomfort can be rewarding, as equities that cause their owners discomfort frequently trade at exceptionally low valuations.

Many investors will look at a list of statistically cheap stocks and conclude that most of them would be awful investments.  But in practice, a basket of deep value stocks tends to outperform, given enough time.  And typically some of the big winners include stocks that looked the worst prior to being included in the portfolio.



Warren Buffett started out as a cigar-butt investor.  That was the method he learned from his teacher and mentor, Ben Graham, the father of value investing.  When Buffett ran his partnership, he generated exceptional performance using a deep value strategy focused on microcap stocks: http://boolefund.com/buffetts-best-microcap-cigar-butts/

(Early Buffett teaching at the University of Nebraska, via Wikimedia Commons)

One reason Buffett transitioned from deep value to buying high-quality companies (and holding them forever) was simply that the assets he was managing at Berkshire Hathaway became much too large for deep value.  But in his personal account, Buffett recently bought a basket of South Korean cigar butts and ended up doing very well.

Buffett has made it clear that if your assets under management are relatively small, then deep value investing—especially when focused on microcap stocks—can do better than investing in high-quality companies.  Buffett has said he could make 50% a year by investing in deep value microcap stocks: http://boolefund.com/buffetts-best-microcap-cigar-butts/

In the microcap world, since most professional investors don’t look there, if you turn over enough rocks you can find some exceptionally cheap companies.  If you don’t have sufficient time and interest to find the most attractive individual microcap stocks, using a quantitative approach is an excellent alternative.  A good quantitative value fund focused on microcaps is likely to do much better than the S&P 500 over time.  That’s the mission of the Boole Fund.



Outside of markets, people naturally assess the value of possessions or private businesses in terms of net asset value—which typically corresponds with what a buyer would pay.  But in markets, when the current income of an asset-rich company is abnormally low, most investors fixate on the low income even when the best estimate of the company’s value is net asset value.  (Mihaljevic makes this point.)

If an investor is considering a franchise (high-quality) business like Coca-Cola or Johnson & Johnson, then it makes sense to focus on income, since most of the asset value involves intangible assets (brand value, etc).

But for many potential investments, net asset value is more important than current income.  Most investors ignore this fact and stay fixated on current income.  This is a major reason why stock prices occasionally fall far below net asset value, which creates opportunities for deep value investors.

(Illustration by Teguh Jati Prasetyo)

Over a long period of time, the income of most businesses does relate to net asset value.  Bruce Greenwald, in his book Value Investing (Wiley, 2004), explains the connection.  For most businesses, the best way to estimate intrinsic value is to estimate the reproduction cost of the assets.  And for most businesses—because of competition—earnings power over time will not be more than what is justified by the reproduction cost of the assets.

Only franchise businesses like Coca-Cola—with a sustainable competitive advantage that allows it to earn more than its cost of capital—are going to have normalized earnings that are higher than is justified by the reproduction cost of the assets.

Because most investors view cigar butts as unattractive investments—despite the overwhelming statistical evidence—there are always opportunities for deep value investors.  For instance, when cyclical businesses are at the bottom of the cycle, and current earnings are far below earnings power, investors’ fixation on current earnings can create very cheap stocks.

A key issue is whether the current low income reflects a permanently damaged business or a temporary—or cyclical—decline in profitability.



Although you can make money by buying cheap businesses that are permanently declining, you can usually make more money by buying stocks at cyclical lows.

(Illustration by Prairat Fhunta)


Assuming a low enough entry price, money can be made in both cheap businesses condemned to permanent fundamental decline and businesses that may benefit from mean reversion as their industry moves through the cycle.  We much prefer companies that find themselves at a cyclical low, as they may restore much, if not all, of their earning power, providing multi-bagger upside potential.  Meanwhile, businesses likely to keep declining for a long time have to be extremely cheap and keep returning cash to shareholders to generate a positive investment outcome.

The question of whether a company has entered permanent decline is anything but easy to answer, as virtually all companies appear to be in permanent decline when they hit a rock-bottom market quotation.  Even if a business has been cyclical in the past, analysts generally adopt a ‘this time is different’ attitude.  As a pessimistic stock price inevitably influences the appraisal objectivity of most investors, it becomes exceedingly difficult to form a view strongly opposed to the prevailing consensus.

If you can stay calm and rational while being isolated and looking foolish, then you can buy deeply out of favor cyclical stocks, which often have multi-bagger upside potential.

Example: Ensco plc (ESV)

A good example of a cyclical stock with multi-bagger potential is Ensco plc, an offshore oil driller.  The Boole Microcap Fund had an investment in Atwood Oceanics, which was acquired by Ensco in 2017.  The Boole Fund continues to hold Ensco because it’s quite cheap.

Oil companies prefer offshore drillers that are well-capitalized and reliable.  Ensco has one of the best safety records in the industry.  Also, it was rated #1 in customer satisfaction for the eighth consecutive year in the leading independent industry survey.  Moreover, Ensco is one of the best capitalized drillers in the industry, with $2.9 billion in liquidity and only $236 million in debt due before 2024.

Here are intrinsic value scenarios:

  • Low case: If oil prices languish below $60 (WTI) for the next 3 to 5 years, then Ensco will be a survivor, due to its large fleet, globally diverse customer base, industry leading performance, and well-capitalized position.  In this scenario, Ensco is likely worth at least $12, over 35% higher than today’s $8.70.
  • Mid case: If oil prices are in a range of $65 to $85 over the next 3 to 5 years—which is likely based on long-term supply and demand—then Ensco is probably worth at least $25 a share, over 185% higher than today’s $8.70.
  • High case: If oil prices average $85 or more over the next 3 to 5 years, then Ensco could easily be worth $37 a share, about 325% higher than today’s $8.70.

Last week, on October 8, Ensco plc and Rowan Companies plc announced that they were merging.  The merger is still subject to shareholder and regulatory approval.

The merger of Ensco and Rowan will likely be accretive to the current shareholders of Ensco.  Ensco and Rowan believe they will achieve cost savings of $150 million per year, which adds at least 5-10% of intrinsic value to Ensco shares.

You might wonder if Ensco is giving up something in the merger, given its ability to offer the highest specification drilling rigs—especially for ultra-deepwater.  However, Rowan’s groundbreaking partnership (ARO Drilling) with Saudi Aramco will likely create billions of dollars in value for shareholders.  Moreover, Rowan is a leading provider of ultra-harsh and modern harsh environment jackups.

In brief, the combination looks to be accretive for the shareholders of both companies.  Therefore, the potential upside for current Ensco shareholders is probably greater if the merger is completed.  So for the low, mid, and high cases, the potential upside for current Ensco shareholders is at least 50%, 200%, and 350%, respectively, and probably more.



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Quantitative Microcap Value

(Image:  Zen Buddha Silence by Marilyn Barbone.)

October 7, 2018

Jack Bogle and Warren Buffett correctly maintain that most investors should invest in an S&P 500 index fund.  An index fund will allow you to outpace 90-95% of all active investors—net of costs—over the course of 4-5 decades.  This is purely a function of cost.  Active investors as a group will do the same as the S&P 500, but that is before costs.  After costs, active investors will do about 2.5% worse per year than the index.

An index fund is a wise choice.  But you can do much better if you invest in a quantitative microcap value strategy—focused on undervalued microcap stocks with improving fundamentals.  If you adopt such an approach, you can outperform the S&P 500 by roughly 7% per year.  For details, see: http://boolefund.com/cheap-solid-microcaps-far-outperform-sp-500/

But this can only work if you have the ability to ignore volatility and stay focused on the very long term.

“Investing is simple but not easy.” — Warren Buffett

(Photo by USA International Trade Administration)

Assume the S&P 500 index will return 8% per year over the coming decades.  The average active approach will produce roughly 5.5% per year.  A quantitative microcap approach—cheap micro caps with improving fundamentals—will generate about 15% per year.

What would happen if you invested $50,000 for the next 30 years in one of these approaches?

Investment Strategy Beginning Value Ending Value
Active $50,000 $249,198
S&P 500 Index $50,000 $503,133
Quantitative Microcap $50,000 $3,310,589

As you can see, investing $50,000 in an index fund will produce $503,133, which is more than ten times what you started with.  Furthermore, $503,133 is more than twice $249,198, which would be the result from the average active fund.

However, if you invested $50,000 in a quantitative microcap strategy, you would end up with $3,310,589.  This is more than 66 times what you started with, and it’s more than 6.5 times greater than the result from the index fund.

You could either invest in a quantitative microcap approach or you could invest in an index fund.  You’ll do fine either way.  You could also invest part of your portfolio in the microcap strategy and part in an index fund.

What’s the catch?

For most of us as investors, our biggest enemy is ourselves.  Let me explain.  Since 1945, there have been 27 corrections where stocks dropped 10% to 20%, and there have been 11 bear markets where stocks dropped more than 20%.  However, the stock market has always recovered and gone on to new highs.

Edgar Wachenheim, in the great book Common Stocks and Common Sense, gives the following example:

The financial crisis during the fall of 2008 and the winter of 2009 is an extreme (and outlier) example of volatility.  During the six months between the end of August 2008 and end of February 2009, the [S&P] 500 Index fell by 42 percent from 1,282.83 to 735.09.  Yet by early 2011 the S&P 500 had recovered to the 1,280 level, and by August 2014 it had appreciated to the 2000 level.  An investor who purchased the S&P 500 Index on August 31, 2008, and then sold the Index six years later, lived through the worst financial crisis and recession since the Great Depression, but still earned a 56 percent profit on his investment before including dividends—and 69 percent including the dividends… During the six-year period August 2008 through August 2014, the stock market provided an average annual return of 11.1 percent—above the range of normalcy in spite of the abnormal horrors and consequences of the financial crisis and resulting deep recession.

If you can stay the course through a 25% drop and even through a 40%+ drop, and remain focused on the very long term, then you should invest primarily in stocks, whether via an index fund, a quantitative microcap value fund, or some other investment vehicle.

The best way to stay focused on the very long term is simply to ignore the stock market entirely.  All you need to know or believe is:

  • The U. S. and global economies will continue to grow, mainly due to improvements in technology.
  • After every correction or bear market—no matter how severe—the stock market has always recovered and gone on to new highs.

If you’re unable to ignore the stock market, and if you might get scared and sell during a correction or bear market—don’t worry if you’re in this category since many investors are—then you should try to invest a manageable portion of your liquid assets in stocks.  Perhaps investing 50% or 25% of your liquid assets in stocks will allow you to stay the course through the inevitable corrections and bear markets.

The best-performing investors will be those who can invest for the very long term—several decades or more—and who don’t worry about (or even pay any attention to) the inevitable corrections and bear markets along the way.  In fact, Fidelity did a study of its many retail accounts.  It found that the best-performing accounts were owned by investors who literally forgot that they had an account!

  • Note: If you were to buy and hold twenty large-cap stocks chosen at random, your long-term performance would be very close to the S&P 500 Index.  (The Dow Jones Industrial Average is a basket of thirty large-cap stocks.)

Bottom Line

If you’re going to be investing for a few decades or more, and if you can basically ignore the stock market in the meantime, then you should invest fully in stocks.  Your best long-term investment is an index fund, a quantitative microcap value fund, or a combination of the two.

If you can largely ignore volatility, then you should consider investing primarily in a quantitative microcap value fund.  This is very likely to produce far better long-term performance than an S&P 500 index fund.

Many top investors—including Warren Buffett, perhaps the greatest investors of all time—earned the highest returns of their career when they could invest in microcap stocks.  Buffett has said that he’d still be investing in micro caps if he were managing small sums.

To learn more about Buffett getting his highest returns mainly from undervalued microcaps, here’s a link to my favorite blog post: http://boolefund.com/buffetts-best-microcap-cigar-butts/

The Boole Microcap Fund that I manage is a quantitative microcap value fund.  For details on the quantitative investment process, see: http://boolefund.com/why-invest-in-boole-microcap/

Although the S&P 500 index appears rather high—a bear market in the next year or two wouldn’t be a surprise—the positions in the Boole Fund are quite undervalued.  When looking at the next 3 to 5 years, I’ve never been more excited about the prospects of the Boole Fund relative to the S&P 500—regardless of whether the index is up, down, or flat.

(The S&P 500 may be flat for 5 years or even 10 years, but after that, as you move further into the future, eventually there’s more than a 99% chance that the index will be in positive territory.  The longer your time horizon, the less risky stocks are.)



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.

Cheap, Solid Microcaps Far Outperform the S&P 500

(Image: Zen Buddha Silence, by Marilyn Barbone)

September 30, 2018

The wisest long-term investment for most investors is an S&P 500 index fund.  It’s just simple arithmetic, as Warren Buffett and Jack Bogle frequently observe: http://boolefund.com/warren-buffett-jack-bogle/

But you can do significantly better — roughly 7% per year (on average) — by systematically investing in cheap, solid microcap stocks.  The mission of the Boole Microcap Fund is to help you do just that.

Most professional investors never consider microcaps because their assets under management are too large.  Microcaps aren’t as profitable for them.  That’s why there continues to be a compelling opportunity for savvy investors.  Because microcaps are largely ignored, many get quite cheap on occasion.

Warren Buffett earned the highest returns of his career when he could invest in microcap stocks.  Buffett says he’d do the same today if he were managing small sums: http://boolefund.com/buffetts-best-microcap-cigar-butts/

Look at this summary of the CRSP Decile-Based Size and Return Data from 1927 to 2015:

Decile Market Cap-Weighted Returns Equal Weighted Returns Number of Firms (year-end 2015) Mean Firm Size (in millions)
1 9.29% 9.20% 173 84,864
2 10.46% 10.42% 178 16,806
3 11.08% 10.87% 180 8,661
4 11.32% 11.10% 221 4,969
5 12.00% 11.92% 205 3,151
6 11.58% 11.40% 224 2,176
7 11.92% 11.87% 300 1,427
8 12.00% 12.27% 367 868
9 11.40% 12.39% 464 429
10 12.50% 17.48% 1,298 107
9+10 11.85% 16.14% 1,762 192

(CRSP is the Center for Research in Security Prices at the University of Chicago.  You can find the data for various deciles here:  http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html)

The smallest two deciles — 9+10 — comprise microcap stocks, which typically are stocks with market caps below $500 million.  What stands out is the equal weighted returns of the 9th and 10th size deciles from 1927 to 2015:

Microcap equal weighted returns = 16.14% per year

Large-cap equal weighted returns = ~11% per year

In practice, the annual returns from microcap stocks will be 1-2% lower because of the difficulty (due to illiquidity) of entering and exiting positions.  So we should say that an equal weighted microcap approach has returned 14% per year from 1927 to 2015, versus 11% per year for an equal weighted large-cap approach.

Still, if you can do 3% better per year than the S&P 500 index (on average) — even with only a part of your total portfolio — that really adds up after a couple of decades.



By systematically implementing a value screen — e.g., low EV/EBIT or low P/E — to a microcap strategy, you can add 2-3% per year.



You can further boost performance by screening for improving fundamentals.  One excellent way to do this is using the Piotroski F_Score, which works best for cheap micro caps.  See:  http://boolefund.com/joseph-piotroski-value-investing/



In sum, over time, a quantitative value strategy — applied to cheap microcap stocks with improving fundamentals — has high odds of returning at least 7% (+/- 3%) more per year than an S&P 500 index fund.

If you’d like to learn more about how the Boole Fund can help you do roughly 7% better per year than the S&P 500, please call or e-mail me any time.

E-mail: jb@boolefund.com  (Jason Bond)



An equal weighted group of micro caps generally far outperforms an equal weighted (or cap-weighted) group of larger stocks over time.  See the historical chart here:  http://boolefund.com/best-performers-microcap-stocks/

This outperformance increases significantly by focusing on cheap micro caps.  Performance can be further boosted by isolating cheap microcap companies that show improving fundamentals.  We rank microcap stocks based on these and similar criteria.

There are roughly 10-20 positions in the portfolio.  The size of each position is determined by its rank.  Typically the largest position is 15-20% (at cost), while the average position is 8-10% (at cost).  Positions are held for 3 to 5 years unless a stock approaches intrinsic value sooner or an error has been discovered.

The mission of the Boole Fund is to outperform the S&P 500 Index by at least 5% per year (net of fees) over 5-year periods.  We also aim to outpace the Russell Microcap Index by at least 2% per year (net).  The Boole Fund has low fees.


If you are interested in finding out more, please e-mail me or leave a comment.

My e-mail: jb@boolefund.com




Disclosures: Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value. This material is distributed for informational purposes only. Forecasts, estimates, and certain information contained herein should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this article may be reproduced in any form, or referred to in any other publication, without express written permission of Boole Capital, LLC.