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Every further new high in the price of Bitcoin brings ever more claims that it is destined to become the preeminent safe haven investment of the modern age — the new gold.

But there’s no getting around the fact that Bitcoin is essentially a speculative investment in a new technology, specifically the blockchain. Think of the blockchain, very basically, as layers of independent electronic security that encapsulate a cryptocurrency and keep it frozen in time and space — like layers of amber around a fly. This is what makes a cryptocurrency “crypto.”

That’s not to say that the price of Bitcoin cannot make further (and further…) new highs. After all, that is what speculative bubbles do (until they don’t).

Bitcoin and each new initial coin offering (ICO) should be thought of as software infrastructure innovation tools, not competing currencies. It’s the amber that determines their value, not the flies. Cryptocurrencies are a very significant value-added technological innovation that calls directly into question the government monopoly over money. This insurrection against government-manipulated fiat money will only grow more pronounced as cryptocurrencies catch on as transactional fiduciary media; at that point, who will need government money? The blockchain, though still in its infancy, is a really big deal.

While governments can’t control cryptocurrencies directly, why shouldn’t we expect cryptocurrencies to face the same fate as what started happening to numbered Swiss bank accounts (whose secrecy remain legally enforced by Swiss law)? All local governments had to do was make it illegal to hide, and thus force law-abiding citizens to become criminals if they fail to disclose such accounts. We should expect similar anti-money laundering hygiene and taxation among the cryptocurrencies. The more electronic security layers inherent in a cryptocurrency’s perceived value, the more vulnerable its price is to such an eventual decree.

Bitcoins should be regarded as assets, or really equities, not as currencies. They are each little business plans — each perceived to create future value. They are not stores-of-value, but rather volatile expectations on the future success of these business plans. But most ICOs probably don’t have viable business plans; they are truly castles in the sky, relying only on momentum effects among the growing herd of crypto-investors. (The Securities and Exchange Commission is correct in looking at them as equities.) Thus, we should expect their current value to be derived by the same razor-thin equity risk premiums and bubbly growth expectations that we see throughout markets today. And we should expect that value to suffer the same fate as occurs at the end of every speculative bubble.

If you wanted to create your own private country with your own currency, no matter how safe you were from outside invaders, you’d be wise to start with some pre-existing store-of-value, such as a foreign currency, gold, or land. Otherwise, why would anyone trade for your new currency? Arbitrarily assigning a store-of-value component to a cryptocurrency, no matter how secure it is, is trying to do the same thing (except much easier than starting a new country). And somehow it’s been working.

Moreover, as competing cryptocurrencies are created, whether for specific applications (such as automating contracts, for instance), these ICOs seem to have the effect of driving up all cryptocurrencies. Clearly, there is the potential for additional cryptocurrencies to bolster the transactional value of each other—perhaps even adding to the fungibility of all cryptocurrencies. But as various cryptocurrencies start competing with each other, they will not be additive in value. The technology, like new innovations, can, in fact, create some value from thin air. But not so any underlying store-of-value component in the cryptocurrencies. As a new cryptocurrency is assigned units of a store-of-value, those units must, by necessity, leave other stores-of-value, whether gold or another cryptocurrency. New depositories of value must siphon off the existing depositories of value. On a global scale, it is very much a zero sum game.

Or, as we might say, we can improve the layers of amber, but we can’t create more flies.

This competition, both in the technology and the underlying store-of-value, must, by definition, constrain each specific cryptocurrency’s price appreciation. Put simply, cryptocurrencies have an enormous scarcity problem. The constraints on any one cryptocurrency’s supply are an enormous improvement over the lack of any constraint whatsoever on governments when it comes to printing currencies. However, unlike physical assets such as gold and silver that have unique physical attributes endowing them with monetary importance for millennia, the problem is that there is no barrier to entry for cryptocurrencies; as each new competing cryptocurrency finds success, it dilutes or inflates the universe of the others.

The store-of-value component of cryptocurrencies — which is, at a bare-minimum, a fundamental requirement for safe haven status — is a minuscule part of its value and appreciation. After all, stores of value are just that: stable and reliable holding places of value. They do not create new value, but are finite in supply and are merely intended to hold value that has already been created through savings and productive investment. To miss this point is to perpetuate the very same fallacy that global central banks blindly follow today. You simply cannot create money, or capital, from thin air (whether it be credit or a new cool cryptocurrency). Rather, it represents resources that have been created and saved for future consumption. There is simply no way around this fundamental truth.

Viewing cryptocurrencies as having safe haven status opens investors to layering more risk on their portfolios. Holding Bitcoins and other cryptocurrencies likely constitutes a bigger bet on the same central bank-driven bubble that some hope to protect themselves against. The great irony is that both the libertarian supporters of cryptocurrencies and the interventionist supporters of central bank-manipulated fiat money both fall for this very same fallacy.

Cryptocurrencies are a very important development, and an enormous step in the direction toward the decentralization of monetary power. This has enormously positive potential, and I am a big cheerleader for their success. But caveat emptor—thinking that we are magically creating new stores-of-value and thus a new safe haven is a profound mistake.

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I would love this bike, but at $70,000.00 just a touch too much. This one is for sale in Auckland. It is new for 2018.

The final edition Panigale 1299R.


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Larry Walters always wanted to fly. When he was old enough, he joined the Air Force, but he could not see well enough to become a pilot. After he was discharged from the military, he would often sit in his backyard watching jets fly overhead, dreaming about flying and scheming about how to get into the sky. On July 2, 1982, the San Pedro, California trucker finally set out to accomplish his dream. Because the story has been told in a variety of ways over a variety of media outlets, it is impossible to know precisely what happened but, as a police officer commented later, “It wasn’t a highly scientific expedition.”

Larry conceived his “act of American ingenuity” while sitting outside in his “extremely comfortable” Sears lawn chair. He purchased weather balloons from an Army-Navy surplus store, tied them to his tethered Sears chair and filled the four-foot diameter balloons with helium. Then, after packing sandwiches, Miller Lite, a CB radio, a camera, a pellet gun, and 30 one-pound jugs of water for ballast – but without a seatbelt – he climbed into his makeshift craft, dubbed “Inspiration I.” His plan, such as it was, called for him to float lazily above the rooftops at about 30 feet for a while, pounding beers, and then to use the pellet gun to explode the balloons one-by-one so he could float to the ground.

But when the last cord that tethered the craft to his Jeep snapped, Walters and his lawn chair did not rise lazily into the sky. Larry shot up to an altitude of about three miles (higher than a Cessna can go), yanked by the lift of 45 helium balloons holding 33 cubic feet of helium each. He did not dare shoot any of the balloons because he feared that he might unbalance the load and fall. So he slowly drifted along, cold and frightened, in his lawn chair, with his beer and sandwiches, for more than 14 hours. He eventually crossed the primary approach corridor of LAX. A flustered TWA pilot spotted Larry and radioed the tower that he was passing a guy in a lawn chair with a gun at 16,000 feet.

Eventually Larry conjured up the nerve to shoot several balloons before accidentally dropping his pellet gun overboard. The shooting did the trick and Larry descended toward Long Beach, until the dangling tethers got caught in a power line, causing an electrical blackout in the neighborhood below. Fortunately, Walters was able to climb to the ground safely from there.

The Long Beach Police Department and federal authorities were waiting. Regional safety inspector Neal Savoy said, “We know he broke some part of the Federal Aviation Act, and as soon as we decide which part it is, some type of charge will be filed. If he had a pilot’s license, we’d suspend that. But he doesn’t.” As he was led away in handcuffs, a reporter asked Larry why he had undertaken his mission. The answer was simple and poignant. “A man can’t just sit around,” he said.

The Inversion Principle

In one of the more glaringly obvious observations of all-time, it is safe to say that Larry’s decision-making process was more than a bit flawed. The Bonehead Club of Dallas awarded him its top prize – Bonehead of the Year – but he only earned an honorable mention from the Darwin Awards people, presumably because, even though things did not turn out exactly as he planned (another glaringly obvious observation), he was incredibly lucky and his flight did not end in disaster. Among his many errors, Larry did not follow the inversion principle popularized in the investment world by Charlie Munger. Charlie borrowed this highly useful idea from the great 19th Century German mathematician Carl Jacobi, who created this helpful approach for improving your decision-making process.

Invert, always invert (“man muss immer umkehren”).

Jacobi believed that the solution for many difficult problems could be found if the problems were expressed in the inverse – by working or thinking backwards. As Munger has explained, “Invert. Always invert. Turn a situation or problem upside down. Look at it backward. What happens if all our plans go wrong? Where don’t we want to go, and how do you get there? Instead of looking for success, make a list of how to fail instead – through sloth, envy, resentment, self-pity, entitlement, all the mental habits of self-defeat. Avoid these qualities and you will succeed. Tell me where I’m going to die, that is, so I don’t go there.” Charlie’s partner, Warren Buffett, makes a similar point: “Charlie and I have not learned how to solve difficult business problems. What we have learned is to avoid them.”

As in most matters, we would do well to emulate Charlie. But what does that mean?

It begins with working backwards, to the extent you can, quite literally. If you have done algebra, you know that reversing an equation is the best way to check your work. Similarly, the best way to proofread is back-to-front, one painstaking sentence at a time. But it also means much more than that.

Thinking in Reverse

Charlie’s inversion principle also means thinking in reverse. As Munger explains it: “In other words, if you want to help India, the question you should ask is not, ‘How can I help India?’ It’s, ‘What is doing the worst damage in India?’”

During World War II, the Allied forces sent regular bombing missions into Germany. The lumbering aircraft sent on these raids – most often B-17s – were strategically crucial to the war effort and were often lost to enemy anti-aircraft fire. That was a huge problem, obviously.

Boeing XB-17

One possible solution was to provide more reinforcement for the Flying Fortresses, but armor is heavy and restricts aircraft performance even more. So extra plating could only go where the planes were most vulnerable. The problem of where to add armor was a difficult one because the data set was so limited. There was no access to the planes that had been shot down. In 1943, the English Air Ministry examined the locations of the bullet holes on the returned aircraft and proposed adding armor to those areas that showed the most damage, all at the planes’ extremities.

The great mathematician Abraham Wald, who had fled Austria for the United States in 1938 to escape the Nazis, was put to work on the problem of estimating the survival probabilities of planes sustaining hits in various locations so that the added armor would be located most expeditiously. Wald came to a surprising and very different conclusion from that proposed by the Air Ministry. Since much of Wald’s analysis at the time was new – he did not have sufficient computing power to model results and did not have access to more recent statistical approaches – his work was ad hoc and his success was due to “the sheer power of his intuition” alone.

Wald began by drawing an outline of a plane and marking it where returning planes had been hit. There were lots of shots everywhere except in a few particular (and crucial) areas, with more shots to the planes’ extremities than anywhere else. By inverting the problem – considering where the planes that didn’t return had been hit and what it would take to disable an aircraft rather than examining the data he had from the returning bombers – Wald came to his unique insight, later confirmed by remarkable (for the time, and long classified) mathematical analysis (more here). Much like Sherlock Holmes and the dog that didn’t bark, Wald’s remarkable intuitive leap came about due to what he didn’t see (that Wald’s insight seems obvious now is a wonderful illustration of hindsight bias).

Wald realized that the holes from flak and bullets most often seen on the bombers that returned represented the areas where planes were best able to absorb damage and survive. Since the data showed that there were similar areas on each returning B-17 showing little or no damage from enemy fire, Wald concluded that those areas (around the main cockpit and the fuel tanks) were the truly vulnerable spots and that these were the areas that should be reinforced.

From a mathematical perspective, Wald considered what might have happened to account for the data he possessed. Therefore, what he did was to set the probability that a plane that took a hit to the engine managed to stay in the air to zero and thought about what that would mean. In other words, conceptually, he assumed that any hit to the engine would bring the plane down. Because planes returned from their missions with bullet holes everywhere but the engine, the other alternative was that planes were never hit in the engine. Thus, either the German gunfire hit every part of the plane but one, or the engine was a point of extreme vulnerability. Wald considered both possibilities, but the latter made much more sense.

The more useful data was in the planes that were shot down and unavailable, not the ones that survived, and had to be “gathered” by Wald via induction. This insight lies behind the related concepts we now call survivorship bias – our tendency to include only successes in statistical analysis, skewing or even invalidating the results – and selection bias – the distortions we see when the sample selection does not accurately reflect the target population. Thus, the fish you observe in a pond will almost certainly correspond to the size of the holes in your net. Inverting the problem allowed Wald to come to the correct conclusion, saving many planes (and lives).

This idea applies to baseball too. As I have argued before, the crucial insight of Moneyball was a “Mungeresque” inversion. In baseball, a team wins by scoring more runs than its opponent. The epiphany was to invert the idea that runs and wins were achieved by hits to the radical notion that the key to winning is avoiding outs. That led the story’s protagonist, general manager of the Oakland A’s Billy Beane, to “buy” on-base percentage cheaply because the “traditional baseball men” overvalued hits but undervalued on-base percentage even though it does not matter how a batter avoids making an out and reaches base.

Therefore, the key application of the Moneyball insight was for Beane to find value via underappreciated player assets (some assets are cheap for good reason) by way of an objective, disciplined, data-driven process that values OBP more than conventional baseball wisdom. In other words, as Michael Lewis explained, “it is about using statistical analysis to shift the odds [of winning] a bit in one’s favor” via market inefficiencies. As A’s Assistant GM Paul DePodesta said, “You have to understand that for someone to become an Oakland A, he has to have something wrong with him. Because if he doesn’t have something wrong with him, he gets valued properly by the marketplace, and we can’t afford him anymore.” Accordingly, Beane sought out players that he could obtain cheaply because their actual (statistically verifiable) value was greater than their generally perceived value.

The great Howard Marks has also applied this idea to the investing world:

“If what’s obvious and what everyone knows is usually wrong, then what’s right? The answer comes from inverting the concept of obvious appeal. The truth is, the best buys are usually found in the things most people don’t understand or believe in. These might be securities, investment approaches or investing concepts, but the fact that something isn’t widely accepted usually serves as a green light to those who’re perceptive (and contrary) enough to see it.”

The key investment application of the inversion principle, therefore, is that in most cases we would be better served by looking closely at the examples of people and portfolios that failed and why they failed instead of the success stories, even though such examples are unlikely to give rise to book contracts with six-figure advances. Similarly, we would be better served by examining our personal investment failures than our successes. Instead of focusing on “why we made it,” we would be better served by careful failure analysis and fault diagnosis. That is where the best data is and where the best insight may be inferred.

The smartest people may always question their assumptions to make sure that they are justified. The data set that was available to Wald was not a good sample. By inverting his thinking, Wald could more readily hypothesize and conclude that the sample was lacking.

Don’t Be Stupid

The inversion principle also means taking a step back (so to speak) to consider your goals in reverse. Our first goal, therefore, should not be to achieve success, even though that is highly intuitive. Note, for example, this recent list of 2017’s smartest companies, which focuses on “breakthrough technologies” and “successful” innovations. Instead, our first goal should be to avoid failure – to limit mistakes. Instead of trying so hard to be smart, we should invert that and spend more energy on not being stupid, in large measure because not being stupid is far more achievable and manageable than being brilliant. In general, we would be better off pulling the bad stuff out of our ideas and processes than trying to put more good stuff in.

As Munger has stated, “I think part of the popularity of Berkshire Hathaway is that we look like people who have found a trick. It’s not brilliance. It’s just avoiding stupidity.” Here is a variation: “we know the edge of our competency better than most. That’s a very worthwhile thing.” Buffett has a variation on this theme too: “Rule No. 1: Never lose money. Rule No. 2: Never forget rule No. 1.” Another is to be fearful when others are greedy and greedy when others are fearful. George Costanza has his own unique iteration (“If every instinct you have is wrong, then the opposite would have to be right”).

If we avoid mistakes we will generally win. By examining failure more closely, we will have a better chance of doing precisely that. Basically, negative logic works better than positive logic. What we know not to be true is much more robust that what we know to be true. Note how Michelangelo thought about his master creation, the David. He always believed that David was within the marble he started with. He merely (which is not to say that it was anything like easy) had to chip away that which was not David. “In every block of marble I see a statue as plain as though it stood before me, shaped and perfect in attitude and action. I have only to hew away the rough walls that imprison the lovely apparition to reveal it to the other eyes as mine see it.” By chipping away at what “did not work,” Michelangelo uncovered a masterpiece. There are not a lot of masterpieces in life, but by avoiding failure, we give ourselves the best chance of overall success.

As Charley Ellis famously established, investing is a loser’s game much of the time (as I have also noted before) – with outcomes dominated by luck rather than skill and high transaction costs. Charley employed the work of Simon Ramo, a scientist and statistician, from Extraordinary Tennis for the Ordinary Player, who showed that professional tennis players and weekend tennis players play a fundamentally different game. The expert player, playing another expert player, needs to win points affirmatively through good shot-making to succeed. The weekend player wins by not losing – keeping the ball in play until his or her opponent makes an error, because weaker players make many more errors.

“In expert tennis, about 80 per cent of the points are won; in amateur tennis, about 80 per cent of the points are lost. In other words, professional tennis is a Winner’s Game – the final outcome is determined by the activities of the winner – and amateur tennis is a Loser’s Game – the final outcome is determined by the activities of the loser. The two games are, in their fundamental characteristic, not at all the same. They are opposites.”

As Charlie wrote in a letter to Wesco Shareholders while he was chair of the company: “Wesco continues to try more to profit from always remembering the obvious than from grasping the esoteric. … It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent. There must be some wisdom in the folk saying, `It’s the strong swimmers who drown.’”

Moreover, it turns out that we can quantify this idea more precisely.

As Phil Birnbaum brilliantly suggested in Slate, not being stupid matters demonstrably more than being smart when a combination of luck and skill determines success. Suppose you are the GM of a baseball team and you are preparing for the annual draft. Avoiding a mistake helps more than being smart.

Suppose you have the 15th pick in the draft. You look at a player the Major League consensus says is the 20th best player and think he is better than that – perhaps the 10th best player. By contrast, the MLB consensus on another player is that he is the 15th best player but you think he is only the 30th best. What are the rewards and consequences if you are right about each player when the draft comes?

If the underrated player is available when your pick comes, you can snap him up for an effective gain of five spots. You get the 10th best player with the 15th pick. That is great. Of course, since everybody else is scouting too, you may not be the only one who recognizes the underrated player’s true value. Anybody with a pick ahead of you can steal your thunder. If that happens, your being smart did not help a bit.

If the overrated player is available when your turn comes up (in theory, he should be because he is the consensus 15th pick and you are picking 15th), you will pass on him, because you know he is not that good. If you had not done the scouting and done it right, you would have taken him with your 15th pick and suffered an effective loss of 15 spots by getting the 30th best player with the 15th pick. In that case, then, avoiding a mistake helped.

Moreover, and crucially, it does not matter if other teams scouted him correctly. You have dodged a bullet no matter what. Recognizing the undervalued player (being smart) only helps when you are alone in your recognition. Recognizing the overrated player (avoiding a mistake) always helps. Birnbaum’s moral: “You gain more by not being stupid than you do by being smart. Smart gets neutralized by other smart people. Stupid does not.” Thus, the importance of the error quotient becomes obvious (obviously, the lower the better).

The same principle can also be demonstrated mathematically, as Birnbaum also noted. Gather ten people and show them a jar that contains equal numbers of $1, $5, $20, and $100 bills. Pull one out, at random, so nobody can see, and auction it off. If the bidders are generally smart, the bidding should top out at just below $31.50 (how much less will depend on the extent of the group’s loss aversion), the value of the average bill {(1+5+20+100) ÷ 4}. If you repeat the process but this time let two prospective bidders see the bill you picked, what happens? If you picked a $100 bill, the insiders should be willing to pay up to $99.99 for the bill. Neither of them will benefit much from the insider knowledge. However, if it is a $1 bill, neither of the insiders will bid. Without that knowledge, each of the insiders would have had a one-in-10 chance of paying $31.50 for the bill and suffering a loss of $30.50. On an expected value basis, each gained $3.05 from being an insider. Avoiding errors matters more than being smart.

That investing successfully is really hard suggests to most of us that being really smart should be a big plus in investing. Yet while it can help, the existence of other smart people together with copycats and hangers-on greatly dilutes the value of being market-smart. On the other hand, the impact of bad decision-making stands alone. It is not lessened by the related stupidity of others. In fact, the more people act stupidly together, the greater the aggregate risk and the greater the potential for loss. This risk grows exponentially. Think of everyone piling on during the tech or real estate bubbles. When nearly all of us make the same kinds of poor decisions together – when the error quotient is especially high – the danger becomes enormous.


Science is perhaps the quintessential inversion. It is the most powerful tool there is for determining what is real and what is true, and yet it advances only by ascertaining what is false. In other words, it works due to disconfirmation rather than confirmation. As Munger observed about Charles Darwin: “Darwin’s result was due in large measure to his working method, which violated all my rules for misery and particularly emphasized a backward twist in that he always gave priority attention to evidence tending to disconfirm whatever cherished and hard-won theory he already had. In contrast, most people early achieve and later intensify a tendency to process new and disconfirming information so that any original conclusion remains intact. They become people of whom Philip Wylie observed: ‘You couldn’t squeeze a dime between what they already know and what they will never learn.’”

The Oxford English Dictionary defines the scientific method as “a method or procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement and experiment, and the formulation, testing, and modification of hypotheses.” Science is about making observations and then asking pertinent questions about those observations. What it means is that we observe and investigate the world and build our knowledge base on account of what we learn and discover, but we check our work at every point and keep checking our work. It is inherently experimental. In order to be scientific, then, our inquiries and conclusions must be based upon empirical, measurable evidence. We will never just “know.”

The scientific method, broadly construed, can and should be applied not only to traditional scientific endeavors, but also, to the fullest extent possible, to any sort of inquiry into or study about the nature of reality, including investing. As I have noted before, the great physicist and Nobel laureate Richard Feynman even applied such experimentation to hitting on women. To his surprise, he learned that he (at least) was more successful by being aloof than by being polite or by buying a woman he found attractive a drink.

David Wootton’s brilliant book, The Invention of Science, makes a compelling case that modernity began with the scientific revolution in Europe, book-ended by Danish astronomer Tycho Brahe’s identification of a new star in the heavens in 1572, which proved that heavens were not fixed, and the publication of Isaac Newton’s Opticks in 1704, which drew conclusions based upon experimentation. In Wootton’s view, this was “the most important transformation in human history” since the Neolithic era and in no small measure predicated upon a scientific mindset, which includes the unprejudiced observation of nature, careful data collection, and rigorous experimentation. In his view, the “scientific way of thinking has become so much part of our culture that it has now become difficult to think our way back into a world where people did not speak of facts, hypotheses and theories, where knowledge was not grounded in evidence, where nature did not have laws.” I think Wootton’s claim is surely true, even if honored mainly in the breach.

The scientific approach was truly a new way of thinking (despite historical antecedents). Wootton shows that when Christopher Columbus came to the New World in 1492, he did not have a word to describe what he had done (or at least appeared to have done, with apologies to the Vikings). It was the Portuguese, the first global imperial power, who introduced the term “discovery” in the early 16th Century. There were other new words and concepts that were also important when trying to understand the scientific revolution, such as “fact” (only widely used after 1663), “evidence” (incorporated into science from the legal system) and “experiment.”

As Wootton explains, knowledge, as it was espoused in medieval universities and monasteries, was dominated by the ancients, the likes of Ptolemy, Galen, and Aristotle. Accordingly, it was widely believed that all of the most important knowledge was already known. Thus, learning was predominantly a backward-facing pursuit, about returning to ancient first principles, not pushing into the unknown. Indeed, Wootton details the emergence of fact and evidence as previously unknown terms of art. The modern scientific pursuit is the “formation of a critical community capable of assessing discoveries and replicating results.”

In its broadest context, science is the careful, systematic and logical search for knowledge, obtained by examination of the best available evidence and always subject to correction and improvement upon the discovery of better or additional evidence. That is the essence of what has come to be known as the scientific method, which is the process by which we, collectively and over time, endeavor to construct an accurate (that is, reliable, consistent and non-arbitrary) representation of the world. Otherwise (per James Randi), we are doing magic, and magic simply does not work.

Aristotle, brilliant and important as he was, posited, for example, that heavy objects fall faster than lighter objects and that males and females have different numbers of teeth, based upon some careful – though flawed – reasoning. But it never seemed to have occurred to him that he ought to check. Checking and then re-checking your ideas or work offers evidence that may tend to confirm or disprove them. By collecting “a long-term data set,” per field biologist George Schaller, “you find out what actually happens.” Testing can also be reproduced by any skeptic, which means that you need not simply trust the proponent of any idea. You do not need to take anyone’s word for things — you can check it out for yourself. That is the essence of the scientific endeavor.

Science is inherently limiting, however. We want deductive proof in the manner of Aristotle, but have to settle for induction. That is because science can never fully prove anything. It analyzes the available data and, when the force of the data is strong enough, it makes tentative conclusions. Moreover, these conclusions are always subject to modification or even outright rejection based upon further evidence gathering. The great value of facts and data is not so much that they point toward the correct conclusion (even though they do), but that they allow us the ability to show that some things are conclusively wrong.

Science progresses not via verification (which can only be inferred) but by falsification (which, if established and itself verified, provides relative certainty only as to what is not true). That makes it unwieldy. Thank you, Karl Popper. In investing, as in science generally, we need to build our processes from the ground up, with hypotheses offered only after a careful analysis of all relevant facts and tentatively held only to the extent the facts and data allow.

In investing, much like science generally and as in life, if we avoid mistakes we will generally win. We all want to be Michael Burry, an investor who made a fortune because he recognized the mortgage bubble in time to act accordingly. However, becoming Michael Burry starts by not being Wing Chau, an investor of Lawn Chair Larry foolishness who got crushed when the mortgage market collapsed. In fact, we all suffered when the real estate bubble burst. When the error quotient is especially high, our risks grow exponentially. Success starts with avoiding errors and looking at problems and situations differently.

Invert. Always invert.


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Volatility is on the rise, thanks in no small part to N. Korea and Trumpster exchanging threats of plunging into nuclear war.

Who knows what will happen.

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Long volatility. That is the trade that I like.

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You who caught the turtles better eat them goes the ancient adage: Ipsi testudines edite, qui cepistis [i]

The origin of the expression is as follows. It was said that a group of fishermen caught a large number of turtles. After cooking them, they found out at the communal meal that these sea animals were much less edible that they thought: not many members of the group were willing to eat them. But Mercury happened to be passing by –Mercury was the most multitasking, sort of put-together god, as he was the boss of commerce, abundance, messengers, the underworld, as well as the patron of thieves and brigands and, not surprisingly, luck. The group invited him to join them and offered him the turtles to eat. Detecting that he was only invited to relieve them of the unwanted food, he forced them all to eat the turtles, thus establishing the principle that you need to eat what you feed others.

A Customer is Born Every Day

I have learned a lesson from my own naive experiences,

Beware of the person who gives advice, telling you that a certain action on your part is “good for you” while it is also good for him, while the harm to you doesn’t directly affect him.

Of course such advice is usually unsolicited. The asymmetry is when the said advice applies to you but not to him –he may be selling you something, trying to get you to marry his daughter or hire his son-in-law.

Years ago I received a letter from a lecture agent. His letter was clear; it had about ten questions of the type “do you have the time to field requests?”, “can you handle the organization of the trip”, the gist of it being that a lecture agent would make my life better and allow me the pursuit of knowledge or whatever else I was about (a deeper understanding of gardening, stamp collections, or Lebanese wine) while the burden of the gritty falls on someone else. And it wasn’t any lecture agent: only he could do all these things; he reads books and can get in the mind of intellectuals (at the time I didn’t feel insulted by being called an intellectual). As is typical with people who volunteer unsolicited advice, I smelled a rat: at no phase in the discussion did he refrain from directly apprising me or hinting that it was “good for me”.

As a sucker, while I didn’t buy into the argument, I ended up doing business with him, letting him handle a booking in the foreign country where he was based. Things went fine until, six years later I received a letter from the tax authorities of that country. I immediately contacted him to wonder if similar U.S. citizens he had hired incurred such tax conflict, or if he had heard of similar situations. His reply was immediate and curt: “I am not your tax attorney” –volunteering no information as to whether other U.S. customers who hired him because it was “good for them” encountered such a problem.

Indeed, in the dozen or so cases I can pull from memory, it always turns out that what is presented as good for you is not really good for you but certainly good for the other party. As a trader, you learn to identify and deal with upright people, those who inform you that they have something to sell, by explaining that the transaction arises for their own benefit, with such question as “do you have an axe?” (meaning an inquiry whether you have a certain interest). Avoid at all costs those who call you to tout a certain product disguised with advice –trying to dump inventory on you. In fact the story of the turtle is the archetype of the history of transactions between mortals.

I worked once for a U.S. investment bank, one of the prestigious variety, called “white shoe” because the partners were members of hard-to-join golf clubs where they played the game wearing white footwear. As with all such firms, an image of ethics and professionalism was cultivated, emphasized, and protected. But the job of the salespeople (actually, salesmen) on days when they wore black shoes was to “unload” inventory with which traders were “stuffed”, that is, securities they had in plethora in their books and needed to get rid of them to lower their risk profile. Selling to other traders was out of the question as professional traders, typically non golfers, would smell excess inventory and cause the price to drop. Some traders paid the sales force with (percentage) “points”, a variable compensation that increased with our eagerness to part with securities. Salesmen took clients out to dinner, bought them expensive wine (often, ostensibly the highest on the menu), and got a huge return on the thousands of dollars of restaurant bills by unloading the unwanted stuff on them. One expert salesman candidly explained to me: “If I buy the client, working for the finance department of a municipality, who buys his suits at some department store in New Jersey, a bottle of $2,000 wine, I own him for the next few months. I can get at least $100,000 profits out of him. Nothing in the mahket gives you such return”. Given that the said customer’s employment was for managing some public employee pension fund, is the New Jersey currently and to-be retired person that was in fact paying more than $100,000 for a $2,000 bottle of wine.

Salesmen hawked how a given security will be perfect for the client’s portfolio, how they were certain it would rise in price and how the client would suffer great regret if he missed “such an opportunity”, that type of discourse. Salespeople were experts in the art of psychological manipulation, making the client trade, often against his own interest, all the while being happy about it and loving them and their company. One of the top salesman of the firm, a man of huge charisma who came to work in a chauffeured Rolls Royce, was once asked whether customers didn’t get upset when they got the short end of the stick. “Rip them off don’t tick them off” was his answer. He also added “remember that every day a new customer is born”.

As the Romans were fully aware, one lauds merrily the merchandise to get rid of it. (Plenius aequo I /audat vena/is qui vult extrudere merces[1])

The Price of Corn in Rhodes

So, “giving advice” as a sales pitch is fundamentally unethical –selling cannot be deemed advice. We can safely settle on that. You can give advice, you can sell (by advertising the quality of the product) and the two need to be kept separate.

But there is an associated problem in the course of the transactions: how much should the seller reveal to the buyer?

The question “is it ethical to sell something to someone knowing the price will eventually drop” is an ancient one –but its solution is no less straightforward. The debate goes back to a disagreement between two stoic philosophers, Diogenes of Babylon and his student Antipater of Tarsus, who took the higher moral grounds on asymmetric information and seems to match current ethics endorsed by this author. Not a piece from both authors is extant, but we know quite a bit from secondary sources, or, in the case of Cicero, tertiary. The question was presented as follows, retailed by Cicero in De Officiis. Assume a man brought a large shipment of corn from Alexandria to Rhodes, at a time when corn was expensive in Rhodes because of shortage and famine. Suppose that he also knew that many boats had set sail from Alexandria on their way to Rhodes with similar merchandise. Does he have to inform the Rhodians? How can one act honorably or dishonorably in these circumstances?[ii]

We traders had a straightforward answer. We called this “stuffing” –selling quantities to people without informing them that there are large inventories waiting to be sold. An upright trader will not do that to other professional traders; it was a no-no. The penalty was ostracism. But it was sort of permissible to do it to the anonymous market and the faceless nontraders, or those we called “the Swiss”, or some sucker far away. There were people with whom we have a relational rapport, others with whom we had a transactional one. The two were separated by an ethical wall, much like the case with domestic animals that could not be harmed, while rules on cruelty were lifted when it came to cockroaches.

Diogenes held that the seller ought to disclose as much as civil law would allow. As to Antipater, he believed that everything ought to be disclosed –beyond the law –so that there was nothing that the seller knew that the buyer didn’t know.

Clearly Antipater’s position is more robust –robust being invariant to time, place, situation, and color of the eyes of the participants. Take for now that

The ethical is always more robust than the legal. Over time, it is the legal that should converge to the ethical, never the reverse.


Laws come and go; the ethics stays.

For the notion of “law” is ambiguous and highly jurisdiction dependent: in the U.S., civil law thanks to consumer advocates and similar movements, integrates such disclosures while other countries have different laws. This is particularly visible with securities laws, as there are “front running” regulations and those concerning insider information that make such disclosure mandatory in the U.S. , though it wasn’t so for a long time in Europe.

Indeed much of the work of investment banks my days was to play on regulations, find loopholes in the laws. And, counterintuitively, the more regulations, the easier it was to make money.

Equality in Uncertainty

Which brings us to asymmetry, the core concept behind skin in the game. The question becomes: to what extent can people in a transaction have an informational differential between them? The ancient Mediterranean and, to some extent the modern world, seems to be converging to Antipater’s position. While we have “buyer beware” (caveat emptor) in the Anglo-Saxon West, the idea is rather new, and never general, often mitigated by lemon laws. (A “lemon” was originally a chronically defective car, say my convertible Mini, in love with the garage, now generalized to apply to about anything that moves).

So to the question voiced by Cicero in the debate between the two ancient stoics , “If a man knowingly offers for sale wine that is spoiling, ought he to tell his customers?” , the world is getting closer to Diogenes position of transparency, not necessarily via regulations as much as thanks to tort laws, one’s ability to sue for harm in the event the seller deceived him or her. Recall that tort laws put some skin in the game back into the seller –which is why they are reviled, hated by corporations. But tort laws have side effects –they should only be used in a nonnaive way, that is, in a way they cannot be gamed. As we will see in the discussion of the visit to the doctor, they will be gamed.

Sharia, in particular the law regulating Islamic transactions and finance, is of interest to us insofar as preserves some of the lost Mediterranean and Babylonian methods and practices –not to prop up the ego of Saudi princes. It is at the intersection of Greco-Roman law (as reflected from their contact with the School of Law of Berytus), Phoenician trading rules, Babylonian legislations, and Arab tribal commercial customs and, as such, it provides a repository of all ancient Mediterranean and Semitic lore. I hence view Sharia as a museum of the history of ideas on symmetry in transactions. Sharia establishes the interdict of gharar, drastic enough to be totally banned in any form of transaction. It is an extremely sophisticated term in decision theory that does not exist in English; it means both uncertainty and deception –my personal take is that it means something beyond informational asymmetry between agents. It means inequality of uncertainty. Simply, as the aim is for both parties in a transaction to have the same uncertainty facing random outcomes, an asymmetry becomes equivalent to theft. Or more robustly:

No person in a transaction should have certainty about the outcome while the other one has uncertainty.

Gharar, like every legalistic term, will have its flaw; it remains weaker than the approach by Antipater. If only one party in a transaction has certainty all the way through, it is a violation of Sharia. But if there is a weak form of asymmetry, say someone has inside information which gives an edge in the markets, there is no gharar as there remains enough uncertainty for both parties, given that the price is in the future and only God knows the future. Selling a defective product (where there is certainty as to the defect) on the other hand is illegal. So the knowledge by the seller of corn in Rhodes in my first example does not fall under Gharar, while the second case, that of defective liquid, would[iii].[iv]

As we see, the problem of asymmetry is so complicated that different schools give different ethical solutions, so let us look at the Talmudic approach.

Rav Safra and the Swiss

Jewish ethics on the matter is closer to Diogenes than Antipater; in fact even more extreme than Diogenes in its aims at transparency. Not only there should be transparency concerning the merchandise, but perhaps there has to be one concerning what the seller has in mind, what he thinks deep down. The medieval Rabbi Shlomo Yitzhaki (a.k.a. Salomon Isaacides), known as “Rashi”, relates the following story. Rav Safra, a third century Babylonian scholar who was also an active trader, was offering some goods for sale. A buyer came as he was praying in silence, tried to purchase the merchandise at an initial price, and given that the Rabbi did not reply, raised the price. But Rav Safra had no intention of selling at a higher price than the initial offer, and felt that he had to honor the initial intention. Now the question: is Rav Safra obligated to sell at the initial price, or should he take the improved one?[v] [vi]

Such total transparency is not absurd and not uncommon in what seems to be a cut-throat world of transactions, my former world of trading. I have frequently faced that problem as a trader and will side in favor of Rav Safra’s action in the debate. Let us follow the logic. Recall the rapacity of salespeople earlier in the chapter. Sometimes I would offer something for sale for, say $5, but communicated with the client through a salesperson, and the salesperson would come back with an “improvement”, of $5.10. Something never felt right about the extra ten cents. It was, simply, not a sustainable way of doing business. What if the customer subsequently discovered that my initial offer was $5? No compensation is worth the feeling of shame. The overcharge falls in the same category as the act of “stuffing” people with bad merchandise. Now, to apply this to Rav Safra’s story, what if he sold to one client at the marked-up price, and to another one the exact same item for the initial price, and the two buyers happened to know one another? What if they were agents for the same end customer?

It may not be ethically required, but the most effective, shame-free policy is maximal transparency, even transparency of intentions.

However, the story doesn’t tell us whether the purchaser was a “Swiss”, those outsiders towards whom our ethical rules don’t apply. I suspect that there would be a species for which our ethical rules would be relaxed or possibly lifted. Otherwise, as Eleanor Ostrom has recently shown, the system cannot function properly.[2]

Members and Non Members

For the exclusion of the “Swiss” from our ethical is not trivial. Things don’t “scale” and generalize which is why I have trouble with intellectuals talking about abstract notions. A country is not a large city, a city is not a large family, and, sorry, the world is not a large village. There are scale transformations we will discuss here, and in a special more technical chapter at the end, in Section X.

When Athenians treat all opinions equally and discuss “democracy”, they only apply it other citizens, not slaves or metics (the equivalent of green card or J1b visa holders). Effectively, Theodosius’ code deprived Roman citizens who marry “Barbarians” of their legal rights –hence ethical parity with others. They lost their club membership. Jewish ethics distinguishes between thick blood and thin blood: we are all brothers but some are more brothers than others[3].

Individuals have been traditionally part of clubs, with rules and member behavior similar to those in today’s country clubs, with inside and outside. As club members know, the very existence of a club is exclusion and size limitation. Spartan could hunt and kill helots, those noncitizens with a status of slaves for training, but were otherwise equal to other Spartans and expected to die for theirs and the sake of Sparta. The large cities in the pre-Christian ancient world, particularly in the Levant and Asia Minor, were full of fraternities and clubs, open and (often) secret societies –there were even such a thing as funeral clubs where members shared the costs of, and participated in the ceremonials, of the funerals.

Today’s Roma people (a.k.a. gypsies) have tons of strict rules of behavior towards gypsies and others towards the unclean non-gypsies called payos. And, as the anthropologist David Graeber has observed, even the investment bank Goldman Sachs, known for its aggressive cupidity, acts like a communist community from within, thanks to the partnership system of governance.

So we exercise our ethical rules, but there is a limit –from scaling –beyond which the rules cease to apply. It is unfortunate, but the general kills the particular. The question we will reexamine later, after deeper discussion of complexity theory: is it possible to be both ethical and universalist? In theory, but, sadly, not in practice. For whenever the “we” becomes too large a club, things degrade, and each one starts fighting for his own interest. The abstract is way too abstract for us. This is the main reason I advocate political systems that start with the municipality, and work their way up (ironically, as in Switzerland, those “Swiss”), rather than the reverse that has failed with larger states. Being somewhat tribal is not a bad thing –and we have to work in a fractal way in the organized harmonious relations between tribes, rather than merge all tribes in one large soup. Is that sense, an American style federalism is the ideal system.

This scale transformation from the particular to the general is behind my skepticism with unfettered globalization and large centralized multiethnic states. My collaborator, the physicist and complexity researcher Yaneer Bar-Yam showed that “better fences made better neighbors” –something both “policymakers” and local governments fail to get about the Near East. Scaling matters, I will keep repeating until I get hoarse. Putting Shiites, Christians and Sunnis in one pot and ask them to sing Kumbaya around the camp fire while holding hands in the name of unity and fraternity of mankind has failed (interventionistas aren’t yet aware that “should” is not a sufficiently empirically valid statement to “build nations”). Blaming people for being “sectarian” –instead of making the best of such a natural tendency –is one of the stupidities of interventionistas. Separate tribes administratively (as the Ottomans did), or just put some markers somewhere, and they suddenly become friendly to one another.

But we don’t have to go very far to get the importance of scaling. You know instinctively that people get along better as neighbors than roommates.

When you think about it, it is obvious, even trite, from the well known behavior of crowds in “the anonymity” of big cities compared to the groups in small villages. I spend some time in my ancestral village, where it feels like a family. People attend others funerals (funeral clubs were mostly in large cities), help out, care about the neighbor, even if they hate his dog. There is no way you can get the same cohesion in a larger city when the other person is a theoretical entity, and our behavior towards him or her governed by some general ethical rule, not someone in flesh and blood. We get it easily when seen that way, but fail to generalize that ethics is something fundamentally local.

All (Literally) in the Same Boat

Greek is a language of precision; it has a word describing the opposite of risk transfer: risk sharing. Synkyndineo means “taking risks together”, which was a requirement in maritime transactions.[4]

The Acts of the Apostles[5] describes a voyage of St Paul on a cargo ship from Sidon to Crete to Malta. As they hit a storm: “ When they had eaten what they wanted they lightened the ship by throwing the corn overboard into the sea.”

Now while they jettisoned particular goods, all owners were to be proportioned the costs of the lost merchandise, not just the specific owners. For it turned out that they were following a practice that dates to at least 800 B.C., codified in Lex Rhodia, Rhodian Law, after the mercantile Aegean island of Rhodes; the code is no longer extant but has been cited since antiquity. It stipulates that the risks and costs for contingencies are to incurred equally, with no concern of responsibility. Justinian’s code[6]summarizes it:

“It is provided by the Rhodian Law that where merchandise is thrown overboard for the purpose of lightening a ship, what has been lost for the benefit of all must be made up by the contribution of all.”

And the same mechanism for risk-sharing took place with caravans along desert routes. If merchandise was stolen or lost, all merchants had to split the costs, not just its owner.

Synkyndineo has been translated into Latin by maestro classicist Armand D’Angour as compericlitor henceif it ever makes it into English, should becompericlity, and its opposite, the Bob Rubin risk transfer will be incompericlity. But I guess risk sharing will do in the meanwhile.

How to Not Be a Doctor

Attempts at putting skin in the game in medicine, while important and needed, usually have a certain class of adverse effects, in shifting uncertainty from the doctor to the patient.

The legal system and the regulatory measures are likely to put the skin of the doctor in the wrong game.

How? The problem resides in the reliance on metrics. Every metric is gameable –the cholesterol lowering we mentioned in the Prologue is a metric gaming technique taken to its limit. More realistically, say a cancer doctor or hospital are judged by the five-year survival of patients and need to face a variety of modalities for a new patient: what choice of treatment would they elect to do? There is a tradeoff between laser surgery (a surgical procedure) and radiation therapy, which is toxic to both patient and cancer. Statistically, laser surgery may have worse five-year outcomes than radiation therapy, but the latter tends to create second tumors in the longer run and offers comparatively reduced twenty-year disease-specific survival. Given that the window used for the calculation of patient survival is five years, not twenty, the incentive is to shoot for the former.

So the doctor is likely to be in the process of shifting uncertainty away from him or her by electing the second best option.

A Doctor is pushed by the system to transfer risk from himself to you, and from the present into the future.

And in the case we saw earlier from future into more distant future.

You need to remember that, when you visit a medical office, you will be facing someone who, in spite of his authoritative demeanor, is in a fragile situation. He is not you, not a member of your family, so he has no direct emotional loss should your health experience a degradation. His objective is, naturally, to avoid a lawsuit, something that can prove disastrous to his career.

Some metrics can actually kill you. Now, say you happen to visit a cardiologist and turn out to be in the mild risk category, something that doesn’t really raise your risk of a cardiovascular event, but precedes the stage of a possibly worrisome condition. (There is a strong nonlinearity: a person classified as prediabetic or prehypertensive is 90% closer to a normal person than to one with the condition. ) But the doctor is pressured to treat you to protect himself. Should you drop dead immediately after the visit, a low probability event, the doctor can be sued for negligence, for not having prescribed the right medicine that is temporarily believed to be useful, say as in the case of statins, but that we now know has been backed up by suspicious or incomplete studies. Deep down, he may know that statin is harmful, as it will lead to long term effects. But the pharmaceutical companies have managed to convince everyone that these –unseen –consequences are harmless, when the right precautionary approach is to consider the unseen as potentially harmful. In fact for most people except those that are very ill, the risks outweigh the benefits. Except that the risks are hidden; they will play out in the long run whereas the legal risk is immediate. This is no different from the Bob Rubin risk transfer trade, of delaying risks and making them look invisible.

Now can one make medicine less asymmetric? Not directly; the solution, I have argued in Antifragile and more technically, elsewhere, is for the patient to avoid treatment when he or she is mildly ill, but use medicine for the “tail events”, that is, for rarely encountered severe conditions. The problem is that the “mildly” ill represents a much larger pool of people than the severely ill –and people who are expected to live longer and consume drugs for longer — hence pharmaceutical companies have an incentive to focus on these.

In sum, both the doctor and the patient have skin in the game, though not perfectly, but administrators don’t –and they seem to be the cause of the troubling malfunctioning of the system. Administrators everywhere on the planet and at all times in history have been the plague.


This chapter introduced us to the agency problem and risk sharing, seen from both a commercial and an ethical viewpoint. We also introduced the problem of scale. Next we will try to get deeper into the structure of things in life by switching our approach when we look at a collection of things –towns, countries, families, markets. Aggregates are strange animals.


Screen Shot 2015-11-18 at 4.55.47 PM

What’s neat about this isn’t what’s changed. It’s what’s stayed the same.

The line, “One million titles, consistently low prices” seems like marketing guff. But it helps explain why Amazon has dominated where others have failed.

The allure of the Internet in 1995 was betting on change. New paradigms born. Old strategies discarded. Something requiring radically different thinking.

Yet Amazon’s focus from day one was as old as it gets. Selection and price. Businesses have pursued the idea for millennia.

Jeff Bezos once explained why this was critical:

I very frequently get the question: “What’s going to change in the next 10 years?” That’s a very interesting question.

I almost never get the question: “What’s not going to change in the next 10 years?” And I submit to you that that second question is actually the more important of the two.

You can build a business strategy around the things that are stable in time. In our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery; they want vast selection. It’s impossible to imagine a future 10 years from now where a customer comes up and says, “Jeff I love Amazon, I just wish the prices were a little higher.” Or, “I love Amazon, I just wish you’d deliver a little slower.” Impossible.

So we know the energy we put into these things today will still be paying off dividends for our customers 10 years from now. When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it.

This is one of those important things that’s too basic for most smart people to pay attention to.


Things that change are amazing. They can fuel massive growth.

But change by itself is hard. Investors have to spot it before it’s obvious. Consumers have to change their behaviors to make it viable. Those two points repel each other like magnets. And things that change tend to keep changing. A company whose pitch is “We’re doing this entirely new thing” likely has to reinvent itself and its product line every year, maybe more. Each iteration is a front-line battle where you’re exhausted from the last war but overconfident from its victory. So the odds keep stacking against you. An investor hoping to ride successive changes in multiple industries over a 40-year career faces tenth-degree difficulty. Practically a claim of clairvoyance.

Change often creates bursts of opportunity. Huge opportunity, yes. But businesses and their investors need more than slippery bursts to succeed. They need endurance. And endurance resides in long-term bets. Things you can pour energy and capital into today with a reasonable chance of still bearing fruit ten years from now. Which tend to be things that are stable in time.

This might seem heretical to venture capital. Marc Andreessen was once asked how his investment style compared with Warren Buffett. He replied:

[Warren is] betting against change. We’re betting for change. When he makes a mistake, it’s because something changes that he didn’t expect. When we make a mistake, it’s because something doesn’t change that we thought would. We could not be more different in that way.

Seems directionally true. But I don’t think it’s that black and white. Both investors pursue the same things; they just weight them differently.

Every successful investment is some combination of change that drives competition and things staying the same that drives compounding. There are so few exceptions to this, regardless of size or industry.

Buffett has owned GEICO stock since 1951. During that time the company went from exclusively selling auto insurance to government employees in cafeterias, to selling several kinds of insurance to everyone on their iPhones. Analytics went from abacus to AI. These are not small changes. But one thing stayed the same, which is that an insurance company selling directly would have a cost and convenience advantage over those paying brokers. That’s been the driver of Buffett’s GEICO bet for 66 years. It’s timeless.

Andreessen Horowitz partner Frank Chen recently talked about two trends in insurance startups. One is better software. “Software will rewrite the entire way we buy and experience our insurance products,” he said. Second is capital structure. “We expect to see more crowdsourced insurance companies … it should be a cheaper way to pool capital.” Both innovations promise lower cost and added convenience. Which is as timeless as GEICO’s edge.

Investors weigh the importance of change and timelessness differently, but every great company has some element of both. The extremes are where things don’t work.

Take three companies in the 1990s: Sears, Beenz, and Amazon.

Sears bet the Internet changed nothing, to its detriment. Beenz bet the Internet changed everything – creating a points-based currency valid only at online merchants – to its detriment. Amazon bet the Internet changed distribution, but rooted its strategy in things that have never, and will never, change. It nailed the center of the Venn diagram of change on one side and timeless on the other. One drove competition, the other drove compounding. Every successful company does this.


In the last 100 years we’ve gone from horses to jets and mailing letters to Skype. But every sustainable business is accompanied by one of a handful of timeless strategies:

  • Lower prices.
  • Faster solutions to problems.
  • Greater control over your time.
  • More choices.
  • Added comfort.
  • Entertainment/curiosity.
  • Deeper human interactions.
  • Greater transparency.
  • Less collateral damage.
  • Higher social status.
  • Increased confidence/trust.

You can make big, long-term bets on these things, because there’s no chance people will stop caring about them in the future.