The million dollar lesson
If you know Paul Moroz, you know he loves to make money — and hates losing it. Paul was 17 when he tried to bet against the Bulgarian currency. He was 21 when he sold his first business. When he joined Mawer, it was everything that our team could do to persuade the frugal young investor to toss out his old sneakers and buy some new shoes. If there was ever someone who seemed destined to become an investor, it was our Deputy CIO.
It is because of this background that I am so fascinated by the story Paul is telling now.
He is calling me from Indonesia, where he is looking for new investment ideas, in order to talk about his most memorable investment mistake: Krispy Kreme.
“I lost money on that stock in almost every way imaginable,” he begins.
As Paul tells it, he was a bright-eyed student in university when he came across the “hot” stock. At the time, Krispy Kreme was trading around $33 per share and at what appeared to be a very steep valuation. Paul was skeptical of the growth projections implied by this valuation and considered it a classic example of financial euphoria. Since Paul believes that you only invest in things that make sense, he decided to short the stock. In fact, he was so confident that Krispy Kreme would go down, he also purchased put options on it — derivatives that pay off if the underlying security goes down.
But Krispy Kreme didn’t go down. It went up. And up. And then up some more.
At first, Paul lost money when the put options expired. He had paid a premium to purchase these derivatives and they expired worthless. Then, he lost money on his short position.
The bank called in the stock that Paul had loaned out as part of his short position — a classic short squeeze — and he had to buy the stock in the market to meet the obligation. Except now, Paul was buying Krispy Kreme at $40. He had shorted it at $33.
When the trade was over and done, Paul had lost over USD 10,000 — a significant sum for a university student two decades ago.
But the ride wasn’t over yet.
A little while after Paul had lost in this trade, Krispy Kreme’s stock crashed the way that Paul originally hypothesized. Investors re-evaluated their growth expectations and the stock went tumbling down. Now it traded at $7 per share. So Paul figured… the stock was now cheap — and he bought it.
Unfortunately for Paul, he found himself in a personal situation that forced him to liquidate several of his investment positions early, including Krispy Kreme. So — at $5 per share — he exited the position. Paul had managed to lose money on both the up and down.
When Paul finishes his story, he laughs in spite of himself. I ask him whether he regrets the experience. He admits that, while it was painful at the time, he is grateful for having gone through it when he was still very young, and for the investment insights he gleaned from it which have turned out to be invaluable.
“Kara,” he tells me, “that lesson has probably saved me more than a million dollars.”
Mistakes happen. They happen every day, all the time, in investing and in life. They are a normal function of learning and a natural part of being human. And yet, for all the discussion these days on embracing failure, there still seems to be a stigma around errors. This is particularly true in investing, where there is an astonishing need to always appear “right” despite the fact that investing is a very complicated domain involving a great deal of uncertainty and in which perspectives must constantly shift.
What does it mean to make a mistake in investing? It is an important question to ask — because it is pivotal to our success and growth as investors — and a difficult question to answer. Investing mistakes are often hard to detect but we need to recognize them when they occur. Mistakes, if learned from, can have a cumulative value over time — and save you millions (or, in the case of our collective clients, hundreds of millions). We need to approach them with a healthy perspective; something with which the investment industry often struggles.
Mistakes are a natural part of the human condition, to be neither feared nor ignored, but to serve us. Out of mistakes, there is often something greater.
It is useful to start this discussion by first defining what it might mean to “win” in investing. As we will see, it is not always as simple as “did the stock go up?”
Most long-term investors have the goal of optimizing wealth at the highest rate of return possible given a specified amount of risk. Skill — not luck — should be driving this outcome. Investors don’t simply want positive outcomes; they want positive outcomes as a result of their logic being valid most of the time.
Let’s imagine that you have just invested in the new stock, Hot Chicken, because you love the taste of their chicken bites and believe the company is destined for explosive growth.
On the day of their earnings announcement, however, you learn that same store sales growth has plummeted, expansion plans have been scaled back, and management is re-organizing as a result of turbulent in-fighting. Fortunately for you, the Chairman of the Federal Reserve announces this same day an aggressive quantitative easing program in order to combat an ailing economy. Stocks rise in reaction — including Hot Chicken.
Were you a genius because Hot Chicken went up? No. You were just lucky. Your investment thesis was still wrong.
For investors, how you achieve investment success matters. While there’s no financial harm in a fluke, these occurrences rarely teach you very much (and can often teach you the wrong lesson). More importantly, you can’t rely on continuously generating flukes over time. A long-term investor wants positives outcomes to be driven by skill, as skill increases the likelihood of repeatable positive outcomes.
Therefore, earned wins are the goal — the combination of a good outcome driven by a good decision. Investment success is realized when earned wins stack up over time. Conversely, an error is any situation in which you made a bad decision (i.e., “Earned Loss” or “Lucky”). If you end up with a positive outcome, like the Hot Chicken example, but your thesis was wrong, this should still be viewed as an error.
And then there’s the scenario where the decision was good but the outcome was bad.
While this isn’t an error, it remains undesirable. Investors need to be really careful with this quadrant: it is the easiest one in which to be deluded. Instead of “unlucky,” investors are often operating in the “earned loss” quadrant, and simply don’t realize (or don’t want to admit) they are wrong. Investors also need to be cautious about the bottom right quadrant — it’s human nature to think that we’re gifted when we’re really just lucky.
Categories of Error
There are many reasons why an investor might make an error. Errors can come from emotional bias, faulty logic, lack of data, weak frameworks, or any number of reasons. However, we see three main categories in which investors typically make mistakes: the investment thesis, the investment philosophy/approach, and execution.
When we think of an investing mistake, we typically think of a faulty investment thesis. This is the archetypal example of having a thesis about a stock that turns out to be wrong (it is also the area we dedicate the bulk of our discussion in this piece). An error in the thesis usually occurs when an investor either a) fails to see reality clearly, and/or b) fails to infer the right logic given the observations made. For example, an investor might draw the wrong conclusions about a company’s management team or its competitive position in the marketplace; or they might make poor forecasts based on these initial observations.
However, it is also possible for your thesis to be correct and your investment philosophy/ approach to be broken, i.e., your philosophy doesn’t put the odds of success in your favour over time. For example, let’s imagine you believe that companies with more expensive valuations outperform. You find a company that is trading at 100x earnings and, since it fits with your approach, you buy it. Over time, the stock falls because the rest of the market re-prices the company's earnings. In this scenario, the problem was not your thesis — which was technically correct (the stock was expensive) — the problem was your underlying philosophy.
Another example is the short-selling philosophy Paul used with Krispy Kreme. While his thesis was technically correct — the stock should probably fall over time because of financial euphoria — his investment philosophy failed to consider the importance of market timing or catalysts for short-selling.
In addition, errors are often made in execution. Sometimes poor outcomes are not a result of an investment thesis being faulty, or an approach being broken, but the system not working for you. Clearly, Paul would not have lost as much money if the bank had not called in the stock.
Avoiding Fatal Errors and Crafting Stone Legs
Muay Thai World Champion, Melchor Menor, lines himself up. In front of him is a maple baseball bat, the kind that Major League Baseball players typically use. His instructions are clear but daunting: break the bat with a kick, a task that should require upwards of 800 lbs of force. Menor steadies himself and then strikes… the bat splinters in two.
Menor had applied an astounding 1000 lbs of force to this kick. It is well above the two other athletes who had been brought in for the experiment — NFL punter, Mike Scifres and MLS star striker, Edson Buddle — and begs the question: how are Menor’s shins so strong?
The answer: a lot of little “mistakes.”
As the narrator in a video recording the experiment explains:
‘Muay Thai masters spend years building up their shin bones by kicking hard objects. Their kicks create micro fractures on their shins. Through a process called cortical remodeling, the fractures heal to form a harder substance.’
In other words, by breaking his shin a tiny bit at a time, many times over, Menor has turned it into a substance as strong as stone and given him a decisive competitive advantage.
Mistakes always have a cost dimension; sometimes there is no cost; sometimes the cost is significant but recoverable; and at other times, it is fatal. As investors, we take risks knowing that mistakes will happen over time. We strive to have “low cost” mistakes — small fractures that we can rebuild from to make ourselves stronger — while avoiding the kinds of big injuries that would take us out of the game permanently.
Two conditions are necessary to make this kind of process effective: consistent rebuilding (learning) and a lot of repeated events (which usually translates into “time”). It’s not useful to go through mistakes, however small, if you’re not learning from them. And the process needs to be repeated many times over to work. There is no skipping ahead on either dimension.
It is this process that has given our team a competitive edge over time. In the over forty years that we’ve been in business, we’ve seen a lot. Like Paul, we’ve had our million dollar lessons.
These mistakes have never been for naught: we’ve been able to make the most out of them because we have a culture of trust, allowing us to feel comfortable reflecting on and sharing our insights.
How Would You Evaluate the Weather Forecaster?
Error detection is anything but straightforward. Error recognition in investing is a very challenging process for two reasons: the stochastic nature of the universe and a challenged feedback mechanism.
For example, let’s imagine that the weatherman makes a forecast for Saturday. He predicts a 90% chance of sunshine and a 10% chance of rain. You plan a romantic picnic based on this forecast. But when Saturday rolls around, it rains and your picnic is ruined. Was the weatherman “wrong?”
Before throwing eggs at the weatherman’s car, it’s important to remember the role randomness plays in our lives. The weatherman predicted a 90% chance of blue skies and a 10% chance of rain. This means that in 9 out of 10 scenarios, it would be reasonable to expect a rain-free picnic. But in 1 out of 10 scenarios, you should expect rain. Unfortunately, it just so happened that this time it rained. This doesn’t mean that you made a bad decision — so long as it was reasonable to believe in the weatherman’s initial forecasts — it just means you had some bad luck. Similarly, it doesn’t mean that the weatherman was wrong and deserves your ire.
This brings us to an important observation. When evaluating a forecast such as this one — a single prediction for which the outcomes follow a probability distribution — it is impossible to say whether that specific forecast was right. You must evaluate the forecasts over time.
In other words, the weatherman should be evaluated over time by how well his predictions are calibrated, i.e., how well they line up against reality over multiple experiments.
Theoretically, it never makes sense to fire the weatherman over an individual forecast. But if, over time, you find his forecasts are poorly calibrated — e.g. it tends to rain 90% of the time when he forecasts 10% of rain — it might be time for a replacement. This is arguably the way that investors should measure themselves, too.
Let’s go back to the Hot Chicken example. When considering a purchase of this stock, you had three main scenarios in mind (this is overly simplistic but should provide the gist of the necessary insight). In the “bullish” scenario, you expected customers to fall in love with the chicken bites, growth to register in line with management expectations, and a 25% return. In the “base rate” scenario, you expected the company to grow in line with industry peers and return 5%. In the “bearish” scenario, you anticipated that growth falters and the stock drops 10%.
Let’s say you forecasted the likelihood of each outcome as follows:
Based on these scenarios, you would have anticipated a positive expected return of 10.0% ((0.4)*(25%) + (0.4)*(5%) + (0.2)*(-10%)). The positive expected value would have been an indicator to buy the stock and you did.
But now that the bearish scenario has unfolded for Hot Chicken, the question is: were you wrong in your forecasts of the probable outcomes?
Maybe — but maybe not. Unfortunately, we just can’t know. In investing, it is never possible to know what the exact probabilities are in advance, or even what they were after the fact.
The only thing we can say is whether we were probably on or off point — and why — and then test out this intuition in subsequent experiments.
This might seem maddeningly inexact, but then investing is an imprecise science. Nonetheless, the process of diligently evaluating decisions can still be very insightful. One way to facilitate this process is by keeping a decision journal where you record why certain decisions were made, and routinely look back at these notes over time. Our team documents our decisions in our reports, decision trackers, models and company notes, and we refer to them in formal “look back and learn” processes. These processes have proven invaluable in helping to improve our understanding of reality over time.
How Little We Know
Another main challenge in detecting investment errors is the feedback mechanism. Unlike sports or poker — where feedback is often immediate and causality is clear — the feedback loop for fundamental investors is typically long and fuzzy. It can often take years for an investment thesis to play out, and even then, it is often difficult to know if the factors that you think caused a stock to go up are the actual contributing factors.
In addition, it can be difficult to accurately observe the feedback mechanism because of the flawed ways our brains take in information. Humans are remarkably deluded and biased creatures. In fact, the list of ways we delude ourselves is so long that entire books have been written on the topic (we recommend Kahneman’s Thinking Fast and Slow and Tavris and Aronson’s Mistakes Were Made but Not By Me). One of our most pernicious tendencies is our compulsion to tell stories to explain events. This is known as narrative bias.
The famous split-brain experiments conducted by Michael Gazzaniga at the University of California show the strength of our desire to make sense of the world through stories whether or not they are based on fact.¹ In the experiments, Gazzaniga took patients who had severed their corpus callosum, the connection between the right and left hemispheres in the brain, and then showed two completely different photos to the subject’s right hemisphere (via the left field of vision) and the left hemisphere (via the right field of vision). Based on these photos, he asked the subjects to point to a picture that related to what they had seen.
Since the right hemisphere (which controls pointing) would see something completely different than the left hemisphere (which controls verbal communication), the patients often found themselves pointing at pictures without understanding why. Remarkably, patients nevertheless told very convincing stories as to why they chose the photos they did.
In one case, a picture of snow was shown to a man’s left hemisphere. In response, he pointed to a shovel. However, his right hemisphere had been shown a chicken claw. Instead of just saying “I don’t know why I pointed at the shovel,” the man explained, “Oh that’s simple. The chicken claw goes with the chicken, and you need a shovel to clean out the chicken shed.”
Our desire to explain events runs deep — so much so, it presents a real potential hurdle when trying to learn from investment mistakes. Investors should be particularly aware of this trap as they seek to evaluate their track records over time. Sometimes, the most truthful answer to whether or not a decision was a success or a mistake is “I don’t know.”
Unfortunately, “I don’t know” is not an answer typically embraced by the investment industry.
Errors, The Elephant in the Room
One of the most common misconceptions about investing is that it is a game for “winners.” Popular culture perpetuates the stereotype of infallible investors making shrewd moves and winning on big, risky bets. Great investors are painted as intellectual titans, perfect in their logic and never making a misstep. It is not hard to see why we eat this up: for the same reason why we love Sherlock Holmes — there is something very appealing about someone who (seemingly) has all the answers.
But this is all just Oz before Toto pulls down the curtain. While there are many bright individuals in our industry, no one has all the answers. How could they? To assume anyone is omniscient or clairvoyant — arguably what is necessary to never make a mistake — is absurd.
Investing is simply not an arena in which perfect decision-making is possible. And that’s fine, because it doesn’t need to be. So long as your investment philosophy is a resilient one — meaning that it puts the odds in your favour over time — perfection isn’t required. The main thing about mistakes is that they happen and they needn’t bring down the ship. Simply put, the strength of your good decisions must overpower your errors. Ideally, you make more good calls than bad, and you win more on the good calls than you lose on the bad ones, over time.
So why does our industry so often act like this is not the case? Why is “mistake” such a dirty word?
One of the most confounding aspects of the investment industry is the prevalence of a paradigm that suggests that mistakes are for losers. According to this view, an investor who admits mistakes is unworthy of time, attention, and reward. Analysts who freely admit to being wrong often risk writing their own pink slips. This perspective ignores the reality that investing is a dynamic arena in which perspectives must constantly shift, mistakes will
happen, and that even the most successful investors will sometimes be wrong. And while the paradigm isn’t universal, it is prevalent enough that mistakes are often ostracized or ignored, to no one’s benefit.
A wise investor once said, “it’s good to learn from your mistakes. It’s better to learn from other people’s mistakes.” It is challenging for a team to learn from each other’s insights — usually driven by mistakes — if they are not shared in the first place.
It’s Just Data
Paul and I are on the phone for only a little while longer after the Krispy Kreme story.
He comments how restrictive it must be to work at a company that doesn’t make space for mistakes — and how limiting this is for growth. He hangs up the phone, off to conduct a series of interviews with CEOs in Jakarta.
This conversation with Paul lingers in my mind. After a few minutes of searching on my desktop, I find what I am looking for: the folder from our team’s annual post mortems.
I see the main investment lessons from every member of our research team since we began formally documenting them in 2013. There are about three lessons, give or take, for each person on our team, for every year… all told, over 300 investment insights. Most of these were gleaned from mistakes. It reminds me just how much of an advantage it can be to have processes that prompt reflection on decisions and a culture that allows for growth without fear of reprisal.
What does it take to really make the most of errors? It seems to boil down to attitude. Paul is a good example on our team of someone who has an attitude conducive to growth.
I have never known anyone so simultaneously willing to own and discuss his mistakes and dedicate himself to growing from them. At the same time, Paul really does hate losing, so he is also meticulous about keeping his mistakes low cost and productive.
In investing, a big part of having the right attitude is detaching decisions from our identity. When you tie your feelings of self-worth as an investor to being right all the time, it becomes very hard to make decisions objectively. When an idea is “yours,” instead of just being an idea, it can be a challenge to throw it aside when necessary. That is why you will frequently hear individuals on our team say “I’m having the thought,” as though ideas were just floating around in the air, waiting to be picked up, investigated and, if needed, discarded. It is not by chance that we use this language. Although the shift in language may be subtle, we have found that removing the possessive from our speech helps our team be more objective in our thinking.
Adopting a growth oriented culture towards mistakes has been one of the most significant decisions our team has ever made — it has probably contributed more to any success we’ve had than the models we’ve built or the reports we’ve written. The cumulative effect of these little pains over time has saved our clients millions.
Mistakes are not something to disregard — they are meant to educate. And, in investing, those lessons are invaluable.
To be clear, Paul was not yet an employee at Mawer when he was trading Krispy Kreme. Our personal trading policy strictly prohibits trading of individual securities in this manner. The policy is designed to align our team with our clients — i.e. we “eat our own cooking.”
¹ Gazzaniga, Michael S.. Nature’s Mind: The Biological Roots of Thinking, Sexuality, Language, and Intelligence. Basic Books, 1992.