[00:02:38] Shawn O’Malley: The most valuable insight he’s learned from taking a multidisciplinary approach to investing is that the stock market is, to quote him directly, a complex adaptive system. Similar to how consciousness is an emergent phenomenon from many parts of our body and brain interacting together, so are the economy and financial markets.

[00:02:58] Shawn O’Malley: They’re systems born out of millions of daily interactions across the world. According to the New England Complex Systems Institute, a complex adaptive system is a system that changes its behavior in response to its environment to achieve a certain goal or objective and is usually associated with plants, animals, or social groups, but as mentioned, the term can also be used to describe the financial system and economy.

[00:03:22] Shawn O’Malley: These systems are complex and diversified, contain both positive and negative feedback loops, are self-organized, and can dynamically adapt to and learn from the world around them. I’m just planting the seed now to think of the stock market as a system that’s more than the sum of its parts. And one that dynamically responds to and evolves from the world around it.

[00:03:42] Shawn O’Malley: We’ll touch on this later in the episode. So you can just keep this point that the stock market is a complex adaptive system in the back of your head, since it’s so critical to how Mauboussin thinks about financial markets. But now let’s dive into Mauboussin’s first essay on investment philosophy. Investment philosophy is important because it dictates how you should make good decisions.

[00:04:02] Shawn O’Malley: A sloppy philosophy inevitably leads to poor long term results, but even a good investment philosophy will not help you unless you combine it with discipline and patience. A quality investment philosophy is like a good diet. It only works if it is sensible over the long haul and you stick with it. That passage is directly out of the book with the point being that what ultimately matters is one’s decision making process, not short term results.

[00:04:26] Shawn O’Malley: Many investors get started with these sort of half-baked philosophies on how they like to invest. They find some short term success and then constantly update that philosophy based on random variations of their results. So they end up chasing insights with no north star guiding them. A good investment process has to rest on sound building blocks.

[00:04:47] Shawn O’Malley: This reality often clashes with incentives though, because investment managers usually earn fees based on the total assets they manage. Their incentives are to grow their assets as much as possible, not necessarily to deliver the best compounded investment returns. A market beating track record helps with attracting assets, but savvy marketing and charisma can just as easily induce investees into a fund.

[00:05:11] Shawn O’Malley: When constructing an investment philosophy, Mauboussin tells us to be like the house in a casino, with the odds of winning always tilted in our favor over time. But having the odds in your favor doesn’t mean you’ll always win, and that’s okay. If someone hits a jackpot and earns a million dollar payout, casinos don’t necessarily take this as evidence that their business model isn’t working.

[00:05:33] Shawn O’Malley: The occasional big payout is sort of the cost of doing business. Rather than using short term outcomes as the determinant of success, such as whether the casino made or lost money on a given day, a better approach involves reflecting on the decision making process. A gambler who bet big and won when the expected value from the odds offered wasn’t in their favor isn’t skilled.

[00:05:55] Shawn O’Malley: They’re just lucky. But that outcome is blinding. If someone is walking around with a million dollars of poker winnings, how could you not think they’re skilled? Results are tangible and easy to assess. Either you won or you didn’t. Yet, if that gambler continues to make the same or similar bet over time, luck will fade away.

[00:06:13] Shawn O’Malley: That is the difference between outcomes and process. The gambler’s process is flawed. His strategy includes risky bets with negative expected values, but temporary success can mask a poor decision making process. The casino is less bothered by short term outcomes and more worried about the process that they follow.

[00:06:31] Shawn O’Malley: In that same vein, making 50 percent trading Nvidia doesn’t make you a good investor if the process underlying that decision was incomplete or unsound. The critical mistake people often make is conflating good outcomes with good processes, rationalizing that they wouldn’t have made money if they didn’t do something right.

[00:06:49] Shawn O’Malley: The complicating factor, I think, is that good processes will sometimes lead to bad outcomes and bad processes to good outcomes. But there’s a reason many great sports franchises live by the motto, trust the process. Teams that draft well, build up their rosters carefully, and follow disciplined decision making rules position themselves best for continued success over time, whereas others may splurge on super teams of expensive star players that either deliver them one off championships or wreck the franchise for years.

[00:07:17] Shawn O’Malley: In stock investing, a sound process is one that effectively identifies discrepancies between a stock’s current price and its expected value, which is the weighted value of a range of possible outcomes for the company’s future. The game then is not to bet on the horse with the best chance of winning, but to bet on the horse with the best chance that’s not properly reflected in the odds being offered for it.

[00:07:40] Shawn O’Malley: Investing is about dealing with uncertainty, recognizing that uncertainty, and incorporating it into your calculations of expected value for companies. Think of expected value as putting a single number value on a bet that’s derived from multiplying a range of outcomes by their payouts and odds of recurring, and then adding them together.

[00:07:58] Shawn O’Malley: When the possible payoffs or downsides are large enough, the distribution of outcomes becomes massively skewed. Just look at options investing as an example. 90 percent of options expire worthless, but that doesn’t mean that options aren’t valuable. Stock options can offer considerable payoffs from unlikely events.

[00:08:16] Shawn O’Malley: So if the payoff is big enough, the expected value for even a low likelihood event may still be positive if magnitude outweighs frequency. In a portfolio of stocks, one big winner with nine losers may still generate a positive total return. The problem is that while this is easy to understand conceptually, it’s incompatible with human nature.

[00:08:37] Shawn O’Malley: Behavioral economists like Daniel Kahneman and Amos Tversky showed decades ago that the pain felt from investment losses exceeds the joy from gains. Making most people risk averse and less able to stick with volatile positive expected value investments to make the point again on how magnitude impacts expected value.

[00:08:56] Shawn O’Malley: Imagine a stock that has a 75 percent chance of delivering on its earnings promises, which should move the stock about 1 percent higher, but its price such that it could fall off 10 percent or more if the company misses earnings. The odds are technically in your favor, but the expected value isn’t. The 25 percent chance of missing with a 10 percent decline in the stock price more than offsets the smaller payoff from the most likely outcome.

[00:09:21] Shawn O’Malley: Of course, no one ever spells out this information for us when investing. You can never know the odds with a hundred percent confidence, but we still must act with even imperfect information. In fact, too much information can introduce noise that may worsen our decision making as investors. In a study on oddsmakers for horse races, participants were asked to determine the handicap for horses with just five pieces of information, then do so again with 10, 20, and 40 pieces of information.

[00:09:49] Shawn O’Malley: Even though their confidence increased significantly with more information, the oddsmakers were only marginally better at making predictions with more information. What I take from that is even though we all crave more information to help with our investing decisions, there’s a cutoff point where more information doesn’t actually help with the quality of our decisions but does create an illusion of certainty and false confidence that can lead us to invest more than we should in an idea.

[00:10:13] Shawn O’Malley: So how do top investors behave in practice and a screen for equity fund managers who beat the S&P 500 benchmark over the decade ending in 2005, a few points of commonality stood out. Firstly, these market beating investors didn’t trade frequently. Their annual portfolio turnover was just 35 percent compared to 89 percent for all fund managers.

[00:10:35] Shawn O’Malley: They also tended to be much more concentrated with 35 percent of their assets invested in their top 10 biggest holdings versus around 20 percent for the S& P 500. Most of these market beating investors, according to Mauboussin, subscribed to the Warren Buffett and Ben Graham School of Investing, where they compared stocks current prices to their assessment of intrinsic value.

[00:10:56] Shawn O’Malley: These commonalities are not on their own what define investment success. More likely, they are symptoms of sound investing processes. An investor who looks for discrepancies from intrinsic value or has low portfolio turnover isn’t guaranteed to beat the market, but it is evidence that they may have a disciplined, well-reasoned investment process.

[00:11:17] Shawn O’Malley: Which would be an indicator of expected long term success. Low quality investment processes usually try to explain the world based on attributes, using labels like size, value, and growth. We call companies with low price to earnings ratios, value stocks, or companies with above average revenue increases growth companies, but nothing about that provides any circumstantial or actionable information.

[00:11:41] Shawn O’Malley: There’s no if then statement. If your sole decision making criteria were to enter into investments, when their PE ratio was low, you would do very poorly. You’d spend a lot of time owning companies that are cheap for a reason with no guarantee that that will change. With a more circumstantial approach, you might find a catalyst that drives cheap stocks to become less cheap.

[00:12:01] Shawn O’Malley: For example, you may realize that when interest rates fall, the PE ratios for already cheap value stocks rise faster than for other companies. So rather than just blindly owning value stocks to an attribute based factor like relative cheapness, you’d know to do so when a certain catalyst happens, like interest rates falling.

[00:12:19] Shawn O’Malley: Super investors like Bill Miller, who is one of the only investors to ever beat the market in 15 consecutive years, tend to think circumstantially in their decision making processes, according to Mauboussin. Despite considering himself a value investor, Miller has invested in famous growth companies like Amazon in the early days.

[00:12:35] Shawn O’Malley: That’s because he doesn’t adhere strictly to some arbitrary attribute oriented definition of value based on price to earnings or price to book. He considers value circumstantially. Sound processes reflect context, and without context, you’ll be lost in navigating constantly changing markets. Too many investment gurus lament what they think the market should do, rather than trying to understand why markets are doing what they do.

[00:12:58] Shawn O’Malley: In terms of studying others investment philosophies for insights, there really is something to be said for learning from the best of the best, at least from those with the longest track records of beating the market. While the hot hand phenomenon has been disproven in sports because most hot streaks can be explained within the realm of expected probabilities, what gets lost in translation is that the probabilities of going on hot streaks vary for each player.

[00:13:22] Shawn O’Malley: It isn’t much of a statistical outlier when a basketball player who shoots 90 percent from the free throw line hits 10 free throws in a row, but it would be if a 50 percent free throw shooter did. We often conflate great players going on shooting streaks in basketball or hitting streaks in baseball as self-sustaining hot streaks, when in reality, a player with a high average shooting percentage will inevitably have sub streaks over the course of their career due to simple statistical randomness.

[00:13:48] Shawn O’Malley: The difference is that good shooters can go much longer before violating probabilistic expectations. So, long streaks of having a hot hand do communicate some information. They tell us that the player likely has a very high average shooting percentage, which makes such a streak plausible. The same is true for investing.

[00:14:05] Shawn O’Malley: With each additional year that an investor beats the market over their career, the less likely it becomes that the explanation is simply randomness. Longer streaks of beating the market are similar to a basketball player with a higher shooting percentage. Underlying skills make the hot street more statistically likely and less of an abnormality.

[00:14:22] Shawn O’Malley: Through that lens, it’s clear that investors like Warren Buffett and Bill Miller have beaten the market for so long because they are actually exceptionally talented. Now, I want to move into Mauboussin’s second essay from the book on the psychology of investing. As he puts it, understanding psychology provides a preview into the types of mistakes you’re likely to make as an investor.

[00:14:41] Shawn O’Malley: We’ve already talked about the importance of defining an investment philosophy and decision making process, but this section brings to life that by considering the mental roadblocks that try to derail us from that process. Rather than throwing a bunch of textbook terms for psychological biases at you, the simplest way to start is with stress.

[00:14:58] Shawn O’Malley: We’ve all experienced the physical and mental effects of extreme stress at one time or another, or at least seen how it can affect others. Stress makes us less patient, more irritable, and can literally destroy our bodies over time. In contrast to how you’ve experienced stress, imagine the sorts of things that may cause stress to a zebra.

[00:15:16] Shawn O’Malley: A zebra’s stress is acute, A lion might be chasing it, and the zebra’s body kicks into action to release cortisol and adrenaline to help it get away. But the list of events that cause stress to zebras on a daily basis is quite slim, especially compared to the list of things that probably cause you stress.

[00:15:33] Shawn O’Malley: Groceries, chores, kids, pets, work, investments, the list goes on and on. Human stressors are psychological and chronic, yet our bodies are suited primarily for managing acute stress, like the zebras. Meanwhile, the physiological responses to chronic stress and acute stress are similar, which throws our bodies out of balance.

[00:15:53] Shawn O’Malley: Lack of predictability and control is particularly stressful for us, and few disciplines have a more potent combination of those two stress inducing factors than money management, and markets only seem to be getting less predictable. The average time that a company spends in the S& P 500 index has shrunk by more than half in the last few decades.

[00:16:13] Shawn O’Malley: The only salvation for relieving investor stress is to turn to the long term, in Mauboussin’s opinion. While stress pushes us to impulsively make decisions today that we hope will provide a miracle fix, a long enough time horizon allows us to better contextualize chronic stress. Deeply understanding a business you plan to own for over a decade should give you the confidence to write out gyrations in the market price or fear mongering news stories.

[00:16:38] Shawn O’Malley: Mauboussin says that if the source of investor stress is largely psychological, so too is the means to cope with it. Commitment and consistency is another one of those potent psychological factors impacting investors. Once we’ve committed to a decision, our brains can sometimes almost entirely turn off critical thought.

[00:16:57] Shawn O’Malley: It’s a survival mechanism ingrained in us to avoid wasting energy going back and forth on decisions. Even worse is that once we’ve publicly committed to a decision, it’s difficult to pivot from it. Inconsistency is not a desirable trait in human social groups. If you cannot count on your neighbor to do as they promised, trust collapses.

[00:17:17] Shawn O’Malley: As a result, there are good evolutionary reasons for us to get locked into our commitments and decisions. Nobody wants to be perceived as being unreliable. Unfortunately for investors, this manifests by making it difficult for us to justify changing our investment views. If you post on Twitter or tell a family member about some company, you’re bullish about, your subconscious tethers you to that decision and resists doing a 180 if the company’s outlook looks bad.

[00:17:41] Shawn O’Malley: Changes dramatically for the worse, but it’s hard to even recognize that the facts may have changed or that your original thinking was wrong. If you’ve started disregarding new information after having made a commitment to being bullish, it’s a relatable feeling. I know that after I’ve done dozens of hours of work researching a company and sort of made up my mind on it.

[00:17:59] Shawn O’Malley: By the end, I’m ready to just kind of be done thinking about it for a little while. I feel like I need a break. And if at the same time I’ve told everyone about what a great company it is, it makes it even harder to be alert and cognizant of continuously evaluating that investment thesis objectively.

[00:18:14] Shawn O’Malley: You subtly tilt toward only processing information that validates your conclusion because it feels like too much work to dive back into researching the company again, or because you worry about appearing inconsistent after previously recommending the stock. Another set of biases that really resonates with me is liking and disliking in general, when we like or dislike something, we justify our opinions in one way or another when it comes to investing.

[00:18:38] Shawn O’Malley: If you really like a company, maybe because you admire its management or its vision, or because you use its products, it’s just a lot easier to dismiss the risks and exaggerate the potential benefits. It’s the same with disliking. If you despise a company’s impact on society, just how a lot of people feel about social media companies or just find the company boring, you’ll probably be more inclined to fixate on the bearish arguments against owning the stock.

[00:19:04] Shawn O’Malley: Disliking a company can blind you from the investment merits of being a shareholder in it. However, emotion is fundamental to our decision making process. That’s Mauboussin’s takeaway, at least, after reviewing studies on decision making among individuals who had suffered brain damage primarily impacting the part of their brain responsible for generating emotions.

[00:19:24] Shawn O’Malley: Emotions triggered subconsciously drive conscious decisions, and without emotion, our decisions tend to just be worse. A subconscious emotional response to seeing a snake stirs fear, which drives us to be cautious and back away. Without any emotional response, you might respond to seeing a snake with less caution, and that could quite literally come back to bite you.

[00:19:43] Shawn O’Malley: So, emotions are critical to how we make decisions, but they also distort our sense of objective probabilities. If you see a random snake, the odds are that it’s probably not poisonous and probably not interested in biting you, but your emotional response from anticipating the worst case outcome of being bitten by a deadly snake is more than enough to make you jump back.

[00:20:03] Shawn O’Malley: In that case, emotions drive a response that’s in your best interest. Using extreme caution around wild snakes may exaggerate the odds of being bitten, but doing so is still a good decision. When it comes to buying lottery tickets with the possibility of life changing payouts, people tend to behave the same whether the odds of winning are 10, or 1,000,000 to 1 because the potential outcome is so emotionally exciting.

[00:20:28] Shawn O’Malley: The emotional response pushes them to ignore the odds and focus on the outcome. It’s a similar problem when investing. If your hopes are high enough that an investment will make you rich, you’ll be much more inclined to overlook the risks. The bottom line is that when investors find an investment attractive, they deem the risk low enough and the rewards high enough, irrespective of the actual probabilities to drive their decision.

[00:20:50] Shawn O’Malley: When they dislike an idea, the inverse is true. Risk is perceived as high and reward is low. If stress consistency and commitment and liking and disliking weren’t enough to deal with investors also must grapple with being social creatures. It’s the whole nature versus nurture debate. We love to imitate others.

[00:21:08] Shawn O’Malley: It’s the backbone of the fashion industry and really any other business that relies on fads. People see others wearing a brand and suddenly they want to wear that brand too. The surge in retail stock investing on Reddit is a perfect illustration of this, in my opinion, of how imitation can overlap with financial decisions.

[00:21:25] Shawn O’Malley: Subreddits devoted to single stocks have millions of members feeding off each other. Buying a stock then becomes as much of an investment decision as a social one. Receipts of your stock purchases are like tickets into a club of people all bonded by their investment decision. And an entire discipline and investing is devoted to imitation.

[00:21:44] Shawn O’Malley: Momentum investors by nature seek to profit by piling into the, what the crowd is doing, but imitation doesn’t have to be a dirty word. It’s quite helpful when other investors know more about something than you do to follow their lead. The flip side is that when imitation of an investment becomes too popular, it leads to bubbles.

[00:22:03] Shawn O’Malley: The takeaway isn’t that markets are completely irrational because markets are made up of people and people are irrational with enough stock market participants. There’s enough diversity that irrationalities can cancel each other out. Someone who is experiencing a bias in one direction may be offset by someone biased in the opposite direction.

[00:22:22] Shawn O’Malley: Therefore markets mostly arrive in appropriate places, except when they’re all irrational in the same way at the same time. This is what panics are. At the same time, everyone is gripped strongly by fear, which creates a cascading effect. Selling drives more panic, which drives more selling. I remember this vividly in March 2020 on March 16th, the Russell 3000 index of us stocks fell more than 11%.

[00:22:46] Shawn O’Malley: I had no idea at the time what the future would hold and how COVID would change the world. But it seemed that fear was driving irrational responses among huge chunks of investors all at once. And in hindsight, which is a bias of its own, actually, it was a great opportunity to take advantage of.

[00:23:02] Shawn O’Malley: Identifying irrationalities in markets is rarely so easy though, and even that example isn’t as simple as it seems. Given how markets have recovered since, my thinking about what happened in March 2020 has been skewed. Trying to time the market based on its collective psychology quickly becomes a game of guessing what the average investor thinks the average investor is thinking.

[00:23:22] Shawn O’Malley: And you cannot assess the quality of your previous decision making. If your recollection of it is clouded by hindsight biases, which is why Mauboussin encourages investors to keep a log of their rationale for decisions at the time they were made so that they can reflect on them in the future without the effects of hindsight biases.

[00:23:39] Shawn O’Malley: In a world with so many biases, what is there to be said of intuition and just thinking with your gut? Actually, more than you might think, at least according to Mauboussin. Studies on in the moment decision makers dealing with crises, like firefighters, reveal that there is no classical theory involved in their decision making.

[00:23:56] Shawn O’Malley: They do not sit around and weigh the pros and cons of a given strategy. Instead, they identify the first satisfactory solution and go from there, implementing new solutions along the way that come to mind. It’s an approach based on satisficing, not maximizing. There is no time to determine the theoretically optimal way to put out a fire and save everyone’s lives.

[00:24:16] Shawn O’Malley: You must spring into action with your best instinct. The same is true in other dynamic, fast paced environments, from Wall Street trading floors to battlefields. In these situations, effective decision makers draw heavily on their ability to quickly see a range of alternatives and mentally simulate different responses.

[00:24:33] Shawn O’Malley: They’re also quite adept at pattern matching. Under pressure, experts can quickly match the circumstances to known patterns. With chess masters, for example, it’s been found that the quality of their moves doesn’t deteriorate significantly, whether they have 130 seconds to make a move, or if they have just six seconds in a moment, they can scan the board and make relatively good moves.

[00:24:53] Shawn O’Malley: Surveys of experts who had poured hundreds of hours into earning the chartered financial analyst designations found that the most well trained investors relied on gut instincts in similar ways. They tended to think in terms of ranges of possible outcomes, using mental imagery, and creating stories based on the available facts.

[00:25:12] Shawn O’Malley: Their decisions, like firefighters or chess masters, are context dependent, and they’re not held up by finding the theoretically optimal investment opportunity. They look for satisfactory opportunities incrementally. Otherwise they’d be paralyzed by a never ending search for the perfect investment. So there’s some tension between what we’ve discussed here today.

[00:25:31] Shawn O’Malley: Sound decision making frameworks are needed for investment success. Meanwhile, some experts may be so experienced or skilled that they can make high quality decisions extremely rapidly. I actually don’t think these two things are at odds, though. The true expert is one who has mastered their decision making frameworks, can adjust for the context, and is then able to filter out the noise to make quality decisions.

[00:25:54] Shawn O’Malley: That wraps up the second essay from the book, so let’s move into Mauboussin’s third essay on innovation and competitive strategy. He begins by going through the names of the companies included in the original Dow Jones Index dating back to the late 19th century, which intended to track America’s largest and most valuable publicly traded companies.

[00:26:14] Shawn O’Malley: In just over a hundred years, things have changed completely. At its debut, the index included companies like American Cotton Oil, American Tobacco, Chicago Gas, Distilling and Cattle Feeding, General Electric, Tennessee Coal and Iron, U.S. Leather, U.S. Rubber, American Sugar Refining, and Blacklead Gaslight Company, National Lead Company, and North American.

[00:26:35] Shawn O’Malley: Of these dozen titans for their era, none remain, and only one is recognizable, General Electric, which was recently split up into three parts. From their names, you can tell that the biggest companies of the 1890s reflected the commodity oriented economy in which they operated. The world has changed, and so have the types of companies that accrue the greatest market valuations.

[00:26:57] Shawn O’Malley: This is just the reality of compound innovation over time. The challenge is that while we all know innovation is inevitable and tomorrow’s most valuable companies will look quite different than today’s, these changes are small and incremental. In practice, a lot of investors hold a cognitive dissonance where they know things are changing, but disregard change because they can’t see it in real time and therefore end up holding onto yesterday’s best companies, expecting them to just continue doing well.

[00:27:25] Shawn O’Malley: An interesting thought experiment is to consider why we’re so much wealthier today than when the Dow Index was first published. The Earth’s natural resources haven’t changed, yet we live much more comfortably than our great grandparents could ever dream, despite having to spread those resources across a much larger population.

[00:27:43] Shawn O’Malley: 130 years ago, control of resources was the primary way to generate wealth. New wealth has come from more effectively rearranging the earth’s resources. 2024’s most valuable companies aren’t those that mine silicon, they’re companies that have found better and better uses of that natural resource, namely in computer chips and electronics.

[00:28:02] Shawn O’Malley: The companies of the original Dow competed in a world defined by scarcity. Whoever held the most of a finite asset, like oil and gas, iron, rubber, sugar, and so on, were the winners. But software has allowed us to build wealth with resources that are not scarce. Software is just information, a set of instructions that can be used by anyone at little cost.

[00:28:22] Shawn O’Malley: When a better way for doing something is discovered, that can be communicated instantaneously across the globe and can be quickly adopted, saving us time to find new tasks that we can make more efficient. In the 19th century, most workers were doing industrial or agricultural work based on series of repetitive tasks.

[00:28:38] Shawn O’Malley: And just a handful of a company’s employees might’ve been concerned with more knowledge based work and designing better systems. The opposite is true now. Entire companies are devoted to paying people to uncover and bring to market better ways of doing things, driving more innovation. Generally speaking, there’s an overshoot of companies in new industries, all competing for market share.

[00:28:59] Shawn O’Malley: America once had over 2000 car companies. And over the last century, that number was whittled down to just four or five that are really of much consequence. An explosion of new companies following a significant innovation is eventually pruned down, which is also known as the boom and bust process.

[00:29:15] Shawn O’Malley: Mauboussin says that investors would be wise to look around at the end of one of these printing processes to see who has survived. You could do much worse than having a portfolio of survivors who endured an industry’s transition from infancy to maturity. He identifies two key inflection points in the S curve for new industries, where growth typically begins slowly, accelerates rapidly, and then eventually slows.

[00:29:38] Shawn O’Malley: The first inflection point is when a new industry goes from slow to rapid growth and overlaps with when investors transition from underestimating future growth to overestimating by extrapolating the accelerated growth indefinitely. The second inflection point comes as investors get burned by their now overly optimistic growth outlook for an industry.

[00:29:58] Shawn O’Malley: As the industry matures, growth falls off and investors quickly revise their expectations for the future. The best opportunities come from successfully identifying an industry’s winners at the first inflection point, while the most pain is felt at the second inflection point. Because innovation is accelerating, Mauboussin believes that investors today will continue to see more and more of these S curves than in the past, as new industries rise and fall at faster paces.

[00:30:24] Shawn O’Malley: With that comes more opportunities to find industry winners early on at the first inflection point, as well as more risks of being punished for owning these companies by that second inflection point to quote him directly. He says in a fast changing world, you’re almost always better off betting on the new guard than the old.

[00:30:41] Shawn O’Malley: You may not know which company will generate the excess returns. But you can be almost assured that the older company will not. In the book, Creative Destruction, Richard Foster and Sarah Kaplan show that new entrants generate higher total returns to shareholders than their older and more established competitors.

[00:30:57] Shawn O’Malley: In a review across 30 years of thousands of companies that were in the top 80 percent of all stocks in terms of market capitalization and had at least 50 percent of their sales in the defined industry. Most of these excess returns came in the entrants first five years, while returns over the subsequent 15 years tended to be in line with industry averages, and then after 20 years, the same companies usually began to underperform their peers.

[00:31:20] Shawn O’Malley: That’s because new entrants improve upon the status quo until they eventually become the incumbents and can no longer earn returns beyond their cost of capital. Another way to think of this is that the duration of companies competitive moats is much shorter in the 21st century, meaning many companies competitive advantages don’t last as long as they used to.

[00:31:38] Shawn O’Malley: To quote Bill Gates in 1998, he said, I think the multiples of technology stocks should be quite a bit lower than stocks like Coke and Gillette because we are subject to complete changes in the rules. I know very well that in the next 10 years, if Microsoft is still a leader, we will have had to weather at least three crises.

[00:31:57] Shawn O’Malley: Saying that innovation is shortening the lifespans of companies advantages is a big claim. As evidence, Mauboussin cites how the average lifespan of 1, 800 U.S. industrial companies assets, including R&D capitalized assets, has fallen from 14 years in 1975 to under 10 years currently. Companies assets just don’t create value for as long as it used to, and today’s companies must generate returns with their assets in less time than they did a generation ago.

[00:32:23] Shawn O’Malley: As an investor, you might wonder whether you should want your companies to think more short term in a more innovative world, or if it’s more important than ever to think long term and see the big picture. I don’t think there’s a clear answer other than to say there are trade-offs to both, and the right approach is context dependent.

[00:32:39] Shawn O’Malley: It’s sort of like driving a car down the highway. If you only focus on looking at the hood, you’re going to have trouble, but you’re also going to have issues if you only stare off in the distance. The right mix of short and distant focuses changes with the context. The long term is really just a collection of short terms.

[00:32:56] Shawn O’Malley: No company has ever had a great five years despite having 20 terrible straight quarters. To invoke Charles Darwin, it is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change. In a word, what matters for both organisms and companies in complex systems is adaptability.

[00:33:15] Shawn O’Malley: For organisms, it’s about creating options through mutations and naturally selecting for the best ones. For companies, it’s about generating value, creating opportunities and selecting the best ones to drive the highest possible long term returns. How he breaks this down as happening is interesting.

[00:33:30] Shawn O’Malley: Companies can take incremental short leaps forward, like process improvement initiatives, or they can take large leaps that either catapult them to the top of their potential or wipe out their potential for earning returns above their cost of capital. Large leaps might include acquisitions and new industries or developing new types of products based on the competitive ecosystem surrounding a company.

[00:33:53] Shawn O’Malley: You can probably guess which types of leaps they’ll take in stable industries. There’s less enthusiasm for disrupting the status quo, so most leaps are small and focused on improving efficiency. In fast changing industries like biotechnology, large leaps are much likelier because companies must make them to survive.

[00:34:10] Shawn O’Malley: Any smaller advantages are likely to be fleeting since the environment around these companies is so dynamic. Traditional discounted cash flow valuations can work quite well for stable companies that make small leaps because the range of outcomes tends to be narrower, leaving less room for errors that can compound when projecting five or ten years out.

[00:34:29] Shawn O’Malley: On the other hand, using discounted cash flow models to value a biotech company sounds crazy. They’re relying entirely on big leaps like drug approvals and medical breakthroughs that happen on unknowable timelines. In a business world that has more big leaps than in past decades, Mauboussin claims that using past data as the basis for valuations is deeply flawed.

[00:34:51] Shawn O’Malley: Since past valuations were set in a different context of the economy, the challenge is actually similar to the problems that social security has had. Social security was devised at a time when a much smaller percentage of the population lived into their seventies and eighties, and legislators assumed this would continue to be true, where there’d always be many more workers paying into social security than retirees pulling funds out of it.

[00:35:14] Shawn O’Malley: In 1935, when the Social Security Act was first signed, America had 42 workers. For every retiree thanks to longer life expectancies Today, that ratio is now three to one. The issue here is that the original designers of social security extrapolated past data forward, expecting things to mostly remain the same.

[00:35:33] Shawn O’Malley: Based on actuarial tables, their plans to pay retirees at 65 seemed conservative at the time and financially sound. They clearly didn’t foresee how their system would come under strain if the demographic structure of society changed hugely. Investors make the same mistake every day in the stock market too.

[00:35:51] Shawn O’Malley: They say things like, well, based on 20 years of data, the average price to earnings ratio for this industry is 15. So because the industry average is now 18, these stocks are overpriced. That thinking is just completely wrong in most sense of view, because past ratios are only relevant to the degree that they capture today’s circumstances.

[00:36:10] Shawn O’Malley: In other words, you’re referencing data that price companies within a completely different context. There’s actually no statistically significant relationship between a company’s PE ratio at the beginning of a year and its subsequent 12 and 24 month returns, according to research covering the last 125 years of financial data.

[00:36:29] Shawn O’Malley: Say it more bluntly, historical averages for investors beloved PE ratios have almost zero predictive power of results over typical investment time horizons. In part, that’s because economic growth, inflation, and tax rates are always in flux, yet each determines the valuation that markets are willing to pay for different financial assets.

[00:36:47] Shawn O’Malley: Lower dividend tax rates, for example, should lead investors to pay higher multiples for stocks because they can earn the same returns on less income. The PE ratios of yesterday reflect different tax rates, inflation levels, and at the index level, different mixes of companies from companies that relied more heavily on machinery and tangible resources to now more knowledge based companies relying on technology.

[00:37:11] Shawn O’Malley: These all have different implications on valuations, which makes apples to apples comparisons of valuation ratios across time very difficult to do honestly. Another element of this discussion that people miss is that stocks are priced based on their economic returns and growth, not just growth. Plenty of companies have grown their way to bankruptcy.

[00:37:31] Shawn O’Malley: So an investment approach premised only on growth is flawed. Embedded in such a focus on growth is usually the belief that returns will improve with scale, which is sometimes true, but not inevitable. WeWork is a really popular illustration of this, where growth only compounded the company’s losses and Tesla is sort of the counterpoint as a company that grew its way out of losses.

[00:37:54] Shawn O’Malley: So, it’s not just growth rates that fluctuate, returns tend to revert to the mean over time because industries earning profits at above their cost of capital will attract more investment and competition, and returns there will then drift downwards, whereas capital will flee lower return industries via bankruptcy or disinvestment, rewarding incumbents as returns slowly drift back up with less competition.

[00:38:17] Shawn O’Malley: To show the point on mean reversion, Credit Suisse did an analysis of over 450 technology companies from 1979 to 1996, ranking companies in quartiles based on their cash flow return on investments, or CFROI. The top group of companies earned an average of 15 percent at the start, but those above average returns declined to just 6 percent after only five years.

[00:38:41] Shawn O’Malley: And the worst group went from earning negative 15 percent returns at the start to earning 0 percent after five years, as many of the worst performing companies went out of business. On both extremes, convergence to the mean drives outliers to earn more normal results, but some companies can still persistently earn exceptional returns and seemingly defy the pull of mean reversion.

[00:39:03] Shawn O’Malley: In another study from 1960 to 1996, 11 percent of companies had an unblemished record of earning returns above their cost of capital. Going back to our discussion of PE ratios, companies that can sustain above average returns will correspondingly trade at higher valuations. If growth is strong too, valuations can go even higher before becoming unjustified.

[00:39:25] Shawn O’Malley: At the same time, expectations for these high performers are high, because their high PE ratios reflect the expectation that they can continue to earn above average returns and continue to grow. The degree to which these expectations for the future prove realistic will determine in hindsight whether a company’s stock was cheap, fairly priced or overpriced.

[00:39:44] Shawn O’Malley: This leads into the bigger discipline of expectations investing, which is an approach where investors try to determine the future assumptions baked into a company stock today, like whether the company’s growth will slow or accelerate, whether its returns will revert to the mean and determine if those expectations are realistic.

[00:40:03] Shawn O’Malley: From that perspective, the companies in the top quartile of returns aren’t necessarily better investments than the companies in the bottom quartile. The best companies could have overly optimistic valuations, and the worst companies could have overly pessimistic valuations. To assess companies prospects compared to the price and expectations, we have management’s projections for the future available to us.

[00:40:23] Shawn O’Malley: While most companies give guidance about the future, the usefulness of that guidance can vary significantly. The underlying bias is that management typically wants to rally employees around grand visions for the future and put their best foot forward to investors, leading most of these projections to be overly optimistic and the book profit from the core.

[00:40:42] Shawn O’Malley: Chris Zook shows his research on over 1800 companies across five industries with three hurdles for them to beat at least 5.5 percent real inflation, adjusted sales growth, 5.5 percent real earnings growth, and total shareholder returns in excess of the cost of capital. These hurdles are actually pretty conservative compared to these companies own projections, where two thirds of the firms assumed double digit growth rates in their future plans.

[00:41:07] Shawn O’Malley: Yet only 25 percent of companies hit Zook’s more modest growth hurdles, and only one in eight companies ticked all three boxes. The vast majority of companies aim to grow at double digit rates, and the vast majority do not. That puts a pin on the conversation about innovation and growth for now. So, let’s move on to Mauboussin’s fourth and final essay in the book, and then we can try to recap everything we learned today.

[00:41:31] Shawn O’Malley: Essay 4 on Science and Complexity Theory begins with a discussion of just how difficult it is to see the big picture of a complex system. An individual looking out on the landscape of financial markets is akin to a single ant trying to understand the full workings of the ant colony around them. The level of complexity is well beyond the ant’s capability for comprehension.

[00:41:51] Shawn O’Malley: Whether in beehives or ant colonies, social systems in the natural world show that the collective interactions of many individuals can solve certain problems. A single honeybee cannot produce honey, nor could they even identify the best place to build a hive. Yet, in aggregate, colonies of bees are excellent at doing both.

[00:42:10] Shawn O’Malley: Without a central authority, tens of thousands of honeybees can coordinate their actions. In fact, the hive can make more intelligent decisions than any individual could. Mauboussin sees financial markets as being similar. You are the single bee fulfilling your own narrow role in the bigger picture, and collectively the system is working to efficiently price financial assets.

[00:42:31] Shawn O’Malley: What’s fascinating is how beehives have evolved to do this. Forager bees do a little dance when they return to their hives to inform others of where the food is, and the duration of those dances not only communicates the richness of the resource in question, but how potentially necessary it is for the colony, too.

[00:42:47] Shawn O’Malley: So, bees dances consider both the hive’s opportunities and needs. The result is a decentralized process where hives make the optimal resource allocation decisions, such as where to forage for food, despite no single bee determining this from the top down. We also see this in prediction markets that tap into collective knowledge.

[00:43:06] Shawn O’Malley: Betting markets tied to politics have an enviable record in predicting what percentage of the vote different candidates will capture that is typically far more reliable and predictive than any single expert’s track record. Whether you agree with the beehive analogy or not, and the power of collective knowledge, the message is really to say that other domains of knowledge can teach us about the financial world.

[00:43:27] Shawn O’Malley: If you only read financial news and listen to financial experts, you’d probably not land on considering the similarities between beehives, And financial markets as decentralized complex systems. But the natural world can teach us a ton about investing because financial markets are ultimately byproducts of human interactions and humans are the result of millions of years of evolution and coexistence with the world around us.

[00:43:49] Shawn O’Malley: For more on what evolution and the natural world can teach us about investing, I’d recommend reading the book What I Learned About Investing from Darwin by Pulak Prasad. The other main focus for this essay is on how fat tails, as statistics experts might call them, or extreme events, drive systems. That is, the world is not always defined by averages.

[00:44:10] Shawn O’Malley: The effects of extreme outliers can present chicken and egg problems, where novel extreme events like 9/11, world wars, asteroid impacts, or pandemics may seem unprecedented if only looking backward, especially if they’ve never happened before or haven’t happened in a long time, yet these extreme events can flip everything upside down.

[00:44:28] Shawn O’Malley: If you’ve read Nassim Taleb’s book, The Black Swan, you’ll be familiar with the idea that infrequent but extreme events occur more often than most people expect and are what spur dramatic changes to the status quo. Mauboussin’s insight is that markets become more vulnerable to extreme events when hurting takes place, with most investors reaching the same conclusion on a topic.

[00:44:48] Shawn O’Malley: Without a diversity of opinions, the wisdom of collective knowledge turns into the tyranny of the masses. Extreme statistical outliers and black swans are not just catastrophes though. In markets, there might be thousand to one payoff stocks like Google and Facebook that fundamentally change the world.

[00:45:04] Shawn O’Malley: Extreme outliers like these in markets raise a paradox because the price upside for stocks is theoretically infinite. The problem is known as the St. Petersburg paradox. And the hypothetical goes like this. Imagine you’re offered the chance to pay to participate in a coin flipping game where the payout doubles each time you win.

[00:45:23] Shawn O’Malley: The first payout is 2, and then 4, and then 8, and so on with each flip. It’s a paradox because the expected value is infinite. With each incremental flip, there’s a 50-50 chance of winning or losing and ending the game while the payout keeps doubling. And the question becomes, what fraction of your net worth should you be willing to pay as a fee to play the game?

[00:45:44] Shawn O’Malley: Half the time, the payoff is just 2, and 75 percent of the time, the payout is 4 or less. But with a streak of 30 in a row, the payout is 1. 1 billion, while the odds of that happening are correspondingly 1 in 1.1 billion. So, if the expected value is infinite, then you should be willing to pay everything you have to play, yet in practice, no one would do that.

[00:46:06] Shawn O’Malley: In studies, people are usually willing to bet around 20 to play. For 200 years, economists and statisticians have struggled with the paradox, and there is still no definitive solution. It’s a thought experiment that takes probabilistic thinking for investors to extremes, where logic begins to break down.

[00:46:23] Shawn O’Malley: If you believe a company is a game, truly the next Google, then there’s almost no price that you could pay today that wouldn’t be justified by that optimism, but doing so isn’t necessarily justified and the odds are stacked against you and finding the next stock to create a massive amount of wealth.

[00:46:39] Shawn O’Malley: Yet these extreme outlier returns aren’t one off flukes either. They actually seem to be a fundamental part of financial markets. From 1980 through 2006, there were nearly 2, 000 companies that IPO’d, and only 5 percent of those companies accounted for 100 percent of the more than 2 trillion in wealth that the entire group created.

[00:46:58] Shawn O’Malley: This reflects the paradox in a different way, because investors must wrestle with the reality that they can pay a small amount today for new companies, of which a handful will generate massively skewed returns. One last concept worth digging into from this essay is the clash between our brain’s desire to have a clear cause and effect description of the world around us, and the fact that as a complex adaptive system, the stock market can have emergent outcomes with no clear explanation.

[00:47:25] Shawn O’Malley: Human consciousness may be the best depiction of a complex adaptive system, where the sum of the parts is not the same as the parts in unison. If you were to break down each neuron in your brain one by one, you could not find an explanation for consciousness. Consciousness very much remains a mystery to scientists.

[00:47:42] Shawn O’Malley: Yet we know it emerges from the complex interactions between the different parts of our brains and bodies. It cannot be explained by summing up the parts that go into it. The stock market is a complex adaptive system as well. It is a phenomenon born out of its parts, but you cannot break down each of its parts to understand perfectly what has happened and will happen in markets.

[00:48:02] Shawn O’Malley: So complex adaptive systems do not always have clear cause and effect explanations. As much as we want to rationalize why the stock market went up or down 3 percent today, there is probably no specific explanation we can point to with much confidence. As a real world illustration of this, after the Black Monday crash of 1987, the U. S. government tasked a commission with determining what had caused the crisis. You’d think a more than 20 percent single day crash in stock market indexes would have a clear explanation, but it didn’t. People throw around a handful of explanations, but after months of work, the commission itself concluded that the causes were indeterminable.

[00:48:37] Shawn O’Malley: Mauboussin argues that this is unsurprising because complex adaptive systems do not owe us proportional or logical explanations. When building a sandcastle, a single grain of sand can trigger a collapse of the entire structure, but good luck trying to pinpoint which additional grain of sand it was that spurred that collapse.

[00:48:56] Shawn O’Malley: Trying to explain moves in the stock market is the same. It’s like pinpointing which grain of sand triggered the collapse. The answer is unknowable, even though most of us find that discomforting and frustrating and will cling to the first plausible explanation that we come across. We touched on a lot of different topics today as we went through Mauboussin’s essays on investment philosophy, psychology, innovation and competitive strategy, and complexity theory in markets.

[00:49:21] Shawn O’Malley: To really soak everything up, it’s a good episode to listen to twice, or you could just pick up more than you know to read for yourself. The book grew on me the more I read it. And by the end, I had a tremendous amount of respect for Mauboussin as an original thinker and for his ability to draw insights from so many different areas to help better understand financial markets.

[00:49:40] Shawn O’Malley: It’s a book that raises as many questions as it answers. The more I’ve learned about investing, the more I’ve realized how much I don’t know from the boundaries of what we understand about human nature and psychology to the St. Petersburg paradox and complex adaptive systems. Mauboussin expands on a lot of ideas that will get your brain going in new ways.

[00:49:59] Shawn O’Malley: I’ll leave you with a quote from Mauboussin reflecting on the book. He says, this book celebrates the idea that the answers to many of these questions will emerge only by thinking across disciplines.

[00:50:11] Outro: Thank you for listening to TIP. Make sure to follow Millennial Investing on your favorite podcast app and never miss out on our episodes. To access our show notes, transcripts, or courses go to theinvestorspodcast.com. This show is for entertainment purposes only before making any decision, consult a professional. This show is copyrighted by The Investor’s Podcast Network. Written permission must be granted before syndication or rebroadcasting.