More Than You Know: Financial Wisdom for Wise Investing w/ Shawn O’Malley (MI364)
Summary
Core Philosophy: Emphasizes process over outcomes and multidisciplinary thinking to navigate markets as complex adaptive systems.
Disruptive Innovation: Advocates favoring new, fast-changing industries and companies leveraging software and technology over resource-heavy incumbents.
Creative Destruction: Highlights evidence that new entrants often outperform incumbents, especially in their first five years, before advantages fade.
S-Curve Growth: Identifies two inflection points—early acceleration for opportunity and later deceleration for risk—urging focus on early winners and survivors.
Information Technology: Discusses how software-driven, knowledge-based firms command different economics and valuations versus industrial-era companies.
Key Examples: References Amazon, Google, Facebook, Tesla, and Nvidia as illustrative cases of skewed outcomes and innovation dynamics, not specific pitches.
Risks and Expectations: Warns against overreliance on historical P/E averages, stresses mean reversion in returns, and encourages expectations-based analysis.
Behavioral Factors: Notes stress, commitment, and social herding can distort decisions, reinforcing the need for logs, skepticism, and long-term orientation.
Transcript
(00:00) 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 with the point being that what ultimately matters is one's decision-making process not short-term results 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 [Music] (00:35) them on today's episode I'll be reviewing Michael Moon's excellent book more than you know if you're not familiar with him mobison is one of the top voices in the value investing space the early days of his career began under the tutelage of the great investor Bill Miller and he's gone on to become the head of credit s's Global Financial strategies team director of research at Blue Mountain Capital Chief investment strategist at leag Mason capital management and more recently he has led (01:03) Counterpoint Global's consilient research team along the way he's worked as an Adjunct professor at Columbia University for over three decades where he's taught the security analysis course written four books on investing and served as chairman of the Board of Trustees at the Santa Fe Institute more than you know is divided into four essays meant to stand by themselves and act as Tools in investors toolboxes covering investment philosophy the psychology of invest in Innovation and competitive strategy and Science and (01:33) complexity Theory I'll be going through each of the four essays summarizing them and sharing my favorite insights we'll cover topics like how the stock market is a complex adaptive system and what that means the pitfalls of using past price to earnings ratios when valuing companies why process is so important to investing what a world with increasing technological disruptions means for investors and much more with that let's get right to it to kick things off moison describes the importance of multidisciplinary thinking (02:07) which anyone who has followed Charlie Munger closely will be familiar with you also might recall my discussion of it in reviewing poor Charlie's Almanac a few weeks ago the key idea is that expertise in Academia is too often confined to specific departments psychologists talk to other psychologists and economists talk to other economists and so on but the most fertile intellectual ground lies between disciplines whereas Monger was completely self-taught and never distracted by the musings of financial academics moison credits monger's focus (02:40) on multi-disciplinary thinking for helping him unlearn much of the conventional thinking on Wall Street the most valuable Insight he's learned from taking a multi-disciplinary 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 from many parts of our body and brain interacting together so are the economy and financial markets they're systems born out of millions of daily interactions across the world according to the New (03:12) 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 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 (03:45) 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 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 your head since it's so critical to how mobison thinks about financial markets but now let's dive into Moon's first essay on investment philosophy investment philosophy is important because it dictates how you should make good decisions a sloppy (04:15) 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 many investors get started with these sort of half-baked philosophies on how they like to invest (04:47) 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 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 (05:20) beating track record helps with attracting assets but Savvy marketing and Charisma can just as easily induce investees into a fund when constructing an investment philosophy moison 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 right the occasional (05:53) big pick out the occasional big payout is 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 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 (06:25) they're skilled at least the winning Gambler will probably think they are 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 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 process that they (07:01) follow in that same vein making 50% 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 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 (07:34) 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 before recovering in Stock Investing a sound process is one that effectively identifies discrepancies between a stock current price and its expected value which is the weighted value of a range of possible outcomes (08:06) 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 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 (08:37) recurring and then adding them together 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% of options expire worthless but that doesn't mean that options aren't valuable stock options can offer considerable payoffs from unlikely events so 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 (09:11) 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 behavioral economists like Daniel Conan and Amos starki showed decades ago that the pain felt from investment losses exceeds the Joy from gain means 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 imagine a stock that has a 75% chance of (09:47) delivering on its earnings promises which should move the stock about 1% higher but it's price such that it could fall off 10% or more if the company misses earnings the odds are technically in your favor but the expected value isn't the 25% chance of missing with a 10% decline in the stock price more than offsets the smaller payoff from the most likely outcome of course no one ever spells out this information for us when investing you can never know the odds with 100% confidence but we still must act with (10:20) even imperfect information in fact too much information can introduce noise that may worsen our decision-making as investors in a study in a study on odds makers 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 even though their confidence increased significantly with more information the odds makers were only marginally better at making predictions with more information when I what I take from that is even though we (10:54) all crave more information to help with our investing decisions there's a cutoff point where 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 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 (11:27) trade frequently their annual portfolio turnover was just 35% compared to 89% for all fund managers they also tended to be much more concentrated with 35% of their assets invested in their top 10 biggest Holdings versus around 20% for the S&P 500 most of these Market beating investors according to moison subscribed to the Warren Buffett and Ben Graham School of investing where they compared stocks current prices to their assessment of intrinsic value these commonalities are not on their own what Define investment success (12:02) 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 reasoned investment process which would be an indicator of expected long-term success lowquality investment processes usually try to explain the world based on attributes alone using labels like size value and growth we call companies with low price to earnings ratios value stocks or (12:39) companies with above average revenue increases growth companies but nothing about that provides any circumstantial or actionable information 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 with no guarantee that will change with a more circumstantial approach you might find a catalyst that drives cheap stocks to become less cheap for example you may realize that when (13:11) 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 due to an attribute based Factor like relative cheapness you'd know to do so when a certain Catalyst happens like interest rates falling 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 mobison despite considering himself a (13:40) value investor Miller has invested in famous growth companies like Amazon in their early days 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 in terms (14:10) 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 it isn't much of a statistical outlier when a basketball player who (14:40) shoots 90% from the free throw line Hits 10 free throws in a row but it would be if a 50% 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 such streaks over the course of their career due to simple statistical Randomness the difference is that good Shooters can go much longer before violating probabilistic expectations so long streaks of having a (15:12) 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 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 through that lens (15:42) 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 M's second essay from the book on the psychology of investing as he puts it Understanding Psychology provides a preview into the of mistakes you're likely to make as an investor 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 (16:11) mental roadblocks that try to derail us from that process rather than throwing a bunch of Tex terms for psychological biases at you the simplest way to start is with stress 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 other 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 a zebra's stress is acute a lion (16:45) 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 groceries chores kids pets work your 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 (17:20) stress are similar which throws our bodies at a balance 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 while the pace of technological disruptions is brisk the only salvation for relieving investor stress is to turn (17:53) to the long term in Moon's opinion while stress pushes us to impulsively make decisions to 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 gations in the market price or fearmongering news stories moison 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 (18:28) 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 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 as a result there are good (19:02) 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 resist doing a 180 if the company's Outlook changes dramatically for the worse but it's it's hard to even recognize that the facts may have (19:31) 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 made up my mind on it by the end I'm ready to just 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 (19:59) continuously evaluating that investment thesis objectively you Sly Tor 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 if you really like a (20:33) 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 which is 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 disliking a company can blind you from the investment merits of being a (21:04) shareholder in it however emotion is fundamental to our decision-making process that's Moon's takeaway at least after reviewing studies on decision-making among that's Moon'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 emotions triggered subconsciously Drive conscious decisions and without emotion our decisions tend to just be worse a subconscious emotional response to (21:39) seeing a snake Spurs 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 emotions are critical to how we make decisions but they also distort our sense of objective probabilities if you see 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 bidden by a (22:09) deadly snake is more than enough to make you jump back 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 bidden 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 10,000 to one or 1 million to one because the potential outcome is so emotionally exciting the emotional response pushes them to ignore the odds (22:44) 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 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 (23:16) 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 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 subreddits devoted to single stocks have millions (23:49) 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 in that case and an entire discipline in investing is devoted to imitation momentum investors by Nature seek to profit by piling into 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 (24:23) side is that when imitation of an investment becomes too popular it leads to Bubbles 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 therefore markets mostly arrive in appropriate places except when they're all irrational in (24:54) the same way at the same time this is what panics are at the same 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 russle 3000 index of US Stocks fell more than 11% I had no idea at the time what the future would hold and how Co 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 (25:28) actually actually it was a great opportunity to take advantage of how do you get started with Stock Investing I've put together a course to teach you everything I wish I knew when I first started investing in stocks let's start at the beginning and ask what is a stock let's zoom on in into what it's actually like to buy a stock a few options are Charles Schwab TD amerit trade Ally E Trade fortunately you won't have to necessarily calculate all of these taxes yourself I'll outline a few main ones to (25:59) be aware of throughout your lifetime investing Journey as Warren Buffett says your best investment is yourself there's nothing that compares to it by the end you'll be savvier about Stock Investing in personal finance than the vast majority of people even if you're not a total beginner I'm confident you'll get a lot out of the principles and strategies I outline which will build on throughout link to the course is available in the description below see you there is among huge chunks of investors (26:29) all at once and in hindsight which is a bias of its own actually it was a great opportunity to take advantage of 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 and you cannot assess the quality of (27:02) your previous decision- making if your recollection of it is clouded by hindsight biases which is why moison 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 with without the effects of hindsight biases 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 moison studies on in the moment decision makers dealing with (27:33) crises like firefighters reveal that there is no classical Theory involved in their decision- making 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 was no time to determine the theoretically optimal way to put out a fire and save everyone's lives you must spring into action with your best Instinct the same is true in other (28:08) 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 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 (28:37) move or if they have just six seconds in a moment they can scan the board and make relatively good moves 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 instinct in similar ways they tended to think in terms of ranges of possible out outcomes using mental imagery and creating stories based on the available facts their decisions like firefighters or Chess Masters are context dependent and they're not held up by finding the (29:11) 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 sound decision- making Frameworks are needed for investment success meanwhile some experts may be so experienced or skilled that they can make highquality decisions extremely rapidly I actually don't think these two things are at odds though the true expert is one who has mastered (29:42) their decision-making Frameworks can adjust for the context and is then able to filter out the noise to make quality decisions that wraps up the second essay from the book so let's move into Moon'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 in just over a 100 years things have changed completely at (30:14) its debut the index included companies like American cotton oil American Tobacco Chicago gas distilling and cattle feeding General Electric Tennessee coal and iron us leather us rubber American sugar finding lack lead Gas Light Company National lead company and North American of these dozen Titans for their era none remain and only one 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 (30:50) acrew the greatest Market valuations 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 on to yesterday's best companies expecting them to just continue doing (31:21) well an interesting thought experiment is to consider why are 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 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 (31:55) that M silicon they're companies that have found better and better uses of that natural resource namely in computer chips and electronics 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 a little cost when a better way for doing something is to discovered (32:29) 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 and just a handful of a company's employees might have 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 things (32:58) driving more Innovation generally speaking there's an overshoot of companies in new Industries all competing for market share America once had over 2,000 car companies and over the last century that number was whittel 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 bus process mobison says that investors would be wise to look around at the end of when these printing processes to see (33:30) who has survived you could do much worse than having a portfolio of survivors who endured in 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 the first inflection point is when a new industry goes from a slow to Rapid growth and overlaps with when investors transition from underestimating future growth to overestimating by extrapolating The Accelerated growth (34:02) indefinitely the second inflection point comes as investors get burned by their now overly optimistic growth outlook for an industry 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 mobison believes that investors stay will continue to see more and more of (34:33) these s-curves than in the past as new Industries rise and fall at faster Paces 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 you may not know which company will generate the excess returns but you can be almost assured that the older (35:02) company will not in the book creative destruction Richard Foster and Sarah Kaplan show that new entrance generate higher total returns to shareholders than their older and more established competitors in a review across 30 years of thousands of companies that were in the top 80% of all stocks in terms of market capitalization and had at least 50% of their sales in the defined industry most of these excess returns came and then first 5 years while returns over the subsequent 15 years tended to be in line with industry (35:33) averages and then after 20 years the same companies usually began to underperform their peers that's because new entrance 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 company's competitive Moes is much shorter in the 21st century meaning many companies competitive advantages don't last as long as they they used to to quote Bill Gates in 1998 he said I think the multiples of (36:03) 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 saying that Innovation is shortening the lifespans of companies advantages is a big claim as evidence Mobis sites how the average lifespan of 1,800 us industrial companies assets including R&D capitalized assets has fallen from 14 years in 1975 to under 10 years (36:36) currently companies assets just don't create value for as long as they used to and today's companies must generate returns with their Assets in less time than they did a generation ago as an investor you might wonder whether you should want your companies to think more shortterm in a more Innovative world or if it's more important than ever to think long-term and see the big picture I 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 it's (37:05) 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 longterm is really just a collection of short terms no company has ever had a great 5 years despite having 20 terrible straight quarters to in invoke Charles Darwin quote it is not the strongest of the species that survives nor the most intelligent but the one most responsive (37:35) to change in a word what matters for both organisms and companies in complex systems is adaptability 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 down as happening is interesting companies can take incremental short leaps forward like process Improvement initiatives or they can take large leaps that either (38:07) 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 in new Industries or developing new types of products based on the competitive ecosystem surrounding a company 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 sleeps are small and focused on improving efficiency and fast changing Industries like biotechnology large leaps are much (38:40) likelier because companies must make them to survive 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 10 years out 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 (39:13) approvals and medical breakthroughs that happen on unknowable timelines in a business world that has more big leaps than in past decades M claims that using past data as the basis for evaluations is deeply flawed 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 70s and 80s and legislators assumed this would continue to be true (39:47) where there'd always be many more workers paying into Social Security than retirees pulling funds out of it in 1935 when the Social Security Act was first signed America had had 42 workers for every retiree thanks to longer life expectancies today that ratio is now 3 to1 the issue here is that the original designers of Social Security extrapolated past data forward expecting things to mostly remain the same based on Actuarial tables their plans to pay retirees at 65 seemed conservative at the time and financially sound they (40:22) 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 they say things like 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 moison view because pass ratios are only relevant to the degree that they capture today's circumstances in other words you're (40:53) 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 24mth returns according to research covering the last 125 years of financial data to 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 all in flux (41:28) yet each determines the valuation that markets are willing to pay for different Financial assets 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 compan companies relying on technology these all have different (42:01) 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 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 (42:34) is a really popular illustration of this where growth only compounded the company's losses and Tesla is the Counterpoint as a company that grew its way out of losses 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 (43:06) returns slowly drift back up with less competition to show the point on mean reversion credit s did an analysis of over 450 technology companies from 1979 to 1996 ranking companies in cor tiles based on their cash flow return on investments or cfroi the top group of companies earned an average of 15% at the start but those above average returns declined to just 6% after only 5 years and the worst group went from earning negative 15% returns at the start to earning 0% after 5 years as many of the worst performing (43:45) 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 pool of mean reversion in another study from 1960 to 1996 11% 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 (44:20) valuations can go even higher before becoming unjustified at the same time expectations for these high performers are 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 this leads into the bigger discipline of expectations investing which is an approach where investors try to (44:51) determine the future assumptions baked into a company's stock today like whether the company's growth will slow or accelerate whether its returns will revert to the mean Etc and determine if those expectations are realistic 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 (45:21) companies prospects compared to the price in expectations we have Management's projections for the future available to us 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 in the book profit from the core Chris zook shows his research on over 1,800 (45:52) companies across five Industries with three hurdles for them to beat at least 5.5% real inflation adjusted sales growth 5.5% 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 2third of the firms assumed double digit growth rates in their future plans yet only 25% of companies hit zook's more modest growth hurdles and only one in8 companies ticked all three boxes the vast majority of companies aim to grow (46:26) at double- digigit 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 Moon's fourth and final essay in the book and then we can try to recap everything we learned today 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 (46:59) the level of complexity is well beyond the ants capability for comprehension 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 without a central Authority tens of thousands of honey bees can coordinate their actions in fact The Hive can make more Intelligent Decisions than any (47:32) individual could mobison 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 what's fascinating is how beehives have evolved to do this forward your bees to a little dance when they return to their hives to inform others of where the food is and the duration of those dances not not only communicates the richness of the resource in question but how potentially necessary it is for the (48:02) colony too so bees dances consider both the hives 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 B determining this from the top down we also see this in prediction markets that tap into Collective knowledge betting markets tied to politics have an inviable record and in predicting what percentage of the vote different candidates will capture that is typically far more reliable and predictive than any single experts track (48:35) 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 if you only read financial news and listened 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 (49:04) of millions of years of evolution and coexistence with the world around us 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 Pac prad the other main focus for this essay is on how fat tales as statistics experts might call them or extreme events Drive systems that is the world is not always defined by averages the effects of extreme outliers can present chicken and egg problems where novel extreme events like 911 (49:39) world wars asteroid impacts or pandemics may seem unprecedented if only Looking Backward especially if they've never happened before haven't happened in a long time yet these extreme events can flip everything upside down if you've read Nim tb'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 Moon's Insight is that markets become more vulnerable to extreme events (50:08) when hurting takes place with most investors reaching the same conclusion on a topic Without A diversity of opinions the wisdom of collective knowledge turns into the tyranny of the masses extreme statistical outliers in black swans are not just catastrophes though in markets there might be thousand to one payoff stocks like Google and Facebook that fundamentally changed the world extreme outliers like these and markets raise a paradox because the price upside for stocks is theoretically infinite the problem is (50:39) 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 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 (51:12) play the game half the time the payoff is just $2 and 75% 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 one 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 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's still no definitive (51:48) solution it's a thought experiment that takes probabilistic thinking for investors to extremes where logic begins to break down if you believe a company is 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 yet these extreme outlier returns aren't one-off flukes either they actually seem (52:17) to be a fundamental part of financial markets from 1980 through 2006 there were nearly 2,000 companies that ipoed and only 5% % of those companies accounted for 100% of the more than $2 trillion do in wealth that the entire group created 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 brains desire to have a (52:54) clear cause and effect description of the world around us and the fact that as a complex adaptive system the stock market can have emerging outcomes with no clear explanation 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 yet we know it emerges from the complex interactions (53:26) 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 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% today there is probably no specific explanation we can (53:57) point to with much confidence as a real world illustration of this after the Black Monday crash of 1987 the US government tasked a commission with determining what had caused the crisis you'd think a more than 20% 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 M argues that this is unsurprising because complex adaptive systems do not owe us proportional or (54:30) logical explanations when building a sand castle 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 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 (55:03) topics today as we went through mobison essays on investment philosophy psychology Innovation and competitive strategy and complexity theory in markets 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 mobison as an original thinker and for his ability to draw insights from so many different areas to help better understand financial markets it's a book (55:34) 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 moison expands on a lot of ideas that will get your brain going in new ways I'll leave you with a quote from moison reflecting on the book he says this book celebrates the idea that the answers to many of these questions will emerge only (56:04) by thinking across disciplines when it comes to investing across a lifetime what really matters is not getting wiped out and you need a good bit of skepticism about any decision you make to avoid betting it all on something really exciting but also really risky I can imagine how many bullets Charlie probably helped Warren Dodge up until his death last year he was still bringing his signature skep ISM to all of today's most popular buzzwords from crypto to Ai and and meme stocks
More Than You Know: Financial Wisdom for Wise Investing w/ Shawn O’Malley (MI364)
Summary
Transcript
(00:00) 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 with the point being that what ultimately matters is one's decision-making process not short-term results 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 [Music] (00:35) them on today's episode I'll be reviewing Michael Moon's excellent book more than you know if you're not familiar with him mobison is one of the top voices in the value investing space the early days of his career began under the tutelage of the great investor Bill Miller and he's gone on to become the head of credit s's Global Financial strategies team director of research at Blue Mountain Capital Chief investment strategist at leag Mason capital management and more recently he has led (01:03) Counterpoint Global's consilient research team along the way he's worked as an Adjunct professor at Columbia University for over three decades where he's taught the security analysis course written four books on investing and served as chairman of the Board of Trustees at the Santa Fe Institute more than you know is divided into four essays meant to stand by themselves and act as Tools in investors toolboxes covering investment philosophy the psychology of invest in Innovation and competitive strategy and Science and (01:33) complexity Theory I'll be going through each of the four essays summarizing them and sharing my favorite insights we'll cover topics like how the stock market is a complex adaptive system and what that means the pitfalls of using past price to earnings ratios when valuing companies why process is so important to investing what a world with increasing technological disruptions means for investors and much more with that let's get right to it to kick things off moison describes the importance of multidisciplinary thinking (02:07) which anyone who has followed Charlie Munger closely will be familiar with you also might recall my discussion of it in reviewing poor Charlie's Almanac a few weeks ago the key idea is that expertise in Academia is too often confined to specific departments psychologists talk to other psychologists and economists talk to other economists and so on but the most fertile intellectual ground lies between disciplines whereas Monger was completely self-taught and never distracted by the musings of financial academics moison credits monger's focus (02:40) on multi-disciplinary thinking for helping him unlearn much of the conventional thinking on Wall Street the most valuable Insight he's learned from taking a multi-disciplinary 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 from many parts of our body and brain interacting together so are the economy and financial markets they're systems born out of millions of daily interactions across the world according to the New (03:12) 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 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 (03:45) 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 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 your head since it's so critical to how mobison thinks about financial markets but now let's dive into Moon's first essay on investment philosophy investment philosophy is important because it dictates how you should make good decisions a sloppy (04:15) 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 many investors get started with these sort of half-baked philosophies on how they like to invest (04:47) 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 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 (05:20) beating track record helps with attracting assets but Savvy marketing and Charisma can just as easily induce investees into a fund when constructing an investment philosophy moison 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 right the occasional (05:53) big pick out the occasional big payout is 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 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 (06:25) they're skilled at least the winning Gambler will probably think they are 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 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 process that they (07:01) follow in that same vein making 50% 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 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 (07:34) 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 before recovering in Stock Investing a sound process is one that effectively identifies discrepancies between a stock current price and its expected value which is the weighted value of a range of possible outcomes (08:06) 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 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 (08:37) recurring and then adding them together 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% of options expire worthless but that doesn't mean that options aren't valuable stock options can offer considerable payoffs from unlikely events so 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 (09:11) 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 behavioral economists like Daniel Conan and Amos starki showed decades ago that the pain felt from investment losses exceeds the Joy from gain means 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 imagine a stock that has a 75% chance of (09:47) delivering on its earnings promises which should move the stock about 1% higher but it's price such that it could fall off 10% or more if the company misses earnings the odds are technically in your favor but the expected value isn't the 25% chance of missing with a 10% decline in the stock price more than offsets the smaller payoff from the most likely outcome of course no one ever spells out this information for us when investing you can never know the odds with 100% confidence but we still must act with (10:20) even imperfect information in fact too much information can introduce noise that may worsen our decision-making as investors in a study in a study on odds makers 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 even though their confidence increased significantly with more information the odds makers were only marginally better at making predictions with more information when I what I take from that is even though we (10:54) all crave more information to help with our investing decisions there's a cutoff point where 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 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 (11:27) trade frequently their annual portfolio turnover was just 35% compared to 89% for all fund managers they also tended to be much more concentrated with 35% of their assets invested in their top 10 biggest Holdings versus around 20% for the S&P 500 most of these Market beating investors according to moison subscribed to the Warren Buffett and Ben Graham School of investing where they compared stocks current prices to their assessment of intrinsic value these commonalities are not on their own what Define investment success (12:02) 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 reasoned investment process which would be an indicator of expected long-term success lowquality investment processes usually try to explain the world based on attributes alone using labels like size value and growth we call companies with low price to earnings ratios value stocks or (12:39) companies with above average revenue increases growth companies but nothing about that provides any circumstantial or actionable information 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 with no guarantee that will change with a more circumstantial approach you might find a catalyst that drives cheap stocks to become less cheap for example you may realize that when (13:11) 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 due to an attribute based Factor like relative cheapness you'd know to do so when a certain Catalyst happens like interest rates falling 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 mobison despite considering himself a (13:40) value investor Miller has invested in famous growth companies like Amazon in their early days 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 in terms (14:10) 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 it isn't much of a statistical outlier when a basketball player who (14:40) shoots 90% from the free throw line Hits 10 free throws in a row but it would be if a 50% 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 such streaks over the course of their career due to simple statistical Randomness the difference is that good Shooters can go much longer before violating probabilistic expectations so long streaks of having a (15:12) 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 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 through that lens (15:42) 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 M's second essay from the book on the psychology of investing as he puts it Understanding Psychology provides a preview into the of mistakes you're likely to make as an investor 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 (16:11) mental roadblocks that try to derail us from that process rather than throwing a bunch of Tex terms for psychological biases at you the simplest way to start is with stress 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 other 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 a zebra's stress is acute a lion (16:45) 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 groceries chores kids pets work your 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 (17:20) stress are similar which throws our bodies at a balance 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 while the pace of technological disruptions is brisk the only salvation for relieving investor stress is to turn (17:53) to the long term in Moon's opinion while stress pushes us to impulsively make decisions to 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 gations in the market price or fearmongering news stories moison 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 (18:28) 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 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 as a result there are good (19:02) 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 resist doing a 180 if the company's Outlook changes dramatically for the worse but it's it's hard to even recognize that the facts may have (19:31) 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 made up my mind on it by the end I'm ready to just 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 (19:59) continuously evaluating that investment thesis objectively you Sly Tor 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 if you really like a (20:33) 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 which is 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 disliking a company can blind you from the investment merits of being a (21:04) shareholder in it however emotion is fundamental to our decision-making process that's Moon's takeaway at least after reviewing studies on decision-making among that's Moon'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 emotions triggered subconsciously Drive conscious decisions and without emotion our decisions tend to just be worse a subconscious emotional response to (21:39) seeing a snake Spurs 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 emotions are critical to how we make decisions but they also distort our sense of objective probabilities if you see 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 bidden by a (22:09) deadly snake is more than enough to make you jump back 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 bidden 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 10,000 to one or 1 million to one because the potential outcome is so emotionally exciting the emotional response pushes them to ignore the odds (22:44) 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 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 (23:16) 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 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 subreddits devoted to single stocks have millions (23:49) 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 in that case and an entire discipline in investing is devoted to imitation momentum investors by Nature seek to profit by piling into 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 (24:23) side is that when imitation of an investment becomes too popular it leads to Bubbles 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 therefore markets mostly arrive in appropriate places except when they're all irrational in (24:54) the same way at the same time this is what panics are at the same 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 russle 3000 index of US Stocks fell more than 11% I had no idea at the time what the future would hold and how Co 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 (25:28) actually actually it was a great opportunity to take advantage of how do you get started with Stock Investing I've put together a course to teach you everything I wish I knew when I first started investing in stocks let's start at the beginning and ask what is a stock let's zoom on in into what it's actually like to buy a stock a few options are Charles Schwab TD amerit trade Ally E Trade fortunately you won't have to necessarily calculate all of these taxes yourself I'll outline a few main ones to (25:59) be aware of throughout your lifetime investing Journey as Warren Buffett says your best investment is yourself there's nothing that compares to it by the end you'll be savvier about Stock Investing in personal finance than the vast majority of people even if you're not a total beginner I'm confident you'll get a lot out of the principles and strategies I outline which will build on throughout link to the course is available in the description below see you there is among huge chunks of investors (26:29) all at once and in hindsight which is a bias of its own actually it was a great opportunity to take advantage of 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 and you cannot assess the quality of (27:02) your previous decision- making if your recollection of it is clouded by hindsight biases which is why moison 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 with without the effects of hindsight biases 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 moison studies on in the moment decision makers dealing with (27:33) crises like firefighters reveal that there is no classical Theory involved in their decision- making 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 was no time to determine the theoretically optimal way to put out a fire and save everyone's lives you must spring into action with your best Instinct the same is true in other (28:08) 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 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 (28:37) move or if they have just six seconds in a moment they can scan the board and make relatively good moves 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 instinct in similar ways they tended to think in terms of ranges of possible out outcomes using mental imagery and creating stories based on the available facts their decisions like firefighters or Chess Masters are context dependent and they're not held up by finding the (29:11) 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 sound decision- making Frameworks are needed for investment success meanwhile some experts may be so experienced or skilled that they can make highquality decisions extremely rapidly I actually don't think these two things are at odds though the true expert is one who has mastered (29:42) their decision-making Frameworks can adjust for the context and is then able to filter out the noise to make quality decisions that wraps up the second essay from the book so let's move into Moon'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 in just over a 100 years things have changed completely at (30:14) its debut the index included companies like American cotton oil American Tobacco Chicago gas distilling and cattle feeding General Electric Tennessee coal and iron us leather us rubber American sugar finding lack lead Gas Light Company National lead company and North American of these dozen Titans for their era none remain and only one 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 (30:50) acrew the greatest Market valuations 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 on to yesterday's best companies expecting them to just continue doing (31:21) well an interesting thought experiment is to consider why are 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 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 (31:55) that M silicon they're companies that have found better and better uses of that natural resource namely in computer chips and electronics 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 a little cost when a better way for doing something is to discovered (32:29) 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 and just a handful of a company's employees might have 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 things (32:58) driving more Innovation generally speaking there's an overshoot of companies in new Industries all competing for market share America once had over 2,000 car companies and over the last century that number was whittel 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 bus process mobison says that investors would be wise to look around at the end of when these printing processes to see (33:30) who has survived you could do much worse than having a portfolio of survivors who endured in 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 the first inflection point is when a new industry goes from a slow to Rapid growth and overlaps with when investors transition from underestimating future growth to overestimating by extrapolating The Accelerated growth (34:02) indefinitely the second inflection point comes as investors get burned by their now overly optimistic growth outlook for an industry 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 mobison believes that investors stay will continue to see more and more of (34:33) these s-curves than in the past as new Industries rise and fall at faster Paces 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 you may not know which company will generate the excess returns but you can be almost assured that the older (35:02) company will not in the book creative destruction Richard Foster and Sarah Kaplan show that new entrance generate higher total returns to shareholders than their older and more established competitors in a review across 30 years of thousands of companies that were in the top 80% of all stocks in terms of market capitalization and had at least 50% of their sales in the defined industry most of these excess returns came and then first 5 years while returns over the subsequent 15 years tended to be in line with industry (35:33) averages and then after 20 years the same companies usually began to underperform their peers that's because new entrance 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 company's competitive Moes is much shorter in the 21st century meaning many companies competitive advantages don't last as long as they they used to to quote Bill Gates in 1998 he said I think the multiples of (36:03) 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 saying that Innovation is shortening the lifespans of companies advantages is a big claim as evidence Mobis sites how the average lifespan of 1,800 us industrial companies assets including R&D capitalized assets has fallen from 14 years in 1975 to under 10 years (36:36) currently companies assets just don't create value for as long as they used to and today's companies must generate returns with their Assets in less time than they did a generation ago as an investor you might wonder whether you should want your companies to think more shortterm in a more Innovative world or if it's more important than ever to think long-term and see the big picture I 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 it's (37:05) 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 longterm is really just a collection of short terms no company has ever had a great 5 years despite having 20 terrible straight quarters to in invoke Charles Darwin quote it is not the strongest of the species that survives nor the most intelligent but the one most responsive (37:35) to change in a word what matters for both organisms and companies in complex systems is adaptability 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 down as happening is interesting companies can take incremental short leaps forward like process Improvement initiatives or they can take large leaps that either (38:07) 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 in new Industries or developing new types of products based on the competitive ecosystem surrounding a company 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 sleeps are small and focused on improving efficiency and fast changing Industries like biotechnology large leaps are much (38:40) likelier because companies must make them to survive 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 10 years out 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 (39:13) approvals and medical breakthroughs that happen on unknowable timelines in a business world that has more big leaps than in past decades M claims that using past data as the basis for evaluations is deeply flawed 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 70s and 80s and legislators assumed this would continue to be true (39:47) where there'd always be many more workers paying into Social Security than retirees pulling funds out of it in 1935 when the Social Security Act was first signed America had had 42 workers for every retiree thanks to longer life expectancies today that ratio is now 3 to1 the issue here is that the original designers of Social Security extrapolated past data forward expecting things to mostly remain the same based on Actuarial tables their plans to pay retirees at 65 seemed conservative at the time and financially sound they (40:22) 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 they say things like 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 moison view because pass ratios are only relevant to the degree that they capture today's circumstances in other words you're (40:53) 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 24mth returns according to research covering the last 125 years of financial data to 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 all in flux (41:28) yet each determines the valuation that markets are willing to pay for different Financial assets 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 compan companies relying on technology these all have different (42:01) 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 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 (42:34) is a really popular illustration of this where growth only compounded the company's losses and Tesla is the Counterpoint as a company that grew its way out of losses 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 (43:06) returns slowly drift back up with less competition to show the point on mean reversion credit s did an analysis of over 450 technology companies from 1979 to 1996 ranking companies in cor tiles based on their cash flow return on investments or cfroi the top group of companies earned an average of 15% at the start but those above average returns declined to just 6% after only 5 years and the worst group went from earning negative 15% returns at the start to earning 0% after 5 years as many of the worst performing (43:45) 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 pool of mean reversion in another study from 1960 to 1996 11% 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 (44:20) valuations can go even higher before becoming unjustified at the same time expectations for these high performers are 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 this leads into the bigger discipline of expectations investing which is an approach where investors try to (44:51) determine the future assumptions baked into a company's stock today like whether the company's growth will slow or accelerate whether its returns will revert to the mean Etc and determine if those expectations are realistic 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 (45:21) companies prospects compared to the price in expectations we have Management's projections for the future available to us 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 in the book profit from the core Chris zook shows his research on over 1,800 (45:52) companies across five Industries with three hurdles for them to beat at least 5.5% real inflation adjusted sales growth 5.5% 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 2third of the firms assumed double digit growth rates in their future plans yet only 25% of companies hit zook's more modest growth hurdles and only one in8 companies ticked all three boxes the vast majority of companies aim to grow (46:26) at double- digigit 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 Moon's fourth and final essay in the book and then we can try to recap everything we learned today 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 (46:59) the level of complexity is well beyond the ants capability for comprehension 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 without a central Authority tens of thousands of honey bees can coordinate their actions in fact The Hive can make more Intelligent Decisions than any (47:32) individual could mobison 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 what's fascinating is how beehives have evolved to do this forward your bees to a little dance when they return to their hives to inform others of where the food is and the duration of those dances not not only communicates the richness of the resource in question but how potentially necessary it is for the (48:02) colony too so bees dances consider both the hives 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 B determining this from the top down we also see this in prediction markets that tap into Collective knowledge betting markets tied to politics have an inviable record and in predicting what percentage of the vote different candidates will capture that is typically far more reliable and predictive than any single experts track (48:35) 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 if you only read financial news and listened 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 (49:04) of millions of years of evolution and coexistence with the world around us 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 Pac prad the other main focus for this essay is on how fat tales as statistics experts might call them or extreme events Drive systems that is the world is not always defined by averages the effects of extreme outliers can present chicken and egg problems where novel extreme events like 911 (49:39) world wars asteroid impacts or pandemics may seem unprecedented if only Looking Backward especially if they've never happened before haven't happened in a long time yet these extreme events can flip everything upside down if you've read Nim tb'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 Moon's Insight is that markets become more vulnerable to extreme events (50:08) when hurting takes place with most investors reaching the same conclusion on a topic Without A diversity of opinions the wisdom of collective knowledge turns into the tyranny of the masses extreme statistical outliers in black swans are not just catastrophes though in markets there might be thousand to one payoff stocks like Google and Facebook that fundamentally changed the world extreme outliers like these and markets raise a paradox because the price upside for stocks is theoretically infinite the problem is (50:39) 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 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 (51:12) play the game half the time the payoff is just $2 and 75% 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 one 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 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's still no definitive (51:48) solution it's a thought experiment that takes probabilistic thinking for investors to extremes where logic begins to break down if you believe a company is 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 yet these extreme outlier returns aren't one-off flukes either they actually seem (52:17) to be a fundamental part of financial markets from 1980 through 2006 there were nearly 2,000 companies that ipoed and only 5% % of those companies accounted for 100% of the more than $2 trillion do in wealth that the entire group created 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 brains desire to have a (52:54) clear cause and effect description of the world around us and the fact that as a complex adaptive system the stock market can have emerging outcomes with no clear explanation 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 yet we know it emerges from the complex interactions (53:26) 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 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% today there is probably no specific explanation we can (53:57) point to with much confidence as a real world illustration of this after the Black Monday crash of 1987 the US government tasked a commission with determining what had caused the crisis you'd think a more than 20% 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 M argues that this is unsurprising because complex adaptive systems do not owe us proportional or (54:30) logical explanations when building a sand castle 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 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 (55:03) topics today as we went through mobison essays on investment philosophy psychology Innovation and competitive strategy and complexity theory in markets 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 mobison as an original thinker and for his ability to draw insights from so many different areas to help better understand financial markets it's a book (55:34) 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 moison expands on a lot of ideas that will get your brain going in new ways I'll leave you with a quote from moison reflecting on the book he says this book celebrates the idea that the answers to many of these questions will emerge only (56:04) by thinking across disciplines when it comes to investing across a lifetime what really matters is not getting wiped out and you need a good bit of skepticism about any decision you make to avoid betting it all on something really exciting but also really risky I can imagine how many bullets Charlie probably helped Warren Dodge up until his death last year he was still bringing his signature skep ISM to all of today's most popular buzzwords from crypto to Ai and and meme stocks