
Kyle breaks down Michael Mauboussin’s best ideas on noise, valuation, the rule of 40, algorithms, and base rates.
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You're listening to tip. Today's episode is a deep dive into some of the most compelling insights from Michael Mauboussin's work from writing the Concilian observer for those who might not be familiar, Mauboussin is a highly respected mind in investing, known for his rigorous and innovative approach to decision making, forecasting, capital allocation, and many other essential investing concepts. Today I'll be breaking down key concepts from several of his Consilian observer articles focusing on how investors can improve their judgment, reduce noise, improve their decision making, challenge commonly held investing myths, and a lot more. Some of the biggest key takeaways include things such as how to use the BIN framework to combat forecasting errors. We'll explore how bias, information and noise distort our thinking and a few simple tools to strengthen your decision making and just cut through the noise. We'll look at how we can utilize checklists and algorithms to improve systemic decision making. We'll examine why traditional valuation metrics like price to earnings metrics and EV to EBITDA ratios are not as helpful as they once were. These evaluation metrics have been go to tools for investors, but some key concepts need to be considered when comparing businesses. We'll look at why short termism, dividends, money losing businesses and the rise of indexes might not exactly be what they seem. Mosen does a fantastic job explaining some of these market myths. We'll go over the rare nature of a business's success and how investors can position themselves accordingly. We'll look at some of the enduring traits of long term winners to hopefully help you spot them in the future. I'll also examine how investors can avoid common pitfalls by focusing on capital efficiency, moats and the right qualitative and quantitative data points rather than just following surface level metrics. If you're serious about improving your investing game and want to improve your thinking process by limiting biases, you won't want to miss this one. Now let's jump right into this week's episode.
Since 2014 and through more than 180 million downloads, we've studied the financial markets and read the books that influence self made billionaires the most. We keep you informed and prepared for the unexpected. Now for your host, Kyle Grieve.
Welcome to the Investors Podcast. I'm your host Kyle Grieve and today I'm coming to you solo, discussing a series of fascinating investing concepts that were highlighted in a few of Michael Mauboussin's articles from the Consilient Observer. Now I've been reading Michael J. Maubouson articles for a few years now, and every time he drops a new one, I feel like my mind is just being blown. So today we're going to cover a few of my favorite ideas from a few hand picked articles that he's written over the years. Now, I also want to mention that nearly all of his articles are co authored by Dan Callahan, but for the sake of simplicity, I'll be referring only to Michael Mauboussin in this episode. I'll get links to each article in the show notes as well if you want to dive further into any of these ideas. So the first one I want to cover is based on a simple acronym that he created that helps us think better by reducing the sources of forecasting errors. The acronym here is going to be BIN B I N. So B stands for bias, I for information, and N for noise. As the article states, noise is the most important factor of these three. So I'm going to go ahead and cover that one first. So he actually has a calculation for noise, which is interesting because I never even thought that that was possible. But what that calculation does is basically shows the difference between the number of a sample divided by the average. So just give you a quick example here. Let's say we have two accountants and they're both looking at someone's tax return. And let's say they both come up with a different number for how much that person owes in taxes. So let's say one of them comes up with $10,000 in taxes and the other one says they owe $14,000 in taxes. So noise would be 14,000 minus 10,000, which comes to 4,000. And we divide that by the average, which is 12,000. So in this example, the noise index produces a number around 33%. So his first point on noise is that many, many of the judgments made by professionals are highly, highly variable. So he writes about an example where kind of piggybacking on this whole tax return thing, they actually reach out to 50 different accountants and asked them to calculate the taxes of a family of four with an income of about $132,000. Now, the answers here varied quite heavily from $10,000 to $21,000. The noise index on this was over 20%, which is considered quite bad. So kind of the number that you're generally looking for that's normal is 10%. Now, how does this matter to investing? I think it matters a lot because the market is essentially a gigantic noise device. You have market participants telling the market what they think a stock is worth, but there can Also be a lot of variability. Of course, in that number, you just look at a large cap and you look at their low and they're high over 52 weeks, you'll notice that it varies quite considerably. And since there are so many people out there trying to tell you how much something is worth, there's clearly going to be a lot of variability. And I think that's the opportunity set for a lot of investors out there. You can take advantage of that variability when sentiment is down. But I don't want to go over that as much here as I want to go over how we can try to attempt to reduce noise to improve your decision making. Michael covers three primary techniques here that can be used for reducing noise. So the first one here is to combine judgments. When we combine judgments, we're attempting to gather forecasts from individuals who are operating independently. This helps reduce errors by offsetting non systematic individual errors. Now this kind of brings to mind Ray Dalio's point on how important it is to utilize other people's strengths if specifically when their strengths are our weaknesses. Since investing is largely a solo endeavor, we can get caught up just talking to ourselves and overlook some of our weaknesses or overlook points where we need to probably spend more time on. And I think Ray Dalio's points here on finding people who accentuate our weaknesses is really intelligent if you have that ability to do that. So if you're able to find independent opinions on the matters that you're trying to learn about, I think we just improve our odds of coming to a better decision. Now the point here as well on being independent is quite strong. This is why asking people with diverse backgrounds and incentives, I think can be really, really useful. You want to try to reduce any biases that these people might have about whatever you're asking them by learning from people who thinking independently. So, you know, I talk about learning from people, especially in the Tip Mastermind community. We lean on, on giving our ideas out and hopefully getting some feedback. And obviously a lot of the people that we're talking to don't own the stock, which is great because that way I'm getting feedback from people that don't own it, asking really, really good questions, asking or telling me why maybe they wouldn't want to own it. And I think that's a really, really good way of getting a nice diverse persp on whether that's a stock idea or just a investing strategy. The second one here is to use algorithms. In this case, an algorithm is a set of rules for performing a task. So this is super powerful because there's really good evidence that using algorithms actually outperforms experts in a lot of different domains. If you're wondering what an algorithm is in the investing lens, it would be something as simple as, you know, using a checklist, for instance. But the article points out that a checklist specifically helps ensure thoroughness and consistency. Now, I personally am a user of checklists, and I completely agree with this sentiment. So if you have a checklist, it can be useful for a number of reasons that I want to share with you here. So, you know, the first one here, it forces you to research things that you might not find as interesting, but will definitely have a large impact on the riskiness of an investment. You know, that might be things like looking at a manager's past history and trying to find out how successful they were in the past. Or, you know, if you're looking at a business going back, say, five, 10 years, trying to see what they were trying to do back then and look to the present day and see if they actually succeeded on those things, I think that's a really, really powerful tool to use, but it's obviously time consuming. The second one here is it illuminates areas of the business that you need to learn more about. That's pretty obvious. I think what you can do with a checklist is just insert items where you've made errors in the past. I just put them in a checklist so that you automatically focus on what those possible errors are in the future and you hopefully don't make them again. The third one is it helps build conviction if you can honestly explain each of your answers on the checklist questions. So what I like to do, you know, sometimes I'll buy business. I won't fill out the entire checklist before I, you know, make a starter position. But I think that going through a checklist is really good because it helps you kind of honestly admit to yourself how much you really understand the business. And if you come to a point where maybe you're not enjoying filling the checklist out, or there's just way too many questions that you can't answer, well, then that's probably a good signal that either the business isn't right for you or you need to do a lot more work and you have to figure out if you're willing to do that or not. And the final one here is that it just helps you do the work that few others are willing to do, which I think helps give you a variant perception. If you are able to see a stock in a different light than the whole investing community is. Well, if you're right, then that means you're probably getting it for a pretty good price and hopefully other people will see what you see over a period of time, and it'll re rate and it'll continue growing and, you know, you can make really good returns that way. So that's it for the checklist. So the third tool here that I want to go over is something that he calls the mediating assessment protocol map. So he says to adopt this map. So MAP is broken down into three distinct parts. The first is to define the attributes that you use to assess something. The second is gathering and evaluating each criterion. And the third is to make a decision based on the assessments and the scoring that you've done. So let's apply this to selecting a stock. We first would figure out which attributes we need to use to assess the business, of course. So we might look at things such as, you know, growth, margins, financial health of the business, capital efficiency, insider ownership, the talent of management. And finally, we look at things like evaluation and evaluation metrics. And maybe for those who like running discounted cash flows, you might run one of those as well. And next we would look at factual, objective data on each criterion. So luckily, this is kind of easy to do with all the technology we have available to us. We can have different attributes that we check for every single company. And then you can grade each attribute on, say, a scale of 1 to 5 or 1 to 10 or whatever you want to use. If you want to use an Alphabet system, that would also work as well. Lastly, we can add up our grade to get a final number and decide if the number makes the cut or not. This is interesting because it also removes a lot of qualitative parts of investing out of the equation. This protocol would be excellent, definitely, for a quant or if you're using, you know, a lot of quantitative metrics to screen for stocks requiring additional qualitative analysis, maybe on the side. Now, I admittedly don't use this method very much other than ranking, you know, a business's moat, which is kind of a subjective ranking, but I still put a numerical value on that. So I think I'm probably breaking a lot of the rules here. So let's look at the next most important letter in the bin acronym, which is B for bias. So the tool discussed for combating bias that I like the most was incorporating base rates into your forecasting. It is common for forecasts to be too optimistic, whether it's the cost and time to remodel a home, how long it will take to complete a task, or the growth rate of a company. Introducing base rates often tempers and grounds an estimate. Now, when we try and forecast things, we generally use our own experience and views, and this is referred to as the inside view. According to Mauboussin, this is how we default on our forecasting. But is there a better way? Mobison thinks there is, and he calls it the outside view. The outside view asks what happened before when other people were trying to solve the same problem that I'm or you are trying to solve right now? Let's go over an example here. For instance, most people think they're better stock pickers than average. Now this should mean that stock pickers think they should be able to equal or exceed the returns offered by the index. But according to research by Dalbar, the average retail investor earned 2.6% annualized returns in over a decade ending in 2013. And you know, I haven't seen an update to this, but I highly doubt the results probably have changed that much since this date. And I don't think I need to remind you that the index has done much better than the base rates of retail investors. So the final tool I want to go over covers both biases and information, and that is the use of what he calls signposts. I know that Michael Mobisen and Annie Duke are friends, so my guess is they may have independently come to some pretty similar ideas. Signposts reminds me a lot of Annie Duke's kill criteria, which I covered extensively in tip 623. So if you like this idea of signposts, I would highly recommend listening to that episode. So Mauboussin suggests the use of signposts to reduce the noise of feedback. In the short term, investors can refine their decision making by identifying key signposts, which are specific, measurable events that indicate that their thesis is on track. Successful investors often hold a variant perception, which is a view that differs from the consensus. This view can further be broken down into smaller, specific numerical assumptions. It might be something like revenue growth, profit margins, and share repurchases. The most effective signposts should be objective, time bound, and relevant to your investment thesis. Extra points if you assign numerical probabilities to these signposts. A problem you may run into when using them is relying on vague languaging. Vagueness just doesn't help determine if you're moving closer or further away from a desired destination. There was a member in the TIP Mastermind community who wanted to use something Similar to signposts to help improve decision making. He wanted to use them to try and determine if management was making the best decisions with shareholders in mind. Now, while I completely agree that, I also want to understand this, it can be really, really difficult to create signposts based on, you know, kind of these more subjective opinions that you'd have on management. So my suggestions were to figure out what quantifiable metrics the business could show that would back up the fact that management was adding value. Maybe that's that the management, you know, is increasing EPS by x percentage over the previous year, or perhaps they're, you know, expanding profit margins. It's, it's your job to pick whatever is the most relevant to the forecasting that you're trying to accomplish. Let's now transition to myths that tend to be prevalent in the world of investing. So Mauboussin gave a talk to the Greenwich roundtable back in 2020 where he described four myths and they were summarized here in an article. So the four myths were number one, the deleterious effects of short termism. Number two, the role that dividends play in equity returns. Number three, the myth of investing in money losing businesses being a bad idea. And number four, the myth associated with the rising index popularity among active managers. I really enjoyed these myths because I felt nearly all of them were pretty hot takes. And I think he delivered a lot of great evidence to support his theses. The first point deals with investors assumptions that the market is focused primarily on the short term. He makes a point that the market has tended towards getting more and more expensive and higher evaluations mean the market is paying up for cash flows many years into the future, which further supports that the market is actually long term oriented. He mentions an experiment he does with his students. I take five stocks from the Dow Jones Industrial Average and calculate the present value of the dividends that they're expected to pay over the next five years. According to estimates by value line, that value represents only about 11% of the prevailing equity value, which means that more than 90% is for cash flows beyond five years. Now, assuming buybacks are as large as dividends and you still only get to about 20%, in other words, most of the value is reflected in long term cash flows. He has a graph in the article where he just looks at five businesses which were Amex, Coca Cola, Merck, Microsoft and Proctor and Gamble. The percentage of share value beyond five years is actually 89%, meaning the market is looking at long term value of these businesses when making their investing decisions. Another point he makes, his regard to turnover. Yes, turnover has gone up overall since the 1950s, but he actually makes a point that transaction costs have obviously changed dramatically over time as well. So this is insane. In 1975, 10,000 shares of a $40 stock would cost about $4,300 to just transact, which is crazy. Nobody pays anywhere, you know, even close to that today, which I think has obviously brought turnover up pretty substantially because it's a lot easier now to buy and sell stocks and cheaper. Surprisingly, however, turnover is actually down over the last 20 years. So he had this chart by the Bogle Financial Markets Research center showing a gradual shift downward from the peak around 1985. Turnover is now around levels not seen since the mid-1970s. This is an interesting myth because my mind typically actually would agree with the premise of the myth. The market seems to me to be mainly focused on the short term. The average investor, in my eyes, is someone who often rides momentum, hold stocks maybe for just a few quarters, tend to sell the winners too fast, and unfortunately holds their losers for too long. So to me, these attributes are those of investors who tend to focus more on the short term. But his data is compelling, especially the decreased turnover point. I wonder if that's being caused by increased passive investing in indexes while active investors keep the turnover obviously a little bit higher. I'm not sure what the answer is to that question. So the next myth involves total shareholder returns and dividends. So the myth here is that dividends play a significant role in equity returns over time. Maubousin contends that price appreciation is the only investment return source that increases accumulated capital. Now, it's quite clear that dividends do play a role in returns, but they do so in a way that most investors don't fully understand. So here's how it works. So when people look at total shareholder return, which I'll Refer here as TSR, let's say of an index like the S&P 500 that I think you're probably familiar with, they assume that they're going to earn those historical returns based off of the tsr. But the problem is that very few investors actually earn the tsr. The reason for this is that dividends are required to be reinvested in order to maximize tsr. And if investors use their dividends as things like income to do things like pay bills, go on vacation, buy real estate, buy expensive trinkets, they're clearly going to be lowering their their TSR on top of that. Even if you do reinvest dividends manually into a stock or an index. There's also transaction fees, and these transaction fees are obviously going to reduce how much dividends are being reinvested. The only way of getting around this is to use a dividend reinvestment plan and have zero taxes. Now it's easy to get a drip. You can do it, set it up pretty easily with your brokerage. The zero taxes part is obviously an advantage you only get if your capital's in these tax sheltered accounts. If you look at TSR for an index fund, you're only going to make that if you meet the parameters that I just mentioned, which are of course very difficult for most investors to do. As a lot of them, especially if you're living off your portfolio, you're going to obviously be using dividends as income, so you're not going to end up earning the tsr. Another part of this myth is that dividends are the main driver of investment performance. So Mauboussin states that this is actually incorrect. Price appreciation is the only source of investment returns that increase accumulated capital. Now let's go over this because I actually kind of found this part a little confusing, but bear with me here. So Mobison writes, to understand this, let's slow down the process. Let's say you have $100 stock that pays a $3 dividend. The day that dividend is paid, you have a stock worth $97.00 and a dividend worth $3.00. The stock is actually marked down on the ex dividend date. You earn the total shareholder return only if you reinvest the full $3 into the stock to restore your investment to $100. From there, it is clear that price appreciation is the driver of accumulated wealth. Now the point here is further evidence of of course, the first point. In order to maximize your returns, 100% of dividends must be invested back into the stock. Otherwise your returns will lag that of the stock or index in question. This is a very important point for investors out there who I think are looking to derive income from their investments. If you're attempting to make a specific return on your portfolio, you'll need to adjust downwards if you are collecting dividend income that you intend to use. If you're like me and not collecting an income from your stock portfolio, obviously this isn't as much of a worry and you don't need to make adjustments. But if you are collecting dividends while still working and don't require to use them, then I would make sure you set up a drip and of course try to set up those in accounts where you're tax sheltered. Let's take a quick break and hear from today's sponsors. 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All right, back to the show. The third myth here is incredibly fascinating to me. It's the notion that investing in money losing companies is a bad idea. And investing exclusively in businesses that make money has been the bedrock of my investing strategy. So I very much enjoyed learning about this myth. But once you read more about what Michael was trying to say, it makes a lot more sense, especially in light of Adam Cecil's book Where the Money Is so Mauboussin's main point is that businesses need to be broken down on an individual basis because a business's value can be hidden by traditional accounting methods. He poses a hypothetical in the article. If he offered you shares in a business that just IPO'd on the new York Stock Exchange and told you with 100% certainty that it would have negative free cash flow for the next 15 years, would you buy it? He points out that Walmart was a business that went about 15 years without generating any free cash flow and yet had a total shareholder return of 33% versus the S P 500's 11 over that time span. Mobison points out that Walmart was just such a good performing stock simply because it earned really high returns on investment. And since they knew that investing back into the business was such a lucrative opportunity, they did just that. They opened new stores, they knew that it was lucrative, so they reinvested all profits and took on additional debt to continue growing. This made the business look kind of poor though on its financial statements, but it delivered massive amounts of value, of course, to its shareholders. Moses points out that in 1977 tangible investments was about two times that of intangible investments. And if you look today, intangible investments are actually now 1.5 times tangible investments. So tangible investments appear on the balance sheet while intangible assets appear on the income statement as an expense. Since many great businesses are capital light, they're investing heavily into their business. But this investment is going to be an intangible investments and this forces their expenses according to go on the income statement, which kind of punishes their profitability. And obviously this can hide some of the value that some of these businesses were able to create because of this, there's many tech businesses that might look ugly or really expensive. According to GAAP numbers, GAP stands here for Generally Accepted Accounting Principles. Clay and I covered AppFolio on TIP698 and in that episode we shared that much of AppFolio's reinvested earnings were going back into R and D, so this decreases their income, making their price to earnings ratio look artificially inflated. When you add back R and D multiple drops quite considerably and that adjusted number is a better representation of the economic reality of the business. Other businesses that I think require this type of adjustments are something like a Constellation Software, Topicus and Lumine Group. In Mark Leonard's Constellation Software Letters, he mentions that they internally use adjusted net income. So he wrote, the most significant variation from GAAP net income is that we assume our intangible assets are not diminishing in economic value. This is a critical assumption that our board challenges and that you as a shareholder need to monitor. You need to make this adjustment as well if you're calculating things like capital efficiency metrics, which Mark believed gives you a number that better represents reality. We're going to cover this topic in a little more detail later in this episode. So Mauboussin believes this myth has created opportunities for investors that are willing to do more work than their competitors. People like, you know, Bill Miller are great examples of investors who looked past the financial statements to just truly understand the strengths of the economics of a specific business. In his case it was Amazon. But you know, I'm sure there are other businesses out there that have their true value hidden to all but the most discerning investors. The final myth we'll cover is that some investors believe that the rise of indexing has made active managing easier. So for any listeners unfamiliar with active management, I'd like to think of a stock picker as an active manager. They aren't buying and selling stocks to mir an index, but are actively trying to find investments that will beat the market or exceed their hurdle rates. Famed value investor Seth Klarman said indexing should give a long term value investor a distinct advantage. The inherent irony of the efficient market theory is that the more people believe in it and correspondingly shun active management, the more inefficient the market is likely to become. But Mobisen actually thinks the opposite is true. So he thinks that managers who are engaged in passive investing, that is to say closet indexing, are actually the weakest possible players since they do not possess an edge in individual stock picking. It's just a lot easier for them to go and hug an index. But this has more second order effects by removing the weakest players from the pool of active managers. And so when all of the weakest managers are gone, you're only left with, say, you know, the average and the strongest possible ones. And these are the managers that other active investors have to compete with over a limited amount of ideas. And therefore that's why Mobison believes that active management has actually gotten harder. The rise of index funds Since a lot of my time on TIP is spent trying to find investors who have beat the market, I can honestly tell you that it's very hard to find them. For every manager whose documents disclose that they beat the market, there are at least, you know, five to 10 managers who have underperformed. I don't have any anecdotal evidence here going back 10 years to say if it was any different, say 10 years ago. All I know is that beating the market is very hard, and I think it always will be. Is it getting harder, as Mobison points out, perhaps. But I think there will always be a place for stock pickers to perform if they have the right work ethic and psychological makeup. Now, let's go over the next article here, which is called Good Losses, Bad Losses. So remember earlier, I'd say that we'd continue the conversation about GAP and how it can show losses for a business that are fundamentally getting stronger. This article is going to go over a lot more specific details on that concept. So Mobisen discusses this condition called aphasia, which breaks the link between thought and language. It's something that's often caused by stroke, resulting in damage to specific regions of the brain. Patients who suffer from aphasia understand images, ideas, or concepts, but have trouble expressing them in words. My uncle, who I'm close to, ended up having a stroke at one point and I spoke to him after, and he had something pretty much exactly like this. He'd have trouble getting words that he wanted to say out in a conversation, but you could tell he knew what he wanted to say. It just would often come out in this form of a stutter, where it was as if he had access to the first syllable, but unfortunately not the following ones. But, you know, luckily for him, the issue actually ended up subsiding over a year, and now you can't even really tell that he had a stroke. So since accounting has often been thought of as the language of money, you probably see where I'm going here with the aphasia concept. So Mobison writes, accounting can be a faceic in many cases, the bottom line figures that are consistent with generally accepted accounting principles, GAAP fail to communicate the essence of a company's economics. He cites some very, very fascinating findings here. So more than 95% of the S&P 500 companies report non GAAP numbers. About a third of Russell 3000 companies reported negative net income in 2021. This ratio has actually been climbing over the past few decades since 1980. Non GAAP results bring in about a fifth of these money losing businesses into positive territories. And non GAAP numbers that we're going to go over here for these adjustments would include things like adding back true one time or non economic expenses. So in case you're wondering what GAAP versus non GAAP is, let's go over that for listeners who might need an update on accounting. So GAAP adheres to established accounting principles and standards. Its existence is to ensure consistency and compatibility across financial statements. GAAP is quite strict on recognition of expenses, which is why losses are going to be higher in GAAP versus non gaap. Non GAAP figures tend to deviate of course from the standard. Generally they're doing things like adding back in numbers, things that you're probably going to be familiar with like an EBITDA or adjusted ebitda. So they may add one time expenses, things like stock based compensation and intangible investments. This generally produces higher numbers which better represent a business's economic reality compared to gap. Non GAAP numbers are kind of a double edged sword though in my opinion. Yes, they can definitely make business look better. Generally you have a higher number, it might make a business that is losing money on GAAP look positive on non gaap. But the problem is I think a lot of businesses end up torturing their numbers to make their non GAAP numbers look really good. Even though in reality, even with non GAAP they're still just losing a lot of money. So one of the biggest culprits of this is specifically in stock based compensation. So this is added back when you're looking at a company's adjusted EBITDA calculations. Now, I've heard both sides of the story. You know, if you want to understand the true cash flows of a business, then you should add back stock based compensation as it's not true cash leaving the business. And while I see this point, I still treat it as a valid expense because if you were to take it out and you know, if it didn't exist, it would probably mean that you're having to pay those people extra money and that would end up going into something like SGNA on the income statement. So adjusted EBITDA doesn't make a lot of sense to me. If stock based compensation is a very small percentage of revenue, then at least you know, it's not an expense that was going to hurt the future value of the business very much. But you're also just not going to get an adjustment which matters very much if you add it back in. Let's look at an example here. Airbnb. I'm choosing them because they release non GAAP numbers of adjusted EBITDA. Net income here in the latest quarter was about $1.4 billion and adjusted EBITDA was about 2 billion. Stock based compensation for the quarter was about 8 and a half percent of revenue, which is very high. And an expense they explicitly mention in the footnotes is not going anywhere. So theoretically, you could use adjusted EBITDA to compare evaluations between Airbnb and other businesses in its industry. That strategy may illuminate that, you know, maybe one business is undervalued compared to another. But generally speaking, you know, it's up to the investor to to decide which investment should be made to represent a company's cash flow best. I prefer leaving SBC out of the equation. Now, businesses that aren't even in tech also use SBC to help retain and attract talent. And I see the reasoning. And if competitors are doing it, it's going to draw talent away from businesses that don't offer sbc. Sure, it would be great if every business just paid out cash bonuses, but that's just not what's going to happen to a very, very wide range of businesses and industries. So now that we have a better understanding of GAAP versus non gaap, let's use that knowledge to hopefully find some better businesses. Wilbisson points out that when looking at a business, you want to differentiate between what he calls gap losers and real losers. So both of these losers have expenses that exceed sales, therefore showing a loss in profit. The difference is that gap losers have a percentage of their expenses that are actually intangible assets. So if we move those investments into intangible assets on the balance sheet, then some of these gap losers are no longer losers. Now, a few researchers did this adjustment and they kept the amortization of capitalized intangibles on the income statement. Mobison has a graph that shows the changes in intangible investments over a 20 year period between 2001 and 2021. So back in 2001, intangible investments was about 635 billion with about 640 billion in capital expenditures in 2021, intangible investments was 2.1 trillion with capital expenditure of 1 trillion. Now if you make this adjustment, it ends up flipping about 40% of the businesses with reported losses into being profitable. Mobisen mentions the main message here is that investors should definitely spend some time and focus on understanding a business investments, return on investment and opportunities for future investment. You just have to take these three into consideration if you're going to determine the long term free cash flow of a business. Now when we look at long term cash flows of a business, we have to know if losses are being sorted correctly, obviously into good losses or bad losses. Just like the title of the article to come to a really clear picture. Now let's get back to the research that mobilis insights here. So on top of looking at how many companies flip from gap losers to winners, they also wanted to see how these companies stock prices ended up performing. And this is where things got very, very interesting in my eyes. So they looked at businesses between 1980 and 2018 and they looked at what $1 would grow into. And here were the results. So in the real loser category, returns were only 2.3%, which was the lowest. In the winners category, the returns were 7.5%. And then in the gap losers, returns were actually the highest out of all three of these at 11.5%. So Mauboussin mentions an interesting point here, which is from 1980 to 1996, the Gap losers outperformed the real losers, but underperformed the winners. But if you Fast forward from 1997 to 2017, the Gap losers delivered much higher returns than both the real losers and the winners. Now this just lends further credence to the fact that the shift towards intangible assets has greatly improved the value creation since the late 1990s. Michael's point was that the market has recognized and pays up for intangible investments that create value, even if they create losses in the short term. Now arguably the best possible example you can put into this framework is with Amazon. If we look at revenues for Amazon from 1996 until 2014, they went from about 16 million to 89 billion, which is insane. But Amazon was actually a gap loser until 2002 when it became a winner. The thing is, people were confused by the business for a long period of time because its profits were still pretty thin according to GAAP. So if we look in 2014, its GAAP operating margin was 0.2%. So you know, obviously from a gap perspective, the business was a winner because it was profitable, but it didn't look like the most attractive investment because its profits were just meager. But what if we made an adjustment similar to what Boveson is advocating here? What if we simply add back R and D to Amazon and pretended like we were putting it on the balance sheet? For the sake of simplicity, we won't amortize intangible assets here. In this case, Amazon actually looks very profitable. In 2014, its adjusted operating income was 11%. And just to compare this to how it moved over time, in 1996, around its IPO date, its adjusted operating income was negative 25%. So as they grew, they were spending less and less on R and D as a percentage of revenues and earning a lot of hidden earnings that gap didn't identify. And this plays exactly into what Jeff Bezos said he was trying to do with Amazon. In his first shareholder letter in 1997, he mentioned investing in the future into things that generated a high return on invested capital. Amazon has pretty consistently traded at a very high PE, often exceeding 50 times. But if you add back R and D, that number drops very substantially. For instance, as of February 5, 2025, Amazon's PE is around 51 times. I mean, if we add back R and D, it drops us down into the low 20s. It's a very interesting thought experiment. The final part I want to add about the subject is that being a gap loser has many other benefits. Since research and development is expensed, it functions to decrease taxable income. While a business like Amazon could obviously show a higher gap income, the fact they don't means that they have billions and billions of dollars more to continue plowing into the business, rather than paying to Uncle Sam. For an intelligent capital allocator like Jeff Bezos, I think he knew this and continued to reap the rewards of GAAP accounting by rapidly increasing R and D spend each year to supp what they paid in taxes and then of course, maximize what they could reinvest back into Amazon. I'm not sure how many other managers are aware of this or would have anywhere close to the success that Bezos did in reinvesting back in Amazon. But, you know, if you can find the right type of manager who can accomplish these types of tasks, you're probably going to be on to a massive winner in the future. Continuing with the theme on businesses, let's have a look here now at Mobison's thoughts on valuation multiples, which I think illuminates some just incredibly important points to consider. In valuing a business. So the article I'm going to refer to here is titled Valuation Multiples. So I think, as any investor listening can attest, valuation multiples are among the most common tools that you probably use, other analysts use and you know, most investors rely on moments asks how useful these multiples are and what they actually end up missing. And this is a key focus of the article, where he's going to examine why these metrics have become less informative over time and how investors can better understand the fundamentals driving a company's value. Now let's start with a crucial distinction that NYU Professor Oswald Damodaran, who's been on the show multiple times, makes. So that's the difference between pricing and valuing a business. Pricing is what most investors do. They assign a multiple to some earnings metric and then they compare it to similar companies. Valuing, on the other hand, means estimating the present value of future free cash flows, which is a more rigorous approach. According to a survey of CFA Institute members, about 93% of analysts use a market multiple approach, with the two most popular ones being the price to earnings ratio, PE ratio and the enterprise value to EBITDA or EV to EBITDA being of course, the two most popular choices. Now, while these multiples provide a shorthand way to assess valuation, they have some very clear limitations that we're going to go over here. Let's take a quick break and hear from today's sponsors.
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So if you look at the numerator of these multiples, you know the price of equity P or the enterprise value EV captures a business's long term cash flows. However, the denominator earnings E or EBITDA reflect only recent performance. And so this mismatch is one reason that multiples can often be kind of misleading. An issue that has come up multiple times in this episode is the shift from tangible investments to intangible investments. You know, decades ago businesses primarily invested in physical assets such as factories and machinery, and obviously these were recorded on the balance sheet and depreciate over time. Today, companies invest heavily in intangibles such as brand building, software and customer acquisition costs. Instead of appearing as capital expenditures on the balance sheet, these costs appear as expenses on the income statement. And obviously like I just went over, this results in a reduced reported earnings and so this distortion means that traditional multiples may actually understate a company's actual earnings power, particularly for firms that rely on intangible assets. So Mobisen has a really good example here where he goes over Microsoft. So if we look at the fiscal year 2023, Microsoft reported a net income of about $72.4 billion. But if intangible investments were capitalized correctly, that figure actually rises to $83 billion, which is a 14.7% increase. And similarly, if we look at Microsoft's reported EBITDA, it was about 102.4 billion. And that would actually end up jumping 43.6% to 147 billion if we adjust for intangible investment. So this results in obviously significant changes in valuation metrics as well. So Microsoft's PE drops from about 35 to about 30 and its EV to EBITDA falls from about 24 to about 17. And these are obviously material differences that investors probably should not ignore. Now, if you decide to use these adjustments, you obviously have to adjust multiples as well. For comps. Let's say we compare this, the exact same example above on Microsoft to competitors like Google, SAP, IBM and Oracle. In that case, we obviously can't use an adjusted net income or EBITDA number for Microsoft and then use the default numbers for the comps. We would need to go into the comps and make adjustments there to get the most accurate comparisons. So let's just look at the vanilla EV to EBITDA numbers for all these businesses in 2024. So Microsoft 22 times, Google 18 times, SAP 31 times, IBM 18 times, and Oracle 25 times. Now, I'm unsure how Michael calculates his intangible investments for Microsoft in 2023, but I'm going to give it a shot in 2024. So in 2024, they spent about 32 billion in SGNA and about 30 billion in R& D. If we add that to their 129 billion in EBITDA for 2024, we get an adjusted EBITDA number of 191. And this is excluding SBC, which is usually added back in as well. That would have dropped their EV to ebitda to about 14 times. This makes, you know, Microsoft obviously look way cheaper compared to its competitors. But still, it's intellectually dishonest not to factor the same adjustments to the other businesses if we want an apples to apples comparison. Now, one point there I want to make. You know, I think in this example, obviously I added back SGA which isn't probably the most realistic way to do it. You probably actually want to add a percentage of SG&A, and you'd have to go through and try to find which line items of SG and A Look more like intangible investments, because obviously, you know, paying employees, marketing, things like that aren't necessarily always considered an intangible investment. Another major issue with valuation multiples is that they often send conflicting signals. It's not uncommon for two companies to have similar PE ratios, but vastly different EV to EBITDA multiples. Why does this happen? One explanation is capital structure. So the PE ratio is affected by interest expenses because it looks at net income where EV to EBITDA is unleavered, meaning it doesn't factor in financing costs. So companies with higher debt levels will often appear more expensive on a PE basis, but more reasonably priced. When using EV to ebitda, taxes, of course, play a role. Earnings are calculated after tax, so variation in tax rates between companies can lead to discrepancies in the PE ratios. Ebitda, by contrast, excludes taxes, which means that the EBITDA is unaffected by these differences. Mobison gives a few examples of this, such as Walmart and Apple. So in early 2024 both had similar PE ratios. It was about 25.5 for Walmart and 25.4 for Apple. But their EV to EBITDA multiples diverged pretty significantly, with Walmart at 13.3 and Apple at 20.1. The key reason for this Walmart carries more debt and has a higher tax rate, so this pushes up its PE ratio relative to its EV to EBITDA multiple. Now, these conflicting signals are why looking at multiple valuation tools is probably very essential. While Walmart looks cheaper than Apple in 2024 According to EV EBITDA, the reason for this cheapness doesn't actually lend much credence to making it a better investment, in my opinion. Why would I prefer a business that has more debt and a higher tax rate when in the example above this is exactly what EV to EBITDA is doing? Now, you do have to think about this kind of thing. I think when looking at multiples between businesses, just dumping to a conclusion based on a multiple can obviously be very misleading, as I hope I've made pretty clear here. And this is why looking at other relevant metrics a company has is very essential. If we incorporate things such as, you know, financial health metrics, we'd probably realize a few key differences that maybe make Apple look a little bit more attractive. For instance, Apple's NET debt to EBITDA is negative 0.3 versus 1.3 for Walmart, and this further illuminates that Walmart has higher levels of debt, which is generally an unattractive trade. If you're going to make a comparison between two similar companies, and you can obviously say that these two companies aren't similar, but still, if you know if you're making a comparison, generally speaking, for me at least, I would prefer a business with lower debt One of the biggest challenges investors face is deciding whether to trust adjusted earnings measures in the first place. So companies frequently report non GAAP figures alongside GAAP earnings. But are these adjustments legitimate? Moon points out that some exclusions actually make sense, such as removing one time restructuring charges, while others, like adding back stock based compensation are more controversial. He highlights Berkshire Hathaway as an example. So in 2022 the company reported a gap loss of $23 billion, but an operating profit of 30.9 billion. The vast swing was driven by unrealized investment gains and losses, which were argued distorts the business's true performance. I won't harp much more on this aspect. I think I've touched on it enough. You get the picture. You know, Gap often wrongly punishes businesses based on specific accounting principles. It's up to you to make adjustments to more accurately portray the economic reality of a business. While valuation multiples remain useful, investors should be wary of their limitations. A company's growth prospects and return on invested capital are far more critical determinants of long term value. So let's go over growth prospects in some more detail here. So in my conversation with Jason Donville and Jesse Gamble, they made the great point that a business that can grow fast in the near future is worth a premium multiple. There are multiple reasons for this, but let's use their framework of utilizing the rule of 40 to illustrate this. So for anyone who needs a refresher on the rule of 40, it states that a business can grow in a healthy manner if the sum of revenue growth percentage and EBITDA margins meets or exceeds 40%. So let's take two businesses that are trading at an EV to ebitda of about 30 today. Let's say they both have 20% revenue growth over the next three years. The difference is that one business meets the rule of 40 while the other does not. Say Company A has ebitda margins of 10% and company B has EBITDA margins of 20%. A few years ago company A's margins were 15%, but they've actually been coming down due to increased competition. Company B's margins were negative a few years ago, but due to scaling efficiencies, they're continuing to improve. This 20% could very well be, you know, 30% over the next, say, three years. So speaking to Michael's points about EBITDA being a measurement of only short term performance, when you look at a business in this light, you can see that company B is much more valuable than company A even though they have the same evaluation today. And that's because company B will have higher EBITDA in a few years time. If we were to use a discounted cash flow, we would see that company B will produce more cash over its lifetime than company A. Another metric that can be used in conjunction with multiples is capital efficiency. Using the same example above, we will note that company B has a higher return on invested capital simply because it has more net operating profits after tax than company A, but with the same share structure and we'll assume equal invested capital so one key in looking at the rule of 40 and returns on invested capital is determining that direction a business is going to be going. For instance, the market often gets scared out of a position due to temporary setbacks in a company's fundamentals. This can cause a business to go from meeting the requirements of the rule of 40 to no longer meeting them, and it can drop the returns on invested capital as well. The key for investors is to determine if this drop is a secular trend or just a one off. For investors who understand a business well enough to realize when a company is going through temporary headwinds, you can find some incredible opportunities as your perception will be opposite the market. Another interesting point on the rule of 40 is looking for businesses that are approaching the rule of 40. So if a business is growing revenue at say 20% but has 0% cash margins, it obviously does not meet the requirements of the rule of 40. But if cash margins have improved from, say negative 20% a few years ago to 0% today, then perhaps that margin will continue improving into the future. And this can be a spot where you could potentially maybe add a business like this to your watch list and make note of margin improvement over time to see if you can eventually become comfortable enough to add it to your portfolio. Research has shown that firms with lower EV to EBITDA multiples tend to outperform, but this isn't a hard and fast rule. The fundamental insight comes from understanding why a company has a particular multiple and whether that multiple reflects the actual economic reality of the business. So please don't get me wrong, you know, the goal isn't to avoid multiples altogether, but to use them with just greater awareness. When you see a business trading at a seemingly attractive multiple, ask yourself just what's missing from the picture. By digging deeper into a company's investment strategies, you know, growth levers, its capital structure, capital efficiency and earnings quality, you can move beyond just simple pricing and move towards true valuation. So the final article I want to cover in today's episode is titled Birth, Death and Wealth Creation. And this covers why investors should understand corporate demographics. I love this article because it taught me that I shouldn't expect a business to succeed at a very high rate. The base rates for long term business success, or even just survival, tend to be quite low. Now, let's start with the birth of companies. Nearly all public businesses started as initial public offerings IPOs. But an interesting thing happened. Since late 2000, IPOs have declined by more than half. Mobison cites three primary reasons for this. The first one being that regulatory costs of going public have risen. The second is that there are larger access to pools of private capital. You know, people like venture capitalists, hedge funds, and mutual funds that invest in startups. And the third is that companies now prefer mergers and acquisitions over going public. You know, it's easier for a small firm to sell to a larger firm than to deal with public markets. So you may be tired of me talking about Amazon, but it's obviously a great example of a successful IPO since 1997. You know, it IPO'd for a few hundred million dollars and today's worth 2.5 trillion. So IPOs obviously can be successful, but as you'll discover, that outcome seems to be the outlier. An IPO horror story, on the other hand, was out of WeWork. Its initial public offering valued the business at about $47 billion in 2019. At that time, they were operating about 44 million square feet across 39 countries. But after it went public, they received very intense scrutiny over corporate governance, the business model and its future profitability. These concerns eventually led to the CEO resigning. He ended up receiving a $1.7 billion severance package from SoftBank. And by the end of 2023, We Work's market cap was $21 million and they filed for bankruptcy. So even if you are looking at IPOs of large businesses, it's very important to understand if these businesses have the right makeup to stay alive into the future. Now back to a few critical data points that Michael shares. So there were fewer public companies in 2022 than 1976. Even though the population in 2022 was actually 1.5 times greater than 1976, the GDP per capita is 2.2 times higher and the number of firms is about 1.5 times greater. Another interesting point he brings up is what he calls the listing gap. So the listing gap is the difference between how many public companies are listed as an estimate of how many should be listed based on things like the size of the population in the economy, as well as comparing listings to other countries. So research estimates the gap in the US at about 5,800 to 12,200 companies. This is great evidence that less businesses today are going public. But for the ones that do, what does their lifespan end up looking like? After all, we know that capitalism is just brutal and just surviving is not an easy task. So he states that the half life of a public company is now about 10 years. Businesses that have survived for 50 years or longer make up about 5% of listed companies in 2023. Mobilson points out that despite the perception that corporate longevity is decreasing, it's actually increased since the 1990s. When looking at businesses that survived both five and seven years after IPOing, there is a steady uptrend. This is interesting and it's also a great exercise to ask why these businesses are surviving. The answers are pretty intuitive I think to value investors. You know, surviving companies have stronger moats, better adaptability and higher capital efficiency metrics. Many listeners of the show are looking for businesses that they can hold for an extended period. And you know, the good news is that if you find an outstanding business that have enduring characteristics, you might have the luxury of finding some incredible long term investments. But the hardest part in this equation is finding businesses that can sustain these advantages for a multi year time period. While it would be great if we could all find Coca Cola type investments like Warren did for Berkshire shareholders, it's not easy. Another important consideration to ask is how many stocks Warren Buffett has sold in his career. I can't find an exact number, but my estimate is probably somewhere in the 300 plus range. And this means that the vast majority of Buffett's investments are rentals. Not forever holds. This is an incredibly important concept to remember. If you are planning on looking for long term investments, realize that you will be wrong. And when you are incorrect, you're going to be much better off cutting ties with a loser than holding on to a melting ice cube. Now let's dig into why businesses die. Mauboussin points out three potential ways that A business can die. They are one, they get acquired by another business. This happens because the business is interesting to other businesses or they're having financial problems and they need to merge with a stronger company just to stay afloat. The second is that they delist due to financial failure. You know, businesses go bankrupt. And if a public business goes bankrupt, it no longer needs to be publicly listed and its equity is often worthless. Additionally, businesses may be forced to delist if they violate some form of regulatory rule. And the third one is that they voluntarily delist. Listing companies cost money, and if the markets aren't providing the ability to raise more capital, or if a business can't cover the listing costs, then delisting can be a good choice. Let's cover these three areas in some more detail. So 58% of companies delist due to M and A. Even though this is death, it's often a win for shareholders. Nearly all M and A is done at a premium to the share price, meaning investors can sometimes close the price gap when a buyer is willing to do it for them. A large tailwind for buyouts comes from private equity world and private equity buyouts constituted about 2% of delistings in 1977 and is up to 20% of delistings in 2022. The data is great for owners of the acquired business Maubous and shows that from 1985 to 2022, the median premium is about 29% over that full period and the average premium is closer to 45%. So as you can guess, the premium tends to be higher when there are multiple bidders. This is why many acquisitions turn out to be kind of meh. You know, the winners of a bidding war is simply the bidder who is willing to take on the most risk for the least forward return. I personally like serial acquirer business models. But there is a very important part of picking your serial acquirers properly, and one of these things is buy discipline. You want people, managers who do the buying to have a very clear understanding of what they're willing to pay and be able to simply just walk away from a potential acquisition if the price being asked is just too high. This is why I give bonus points to serial acquirers who have little to no competition on their bids. So the second reasoning for delisting again was bankruptcy or cause, which comes out to about 39%. Like I previously mentioned, bankruptcies will trigger a delisting, but a company can also fail to meet exchange requirements, which will also trigger a delisting. The data on bankruptcies is Pretty intuitive. You know, they peak during recessions when less corporations and people are spending money. This causes businesses to decrease their revenues. And if they can't pay their bills, then bankruptcy is a way out. Now, as the SPAC mania taught us, many businesses will go public before they are even ready for it. Founders often want to cash out, and they'll do so when the market is conducive to this. This is usually when the market has a speculative feel to it. Those are the times when there's a lot of money in the market just chasing fewer and fewer opportunities. What happens is that a lot of the opportunities during these times end up decreasing in quality. This happens simply because people are willing to pay for low quality, unprofitable businesses. Now, I strongly encourage you to avoid trying to participate in this type of activity as it usually doesn't end up very well. One business that was forced to delist is Blockbuster. Now, it was a business that could still be thriving today if management had the wherewithal to see that Netflix was just eating its lunch and the ego to admit a better business model existed. Blockbuster had an opportunity to buy Netflix for about $50 million. The CEO at the time thought this was an actual joke and took a hard pass. Blockbuster today has one novelty location, while Netflix has a market cap of $435 billion. So what red flags can you look at to help identify potential delistings? I'll comment on some of the obvious signs here. If a business has excessive debt, it increases its chances of bankruptcy if it cannot service that debt. Another one is declining sales. All businesses have some degree of fixed costs. If a business has no moat and begins losing revenue at some point, the revenue won't cover fixed costs, meaning they will have to fire people, sell parts of the business, or declare bankruptcy. Another point here is corporate governance. If you get a sniff, a business is taking part in illegal or not even illegal, but maybe behavior that isn't aligned with your values or is unethical, that's a pretty good signal that you probably should get out. And this can obviously be really difficult because, you know, if someone in the business is partaking in bad behavior, they're also probably really good at hiding it. And if they're able to hide it from their colleagues, it's going to be a lot easier to hide it from investors. So, you know, a simple defense to this. Again, it's not perfect, but it's to just study the people who are involved in a business. And if you find any unscrupulous characters, then you should probably just put the business in the too hard pile and move on from it. Most of Mobisen's conclusions are from his research into Henrik Bessembinder, who clay interviewed on tip 667. Basically, it's that the stock market returns are not evenly distributed. About 60% of companies underperform one month treasury bills and only 2% of stocks account for 90% plus of market wealth creation. The way to play this is if you don't think that you can find big winners is to just own index funds. This ensures that you'll have equity in some of the biggest winners. Diversification protects you from the downside risk as well as the big winners do tend to be kind of volatile if you were to just own them. If you find this volatility difficult to manage, it might be easier just to hold an index versus individual stocks. Just obviously realize that when you do hold the index, you are exposing yourself to a large amount of mediocre businesses as well, and this serves to decrease your overall returns in the market. There are obviously pros and cons to every investment strategy, so there are three key takeaways for investors who consider themselves stock pickers here. The first one is that traditional valuation models, like discounted cash flow, assumes companies last forever, but most don't, so keep that in mind if you use them for valuation purposes. The second here is that you can attempt to adjust valuation models to consider the fact that corporate mortality is the norm. And lastly, if you pick socks, you will need to obviously select future winners, but more importantly, you have to hold them while they continue winning. That's all I have for you for today's episode. If you want to interact with me on Twitter, please follow me at rational, MrKTS or LinkedIn under Kyle grief. If you take anything away from my episode today, please drop me a line with your feedback. Thanks again for tuning in. Bye bye. Thank you for listening to tip. Make sure to follow we study billionaires on your favorite podcast app and never miss out on episodes. To access our show notes, transcripts or courses go to theinvestorspodcast.com this show is for entertainment purposes only. Before making any decision, consult a professional. This show is copyrighted by the Investors Podcast Network. Written permission must be granted before syndication or rebroadcasting.
In this solo episode, host Kyle Grieve offers a deep dive into the work of Michael Mauboussin, a leading thinker in the world of investing and decision science. Drawing on Mauboussin’s “Consilient Observer” articles, Kyle explores the pitfalls and limitations of traditional valuation metrics, how investors can improve judgment and decision-making, and the enduring traits of long-term winning businesses. He challenges popular investing myths and provides practical frameworks and checklists for smarter analysis.
Michael Mauboussin's BIN framework (Bias, Information, Noise) offers a structured way to improve judgment and forecasts.
Noise:
Combating Noise: Three Techniques:
Bias:
Signposts:
Drawing on Mauboussin’s 2020 Greenwich Roundtable address, Kyle unpacks four central market myths:
Multiples (P/E, EV/EBITDA) have become less informative due to rise in intangibles:
Comparability Problem:
Adjusted Earnings Measures:
Growth Prospects:
Temporary Setbacks vs. Secular Declines:
Fundamental Takeaway:
"The goal isn't to avoid multiples altogether, but to use them with just greater awareness."
On Noise & Variability in Professional Judgment (03:30):
“Many, many of the judgments made by professionals are highly, highly variable.”
On Price Appreciation vs. Dividends (27:53):
“Price appreciation is the only source of investment returns that increase accumulated capital.”
On Misleading Valuation Metrics (1:05:23):
“It’s intellectually dishonest not to make the same adjustments for every company if you want an apples-to-apples comparison.”
On Why Most Companies Don’t Survive (1:18:42):
“The base rates for long-term business success, or even just survival, tend to be quite low.”
On Indexing and Outlier Wealth Creation (1:24:38):
“About 60% of companies underperform one-month treasury bills, and only 2% of stocks account for 90% plus of market wealth creation.”
On the Psychological Challenge of Long-term Winners (1:26:12):
“If you pick stocks, you will need to select future winners, but more importantly, you have to hold them while they continue winning.”
Host: Kyle Grieve
Guest/Source: Michael Mauboussin (via analysis and summary of published articles)
For more, connect with Kyle on Twitter @Rational_MrKTS or LinkedIn (“Kyle Grieve”).
This summary was created for those seeking a comprehensive breakdown of TIP775 without audio. For further learning, explore the show notes or the referenced Consilient Observer articles.