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The Investor's Podcast (We Study Billionaires) - The Investor’s Podcast Network
TIP805: Stock Market Maestros w/ Kyle Grieve
01:04:08
Kyle Grieve discusses Stock Market Maestros, revealing that elite fund managers succeed not by picking winners the majority of the time, but by making dramatically more on their wins than they lose on their losses.
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- [00:01]
Tip
You're listening to Tip.
- [00:03]
Kyle Grieve
The world's best investors are wrong more often than they're right. Let that sink in for a minute. The elite investors profiled in today's episode had a median hit rate of only 49%. This means they actually lost money on the majority of their picks. However, they have also dramatically outperformed the market. How is this even possible? You may be wondering. They made a lot more money on their winners than they lost on their losers. Today we're going to look at key lessons from the book Stock Market Maestros. I honestly think this book will help reshape just how you think about portfolio management because it does an exceptional job of showing why treating your winners and losers is vital to investing success. The problem that most investors have is that they optimize for finding the next great stock pick. But the real edge in investing lies in how you manage what's already in your portfolio. Specific strategies for how you enter and size a position, how long you hold it, and how to exit properly are more important than finding your next great idea. So today I'll discuss three important metrics used in this book to distinguish truly skilled investors from just the lucky ones. You'll learn why riding winners is so crucial to performance. You'll learn why losers are costing you more than just money. And you'll walk away with simple strategic ideas to ponder that can help you better handle winners and losers like some of the world's greatest investors. So no matter if you're a novice investor or have been investing since before the tech bubble, this episode will really get you thinking about how to best manage your portfolio for outperformance. Now let's get right into this week's episode on Stock market maestros.
- [01:37]
Tip
Since 2014 and through more than 190 million downloads, we break down the principles of value investing and sit down with some of the world's best asset managers. We uncover potential opportunities in the market and explore the intersection between money, happiness and the art of living living a good life. This show is not investment advice. It's intended for informational and entertainment purposes only. All opinions expressed by hosts and guests are solely their own and they may have investments in the securities discussed. Now for your host, Kyle Grieve.
- [02:19]
Kyle Grieve
Welcome to the Investors Podcast. I'm your host, Kyle Grieve, and today I'm going to cover a book that I found highly, highly illuminating and helpful regarding portfolio management, especially in regards to handling both winners and losers. So the book is titled the Stock Market Maestros by Lee Freeman Shore and Claire Finn Levy. Now, the reason that I enjoyed this book so much was that it went over these three super simple metrics that really helped find managers that they wanted to interview for the book. Then they had a bunch of these great case studies on how each of these outperforming managers handled real life examples of both winners and losers. After doing my recent episode on Lessons from Venture Capital, it's really got me thinking just how important it is to handle your winners properly. Now, reviewing my own numbers, I realize that I've tended to do a pretty good job with my winners. But I can maybe eke out some more returns if I also find some way to mitigate risk for my losers in a more strategic way. So I was very excited to read all of the interesting strategies that these investors do, and they are very varied. So there are literally strategies for all sorts of investors. Whether your average holding period is, you know, 10 years or 15 months, you're going to find something very interesting. Strategically speaking, from this list of outperforming investors that I go through now just to get you prepared here, I didn't cover all of them because there was just way too many details that I wanted to go over. So I just covered a couple of them. But let's start us off by quickly going over Lee Freeman Shore's basic concepts from his first book, the Art of Execution. That book covered the winning habits of 45 of the world's top fund managers. So in it, Freeman Shore focused on these investors behaviors and actions, categorizing them into five different categories. These categories were based on how they reacted to winning and losing stock ideas. So the five categories are number one, rabbits. This is when you have a losing position, you just do nothing. Number two is an assassin. Assassins, when they have a losing position, tend to cut their position before too much damage is done. Number three is hunters. When they have a losing position, they materially add to the position. Number four is raiders. When they have a winning position, they tend to cash out after they just make a small game. And then number five is connoisseurs. When they're winning, they ride the winner and they try to win big. Now Lee's finding was that the successor failure was largely determined by how an investor behaved after the making an investment. The book states that the top investor's best ideas makes money only 49% of the time. This means that 51% of the time they're actively losing money on their ideas. Now this data is very interesting and somewhat aligns with other legendary investors such as Peter lynch and John Templeton. Both of whom guess that they made money on about 50 to 60% of their ideas. Now, when Freeman Shore wrote his first book, he was shocked at that figure. How was it that the world's best investors were able to outperform the market when they were just wrong more often than they were right? And the answer is pretty simple. They just make a lot more money on their winners, which helps offset their losers. The winners also fit neatly into three of the categories that Lee devised. So they were all connoisseurs who squeezed as much as possible out of their winners. But when it came to losing, they all had different strategies. Some of them were assassins, quickly selling out of positions before any real capital was put at risk. Or they were hunters and had so much conviction in their ideas that they just simply add to them when they went down in price. The book I'll be going over today will go over exactly how many of the world's top fund managers handle their winners and losers. Freeman Shore brought on his co writer Claire Finn Levy, who owns an analytics company called Essentia Analytics. It's a fintech that specializes in analyzing the behavior of professional investors to deliver unique and helpful insights. Now, the software will go through a fund manager's trade history and it helps identify trends in their own behavior. It finds out where they're adding or subtracting value. It helps them understand areas where luck and skill might be confused for each other. And it will also be able to send alerts based on past and current behaviors just to remind these professional investors how they can improve their thinking about specific trades using their data in real time. Now, because Levy deals with a large volume of professional investor data, she was able to help Lee find investors with compelling data points that really help explain just why they've succeeded at such a high level. Another point of interest is that within financial academia, case studies tend to be pretty light, while theorizing tends to be very heavy. Using her company's analytics gave her very clear real world insights into how her customers were behaving and how that was impacting their performance. Now let's look at how Freeman, Shore and Levy found the 12 investors that were profiled in this book. So as I mentioned earlier, they just focus on really three key data points. The first is called Behavioral AlphaScore, which is essential proprietary metric based on seven decision types. These are picking, sizing, entry timing, scaling in size, adjusting, scaling out and exit timing. The behavior alpha score is is important because it differentiates between skill and luck. If your score exceeds 50, it means that you're adding alpha through your skills rather than through luck now, the book shares some interesting facts about the Behavior Alpha score, which I'm just going to refer to as the BA score. First, it shows your score based on the last three years of data. If you have a long term track record that's very good but have been underperforming lately, this score will help you be able to determine if you're still adding value or if your skills have maybe diminished as you've gained more experience. Essentia's data also shows that a BA score above 50 meant investors were about 1.5 times as likely to outperform in the next year as those with a BA score of less than 50. And this is pretty sound. If you're making good investing decisions, then you probably should have a better chance of outperforming investors whose decision making just simply isn't as good as yours. Now here's where things really get interesting. The BA score of the 12 investors interviewed in this book ranged from 53 to 63, with a median score of around 55 and a half. This means that all 12 investors have demonstrated above average decision making skills over the last three years. Now, the second KPI here was hit rate, and this is simply a measure of how often investors get it right. Since many investors like baseball analogies, the hit rate is often been referred to as batting average. If you want to calculate it, it's simply the percentage of positive outcomes out of the total amount of outcomes. Now, I've defined this for myself. A positive outcome is basically if a business makes me money and a loss is if it loses me money. It's that simple. Levy makes a great point, though. Outcomes can be defined differently for different people. Levy's definition is the percentage of all positions in the portfolio that generate a positive return or positive relative return during the portion of the period they were held. Now, the end there is very, very important. Her definition tends to be pretty much the exact same as mine, but the point she made there about during the portion that they held is very, very important. So I guess I don't know, but I guess there's investors that count their hit rate as businesses that continue to do well after they sell them. Now, I personally don't understand why anyone would use a hit rate on a business that they don't own. And you know, her point, which I completely agree with, is that investors should be rewarded only for their hit rate when holding a company that does well. And if you're selling a position that continues to do well after, then you don't get credit for it. Makes complete sense. Now, as I mentioned, the hit rate was interesting because in order to qualify as a great investor, you didn't even need to have a hit rate over 50%. The median hit rate for the maestros outlined in the book, again, 49%. So now this picture is starting to become a little clearer. The best investors behave well enough to add value to their decision making, but they're also right on the winners, slightly less than they are wrong. So the final data point is the payoff ratio. The payoff ratio is somewhat similar to the hit rate in that it accounts for both your wins and losses. But the payoff ratio focuses on how much you make when you're right versus how much you lose when you're wrong. It's calculated by dividing the profits from your average good idea by the losses from your average bad idea. Levy believes that if you remove the BA score from the equation, the payoff ratio is the strongest stat for differentiating skilled investors from average or below average investors. All of the maestros chosen for the book had payoff ratios well in excess of 100% with a median score of 182%. That means that on average, they make 1.87 times more on their winners than they lose on their losers. Because I find point 2 and 3 most interesting, and since it's easier to run on my own portfolio, I decided to try running it on my own portfolio using data that I pulled from Share Site's contribution analysis. My current hit rate as of March 17th of 2026 since the inception of my portfolio is 46% and my payoff ratio is 262%. Now, I have no ability to get my BA score, so I have no idea what that would be. But even without a BA score, this is an interesting set of data because I think it really helps assess the quality of decision making. Even though I lose, you know, 54% of the time, I'm still winning overall because my winners are much bigger than my losers. My tagline should be something like be wrong often but small and be right less often but big. This data tells me a few interesting points about my investing style. Now, I ran my numbers through chat GPT and it really nailed down my investing strategy. It told me I tend to let my winners run. I'm not over optimizing for hit rate and I tend to think in asymmetric bets this is totally true. So I have two investments that if I sold them early, would dramatically alter my results in terms of my payoff ratio. A lot of my investing success has simply come from holding these two positions while they've compounded and not interrupting them unnecessarily. My data on asymmetric bets is also helpful as that tends to be what I look for. Bets where if things go wrong I don't lose much and if they go right I make an outsized return. So far, so good, but the real learning for me was the point of hit rate. While I don't think I need to optimize to get my hit rate much higher, if I had a handful of positions go from, you know, losses to hits, it would positively affect both my hit rate and my payoff ratio. Currently in my portfolio I have six losers and eight winners, and I have very strong conviction that at least two of these losers will become winners over the next few years. I'll keep you up to date. Now my goal in investing is to minimize losers, just like Buffett has done for the entirety of his investing career. It would be amazing to run his data on his picks, but you know, that would also be quite the undertaking. If anyone has done this before, please reach out to me as I would love to know what Buffett's numbers look like. My guess is he would probably fit into the same range of winners that are outlined in this book, with a hit rate somewhere around 50% and a payoff ratio well in excess of 100%. Now I want to transition to discussing the investors in this book as well as their case studies. Most of the case studies are very modern and quite easy to grasp. So the first investor featured was this gentleman named Josh Goldberg who manages G2 Investment Partners Management. His stats for the three KPIs are a BA score of 55 and a half, a hit rate of 55, and a payoff ratio of 171%. Now Josh has an interesting investing strategy based on earnings expectations. He focuses on surprise in metrics such as revenue earnings and ebitda. His strategy is a true inflection point strategy. Once he's notified that a business has an earnings beat, he begins researching the business. His strategic rationale is very interesting. Imagine you have a company that analysts Expect will earn $0.25 per quarter for a year, basically flat growth. But then in the first quarter, instead of earning 25 cents as expected, the company earns 40 cents. That's a 15 cent earning surprise. Logically, analysts should increase their earnings forecast for the subsequent quarters to reflect this new reality, but they don't do that until some time has passed. They are anchored to their original Forecasts that gap is what we look to capitalize on. Josh then looks to see if he has a variant perception on the stock versus the market, which helps determine if the business would make a good investment or if it's just a pass. He tends to focus on small cast because he feels it's more likely to have a variant perception on a small cap versus a mega cap such as Alphabet. Now, Josh's holding periods from analyzing decisions are quite short. This helped him create a 15 month rule. So this basically states that they don't really want to hold winners for too much longer than 15 months and if they hold it longer, they risk outstanding. They're welcome. G2 selling criteria are very simple and different from what I've seen in many other funds. They sell for just two reasons. So the first is that the business has an earnings miss. And the second is that they'll sell once 1% of the company's capital is at risk. So let's say they have a 3% position. That position loses around 30%, then it's time to sell, which reduces the risk of losing any more than 1% of the capital. Now, as a second rule there shows Josh is most definitely an assassin. If an idea is working out fundamentally but the market isn't liking it, he will still cut the idea even if it has a positive earnings beat. This is a very interesting way to look at risk and it favors a much higher turnover approach. Let's have a look at one of his winning investments in Fiverr International. So this is a business that many listeners have probably used before. It's simply a marketplace for freelancers. The business benefited greatly from COVID as there was a massive influx of people that were starting to work from home who used Fiverr to help them generate income. And G2 made a great return on this. So they began buying right after the shutdowns, after they saw the earnings surprise. Josh ended up averaging up with his initial entry price somewhere around the 20 range, but an average cost basis in the 30s. So 12 months after buying it, the share price had hit an incredible $230 and it actually went up even higher after that tooth around 300. So Josh ended up following his 15 month rule and he spoke to an analyst. So he concluded that much of the results were kind of a pull forward of new customers that most likely wasn't going to be maintained into the future. So he took his 10x and he sold the position, which was the right call. Now, some of the other big lessons from Josh regarding winners are the following. So Average up on winning positions and try not to get anchored onto your initial buy price. Follow the 15 month rule. While I personally wouldn't follow this rule, I can see his rationale for it. It works for him, his investing style and his strategy. But the point about actively trying to not stay invested in a business that is getting worn down as it grows is definitely a good one. A business that has grown due to something like high earnings then goes through a periods of no growth or even negative growth is likely to lose you a lot of money. So it's important to pay attention to the fundamentals of the business and if you have to sell before the top blows off, you're going to be much happier than taking the full ride down. Another interesting signal Josh uses here is to look at the multiple so multiple compression is a signal to Josh to get out of a business. This makes sense as his strategy is again primarily based on momentum and multiple compression obviously acts to slow momentum. Now I want to cover one of Josh losers that was discussed and this was in a business called Stem Inc. The business specialized in storing electricity during low use times. So stem IPO'd at the perfect time. In 2020 when the IPO market was booming, its price went from about $15 to $50 in just a few months. G2 got interested once the stock settled down to about $20. Now it didn't do anything for about two years and Josh ended up selling it as it reached that 1% total capital loss rule. So at the time of this investment he didn't have that 15 month rule. Otherwise he said he would have sold it earlier and made less of a loss. The main lesson regarding losers that Josh shared was just to simply not add to losers. Now this is an idea that I personally disagree with, but it's clearly worked wonders for him. So he shared a quote by Paul Tudor Jones. Losers add to losers. So why do I disagree with this? Because compounders go through periods where the market dislikes them for irrational reasons. If you get scared out of these positions that can be held for multiple years as they compound, you risk giving up a ton of potential upside when the best strategy would have just simply been to add to them. Now I think there's enough great investors out there that consistently add to their losers that prove that losers don't always add to losers. Now Josh made one great point regarding losers and that was how they tend to make up a disproportionate amount of your mental energy. For that reason, removing a loser which maybe only makes up 1% of your portfolio, but maybe 10% of your mental energy can be a very smart decision, and I definitely resonate with this. I've noticed in my own investing journey I've had some businesses where I have this feeling of disdain whenever I think of them, and these are the types of businesses where I've been much better off just selling them, and I've rarely regretted it. The final point on losers that I want to discuss from Josh Goldberg was the importance of having positions that act as your captain. So he said, if your number one position is not doing well, that's a signal that something's just completely out of sync. Your best position should act as a captain on a ship, doing better on down days and outperforming on the up days. This metal model helped him gain confidence that if his best idea was performing well, it would reverberate through the entire portfolio. Now, I think this is a useful notion, as I found that I can get down on my own portfolio when literally everything is doing poorly. But this, luckily, tends to be quite rare. For instance, when I look at my Portfolio Today, on March 18th of 2026, nearly all of my positions are in red. But since I'm ambivalent to what the market is doing on a short term basis, all I really care about is that my positions will go up over the next few quarters or the next few years. So even though my top five positions are all down year to date, I'm okay with that because they're also positions where I think they're fundamentally sound over the next few years. Let's take a quick break and hear from today's sponsors.
- [20:00]
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- [23:58]
Kyle Grieve
All right, back to the show. The next investor the book covers is a gentleman named Greg Padilla who manages money for Aristotle. Greg has a BA score of 54, a hit rate of 56%, and a payoff ratio of 216. Padilla's investment strategy is to find good quality businesses that have an inflection point created by fundamental catalysts trading at attractive prices and have a market cap above $5 billion. They don't use screens, nor do they use charts as part of their investing process. One reason that he gave regarding charts is that if he looks at a chart of a business that he owns and sees that maybe it's at an all time high, he'll want to wait to buy it on a dip and it may go up another thousand percent and offer him nothing but regret. So let's look a little more here at inflection points or the catalysts that Padilla looks for. They include things like new management teams, new products, or maybe even resolving legal issues. They don't focus on businesses going through a catalyst that is easily visible to the market today. Instead, they want to get into a business where they believe that there's a very high probability of a catalyst in the next one to three years. This allows them to get a decent price before the market is aware of the beneficial effects of that catalyst will have on that business's fundamentals. Now, since Aristotle invests in high quality companies, you probably expect that they're going to have pretty high levels of concentration as there are only so many high quality companies out there. But his stance has actually shifted as he gained more and more experience. Instead of investing heavily into high conviction bets, he's steadily gone back from too much concentration into a more diversified approach. Today, a concentrated bet will just look like a two to two and a half percent position in the portfolio. So the portfolio tends to hold about 40 to 50 positions. Now this means that they essentially are equal weighting their positions, which is a very interesting strategy and not one that I would have thought would occur in this cohort of outperformers. But obviously it's worked incredibly well simply because they're able to cast a much wider net around their universe of stocks. And once they have a winner, they know how to milk them as much as possible, which is shown in his payoff ratio of 216. Now, when it comes to how they manage stocks already in the portfolio, Padilla's strategy is mostly based around inaction. Even if he holds a cyclical like Lennar, a home builder, they'll just hold it through the cycle. They take the stance of thinking of a position as kind of being married to Padilla even mentions that he takes kind of this VC approach to his positions. And even though public markets offer liquidity, therefore allowing portfolio managers to get out of positions, Greg decided to avoid managing position sizes like that because if a position does well, great, it will make up a larger percentage of your assets. And if it doesn't succeed, then it just makes up a smaller percentage of your assets, but it's not going to kill you. Padilla will begin trimming when a position reaches about 6%. And the reason for that was that he never wanted to risk more than 6% of his partner's capital on any single idea. So as you can see here, Padilla's strategy is quite different from Josh Goldberg's. And yet they both succeeded. Padilla explicitly avoids trading, even though he sees the allure of it. Padilla said it takes a lot of work to decide not to trade. When we have made an 80% profit. Selling would be the simple thing to do. It would feel good, it would make our clients happy, it would make the analysts happy. But it would likely be the wrong call if we were right on the quality and the compounding potential of the business. Now, I like this approach because many fund managers feel they need to be active. And one such way of staying active is to trade. If a manager feels they need to be active in order to justify their fees, then I can see how they might feel like they have to go out and make trades, even if these actions add zero value or actually hurt the value for their clients assets. Now let's move here to a case study on some of Greg's wins. I mentioned earlier that he was willing to invest in Lennar, a clear cyclical business, and ride both the up and down cycles. This worked out incredibly well for Aristotle. Padilla has held the position for about 14 years, and judging from the book, I believe he still held it after the book was published. But it hasn't been an easy ride, which you'd expect from a cyclical business that is, you know, somewhat of a slave to the new home building cycle. Now it has had 6 drawdowns over 30% and 3 drawdowns greater than 50% and even mentions at one time the price fell 65% in only a month. But he's also made over 10x on the investment. This is a valuable lesson. So I would like to believe that my businesses will go up in a linear fashion on its way to becoming a multi bagger. But the fact is, most businesses tend to have some sort of cyclicality embedded in them. Some are just a lot more sensitive to cycles than others. The point being, if you want the right to say you've got a multi bagger, chances are you'll also need to be able to withstand large amounts of volatility. So looking at my largest position, Aritzia, it's clear that this is true. So Aritzia has been about a five bagger for me, and since I've held it, it's had three drawdowns greater than 40% and one drawdown of 65%. Consumer goods will always have some cyclicality because they will attract and lose customers based on consumer spending. But Aritzia has actually been a business that has been largely resilient to this compared to the average retail company. But it still has that exposure now. Padilla found a great business in Lennar, and his timing of when he began buying shares could not have been any better. So he started buying in 2011 after the GFC, after the share price fell from $64 to just $7. During these lean years, new home builds were suppressed, falling from an average of about 2 million to only 500, 000. Padilla saw the structural tailwind as his thesis included a regression to the mean, where new builds would eventually catch up to the normalized demand. Now, part of the reason that Greg held onto them for so long is that their business model has changed. So in 2011, they could buy land for cheap from distressed owners. But it's just not the case today. So they've had to change their business plan. So now, instead of owning about 80% of the land that they built on when they first started buying shares, now they only actually own 20% through partnership agreements. Now this has allowed them to become much less capital intensive business over the years. When asked what it would take to sell a business like Lennar, Greg mentioned a mental model that he calls why are we idiots? Or wawee. So this is a test to ask questions like what are the reasons we won't make money on this investment? What are our primary concerns? So when it comes to Lennar, it's a business that relies on these land partners at scale. So the major risk is if these partners avoid scale due to Things like high interest rates which reduce returns. Now let's look at how Padilla handles losers. In his case study, there was a business called Elanco Animal Health. Elanco was an animal health spinoff from Eli Lilly. They manufacture things like animal feed, supplements and accessories. The thesis was that they had a great manager. They acquired another animal health business from a for seller. They were developing and scaling some of the higher margin business lines in the animal accessory business. And Greg knew people were willing to spend money on their pets over even their own well being. Now Aristotle bought this during COVID figuring that would be an even better time for pet owners to focus on them. And the investment worked very well at first, doubling in a little over a year's time. But then the price went back to their average cost basis. And once the price reduces by 15 to 20% or underperforms their industry or the rest of the portfolio by the same amount, it triggers a sale review. Now in that review, they discovered that the business hadn't been executing at the level that they had initially hypothesized. The new acquisition just wasn't panning out and it just wasn't adding value. They were also losing market share to one of their biggest competitors, Zotis, which was not part of the thesis. And lastly, Padilla expected them to use their cash to pay down debt on that acquisition. But it just wasn't really happening at the pace that they expected. As a result, they sold out at a 25 loss. Now the book goes over some of the interesting ways that Padilla handles losers. Just like his winners, he doesn't really fiddle around too much. It's no surprise then to learn that he just doesn't really tend to add to his losers. Now I think for long term investors this is generally not a good quality to have. But as you can see, Padilla still did the work on the business after it faltered, getting out before any more damage could be done. But his exit strategy is more fundamentals based rather than based on some sort of objective loss number that they try to avoid. The rationale here is to allow businesses inside of the portfolio to grow or shrink at their own pace. If a business drops to a 1% weighting, then it's likely that the business has some issues. But as we know with markets, these issues can just simply be the product of the market's incorrect perspective. Now I resonate with parts of Greg's strategy here. I personally would never have a 2% waiting simply because I have no ability to Track, you know, 40 to 50 companies 15 is kind of the maximum that I feel that I can make time for. For that reason, my weights are a lot larger. But I do resonate with having smaller positions. For example, I took a business called evolution gaming and iGaming business to a 15% cost basis. But I would no longer do that today on pretty much any business, even though that I have businesses that I have much higher conviction on. And the reason for this is simple. I know I'm going to be wrong often, so I need to make sure that I'm avoiding any large losses. Now, I was lucky that I actually made a small profit on Evolution Gaming. But when I see that I have a position that is very strong fundamentally, but not so strong in share price and I need capital, then I'll look first at my cash holdings and if that's depleted, then I'll look to positions that I own that I have the lowest conviction in. And it's probably not a surprise that these positions are also the ones that tend to have the lowest weightings in my portfolio. So the next investor featured was John Barr, who Freeman Shore referred to as the lumberjack. Now I'll get to why this is shortly. John Barr manages the Needham funds, specifically the Needham Aggressive Growth fund. He has a BA score of 56, a hit rate of 49% and a payoff ratio of 288%. John specializes in small caps, a market that is definitely near and dear to me. And he goes small. He focuses on businesses with a market cap of 50 million to 500 million. Since he deals with businesses that have low liquidity, he tends to scale into positions, sometimes with starting weights of just 10 to 100 basis points. He looks for businesses that he calls hidden compounders. These are businesses that are doing something that the market just hasn't analyzed properly yet. This is usually things like developing a new product or service with a very large and untapped potential. Market size. The fascinating thing about small caps is that they tend to be very agile. Now this is both a positive and a negative. If a business finds a new business line, it can often fully switch, resulting in spending more resources, time and energy onto this new area. Now if it works, then the business is then perceived as having a highly intelligent management capable of adventuring into new frontiers. But if it doesn't, then management tends to be viewed as excessive risk takers. Now, one of my greatest winners is actually a direct example of this. The business in Canada, which I won't name, used to specialize in creating products for the oil and gas industry. Think about things like lights used to light up pipelines. So one day a customer asked management if it would be possible to maybe add cameras to the towers where the lights were mounted because it had an increased rate of vandalism. And so the business said, yeah, they would give it a shot. Fast forward to today. The business has over 2,800 of these security towers and has divested its original business line. This is an example where things have gone completely correct. But micro caps are littered with businesses where things have gone completely wrong as well. One potential issue with micro caps is customer concentration. We'll go over this when we look at one of John's mistakes. Another interesting part of John Barr's strategy is in his turnover. So most micro cap funds tend to have pretty high turnover rates since many of these businesses are just not well established and are therefore not really worthy of holding on to for long periods, which obviously increases turnover. But John has actually distanced himself from this norm. His average turnover is an astonishing low, 10%, meaning his average holding period is 10 years. Bar takes a strategy that I've come to take as well. Regarding my small caps. I start small. Then when it becomes obvious that things are working and I can tell the business has incredible compounding capabilities, I'll add meaningfully to that position. Bar starts his position then in about the 1% range. Once he's given it some time, the inflection has happened and it's obviously working. Then he's not afraid to add to the position, going up to 2 to 5%. Now I take a very similar strategy. I'll start my inflection points at around half a percent to 1%. Then as the fundamentals develop and I can see that they're establishing better connection with customers, taking market share from competitors or expanding their customer base, I'll then add to the position. I tend to limit these early compounders to about 5%. Let's go over one of Bar's biggest winners. A business that he called Nova Limited. So Nova makes metrology systems used to debug advanced semiconductor manufacturing systems. John's knowledge of technology is what really helped him find this idea. He found it all the way back in 2009. The reason he invested in Nova was because he already owned another business that was a peer of Nova. This allowed him to meet Nova's management team, which ultimately led to his investment into the business. NOVA was signing up big time customers like TSMC and had zero analyst coverage when Barr found it. So he did his own research and thought the business could grow its top line 50% from about 40 million to 60 million, which it ended up doing. Now, just to give you a point of reference, Nova's full year revenue in 2025 is $880 million. Now the business turned out to be a hundred bagger for Needham, but as it increased in price, John has sold bits and pieces of the business as it scaled. He still keeps it at a meaningful weight, but nowhere near where it would have been if he just left it untouched. That's his way of risk mitigation. Now the primary lesson that we can learn from Bar are the importance of letting winners run. Barr discovered that only about 20 stocks he's held have returned 7x to 100x's money, making up the lion's share of his returns. But these businesses only achieve these returns from having these long holding periods. Another Abar's advantage lies in his ability to remain patient. He's prepared to wait up to five years for an investment to work out. Whereas I think most sell side analysts want to position a workout within the next 90 days. You can definitely see the contrast. Many fund managers simply can't handle a business that does nothing for multiple years before breaking out. Barr is lucky to be equipped with the patience necessary to allow his hypothesis to work out, even if it means withstanding some short term pain. Now, Bar tends not to trim unless the Stock reaches about 10% of assets. He avoids stop losses as well as they would stop him out of basically every single one of his 20 biggest winners. If you have a long term strategy in mind, using a stop loss was probably going to handicap you from ever achieving any major winners. One of Bar's biggest losers was in a business called Juan Disco, now called Serrata. So Serrata was an interesting business, so it was founder led and it specialized in data migration. So just to give you an example, let's say you had your data stored with a cloud provider like Microsoft Azure. If for some reason you then want to switch, you'd use Serrata services to move your data seamlessly with minimal downtime to another service. Let's say you know, Amazon Web Services to increase distribution. Serata was in talks with Microsoft to get its product to market. Now the business plan to go live with Microsoft, but a number of delays caused a launch to be set back. Additionally, Barr wasn't overly impressed with their economics, but he still felt they had a pretty good chance to succeed. One of their customers at the time was at AND T, which Barr asked about at a meeting with management. Now the reason that Barr focused on AT&T was. He observed that AT&T had been removed from all of their slides on their investor deck, which he found a little bit strange. When he asked management about it, AT&T said it was, quote, still engaged, unquote, which he thought was a pretty odd answer. Now, the Microsoft and AT&T red flags were significant enough that he just ended up selling it. But the story of this one's pretty strange. So while Bar sold out at a loss, the business actually had a massive spike in its share price due to an increase in reported earnings. So the business when Bar sold was about 3.5 pounds down from his purchase price of about 6.5 pounds. After he sold it, it quickly rose to 18 pounds. Now, the reason for this increase had actually been fraudulent accounting. It then cratered to about 27 pence, where it has mostly stayed since. So now we get to why John Barr was regarded as a lumberjack. So Freeman Shore points out that allowing a business to go down 70%, as it did in one of Bars picks, is not the best capital allocation. This would technically make Bar a rabbit who does nothing when the price goes down, hoping that the price will eventually return to what they bought it at. But because Bar is so diversified, the book points out that his average position sizing is something like 70 basis points. This means that he can actually easily survive these larger 70 drops. If you contrast this with an investor who takes larger, you know, 5 to 10% position, where a 70 drop can have very heavy consequences on a fund's performance. So if he loses big on a loser, let's say that loser gets halved, he's only down 35 basis points. But because of his framework on his winners, where he has a number of these large multibaggers, he's able to easily make up for the large losers that he knows he's going to get. So even though John won't ruthlessly cut a position when it's down, let's say 30%, because of his smaller position size, he can allow for larger losses than an assassin would while ending up with the same absolute losses. Let's say an assassin has a position that's 3% of assets. It drops about 33%. Then they have still lost 1% of assets, which is actually larger than Bar would lose. Now this is a very interesting characteristic and it works if you're the type of investor who actively searches and can actually achieve multibaggers. Fair warning, if you never get multi baggers, meaning you're unable to hold on to your winners long enough to get multiples on your return. This strategy will simply not work because your winners won't be large enough to cover your losses. The next investor that I want to discuss today is John Lin. So he made up the Asian market cohort. John is the Chief Investment Officer of China equities at Alliance Bernstein and manages about 5 billion in assets. He has a 60.5 BA score, a 43 hit rate and a 264 payoff ratio. His investment strategy differs from most of the investors that I've covered so far as he sticks with companies just in China, but like the other investors, he's looking for companies that produce cash and are trading for a cheap price. And he has a very good reasoning to choose China as his battleground. He believes China is unique in the fact that it's one of the few markets in the world that offers quality and value. At the same time, he feels if you look at many stocks out west, if you find something cheap, you're generally looking at a business that has a lot of embedded cyclicality in it and you increase your chance of getting stuck in a value trap. His reasoning for why this arbitrage exists was very interesting to read about. In a nutshell, Lyn believes that retail investors dominate China much more than in the West. And since retail investors in China are so short term focused, it offers incredible opportunities to investors who are willing to take a long term view, but they have to also be able to withstand short term volatility. Now I think the same story plays out exactly the same in the west as well in terms of how retail investors tend to be more short termed. But the share of institutional investor capital is also much higher. Now this is actually all backed up by data. So in the U.S. institutional investors own approximately 70% of the market. In China it's closer to 25%. In the U.S. 25% of households own the market's equity, whereas in China that's more like 35%. So Lynn uses a strategy that he calls the quantamental strategy. Now this is just a clever way of saying he looks at a businesses half through the lens of quantitative analysis and half through the lens of the fundamentals of the business. For the quantitative analysis, he looks at things I've never heard of, like the pain index. Then he'll look at metrics like earnings revision breadth. He says momentum as a quantitative measure is not very helpful in Chinese markets because of what he calls the taxi driver narrative. So imagine this. A Chinese taxi driver buys a stock in January and if it goes up by 10% in February, they're just banking a profit. And even in the mutual fund industry in China, they're actually incentivized to think short term. For instance, John mentioned that in some funds, if you beat your peers for just one week's time, you receive a bonus on the Friday. Obviously this further incentivizes short term trading. Let's take a quick break and hear from today's sponsors.
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- [47:42]
Kyle Grieve
The other area of the strategy worth mentioning is initial position sizing. So his standard position size is about 80 basis points, so pretty small. Now let's move on here and talk about one of John's winning investments. We're going to look at a business called Utong Bus. This is a great study, but from the looks of it, John has invested in this business actually two times and made a profit both times from the looks of it. So the first investment went really well. Then he exited near the top and then once it fell again in 2022, he bought a position. And as at mid 2024 when the book was published, he still held the position for a very good unrealized game. Now let's get into Utong Bus. What is it? They make buses and they're the number one bus company in China. They have two primary segments, the first one municipal buses and the second is tour buses. Lynn noted that Utong is cyclical, so my guess is once he owned it and he became proficient at understanding the cycle better, this was why he was able to buy it again at the bottom of the cycle at a future date. Now, for the first investment he made a pretty large 3% position and as it grew he trimmed it to keep it somewhere in that 3% concentration range. What made him fully sell out of the position the first time was simply that the multiples on the book value were going up fast, telling John that it was time to sell. So Yu Tong's book value increased from one times to four times. So he ended up selling out of the position. Now the interesting part about this case study was that there was no narrative change that acted as a catalyst to sell. The business was still in great shape, but it was getting very expensive. Lyn also observed that the business was being discovered more. After speaking with some colleagues in New York, he learned that they also knew the name Utang bus, which was another signal that he should probably sell. Now. After Lin sold Utong, he kept tabs on it. And shortly before selling, China had been subsidizing buses. But after 2016 the subsidy was completely removed. Now because of the removal, the stock had been out of favor for multiple years. And as it got more and more out of favor, Lyn watched it closer and closer. And eventually he got a chance to buy back in Once the share price began to recover and he felt like the cycle was turning. Now the setup on a second go was really good since sales had been depressed over time. If domestic sales picked up and even just a little bit, they would see a lot of growth. So sales growth didn't need to go back to historical averages to make a return. In fact, he said that they could go to half of historical averages and he would still see really, really good growth in the business. Now these are some of the best situations that you can put yourself in. If a company's shares are so depressed that they can grow at 50% of historical rates and still make a great return, that's basically an automatic bet. Plus you get the added upside where if historical rates return, you'll see a massive swing in growth which can even offer more returns as you'll get earnings and multiple expansion. Now let's go over some of the insights that John had here regarding handling winners. So he looks to add to holdings where things are going well. He will generally increase weightings from about 80 basis points to 150. And if he really likes it, he'll go all the way back up to 300 to 400 basis points. To help determine winners, he looks for fundamental milestones inside of businesses. He focuses on what management is saying and signs of high level execution. Now I want to look at his losing case study. And this is in a business called Longi Green Energy Technology. So this business was a minor loss for John, but it has slid considerably since he sold. Longi makes wafers used in solar panels. This was basically a Covid play. Silicon prices had gone up nearly 10 times and Longi was making an ROE of over 70%. But this is actually a good example where having a large roe can be a dangerous thing. Since other businesses saw the returns that they were getting, they decided to also manufacture wafers. And this increased supply. And since demand is not infinite, it will eventually reduce wafer prices. Lynn realized this, which was why he reduced his position. As it grew, he added again as a result of a fire in a silicon manufacturing plant. But the bump in the share price was very short lived and Lynn wanted to get out before supply increased too much. So he exited at only a 17 loss, which actually sounds very good for managing a cyclical business during a downturn. Let's look at some of the strategies that John employs here around selling. So he doesn't use stop losses because it's unclear how low you should make the stop loss. He said, I know when I should throw in the towel, but it is based on other factors and when I decide to get out, I cut the whole thing. In my experience, selling in stages usually means you just bleed performance along the way. Now this is actually how I like to sell as well. Generally I have a position I want to sell because I just don't like its forward prospects compared to first businesses that I already own. And second to other potential portfolio additions. I've trimmed some losers before to add to other positions, but that's only actually happened twice. Usually if I'm selling, I get rid of the entire position and in those two instances I eventually sold the entire position over a few months. In the other instance I still actually have it, but I've come to realize it was just that too high of a waiting before and I'm more comfortable with where it is now. Now back to John. He doesn't focus at all on the macro and when it comes to handling losers, he's not afraid to double down. But it's definitely situation dependent. If a business is coming down in price while cash flows are going up, then he may add, but if the cash flows are stagnant or declining, he's unlikely to add to the position. Historically, when he's made a poor investing decision, it was actually due to thesis creep. The typical narrative is that the company got cheaper, but it did so because the thesis changed. And John would then alter the thesis to accommodate that change and therefore keep it. But now he focuses more on his thesis and when it's obvious that it's broken, he sells it rather than pander to the idea of changing his thesis. Now this is a really, really, really good lesson because when we make investing decisions, we tend to anchor ourselves to it. There is also biases involved here, like liking bias, where even when things aren't going our way, we stick with the original thought process of liking the business or management, believing that they will have the skill to get out of the hole. And while that is, yeah, sometimes true, it's important to at least ask yourself what you think the possibilities are that a business can improve and get back to the original thesis. If you find yourself contorting things to fit your reality, that's a great signal that you should probably exit a position the Next Investor is from the European Cohort I really like this investor's profile because of his affinity for quality businesses. So the investor's name is Gorham Thomason who manages Ako Capital. Gorham has a 55.4 BA score, a 56 hit rate and a 281 payoff ratio. Now, as a quality investor, you can probably guess some of the traits that he has as part of his investing strategy. He likes quality businesses. He likes market leaders. He likes businesses that have high and persistent capital efficiency and a very strong balance sheet. He also prefers businesses that are growing faster than the market. Gorham doesn't place a high emphasis on discounted cash flows. All he wants to do is make sure the business will have a meaningful growth over the next few years and avoid a decline in its growth metrics. Since he's influenced by Nikolai Tangent, who co created Ako, it's no surprise that he thinks deeply and differently. For instance, when thinking about ideas, he would rather spend time on a business that could be expanded from, say, a 5% position to a 10% position, rather than spending time and energy on just a 3% position of similar complexity. When it comes to debt, Gorm just tries to stay away. He knows that out of his top 10 holdings, only one has meaningful debt. There's no definition of what meaningful debt is here, but he basically feels that if companies are riddled with debt, it increases their chance of having problems during turbulent times. For instance, in 2008 Gorm observed that quality businesses with lower levels of debt flourished better than businesses that had to deal with refinancing while their business was in a poor environment. Gorm is a long term shareholder. Unlike some of the other investors that we've discussed today, he doesn't really rely on things like catalysts, price targets, or specific time horizons for his picks. To understand a business, he believes you need to research your ecosystem, including parties like customers, competition, the regulatory environment, and suppliers. Failure to do this will result in you maybe getting blindsided and losing capital. Additionally, when you're long term, you establish very deep relationships with those parties which allow you to continue to have access to their information. Now, when it comes to scaling into positions, he will take much larger position sizes. Gorham still scales in small, but he's not afraid to take a position to, you know, 6 or 7% by cost basis. His cutoff point is about 10% and he won't invest past that level of concentration level. Now, one of the biggest winners in his portfolio is a business that is very unsurprisingly high quality and one that I think everyone's going to be familiar with, which is Louis Vuitton, Moet Hennessy or LVMH. LVMH, for those who don't know, is a conglomerate of 75 luxury brands like Louis Vuitton, Dior, Tiffany, as well as a variety of other premium liquor bands like Moet Hennessy. Now here's what Gorm said about why he invested in lvmh. The company has all of the characteristics that I want to see in a prospective investment. It's a market leader in an industry with above average growth and pricing power. In an industry where higher prices signify higher quality, its pricing power is in a league of its own. It enjoys a high sale return on capital and has a strong balance sheet. The management has an outstanding track record of acquiring excellent assets. In luxury, LVMH is so powerful that you just don't need to focus that much on competition. You just need to focus on what LVMH is doing. Most quality focused investors focus the majority of their time determining the state of the fundamentals of a business rather than guessing next quarter's EPS numbers. And Gorm is no different. When analyzing lvmh, he and his team determine that success in luxury comes down to just three key areas. Distribution, avoiding discounting, and avoiding chasing the latest fashion fads. LVMH is great at all three of these areas. When it comes to these three keys, LVMH completely excels. Ako has held LVMH for over a decade and in that period it has gone up over 450%. So it's not surprising that the business has a large weighting in the portfolio. What determines Gorm's concentration limits isn't some sort of arbitrary number. Instead, he focuses on the liquidity of the business. This is because if something were to go wrong or the writing's on the wall that maybe the business is just no longer attractive, Ako needs to be able to get out of the position without killing the share price. So a business has higher liquidity, they can afford to have a larger weighting. Now, in terms of adding to winners and trimming, he prefers to do as little as possible. Unless a large market sell off gives him the opportunity to deploy more capital, he'll leave the position untouched other than trimming positions that go above a 10% threshold. Also of note, he rarely trims based on valuation. Now nearly all of this speaks to me. I also tend to focus a lot of my time on optimizing my understanding of a business's fundamentals. While I do some basic modeling to see what kind of returns that I can expect from a business in say three years time, it's more of a product of that fundamental analysis. All the work that I do into understanding the business kind of helps shape how much growth is embedded inside of it. And if the business continues to maintain good fundamentals, then chances are it's going to continue to make a great investment. When it comes to trimming, I'm not picky about trimming about benchmarks. I've had positions get up to 30% of my assets and I slept very well. If I have a position doing well, I'm much more likely to just not touch it and let it keep doing its thing rather than trimming. I like scorm idea there of being picky about adding and trying to stick to adding based around market wide pullbacks rather than just small corrections. Now when it comes to macro, no surprise he doesn't bother with it. He had a great quote here that he learned from his economics professor. I have known many Nobel Prize winners, yet few of them were rich. The point being, leave the academic stuff to the academics as the information, even if it's correct, will be largely useless in the lens of making a quality investment. I spoke about this at length in my recent episode on John Maynard keynes in tip 794, which I'll be sure to link to in the show notes. Now the last point on winners I want to share is how Gorm thinks about taking profits on big winners. For instance, if he had a 5 beggar, would he think of taking profits? Gorham answered that he understood his psychology very very well and he felt that trying to time a position is very hard not only to execute, but also hard to do psychologically. If Ako were to sell part of a winning investment, it would be unlikely that they would add to it again in the future. And since multi baggers are just so rare, his best option has always seemed to be to just do nothing. Now let's go over one of Gorm's losers. A business called Just Eat. Just Eat dominated the food delivery market in Dutch and German markets. So Gorm's thought was that they could continue to take a dominant market share in other geographies as well. But the fundamentals said differently after the fact, after it became clear that they would not be able to achieve dominant market shares in the US and UK markets, they exited at just a 10% loss. Now Gorham discussed a mental model that he calls the boiling frog to help him uncover a smoke signal early in a business before the market gets spooked. So for those who don't know, the boiling frog is a metaphor for placing a frog in, you know, blue warm water and then gradually increasing the temperature until the frog just boils to death. Gorm is going out and actively searching for where the water is starting to heat up, potentially signaling that the thesis might be broken down the road. One example that I have on this is actually in one of my biggest losers, which was simply Solventless Concentrates, a cannabis roll up company. So I ended up losing 69% on this one position. So the reason that I exited the position in the first place was that the accounting just got more and more confusing. And I found it odd that it got to this point since the CEO was a former CFO and therefore I thought should have been able to understand and portray the books in a very understandable manner to the market. While it initially appeared to me that maybe the business could still work it out, I was just not comfortable holding onto it and I ended up selling it. So, you know, that was my frog boiling point. Unfortunately it was probably kind of late. I would have loved to have sold much earlier, but unfortunately the waters for that company have continued to get hotter and hotter. They've had a number of acquisitions that are now being restructured in bankruptcy court that clearly states that they're not working out. So since I sold my shares, they have fallen an additional 70%. So even though this was a painful loss, it could have been much, much worse. Now the final investor I'd like to cover is Andrew hall, who manages a global investing strategy at Invesco. So hall has a BA score of 62.3, a hit rate of 48% and a payoff ratio of 182%. I really like Andrew's investing strategy. Since he's global, he can invest wherever he feels comfortable investing. And his focus is on businesses that can reinvest earnings at a High rate of return. He clearly has a very good idea of how compounding works because the math is just simple. If you can reinvest most of your profits back into a business that generate a high return on investment, you can continue feeding the compound engine for a long time, which generates exceptional shareholder returns. Now he utilizes a stock comparison sheet to help with his decision making execution. The stock comparison sheet shows metrics such as the forecasted total shareholder returns over the next decade. That way he can compare two businesses side by side to see which one's offering the best forecast returns based on its current price. He can also track total shareholder returns on potential positions, which help him determine buy and sell decisions. I do something very similar, so I track all my businesses and I forecast them on three year returns for the businesses. Now I purposely chose three years because I just can't forecast 10 years ahead. So I just stick with the shorter time period and I adjust the numbers annually as the fundamentals of that business change. It helps me see what's cheap or expensive in my portfolio and where I may need to adjust my growth numbers. Now Andrew also has had about 10 to 15 positions that act as tracker positions that he follows closely in case the price is right to meaningfully add to those positions. He calls this the farm team. This consists of positions that maybe did really well in the past, but he ended up having to trim. Or they could just be starter positions that haven't given him a good enough chance to add to meaningfully yet. Andrew has had a few great winners, and one of them being Nvidia, a business that most listeners are already going to be very familiar with. So Andrew had done research on Nvidia back in 2018, but at that time the business was much more focused on graphics cards. Hall noted the business was a little too boom or bust for him at this time and he just took a pass on it. So if you fast forward a few years to 2021, his view of the business had changed. After discussing it with another analyst, he saw Nvidia as a play on data centers. He and his team looked at all the data centers in the world, assessed their needs from Nvidia and determined that Nvidia now offered asymmetric upside for scaling. He started at 0.5%, then doubled that within about six months to a 1% position. He trimmed the stock back in 2023, but he admits that was probably a mistake. So his reasoning for trimming was that the asymmetric upside angle started to become less powerful since the market was underwriting a 75 GPU penetration. He felt that the cat was, you know, out of the bag and that previously existing asymmetry had disappeared. Now, I completely resonate here with his case study on his loser, because it was loser for me as well. And that case study was for Alibaba, which is a Chinese e commerce platform. So he bought this in April of 2020, nearly bottom ticking it during COVID He trimmed on the way up. Then he ended up selling around the time that their founder, Jack Ma, began speaking out against the government. After selling it, it dropped an additional 62%. Now, unlike Andrew, I didn't make it out nearly as unscathed. I lost 24 annually in this position. Unfortunately, the position was just too large for me. So this loss was actually negative 4% on my contribution margin. So hall did a much, much better job containing his losses. Now, there are so many other great investors in this book that I just couldn't get to and a number of short sellers as well. So it goes to show that you can truly succeed in investing in a multitude of different ways. I had a number of insights on how these investors invest and how it's different from what I'm doing. So I believe many of the differences stem from being an institution versus managing my own money. But here are some of my biggest takeaways from today. The first is that decision making trumps stock picking. Two investors can make the same pick but have dramatically different outcomes based on how they treat the position. As in the Alibaba example I just discussed, Andrew managed the position very well, whereas it resulted in a large loss for me. Second is ride your winners. If you must trim your winners, at least keep them in your portfolio so you can continue to reap the rewards. This is an area where I differ from most of the investors outlined in the book. I am okay having a position that goes up to, you know, 20% plus in my portfolio. Institutional investors are not okay with that as they have regulators that track these sort of things and they have position limits that are explicitly stated with their investors or partners. Since my approach has worked for me and I have no position limits, I don't intend to change it as doing so would have dramatically limited my upside performance. And third, here is just have a selling strategy. I don't think you have to limit yourself to being exclusively an assassin, hunter or lumberjack. Since I run two kind of different strategies. Being a hunter, and one wouldn't make as much sense as in the other strategy. For my compounders, I think being a hunter is probably the way to go. But for my inflection point businesses, I tend to lean towards being more of an assassin. And I think there's a general trend where low turnover investors tend to be hunters or lumberjacks and higher turnover investors tend to be assassins. Now I'll close this episode off by saying that execution matters, and it matters a lot. Position, size, scaling in out of positions and maximizing your winners while minimizing your losers are all just as important, if not more than finding your next big idea. They are all aspects of the art of investing and while you can never optimize for every single one of them, you must devote attention to each in different doses to maximize your compounding abilities. That's all I have for you today. Want to keep the conversation going? Then follow me on Twitter rationalmrkts or on LinkedIn. Just search for Kyle Grief. I'm always open to feedback, so please feel free to share how I can make this podcast listening experience even better for you. Thanks for listening and see you next time.
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Tip
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