Chris Mayer On 100 Baggers

TITLE: Chris Mayer on 100-Baggers CHANNEL: MicroCapClub DATE: 2016-11-15 ---TRANSCRIPT--- [Music] all right thank you very much for that intro and it’s good to good to be here it’s a tough tough act to fall a lot of great speakers this morning so I’m going to talk a little bit about 100 Baggers and what I’ve learned doing the research on 100 Baggers the last 50 years or so and then at the end I’ll have an idea to talk about I’ll uh bring up Thompson Clark who’s the lead analyst helping with me uh helping me in the family office and we’ll go through an idea cuz know you don’t care about what I’ve learned you want names right so first let me talk a little bit about how this got started so there’s an investor you guys may know Chuck Acra he’s an excellent investor and in 2011 he gave a speech called the invest an Investor’s Odyssey you can Google it and read it i’ I’d highly recommend it he talks a little about his investing approach and he’s uh he’s actually had 200 Baggers to his credit he’s owned Burkshire for a long time and the other one was American Tower um and in that speech he talks about a book called 100 to one in the stock market written by a guy named Thomas Phelps and this book came out in 1972 and what Phelps did Phelps was a uh well he was a lot of different things he was a money manager of no particular distinction as far as I know he was uh he worked at the Wall Street Journal for a while he worked with Scutter Stevens and Clark so he had a varied career and he wrote this book which was a look at all the stocks that had gone up 100 to one from 1932 up until when he published the book and the idea is just to see if he could find some similarities and use them in in investing today so his book is is very well written it’s very folksy uh very quotable and so I I read that book and I fell in love with it right away and I started to quote it and and talk about it and finally a reader asked me he said you know you should really update it so I thought well that’s a that’s a good idea so that’s where my book came in was really an update of phelps’s study I looked at all the stocks that had returned at least 100 to one from 62 uh to 2014 and that’s as far back as I could get data was I used cyat data and I screened out some of the tiniest names so you know like the 12 cent Junior Mining stock that goes up you know three bucks and the idea is really just to find if there were any similarities or qualities that a lot of these stocks had that we could look for in investing today so I got to 365 different names so just to go a little bit through some of the outlines of what this uh what they look like just in very broad terms this gives you an idea of sort of how long it took so you know most most of them fell in that column there took between 16 and 30 years and uh it’s really just a math problem at this point so this shows you the number of what rate you have to compound to get to 100 Baggers and how many get to 100x and how many years it takes you to do it so if you compound at 25% a year it takes 21 years to get there so it sort of gives you the outline already of the hurdle that you have to get over it’s a compounding at high rate for very very long time so the main point of this chart this shows you the top performers in the study and the main thing takeaway here is just to note that there were really no industries that dominated the list there’s all kinds of businesses on here so you have you know an airline actually in Ian’s book Southwest Airlines is one of is a very good case study uh you have a retail you have uh you know a railroad way up there which was surprising um but the railroads are interesting case studies too because they own so many different assets and they wound up spinning off things and so they became tremendous creators of wealth Kansas City Southern actually owned Janice which which helped them helped that return quite a bit and then normally it takes a long time but here’s some of the fastest uh to 100x uh this just again kind of an interesting list because it again includes a number of different businesses NVR is a homeb builder which you wouldn’t normally think of a business of a business you can make 100 to one um Valiant is on here and a funny story about that is that um in the book I pull out a number of these and do sort of little case studies on them and um monster beverage was one Pepsi was one uh Gillette Amazon and uh I I thought it might be good to do Valiant because it was kind of a well-known name this is when it was still you know climbing on its way to $200 and Thompson is one of actually one of the analysts was helping me work on these case studies and uh I remember his call from May 2015 he called me he says you know I I can’t figure this out I don’t know you know I don’t know how they make money and I said well we’ll just skip it let’s let’s pick something else you know if I was really paying attention about what do you mean you can’t what do you mean you can’t figure it out what do you mean it would have been a great short idea cuz it subsequently collapsed so a good thing I didn’t put that one in the book so I’m just going to go over some of the kind of kind of take out some of the dis tell some of the main lessons and the first one’s kind of obvious and then I’ll go through some others so the first one is we are at the micro cap conference so let’s throw the micro cap space a bone uh you have to start small or helps to start small and and Ian had a great slide where he showed a number of great companies that you know today are enormous and we know are great companies that started off very small um once may be surprising thing to point out is that at least in the 365 stocks that I pulled together for this study um they were small but they weren’t tiny it’s kind of like the median sales figure is about $170 million that’s you know pretty substantial business the second lesson here is uh or one of the most important lessons is we got to hold on to them for a long time and and that may seem obvious but I I have a story to tell you that uh I just want to pull out some notes here because I want to get some of the details right although it doesn’t really matter you guys wouldn’t know if if I’m telling the truth or not um but as a friend of mine who’s a hedge fund manager had bought this uh painting and this illustrates so many interesting things about investing for the long term but in 1999 he bought this painting it was a it’s a painting by Ed rusa called Sunset to Pico and he paid $150 $150,000 for it you know his wife thought he was crazy it was by far the most he ever paid for art but he’s a hedge fund manager decently successful wasn’t like you know broke broke the bank or anything so he takes this picture and he hangs it up in his uh you know whatever his in his living room and he likes the painting he leaves it there and he hears over time that you know painting is probably worth more than he paid but he doesn’t think anything of it and so finally last year he decides to that he’s going to sell it because he’s getting older and he decides he wants to pay off the mortgage on his house and he’s just thinking to do some things so he goes to soube to get it appraised and they tell him they think they can sell it for a million bucks so you know remember he paid $150,000 so he goes and uh puts it up for auction and the way the auction works is you put up a reserve so that he put up a number that you’re not going to sell out for less than and that number was 850,000 so the bidding starts at 500,000 he tells me the story like he’s all excited and he gets there with his wife and daughter and all dressed up and it’s like going to Derby Day or something so they go there and the bidding starts and very quickly it gets to 850,000 so he you know breathe the side relief he finally he sold the painting and the bidding keeps going it hits a million dollars and he takes a a picture of it and uh say you know wow I sold the painting for a million bucks bidding keeps going up to a million5 and then the bidding starts the flag a little and and she’s getting ready to hit the gavel and someone comes in million six and it keeps going million 7 million 8 uh hits 2 million 21 22 when she finally hits the gavel it’s $2.3 million so he’s telling me the story and the first thing I said was you know if if that was a stock you never never would have held on to it that long so so when you think about why why is that you know what helped him hold this painting all this time to make that much money at the end and I think one big reason was that he didn’t have somebody coming in every day offering him a price what what they’ pay you know just imagine like when we own stocks we see stock price every day oftentimes multiple times a day we’re checking our stocks checking our stock it would be very very hard to hold on to that painting if you know you had someone come and every day hey I’ll give you $500,000 for come on and then two months later say no I’m going to give you 250 you know think how it works on your psychology all that stuff so one of the big lessons of that I think is that you can’t price your performance so much uh because it just wears on you and then the Phelps book The Original Phelps book he has a great uh one of my favorite tables in the book is as a a table of fizer’s financial results and I think it’s like sales then income but one of them is definitely return on equity and it’s for like a 25y year period of time and and he just says looking at this column of numbers is there any point where you would have sold this business and so it starts from whatever you know 19 let’s say 40 whatever and you see it’s 20% Roes very high Roes every year yeah some a little lower some a little higher sometimes sales are flat maybe there’s a year where it went down but just looking purely at those numbers you would never have sold that business but yet and you would have had 100 times your money if you held it but of course lots and lots of people sold that business and why because they saw the price every day and they read the newspapers and you see interest rates going up down and wars and depressions and cats and dogs living together and all kinds of crazy stuff and you know you would never You’ never have held on to it but if you just followed the business it makes it easier so in the book I talk about this idea none of us are going to do this but I just like the the metap metaphor of it and and uh maybe maybe it will help you this this idea called the coffee can approach um actually I had a reader of the book tell me that he has a coffee can now on his bookshelf to remind him of this idea I thought that was kind of cool but this is an oldfashioned coffee can there was a guy named Robert Kirby who was a very famous money manager for Capital group he wrote a number of famous essays one of them was called the coffee Canon it was in the Journal of portfolio Management in 1984 so the idea goes that you know in the old west when you had valuables or something you put in an old coffee can and you bury it somewhere and and that’s how you storage are varable valuables whether it’s true or not I don’t know but it’s interesting story and so he he got this idea because he managed this uh one of his clients he managed This Woman’s account and uh over time you know he made buys and sells and then years and years go by and her husband dies and and he she takes uh her husband’s accounts and gives them to Kirby to manage and so he gets the account and he’s amused to look at it and say it has all the stuff that he been buying for her you know he’s sort of his piggybacking on his ideas with one difference which is that he never sold anything and so you know he’s he’s looking at the list and he’s like my God you know some there’s some of these stocks that are just huge positions and there’s one stock that’s worth more than his entire account that he’s managing for her now and so he he writes about you know the power of the of the coffee can and how again it’s this um this idea that you don’t want to price your performance every day all the time and how much that can really affect your investment results so um another thing I’d like to say or like to add here is that lower multiples preferred it’s tempting when you look at these 100 Baggers to think that it doesn’t matter what price you pay you know if something’s going to go up 100 fold but it does really matter and a lot of these stocks uh started at fairly low multiples and then over time not only did their earnings grow over time but so did the multiple and and there’s lots of examples of this there’s one that I put in the book that um chip Maloney of micro cap Club wrote up which is most extreme example I found and so that’s why I used it which was mty foods which went from trading at like three times earnings when nobody gave it credit for anything and at the end of 10 years it was trading for 27 times earnings so even though earnings only went up something like 12-fold it turned into 100 bagger so that really can really provide a very nice tailwind and there are other examples Gillette in the 80s was was one that I remember where it was trading something like 10 times earnings at the beginning and then at the end is was trading for 30 times earnings and then there are examples on the other hand where you start off with a high multiple um and earnings grow but your return Isn’t So great because the multiple went from 50 to 25 so that’s an important um Quality to look for although we can overdo it and what this table just shows you really quickly is it’s basic math and you all know it but sometimes it’s helpful to see it again which is the difference of having two companies one that grows 20% a year grows earnings 20% a year one that does a 10 and you can see after you know the end of 10 years the amount of earnings that you get with the faster grow is enormous enormously larger so even if you know you wound up paying 20 times earnings for company a and at the end of The Run you’re down to 10 times earnings you still you’re still going to wind up probably much better than if you were with Company B so one lesson is that you you know you have to take into account those growth rates and you shouldn’t be um afraid to pay up for something that’s going to grow especially if you’re pretty sure about it this one is really important High Returns on Capital almost all of these businesses that became 100 Baggers were at the end of the day they were really good businesses and they earn very high Returns on on their capital and this reminds me of a Charlie Munger quote got to have the obligatory M quote where he says that over the long term it’s much harder for you to earn much beyond what the business earns on its Capital so you know it’s interesting experiment because people say well you know do you have any hund Baggers or they want they want to kind of know that the stocks that might be 100 Baggers but the first step is really identifying those businesses and I would bet that if we were to you know say we had to come up with 10 names and collectively we all had degree 80% of us had degree before we put it on the put on the board that we could come up with a list of some very good really good good businesses I don’t know if that’s the hardest part I think the hardest part is is kind of knowing when to buy them and and hanging on that you know that long so uh one other thing that and other speakers have talked about this this is something that wasn’t really necessary in the study there are lots of stocks that went up hundredfold that didn’t have owner operators or relatively faceless management teams you know you look at Gillette I don’t know if the CEO of Gillette necessarily was you know so critical in that case you had just such a great business model but there were uh there it did appear enough that it was important to have a face so when you think about some of these businesses you you can think of the people involved if I say Walmart you know you think of Sam Walton if I think Microsoft you think Bill Gates Apple Steve Jobs and you go on and on there’s there’s often not always but often a brilliant entrepreneur Behind These companies so there’s a lot of other empirical evidence Beyond more anecdotal hund bagger study is just um you know it first off it makes intuitive sense when we think about the the kind of feedback you get when you’re an owner versus if you’re a Hired Hand and then there’s a lot of additional studies so on this slide I have a few that I thought were interesting there’s plenty plenty more I’m sure you can find uh many more studies but these are some that um I thought were pretty good uh one of them just says the historical stock performance of companies managed by world’s billionaires tend to outperform and the paper goes on to think um to put forth a number of ideas maybe why that is billionaires are very well connected and they know people and they can get things done in ways that maybe lesser Mortals can’t uh family uh family Leed companies is another one that’s uh been mentioned again today and then there’s plenty of anecdotal evidence uh The Outsiders of course you’ve all probably read and uh Ian’s book which I read last week which I think is also excellent has a number of great case studies most of these uh people who ran these companies that became huge successes uh were owners and they behav like owners an older book that I like a lot um is called Silent investor silent loser it’s been out of print for a long time but you might be able to find a used copy um it’s a fun read um and Martin snoff is a uh is a money manager has been a money manager since the 60s um and he has a quote in here that I you can read it but there’s a part in here that I particularly like where he says that entrepreneurial Instinct equates with sizable Equity ownership which I’ve certainly found to be true and when I look at companies I that’s where I often start was we’ll start with the proxy and see who owns what and um and what their incentives are so those are uh a summary of some of the things that have come out of the study and there I WR I’ve written about them in the book that I think all these are are important but really the most important thing of all is something that um uh Chuck ARR too has uh talked a lot about so this is a this is him quote from you can read it but it’s really that idea of being able to reinvest so not only do you have to have a a great business but it has to be a business that can then take all of its profits and reinvest and earn that same return again and again and again and that’s really where you get this sort of magical uh flywheel effect and then the most important lesson of all um is just in looking at these stocks is I think that it’s it’s there are two things really one is that it’s both a roller coaster and it’s also can be incredibly boring to hold on to these stocks so first the roller coaster part is probably one you you are more uh you would think of first but just to take a couple examples like apple for example suffered four different 40% drops over the last two decades including a 60% drop in 200 uh on its way to 100x so that’s you know that’s quite a challenge to be able to hold hold a business through those kind of draw Downs another favorite of mine to use is Netflix which is a 100 bagger since 2002 and it’s lost uh 25% of its value in a single day four times I mean that’s really that’s that’s pretty brutal um monster beverage which is a case study that I write about in the book it was a 100 100 bagger in a 10-year run but in that 10- year run it had a drop of more than 40% drop of more than 30% and had several 20% plus drops um so you know the defense there is you really have to know the business I think and even then it’s it’s going to test you psychologically and then it can be very boring so I just pulled out randomly it was really just eyeballing the the companies that are in the study I have this vast spreadsheet and you I can just see there’s lots of times where these stocks just went nowhere for for for pretty long stretches so just to pick out a few Bank of New York melon went sideways from 1976 to 1981 amidst 100x run so if you own that stock and you just held it uh for about 20 years you up 100 to1 more than 100 to1 but there was you know five years there where it did nothing Texas Industries was Sideways from 80 to 85 American Express was flat from 85 to 92 you know these are these are very taxing things and um I’m sure you’re all investors most of your investors is room and you can appreciate how difficult it is to hold on to a stop for that long that goes nowhere because we’re in the business and we see new ideas all the time and we get excited about things uh but the lesson of 100 Baggers is that you have to hold on to these things for a long time U my question is on the hund Baggers uh I’ve read some of your articles on that and I I uh I love it I think you’re you’ve really highlighted a great thing so don’t take my next comment too snarky which is is a 100x also a good sell sign because I can think of a lot of companies that hit their 100x in the 90s Microsoft Oracle visor that haven’t hit Cisco that um are still selling for Less today than they did 15 years ago yeah so should we sell at 100x or should sell at 90x or 110x it’s a real high class problem to have yeah I think that’s what they call a high class problem right do I sell at 100x or 90x um yeah I mean that’s it’s almost almost a little bit like analogy with uh earthquakes is you know you don’t know the difference between a small earthquake and a big earthquake is it just a small earthquake just keeps going and becomes a big earthquake it’s really hard to tell when they’re done um I don’t have a good answer to that other than to say that a lot of these that went beyond 100x you know they’re if you again if you just focus on the business you would never have sold it so I would only I guess the main way I would answer that is to say to really focus on the business not so much the price because you can have a stock go up 100x and still be a bargain when you’re talking about in the late 90s definitely uh you know a lot of those stocks were outrageously priced it would be hard to hold on to those uh but I’m thinking of other stocks that I remember seeing in the study that went up 100x and were still pretty reasonably you know valued they weren’t ridiculous and you might have continued to ride it if the if the economics were still in place yeah Amazon I even thinking of monster beverage because again that one that apple or Monster Beverage is one of the ones that you know went well beyond 100x and again the economics of that business never really changed hi um I’ll caveat this with the fact that uh if I wasn’t you know looking for this type of thing I wouldn’t be in the room here but um just to hear your point of view so they’re about 365 over the past 50 years or so if you look at the past decade there’s a whole lot more private money out there that funds things much further up the growth path so if you look at when an Amazon went public to a Google to a Facebook it’s just they’re coming public later in the game um where do you see you know the number of potential Public Market H H Baggers going over you know 20 years from now yeah and that’s a good question and I think uh you know when you combine phelps’s study and my study you get to cover a pretty broad uh 70 80 year period of time and um there are all different points where you might say uh there would be more or fewer hundred Baggers but the number is is of any given time there’s always there’s always a bunch I mean there’s always multiple multiple companies you could buy any month in any Market any time and made 100x true I mean like in 1932 there’s a lot more opportunity than there was say 2000 so the market has some impact and what you’re talking about is a more you know a structural thing having to do with the market today I don’t really know maybe that you know that’s true um that it would uh affect number going forward or not but I don’t know I don’t um I don’t necessarily worry too much about it again because I don’t know that I get too hung up on if it’s actually going to be 100x or not I mean I’m just looking at companies that have these same kind of economics and and the supply is going to e and flow I’m not sure I have a really good answer to tell you about you know where they might be in the future yeah um one uh I I totally agree it’s it’s very difficult one key problem I think is that before let’s say over the last 50 years the if you take what Buffett did a lot of a lot of what he did is basically ride very gradual dis disruptions like Walmart is Was A disruption to M and pops and so he had time to understand and being able to predict certain businesses if you look at the last 10 years disruption have become far more faster what took 50 years now can take 3 to 5 years yeah you know getting to 100% penetration rate the population you know if it was TV newspapers all of that took 50 to 100 years now it’s like a new mobile app can take you know can get to 10 million in like one or two years right which also means it will disrupt somebody else so that makes the whole thing more difficult you cannot Escape you cannot Escape dealing with with techn technological disruption as you could uh let’s say over the last 50 years MH uh yeah no that I agree that and that’s empirically true there’s a section in the book where I talk about the um lifespan of companies and you can see you know you probably all read this elsewhere where the it’s it’s shrinking and I think on the S&P 500 population it’s maybe down to 15 years or something like that so that makes it harder uh on the flip side I guess you could say that the the acceleration to get there is faster too I mean the number of companies that you know that have those kinds of runs these days that do it in less time but the whole game is much more difficult you it’s it’s really difficult to think of a business that you could sit on today for 20 years that’s not going to that doesn’t face some sort of existential threat from disruption somewhere it’s definitely true last question we’ll take a break then so Chris uh amongst the things you you highlighted what you learned U I was wondering if it’s the same thing Tom Phelps uh learned in his study and the second part was what is the predictive power of these learnings like uh like if he learn similar things and if you do what is stati stati people in statistics do call out of sample testing they they test it over a sample and then they test it the results over the sample uh for which from they have not drawn drawn the conclusion so um I don’t know if I’m making myself clear which is um um you learn these seven eight things and then you apply it to a part of the sample from which you’ve not donear that learnings and does it still hold so what basically getting to what is the predictive power of these learnings yeah yeah that’s a good question so the first part was Phelps um yeah I mean I think with Phelps there were the conclusions were very similar he I mean there’s when you think about it there’s only there’s some basic rules here with 100 bger so to get to 100x you know you have to compound at a certain rate over a certain time to get there and to compound at a certain rate you have to do certain things you have to have certain return on Equity return on invested capital which implies certain margins which implies certain sales growth so some of it’s comes down to that and our conclusions are similar you know in his book he talks about other things uh investing abroad and he answers some different questions than I chose to focus on but the results between the two books is very similar if you read them both um very similar as far as predictive goes um some things are a lot are seeming are seemingly more predictive than others like the owner operator thing is is I would say is predictive and you can look at a number of studies and and see that as a class CEOs that have 10% or more of the stock against CEOs as a class that have less than 10% of stock they do better they outperform their Hired Guns in the book I talk about a couple other predictive attributes like for example high gross profit margin tends to be predictive and sticky so companies that have a 55% gross profit margin tend to keep it whereas companies have a a a more narrow gross profit where that doesn’t persist as much and again this is in data speaking of Cl lots of input so there’s lots there’s always exceptions um so that’s that’s an interesting one the gross profit um high gross profit margin is is predictive um those are two that come to mind right now maybe I if I think of another I’ll let you know well um I guess we’re done but thank you very much for your attention your time appreciate it [Applause]