I mean, having a fixed mindset, and I’m specifically talking about Steve Case, the AOL founder and Paul Allen. To me, that seems at least for a billionaire, seems to have somewhat a fixed mindset. I think it’s interesting to see how they’ve been successful in business, but perhaps just with one business. 

Whereas, I’m looking to someone like Reid Hoffman, and we talked about his book in episode 125, where he talks about PayPal, his success with LinkedIn, and now having a successful VC [venture capital] company. And not only in terms of net worth, that’s actually not really what I’m talking about. But how they came off as really happy and always learning and connecting with smarter people and really try to grow that way. 

Whereas, if you read Paul Allen’s book, “Idea Man,” which is also a really great book, there’s a lot about rivalry with Bill Gates. And there’s a lot of really negative emotions attached to that. And I think a lot of that has to do with which type of mindset we choose to have in life. So, I think if there’s a really one takeaway for me, really just to kick off this show, it’s about choosing your own mindset. And by doing so, you will basically balance your financial success and your happiness. 

Preston Pysh  4:49  

So, I completely agree with you. I mean, this one’s huge. And, believe it or not, my first point has somewhat to do with your point, but it’s not going to seem very obvious when I first start describing this. 

So, we had an interview where we were talking to Brad Stone, who’s this huge writer out in Silicon Valley. He wrote the book on Jeff Bezos. At the end of the interview, and I can’t remember how much it actually made into our final cut, but we had an in-depth discussion with Brad about what’s coming next in Silicon Valley. He started talking about artificial intelligence. He was just telling Stig and I like this is going to be such a game changer that people don’t really realize it is coming in the future. 

Honestly, I know nothing about artificial intelligence, and so I started doing some research after talking to Brad Stone on why all these billionaires out in Silicon Valley are investing heavily into artificial intelligence, and I guess what’s changed that’s made this such a big deal. 

And through a little bit of research after that show, I came upon a gentleman called Demis Hassabis. Demis is the founder of a company called DeepMind, and DeepMind was recently acquired by Google for something like $700 million or some outrageous number. 

Let me just tell a little bit of a story about this gentleman because this stuff is so fascinating. It is just mind blowing how much this is going to impact you as an individual in the next five years and how much I’ve just learned through that little quick conversation with Brad Stone. 

So, the story about this Demis Hassabis is fascinating. At the age of 4 years old, he started learning chess. By the age of like 12, or somewhere around in there, Demis became like a grandmaster. He’s one of the best chess players in the world. And so, this guy is wired for like, just, he’s one of the smartest people around. 

Well, he goes on, and he starts programming. He gets into this programming stuff in his teens, and whenever he was something like 15 years old, or somewhere around in that age, he programmed a chess game to play, and he actually, in one of the interviews I saw with him, he said that the chess game was so good that it actually beat some of his siblings whenever they played it. 

Now, for anybody who’s ever done any programming work before, programming chess is so hard, because there’s so many different outcomes that can occur in that game, to the point where I don’t know how anybody could even begin to start cracking that code because there’s so many different positions and so many different moves that can be made. So, he’s doing this in his mid-teens. 

Long story short, by the age of, I think it was 17 years old, he created one of the very first Sim games, and the Sim game was about creating an amusement park, where the player can create rides, and then these fictitious people show up, and it was the very first attempt that he had made to use artificial intelligence in this game where the people would show up, and they’d bring friends if they liked the amusement park the next day. 

This thing went on to be a huge hit. He made tons of money with this video game that he programmed and long story short, he has this history of working with artificial intelligence. Well, he goes off to Harvard. He gets a doctorate in neuroscience, and he starts studying the brain and how the brain works and all the neural networks within the brain. 

He then went and founded this company called DeepMind. What DeepMind is all about is using machine learning, artificial intelligence, and what he’s done is he basically mapped out how the human brain works through neural networks and hyperdimensional space. And he’s recreated that into a computer algorithm. 

Now, I know all this stuff sounds absolutely crazy. But there’s a video out there that I watched. Stig and I are going to put this in the show notes of this episode. In the video, what he talks about, what Demis talks about is, I wanted to take an approach to artificial intelligence where we basically created the human brain on a computer. 

And to test that out, what he did is he took all these 1980s video games like Atari and Nintendo games, and the input to the computer was simply a video capture. They hooked up like a video camera to look at a TV screen, and that was the only input into the computer. So, it’s looking at the pixels on the screen, and that’s the only input that the computer is receiving. And then, the computer is told, alright, you have a joystick. You can move left, right up, down. You got an A and B button or whatever it was, and that’s the only thing you can control. 

Now, once he set up this computer to do this scenario, the computer had no idea how to play the game. It had no idea what it was doing. All it was doing was looking at the screen and it knew it could control the little player on the screen, and it was told to maximize the score. Look up here in the top left side of the screen, and whatever gives you the highest score, that’s what you’re trying to maximize, and that’s the only thing that the computer was told. 

So, in this video, he shows the iterations of the computer playing the game. And so the computer is playing it at first. If you ever see the game Pong where there’s like a little bar at the bottom and the ball kind of bounces around. It bounces off the side of the screen. So it was playing a game like that but only at the top of the screen there were these blocks. And the ball would bounce off the bottom of the little bar that’s being controlled, going left and right. When the ball goes up, and it bounces off the blocks, and it would break up the blocks as it would do this. And the goal was to not let the ball drop below the little bar that the person is controlling. 

He shows the iterations of this. And the very first iteration, the computer is controlling the little bar at the bottom and it’s all over the place. It’s not working well at all. It’s failing. It’s not able to do it. But then he shows, okay, so this is what the game looked like after 50 iterations. And the computer’s learning how to control these inputs and trying to maximize its score. And he says, “We haven’t taught the computer how to play the game at all. We haven’t said, ‘If the ball moves here, then do this. There’s no if-then statements or anything.’”

So, I’m sure there’s some in the code somewhere, but as far as my technical knowledge of programming, you got to bear with me here. So, after 50 Games, he looked at how this thing was performing, and the game was starting to figure out that it needs to move the bar in order to bounce the ball, and it was getting a lot better. It was still making mistakes but it was getting a lot better. 

Then, he fast forwards and he says, “This is how it performed after 300 games.” And after 300 games, the bar at the bottom that the computer was controlling was not missing this ball that was coming back at all, and it was bouncing up, and it was hitting the blocks, and destroying the blocks at the top of the screen. And so, he says, “After 300 games, we had the computer performing just as good as a human.” He said, “Then, we got this crazy idea like what would happen if we just let this thing play 600 games.” 

And so he fast forward. He showed, okay, this is how the computer played the game after 600 rounds of this thing learning. And lo and behold, the game or the computer had figured out that it needed to knock the ball off the left hand rail of the screen in order to knock all the blocks that are aligned to the left side of the board, and it buried like a hole into the left hand side, and then the ball got to the top where there was a little gap, and the ball was actually knocking all the blocks out without the computer even controlling the bar at the bottom. It was automatically doing it. It figured out it needs to burrow a hole on the one side, and then the ball would just take care of the rest. 

And he said, “The most fascinating part of all this is,” he said, “Our programmers are really good, but our programmers had no idea that this technique could even be done in the game.” And so he said, “What had happened was we created an algorithm that ended up teaching us how to play the game, which was totally mind blowing for me.”

Now, this is just a little 1980s video game. And just so you know, the algorithm was applied to every video game that was loaded into Atari. It wasn’t just this one game. They were able to apply the same algorithm to all the games. 

Now, this is where my mind basically has exploded recently with where all this is going. So there’s a Chinese game called Go, and for anybody that’s ever seen this, the board has 49 positions, basically like when you look at a checkerboard. It’s black and white, black and white. Only in the Chinese game of Go, it’s 49 by 49. So it’s a huge board. 

There are more positions that can be played in this game, than there are atoms in the entire universe, to give you an idea how complex this game can be, with respect to how many positions can be played. And that’s not something that I’ve just made up. That was actually a quote from Demis Hassabis, the founder of DeepMind himself.

So in the past, the professional, the best players in the world at Go have never been beaten by a computer ever because it’s such a hard programming challenge to program so many different positions. So what does DeepMind do? They take on this challenge. What they did is they loaded all the past games that have occurred with this Chinese Go into the index, so that the computer had a baseline of how it should play the game. And then they did this. 

This is what I find so fascinating. They took the computer, and they made it play itself to get better at playing the game of Go. They set it against itself. And then then they made it play itself like a million times, and every time the game lost to itself, it learned why it had lost, and it got better, and it got better, and it got better. 

And back in January of 2017, there was a tournament where an individual from China was playing. He was one of the top 30 or something in the world. And he was playing against this unknown competitor, and it was over an online platform. 

Well, lo and behold, this unknown competitor ended up beating him. He was so devastated that he checked himself into the hospital because he was so mentally fatigued from the situation that he couldn’t believe that he lost. He couldn’t believe he lost to somebody that he didn’t even know. And there’s a very profound point that I’m getting to with all this. So hear me out with the rest of the story. Lo and behold, it was revealed that the person was actually playing DeepMind’s Go computer, and he had lost. 

Just recently, I think it was in May of this year of 2017, the DeepMind Go computer took on the number one player in the world and beat him, four out of five games. And they’ve never programmed this computer on how to play the game. They’ve just set it loose on taking the inputs from its environment and continuing to pursue being the best and learning as it goes along. 

So, there’s so much more that we could discuss on this topic. I want to give you this background, a) because I find it very fascinating, but, b) because it actually ties in to Stig’s point about mindset. So if Stig’s talking about mindset and how you have to have a positive mindset, you have to have a growth mindset when you’re trying to achieve something and that you do it over and over and over again until you actually figure out all the variables at play and you’re actually able to solve the puzzle. Through artificial intelligence, we can see that the only way that these computers were able to become the best in the world at things that people have dedicated literally their entire lives to, and be able to do it in such a short amount of time is because the computer had no choice but to keep a positive mindset when it was learning. 

When it was playing a million games against itself, it never got discouraged and said, I’m going to quit because I just lost this last game. It didn’t have that option. In a way, artificial intelligence is programmed to be a positive mindset at all times and a growth mindset at all times. And there’s so much we can learn from that as human beings. When we sit back and we look at this because we can see that what’s being preached with some of these books like the “Mindset” book is real. And the reason that it’s real is that it’s 100% provable through artificial learning and machine learning at this point. And that’s how these machines are able to achieve at such high levels. 

Now, where it’s going in the future with cars and everything is going to take me to probably my second point, but we’re not going to talk about that right now. But I find this stuff fascinating. I find the fact that if you don’t know anything about this, I would tell you to get on YouTube and start watching some videos and start reading and start learning about this, because it’s going to be a very, very important thing in your lives within the next 5 to 10 years.

Stig Brodersen  17:17  

So Preston, I mean, what a fascinating story. You know me, my first thought is always how does that tie into stock investing? Because what you said about artificial intelligence, I guess there’s some kind of way to program an algorithm just to test a lot of different investments. I don’t know if it’ll just be a mock portfolio or whatnot. 

But in terms of how to find the best stocks, and perhaps look at key ratios, or some more qualitative things that have really hard time quantifying today that artificial intelligence can find. So what are your thoughts on that? I know that you must have thought about that.

Preston Pysh  17:52  

So that’s probably one of the first things I thought about after watching some of this stuff, and learning about this stuff. And one of the interesting videos that I watched that will also drop into the show notes was about how machine learning is augmenting text. Have you ever filled out a CAPTCHA code whenever you’re applying to a membership on a website or whatever to make sure that you’re not a robot, and it gives you like these really strange letters and numbers that only a human can basically decipher and that a computer can’t. Well, with this machine learning, they’re actually getting so good that machines can actually decipher that without anyone typing any code about it. It has learned this through itself. And what it’s using is a thing called hyperdimensional space. 

So, instead of trying to describe hyperdimensional space to people, a) because I’ll probably mess it all up, but, b) there’s a video that goes along with this and it makes it so crystal clear for understanding. And we’ll drop that into the show notes for people to watch. So, what this hyperdimensional space can do is it can figure out words, like, you could load 10 million characters of text into the computer. And the computer is going to go ahead and it’s going to look at all this tex, and it’s going to learn which words are associated with what, what that means. You could also provide other inputs like, let’s say we were loading up 10-Ks and 10-Qs from companies across the entire stock market into this algorithm to learn this DeepMind algorithm. 

And so, it’s learning what words are associated with what. And then what you could also do as another dimension in that hyperdimensional space is you could say, this company had a P/E ratio of x at this point in time. This company had a debt to equity of whatever at that exact moment in time when that 10-Q was published. And so, those other aspects can then be attached to that single point in space. 

What the machine learning can do is, if we then said, let’s say we go five years into the future, and we say Company A, B, and C all went bankrupt. Now tell us, where there were similarities in their 10-Qs, or similarities in certain numbers that made these companies kind of stand out. And with machine learning and this DeepMind protocol that’s using neural networks that are completely shaped after the brain, and the way that the brain learns, you could actually see in 3D like in this video. 

It does a great job of showing you in 3D how this looks, but you could actually potentially see where those companies were at, with maybe their bond ratings. It really depends on how many variables you want to add in there. The more variables the better because this thing, it works better when you add more variables into it because it can decipher all that stuff out. 

So, I’m thinking of it in terms of rating agencies, like Moody’s. You have maybe a couple analysts that are looking at things and saying, yeah, I think it’s a double A, or a single A minus whatever. I think with machine learning, all of that is going to be drastically changed in the future. And I mean, that’s just one little aspect of where this could potentially go. I think that there’s big, big potential for this stuff changing in the future.

Stig Brodersen  21:04  

Given how digital everything in stock investing is, and really, all the algorithms that stock traders are already using on Wall Street right now, must be a question of less than a decade before some version of this, efficient or not, will be taken to use. At least in my opinion.

Preston Pysh  21:21  

My second point really comes down to something that Stig and I and the rest of the TIP community heard when we were at the Berkshire Hathaway shareholders meeting. It totally relates to the artificial intelligence stuff, and that comes down to this idea of productivity and the impact of some of these technologies moving forward with labor and competitiveness for people out there listening to the show. 

So, I was watching a video with Elon Musk, and Musk made the comment that 15% of all jobs in the United States are driver-based jobs. Whether you’re a taxi driver, an Uber driver, a truck driver, somebody driving something, delivering Coke or whatever, that’s 15% of all employment inside of the United States today. And Musk said, I can’t remember the exact number, but I want to say that he said, within 20 years, all of those jobs are pretty much going to be gone. There’s going to be no need for those types of jobs anymore. 

The argument for him is that with machine learning and artificial intelligence, I mean, get this, Stig, listen to this. They’re saying that with this neural network, machine learning that with the way that they’re programming autonomous cars, they’re taking all these inputs. Call it LIDAR [Light Detection and Ranging] on the car. 

They’re taking the cameras from the car. They’re taking all that information. And those are the inputs, and it’s able to actually learn, so that the more that the car is driving, it almost becomes flawless at driving over an extended period of time, if you have a large volume of people that are actually exercising the algorithm. 

So in a way, they’re not not even programming the cars to learn the stuff. The cars are learning by themselves by exercising this DeepMind protocol that they’ve set up through machine learning. I find that fascinating. 

But anyway, back to my point with productivity. So if that’s true, and based on the talk, I watched with Musk, I mean, there was no doubt in his mind that this is happening and it’s happening within a couple years. He displayed this picture of this large semi-truck that’s electrically run, that’s completely AI-based, driverless technology on the thing. So for me, whenever I think about this, and this is just one aspect of how all this is going to impact jobs in the next 10 years, is just the driver piece of it. 

I can’t imagine where that’s going to go in healthcare, where it’s going to go and finance, where it’s going to go in all these different directions. So let’s just say 15% of the driver part is the only part that we’re talking about. Let’s just take a very conservative estimate on what we think the displacement is going to be for labor in the next 10 years. 15% of people are going to have to go out there and they’re going to have to find new employment. I guess for me, whenever I’m thinking through all this, I started thinking to myself, well, what’s my competitive advantage? What skill set do I have that’s going to remain competitive that somebody is going to be willing to continue to pay me, whether that’s a customer, a company or whatever, for what I know, and what I can bring to the table? And how might that be eroded moving forward? 

And I think that that’s such an important question for people out there that are listening to this, that they really need to think about. Because if you’re not prepared for this thing, this stuff doesn’t care whether you’re prepared for this or not. It’s coming and it’s coming like a freight train.

And for all the students out there, you really need to think about, how can I design a competitive advantage around my skill set as an individual person that’s going to be a contributor to the labor force moving forward? And I think this is a really, really important thing for people to think about.

Stig Brodersen  24:57  

I really liked what you said, especially near the end, Preston about encouraging students to pinpoint their competitive advantage. And, having hundreds, if not thousands of conversations with my own students, this is something I always go back to one way or the other because students would typically like to know how to get a good grade? Or what will you ask for the exam? 

I mean, obvious questions you will ask if you were a student. I always tell them to ask the right questions instead, why not, focus on really understanding what it is and perhaps even challenge me. And sometimes they would say, well, you know, you’re given the grade, so why would I ever tell you that you’re wrong? Which is just not a good approach because you always need to keep educating yourself and to make yourself irreplaceable. 

If you’re thinking, just for the simplicity of this example, like as a student saying, how do I get the best grade? What is the formula? What do I need to find on Google, and copy-paste into my exam? If you try to come up with some kind of formula or process that everyone can replicate, then you’re just not positioned for the new future that we’re going into. 

So, my final thing is something that I learned a lot from. I decided to call this part the simplicity and complexity of the best investors in the world. And here, I’m specifically talking about Mohnish Pabrai, who we interviewed on episode 120 and 121. And also, Bill Miller. And just a really quick introduction to these two gentlemen. I mean, both of them have really been crushing the S&P 500. Mohnish Pabrai has been doing that through his fund, Pabrai funds. And Bill Miller through Legg Mason Capital Management where he has been managing more than $75 billion. 

What really dawned on me whenever we were talking to these guys was in a way how simple the process was. So for instance, Mohnish Pabrai. He said multiple times that he didn’t find he was unique. He was actually a cloner. So what he did was he was going through the 13F filings. 

The 13F filings is something that all money managers in the US have to file if they manage at least $100 million. So, he was saying I have the best stock screen in the world. I mean, I’ll just be looking at super brilliant people and what they’re analyzing. And then, if there’s something that I understand, I might invest in it. 

And then, you have someone like Bill Miller. What he was saying is that he was looking at the free cash flow yield. So he was basically saying, where can I get the highest free cash flow for the least amount of dollars? That was really his starting point, then he would rank them and then he would go through them one by one and ask, do I understand the business? Can they sustain the cash flow? So they were more or less using their own version of a very simple stock screener method. 

For me, whenever I’m ranking the cheapest stocks out there, I mean, one of the cheapest stocks that I can look at that would be Fiat Chrysler, for instance. This is a car industry.  I’m not saying it is super complex, but it’s definitely not my forte. And then, another super cheap stock out there would be traveling surance. I mean, I’m definitely not the authority within financial institutions. So I mean, I will not look at that. Pabrai might, Ben Miller might, but I’ll definitely not. 

For me personally, I would come down to something like Bed, Bath & Beyond, or GameStop. We just did an episode about those two picks in episode 143. But in any way, that’s something that I understand. I think I have a pretty good idea about the moat, and how to value the stock. 

So, I think that really tells you something about in many ways, how simple approaches, ranking your stocks, kind of like, using a stock screener, if more efficient stock screener, perhaps. And then based on that, use your own qualitative skills to value the stock. Like, is it something you understand and what do you think the value is?

Preston Pysh  28:48  

So I have a comment about Mohnish Pabrai. So, Stig was mentioning how Mohnish comes out and says that he’s just a shameless cloner and all this stuff. I guess to a certain extent, yes. But I think that there’s a really profound learning point that I think a lot of people miss whenever he says things like that. So what I think Mohnish Pabrai really is, is he’s a cloner of a keystone habit. 

So whenever I look at Mohnish Pabrai, and the keystone habit that I’m really referring to is that he’s a hardcore learner. The guy, if you go to his website, and we need to go find the link, and we’ll put this into the show notes. Mohnish has a reading list of all the books that he’s read. And I’ve looked at this thing, and I feel like I’ve read quite a few books. There’s definitely people out there that read a whole lot more than I do, but whenever I looked at his list, I was like, there’s no way there’s a human being that has read this many books. I mean, it is an ungodly amount of reading. 

And so then I started thinking, well, I could only imagine what Charlie Munger and Buffett have read in their day because that’s where he got this habit from. So when he says he’s a cloner, he is a cloner of habits. He’s looking at the critical elements that have made Buffett and Munger so successful, which is reading and learning, like an absolute maniac, and he’s cloned that. 

Now there are other aspects of things that he’s cloned from Buffett and Munger, but I would argue that those are much less a factor of him just ripping somebody off of what their idea was and what it was, is he so well-read that he’s like, oh, this is definitely the best model because of a, b, and c, because I’ve learned all these other things that teach me that this is probably the best approach to do something. 

So, when Mohnish says that, I think people need to pay attention to what he’s actually talking about, which is he’s cloning their habit of doing a lot of hard work and studying his face off, because that’s the real thing there, folks. It’s not that he’s just copying stock picks, and modeling his company after Buffett’s original partnership, although he did that. I think that that’s a lot less important than the other piece.

Stig Brodersen  30:57  

Yeah, I really think it’s a good comment, Preston, because that really tells you something about the simplicity and the complexity of his process. Like, it’s really simple to go in and read all the 13Fs and really say, wow, this is what the best investors in the world. That’s what they’re investing, you have to do the same. Mohnish Pabrai actually proved that, that you can actually beat the market by really decent return just by not thinking at all, but just by copying the best investors in the world, with their 13Fs filing. 

But really, the complex thing that he’s bringing to the table is he’s saying, okay, so this is my pool of stocks. Now, I need to use all that I learned from the hundreds, if not thousands of books to identify. So which stocks should I focus on? You know, that’s where the complexity part comes in, because it’s really, really hard to outsource. You really need to learn that yourself.

Preston Pysh  31:49  

It’s amazing, and I hate to bring up the artificial intelligence learning stuff again, but it all ties into this. Because when you look at how this machine learning takes place, and it sets up neural networks and how these nodes interact with other nodes as if they’re synapses firing within the brain. The more that the artificial intelligence machine learning can basically pack into these different dimensions, the more it can add each one of those neural spaces on the hard drive. The more creatively, and I know that probably a lot of people might argue this, but you need to go watch these videos on how this individual is being creative and intuitive with machine learning. 

It really gets quite fascinating, and you understand why it’s so important to read not just one topic area, but multiple topic areas because of the way that the brain works and the way that the brain is structured, and the way that your decision making changes as you learn other aspects and how those synapses are tied to each other within the brain. 

So I can’t tell you, folks. You need to come to the show notes and check out these videos that we’re going to put on here because after you watch these things, your mouth is absolutely going to hit the table as you’re watching this, and you’re going to have a deep appreciation for how powerful your brain is. 

It really starts making a lot of sense why reading and expanding your knowledge and studying various areas, whether it’s art, whether it’s science, whether it’s all this stuff, but how much better of a decision-maker you become when you are doing that. And the person that comes to mind for me is Charlie Munger. In fact, Buffett said that at the last meeting, he says, you know, Charlie’s a much smarter person when it comes to understanding just various areas of interest. He said, “We’re much more narrow and focused just on investing and how I can make money for Berkshire Hathaway.” And I think, honestly, I think that’s one of the reasons he’s held on to Charlie so closely is because he can tap into Charlie’s mind, and basically gain that perspective of all these other areas that he doesn’t have knowledge in, and it drastically impacts his decision making, and it helps him understand things better because he’s able to tap into Charlie’s mind.

Stig Brodersen  34:00  

Even though you might look up on Google that his net worth is, call it, $1.4 billion, and Warren Buffett is in excess of $60 billion. I think, in many ways, Charlie Munger might be an even better investor. And this is in terms of evaluating the moat of different businesses. Simply because he’s so knowledgeable about so many different things. And he wanted to retire as soon as possible, but he did that at age 42, when he was like a multi-millionaire. 

And the reason why he did that was just to become smarter about the world, not necessarily to make money. Making all that money was just more like a byproduct of him putting some things he read into practice, and really found a good way through Berkshire Hathaway to do that. I’m a hundred percent sure that Charlie Munger could have met multiples of the net worth that he has today if that was his goal. 

Preston Pysh  34:46  

We were interviewing Robert Cialdini, who’s one of my favorite authors on the planet. And when we asked Robert what his favorite book was, he said, “Poor Charlie’s Almanack”. I have a copy of it at my house. I couldn’t agree more. When you read that book, you have a whole different perspective of who Charlie Munger is, after you read this book. It is mindblowing, the content in this book. 

Anyway, so let’s get to the fun part of the episode here. We’re going to start cold calling members of our audience that had said they wanted to be contacted. So, we’re just going to play some calls here and see what happens.

Brittany  35:26  

Hey.

Preston Pysh  35:27  

All right, so today, we have Brittany with us. And Brittany, welcome to the call. 

Brittany   35:32  

Thank you. It’s very good to be here.

Preston Pysh  35:34  

So Brittany, this is your opportunity to ask Stig and I any question that you want. How long have you been listening to the show for people just to kind of know when you started?

Brittany   35:44  

Yeah, probably about 16 or 18 months, I’d say.

Preston Pysh  35:48  

Okay. All right. So you’ve been around for a little bit. And so what is on your mind? What do you want to hit us with?

Brittany   35:54  

Well, first, I just have a kind of a general question off the wall, not necessarily strictly stock market-related, but more pick your brain. I know you guys are huge Buffett fans, and he has strict rules on what he follows as far as a good buy. So keep that in mind, and I’ll ask you this question here: If you had to choose to invest in one of these two scenarios, which would it be and why? 

And just assume that the business model and the personnel must remain the same. Okay, so it’s kind of a riddle. Company A has a great competitive advantage and a mediocre leadership team, and Company B has a mediocre competitive advantage, but a great leadership team. Which would you invest in and why?

Preston Pysh  36:37  

If it was only those two variables, I’m probably going to take the leadership team every day of the week, and I’d probably put the competitive advantage being mediocre as my second choice. Because I mean, if you have great management, you have creative people. You have something that’s a well-oiled machine of leadership. They can create a competitive advantage over time that’s not there. I’m curious to hear what Stig thinks.

Stig Brodersen  37:01  

Yeah, this is really interesting. I have a different opinion. And then, I also have a comment to that, I guess. Because Preston, what you were perhaps relating to before was what we talked about with Ed Catmull’s book, “Creativity, Inc.,” where he really talks about, it’s all about people. You don’t need to have a good plan or good strategy, as long as you have the good leadership, the right people, they will ultimately come up with what the right plan is for them, and then also, for the company.

But Munger and Buffett had been really vocal on this, and Munger actually said, it’s probably a decade ago or something like that, in one of the Berkshire meetings that if you had to choose between the two, he would take the quality business, because the quality business can really carry bad management. 

And one of the examples that Warren Buffett comes up with is typically the horrible experiences he had with the textile industry. He spent 20 years in that industry, even though he might be a great manager and good high grade managers, the industry was just doomed to be heading for trouble because the commodity prices for the inputs for the company just didn’t pan out. And it was just a horrible business in so many ways. 

So, I think my take would be the business model. And if I can come up with another example, it will be something like McDonald’s. A lot of people don’t know this, but McDonald’s doesn’t make that much money on food. They’re making a lot of franchise, and they’re making a lot basically in real estate. That’s what they do. 

If you’re in comparison with trying to make money just from food, it is actually very, very hard, regardless of having the best chefs, and regardless of having really good leadership in place. So, I think that would be my perspective. I see you have something here, Preston.

Preston Pysh  38:39  

Yeah. The quote that Stig is referencing goes like this. This is by Buffett. He says, “When a management with a reputation for brilliance tackles a business with a reputation for bad economics, it’s the reputation of the business, the one with the bad economics that remains intact.” So, I completely agree with that. 

But again, it goes back to how I kind of opened up with the question. I think that to just say, there’s two variables that makes this almost impossible to answer. If the business was Google, and let’s say Google had really poor management, but the competitive advantage is that every single brain in the entire US in the global economy, for that matter, just automatically logs onto the internet and types Google without even thinking, that’s a pretty insane competitive advantage that’s almost impossible to overcome as far as I’m concerned. 

So, that’s a situation where I completely agree with Buffett and Munger, and I think that that quote is going to ring true. There’s other businesses out there. And I guess I’m thinking more because I run a small business. I run a team of just a few people. And I think so much about leadership and making good decisions as a leader, without, let’s call it, this massive competitive advantage that some of these other businesses have that I guess I’m kind of polarized in my thinking and want to lean more towards finding great management and building the competitive advantage over time.

Stig Brodersen  40:01  

Well, Preston, I mean, you are the competitive advantage. So I mean, I don’t think you’re wrong here. I mean, if you’re a small business owner, the leadership is the competitive advantage because you typically don’t have a moat. You don’t have Google’s algorithm, or you don’t have McDonald’s set up. So, you are a competitive advantage. I don’t think we are that far away from each other.

Preston Pysh  40:21  

So I’m more curious. Brittany, why are you interested in that question?

Brittany   40:26  

You know, I actually have to give credit to that question to Dana, because we were chit chatting back and forth. And I asked her, I said, “You know, would you have any questions to ask the guys?” And she’s an entrepreneur. Her terminal degree is on entrepreneurship and leadership. And so, of course, she went to this sort of realm. So I thought it was a great question, and I honestly thought that you both were going to pick the same answer. But, this is nice to see that you guys disagree on something else for a change. Thank you.

Preston Pysh  40:55  

For me, I really would have to say honestly, it really depends. It depends on more variables than just the two. And I think this brings me to another point. So, I get really frustrated when people think that they only have two options, or when things are binary, or even three options in their life. 

Most of the time, almost all of the time, decisions are so much more complex and have so many more outcomes than what people realize. I think that’s a really important learning point because so often people are presented, well, are you going to do A or are you going to do B? And I think that the response that most people should say is, are those the only options that are available? 

How about C, D, E, F, and G as other options, and what are the outcomes and potential probabilities of all those? And I think that that’s something that’s really important that a lot of people miss, especially early on when they’re starting their own businesses. They don’t necessarily think outside the box, maybe as much as they should.

Stig Brodersen  41:53  

All right, Brittany, so thank you for the awesome question. Do you have another one?

Brittany  41:58  

I do actually have another one. This one is in regard to your personal thought process behind reallocating your funds. So, as we all know, with everything being overvalued currently, a lot of people are holding a large cash position. So I’m curious what thought process you go through and what market drivers or driving factors do you look at that will prompt you to put your cash position back to work for you in the market?

Preston Pysh  42:23  

So that’s a hard one.

Stig Brodersen  42:26  

Yeah, I guess for me, it’s all about valuation. I mean, when the valuations are good, I’ll be putting money back into the market. I think some people like appreciation of how much the valuation really means for your expected return. 

So, there are a lot of businesses out there. They’re not bad at all. I mean, for years, I would have liked to be invested in Coca-Cola or Disney because the competitive advantages of companies like them, they’re just so strong, but the valuations have been outrageous for years now. You can’t expect to get a good return if they’re overvalued. 

And so for me, I like to think about it like this. And this is a calculation I did some time ago really to simplify and illustrate how much it means to buy in at a good price. So, say that you were to buy a stock for, call it, $100, and you will be buying into that at fair value, and the intrinsic value of that would compound 10% a year. 

So after 10 years, you would be making something like 10%, right? I mean, it’s a pretty standard calculation. Now, if you bought this at $200, so you bought at $200 even though that the fair value would be $100, but the intrinsic value would still compound 10% over the next 10 years. You will only be making a 2.6% return. Compare that to 10%. 

And even worse, if you compare this to buying this hundred dollars worth of stock for $50, and you would still again compound 10% a year for intrinsic value. You could be expecting an annual return of 17.9% That’s just like to give you an idea how much the valuation means. 

So, whenever I look at the stocks out there again, it’s not because the stock market per se or the companies are bad. I mean, they’re still great, but the valuations are just outrageous. I have a really hard time entering the stock market or companies that are expensive.

Preston Pysh  44:17  

It’s obviously very similar to the way Stig looks at it. I’m going to describe how I think about it as a business owner, then I’ll describe it as if I wasn’t a business owner, and if I had a job and that was my only source of income. 

So as a business owner, I think of it in terms of two outcomes. As soon as we bank retained earnings or net income in the company and then it goes into retained earnings. There’s two paths for me with respect to how that money can be employed, a) it can be employed operationally, or b) it can be invested non-operationally, meaning, we’re going to buy stocks, we’re going to buy bonds, we’re going to buy commodity, something that would be passively managed. 

Whenever I look at those two options, a lot of the time, there’s a lot more advantage for me to invest operationally in my own business creating assets than non-operationally because there’s these second and third order effects that drive more revenue to the company by investing operationally opposed to non-operationally. 

So, I’m immediately thinking in that direction first and foremost. And I think that when you look at people like Buffett, this is one of the biggest misnomers that people don’t understand is, I believe, he thinks the exact same way. I think he’s always looking, “How can I invest operationally way before? What stock can I buy?” That’s what he’s doing with stuff that he doesn’t have ideas for, really, it’s what it comes down to. 

So if I don’t have any good ideas on assets that I can organically create for my business, and I really have nowhere to go with that retained earnings. Then, it’s going into, well, what’s the stock market look like? What kind of yield can I get there? What’s the commodities market look like? What’s the fixed income market look like?

 

If I feel like all three of those are overvalued, and in a position that’s precarious, then maybe I might even sit in a currency, which is kind of where I’m at today, to be honest with you. So, that’s how I think as a business owner. 

As an individual, I think very similarly about the situation. Let’s say I work, and I make $50,000 a year. That money is mostly just going to living expenses. Whatever’s leftover, I would think, how can I invest this operationally? How can I invest this back in myself? Well, the most obvious answer for me is in learning, in books, and educating yourself because that’s how you really accumulate a competitive advantage over everybody else is by just being very knowledgeable. 

I would tell you go buy a book on learning how to program. Go pay for a subscription on a website. Go to YouTube. Get it for free. This is the thing that I find fascinating. You can go on Amazon, and you can buy books that are like top selling books. In fact, the best selling books on Amazon are often the cheapest books to buy because you can buy them used for sometimes at $0.99. Then, you pay like $3 or $4 for shipping. 

So when you think about the investment in yourself at $5, total cost to have it delivered to your door, that’s insane. To think that people are passing up on that operational investment all the time. And so, I would tell you. If you’re investing operationally, call it books or whatever you’re doing, call it a $100 course or something. If you’re investing in that, and it takes you a month to complete it, you should have quite a bit of money in retained earnings leftover to invest non-operationally, or you can invest in other ideas or something that maybe you’re coming up with, a new business or I don’t know what it is. 

You come up with whatever your passion is, that’s what you need to create something around. That’s where you need to be investing your money first. And then, whatever’s left over is where you’re putting it into the stock market or whatever the yield is, and then we could get into a whole discussion on that non-operational side. 

To be honest with you, that’s what we mostly talk about on the show, despite I would argue the operational stuff is probably more valuable.

Brittany  48:05  

Nice. Good answers, gentlemen. 

Preston Pysh  48:08  

Thank you so much for calling into the show. It’s so much fun for us to meet members of the audience and to interact like this and to answer your questions because it helps us with our thinking too, because a lot of the times we don’t necessarily state out loud what or how we actually feel about things. 

Stig and I are business partners, but sometimes it’s good for us to hear how each other think about certain things, too. So that’s good. We’re going to hook you up with a free subscription to any online course that we have on our website for calling in. And we really appreciate you taking time out to talk with us tonight, Brittany.

Brittany   48:42  

Excellent. It is my pleasure. Thank you so much for everything that you guys do and keep it up. I’m loving it.

Stig Brodersen  48:47  

Awesome questions, Brittany. Really. 

Okay, Preston. So let’s call up the next listener. That’s Jay.

Preston Pysh  49:02  

Hey Jay, how’s it going? 

Jay 49:03  

Hey Preston. I’m good. How are you? Great to see you guys.

Preston Pysh  49:06  

Yeah, great to see you too.You’re all out in the West Coast, right?

Jay  49:12  

That’s true. Yeah, I’m in Seattle. 

Preston Pysh  49:14  

Oh, my. So Jay, this is how the segment works. You can ask Stig and I anything that you want. And you can bring up a new topic. There’s a strong chance we might not know the topic, but we’ll try our best. And we’ll go from there.

Jay  49:30  

So I actually had a couple of questions that I was really curious to get your thoughts on. The first one was, it’s a bit of an experiment that I’ve been doing. So basically, what it is, is that if I have a stock that I’m interested in, let’s say I valued it with a margin of safety for some price x, but it’s still a bit higher right now. It’s sort of trading at 30% to 40% higher than x. If I wanted to protect my downside, I’m thinking how do I reduce my basis? One thing I’ve been looking at is to set a cash covered put option. That’s with a strike price of x, and that’s far out. 

And if I get the premium, once I sell the put option, so that it helps lower my basis, and if the price ever hits and the option gets exercised, then I don’t mind owning the stock. So, I was curious to know what your thought is in that sort of strategy. What are the pitfalls? And what do you guys generally think of that approach?

Stig Brodersen  50:26  

I generally like that approach. And I know that this is something that Toby [Tobias Carlisle] also does from time to time. It’s typically also presented as a nice way to make money while you’re waiting. One thing definitely to keep in mind is also it’s not free. We’re definitely also paying a lot of commission, and you also tied your money up, which is another cost. 

One could argue that that is not a huge expense right now because of the opportunity cost being a little low in the market. Not the risk, though. That’s a huge opportunity cost if you do into the market. 

But if you’re just looking at the individual stock, and you’re saying. well, this is a good price. This is the price I would be comfortable with, and definitely, I would imagine though, that the stocks that you’re talking about whenever you’re saying 30% less, it’s not a lot of money that you would get out of that position like that, based on how options are generally priced. Could you give us some numbers in terms of the returns that you can expect to something that is so far out of the money?

Jay 51:22  

Yeah, so I typically have been looking at something like one year out positions, and then a strike price, which is 30% lower than what it’s currently trading at. And so I have been typically getting 2.5% to 3% yields on those. So it’s sort of like a dividend almost. It’s not a lot of money, but I’m just waiting, and the cash is just there. I’m not doing anything with it. So, I’m just sort of partially committing it to if it ever hits that price, then I buy. So it’s like around 3%-ish, is what I get.

Stig Brodersen  51:52  

Okay, and what would it be net after commissions? Because, I mean, that’s another concern. I mean, obviously. How much would it cost for you to take a position like that?

Jay  52:00  

It’s just a standard commission. If I do it through Fidelity [Investments] or whatever it’s going to be whatever their rate is. So, it’s not a lot of commission. I mean, it depends on the broker, obviously, but it’s a standard commission. It’s still 3% is post commission.

Preston Pysh  52:13  

So Jay, let’s say that there’s a lot of momentum behind the market as it comes down through that 30% drop, would your strategy at that point be just, I’ve got to buy it, and then I quickly release it back onto the market for whatever the hopefully, you’d be able to basically buy-sell without any much of a delta between those two price points, is that what you’ve been thinking? If there’s a lot of momentum behind the sell off?

Jay  52:35  

I was thinking mostly just as a long position. So if it hits down and it comes off 30%, and then it’s at the point where I’m forced to exercise the option and then buy the stock. Then at that point, I just treat it like owning any other stock. If I’m really happy with the stock, then if it goes down, then maybe I’ll buy some more, but the thesis behind it is that my research should be strong enough that if it’s a good long term buy, then I don’t mind entering it at that position. And then I’ll just treat it like any other position.

Preston Pysh  53:02  

I think whenever I’m thinking through what you’re describing, I think that it makes a lot of sense if you’re a value investor, if you’re wanting to get something at a certain price, you feel comfortable with the assets of the underlying business, you’ve done your research on the underlying business. I think it makes sense.

Jay  53:17  

So the other question is, oftentimes, when I’m looking at balance sheets. The assets part, I always have difficulty in understanding how current those are, like how mark to market those are. So I’ve been trying to get a sense of how I can go about getting a good framework for knowing whether those are actually mark to market or what industries are sort of current, and what are not, what are lagging behind. So I was wondering if you guys have some good resources or some advice on how to get a sense of how current or how much should we trust the assets on the balance sheets of the companies?

Stig Brodersen  53:53  

Well, I think the best resource to really go into detail with that would be, “Security Analysis”, by Benjamin Graham, and it’s not the easiest book to read. I don’t want to say that, but he actually has a really lengthy, very interesting discussion about how to determine what the value of the assets is. And basically, when you look at a balance sheet, what you have at the very top, that is what is most liquid, so that would be your cash. What you have down at the very bottom, is least likely, this will be your property, plant and equipment. 

You’re basically looking at a variety of different assets and, if you take the top half that would be your current assets. So, that is what you expect will turn into cash within the next 12 months. But even so, even within that category, you cannot equate everything to cash. So, it really depends on how you look at it. For instance, how much inventory do you have? Inventory is not as liquid as cashes, and you cannot necessarily expect to get the same return of inventory. So you basically need to kind of know which type of product are they selling. Can I expect that to be converted into cash?

When it comes to, for instance, property, plant and equipment, you really can’t take that as the carrying value. Carrying value basically means, if it says $3 billion, that’s the carrying value. You can’t really use that. The way that, for instance, Seth Klarman is talking about that, Seth Klarman is the author of ” The Margin of Safety”, is that you should ask yourself, how much cash flow can I expect to generate from the property, plant and equipment? Because the number that you see listed is really an accounting number. 

I guess you can say that about most everything on the balance sheet, but especially that line is so much an accounting number, like, how do they decide to depreciate it? What happened? It can do all kinds of things with that, but the property, plant, equipment, the way to value that is what is the worth? What is the cash flow they can take away from that? And then put that as your value instead.

Preston Pysh  55:53  

So if the asset goes back onto the market, and it’s going to be repurposed, and you’re really kind of looking at this factor more from a liquidation standpoint than anything else. But, if it can be repurposed very easily, then the value might be worth more. And again, you’re looking at the actual cash flow that it could generate after being repurposed. I don’t know if you’ve ever read the book, “Fooling Some of the People All of the Time”.

Jay 56:17  

I’ve heard of it, and it’s in my list, but I haven’t read it.

Preston Pysh  56:20  

Yeah, so this was written by a billionaire. His name is David Einhorn. The book is almost an entire book around this question.

Jay 56:30  

Okay, that’s awesome.

Preston Pysh  56:31  

I don’t know if it’s necessarily going to help you determine what the value of certain assets are on a balance sheet or the liabilities, but what it’s going to give you is an appreciation for how much companies can manipulate that, and how little the SCC [State Corporation Commission] does about it. And the SBA [Small Business Administration]. 

Jay 56:50  

I think that’s pretty cool. I think I’ll check that out. Because in general, I just wanted to get a good feel for what kind of companies, and what kind of industries have different levels of how they are manipulating it, and what form, and how much you trust it. So that’s really what I’m looking for. So that’s pretty cool. I’ll check that one out.

Preston Pysh  57:07  

Yeah, it was interesting. He talks about how he was a short seller against a specific company called Allied [Capital]. And you know, how he was able to identify that they were using wrong accounting practices. And a lot of it had to do with mark to market, and stuff like that. And at the end of the day, he went and told the SBA because they were actually implementing SBA laws and should have been using SCC laws. 

It was quite an amazing read, very meticulous read, but you gain a deep appreciation for what companies actually have quite a bit of latitude with, and how little they’re able to do about a lot of it until maybe the company goes bankrupt, and then it all falls apart. But for Allied, that never happened. The company that he was, that he kept bringing this up over, it never went bankrupt. And so they just continued to get away with quite a bit of stuff that was quite interesting to read about.

Jay  57:57  

That’s awesome. That’s great. Thanks so much for the answers and explanation. I’ll definitely check those out. 

Regarding “Intelligent Investor,” is that still very relevant? Like the methods and explanations that Benjamin Graham has given in terms of the kind of companies, industries we see because like the more and more we’re moving in the tech industry, and a lot of the stuff is quite different from his *inaudible*. So how current do you think that still is?

Stig Brodersen  58:21  

I think it’s very current, perhaps especially because we’re moving into technology. Again, I don’t know what’s going to happen. I definitely think that you will see a massive disruption in almost all industries. But it’s kind of like whenever the internet came out. Eventually we all realized that the internet was here to stay, and it’s going to change everything. But it was not people who were, call it, creating internet that was successful. That was not it. I mean, a lot of money profit from that, but it was really, really hard to see who would eventually come out on top of that. 

Yesterday, everyone would say that it’s quite obvious that Google has such a competitive advantage. It has the best product, but I remember when I was growing up, everyone was using AltaVista. 

I mean, that just disappeared. So, I think his teachings about how to value businesses and how to evaluate businesses, arguably, from a very quantitative standpoint, I think that might be even more important today because it’s so easy to find a good narrative about, for instance, artificial intelligence. 

Previously, in this episode, we talked about driverless cars. It would be easy to say that driverless cars would be a big thing. Yes, but that doesn’t mean that if you invest in a company who created these cars, that would be a good investment. We’re talking about the technology, and we’re talking about stocks. And it’s two very, very different things, in my opinion.

Preston Pysh  58:56  

So in the past three to four years, value investing has underperformed momentum. And I think that anytime that that happens, and it almost always happens during the last phase of a business cycle, the last part of the credit expansion of a business cycle. And so, typically, what you’ll have is you’ll have people that start bashing value investing. They’ll bash the “Intelligent Investor”, all this stuff. 

And I think there’s a good reason for that. If anyone’s interested in understanding how these two things go hand in hand, momentum investing and value investing, I’ll tell you look up Wesley Gray because he has some amazing research. 

I agree with Stig. I think value investing, especially the “Intelligent Investor”, all that stuff is alive and well. It’s more of a function of where central banking has kind of taken things. You know, within two or three years, it’s going to be a different story.

Jay 1:00:31  

Cool. No, that’s awesome. Thanks for the resources. Let me check out those ones. That’s really good. I’ve *inaudible* read the “Intelligent Investor”. I was sort of wondering, how much has changed since the time he wrote and how much of applicability do people still follow. But it definitely sounds like it’s still one of those books, which has stood the test of time. So probably worth reading it again, [to] reinforce those ideas.

Preston Pysh  1:00:53  

The problem with the “Intelligent Investor,” it’s just so dry. 

Jay 1:00:56  

It’s kind of hard to read at times. 

Preston Pysh  1:00:57  

Yeah. Benjamin Graham’s writing style, I mean, is just extraordinarily dry. I mean, it’s very academic. He backs everything up, you’ll especially see this in security analysis where he’ll present an idea. He’ll say, I think this is why things do this. And then he’ll provide 10 case studies to back up his research.

Now, what’s interesting is when we read Joel Greenblatt’s book, who now teaches Benjamin Graham’s stuff up at Columbia. Joel Greenblatt took a very, very similar approach to the way he writes his books, where he presents an idea then he provides a bunch of analytical proof and statistical proofs through actual case studies. But Joel Greenblatt’s book was a blast to read.

Stig Brodersen  1:01:36  

Yeah, I mean, his [Graham] writing style was definitely not too easy. Another thing is just that, the book was written in 1949, and “Security Analysis” even before that. It’s a very hard language to read simply from that. So I definitely feel your pain, Jay. Especially if you want to re-read this.

Jay 1:01:56  

I’ll definitely check out the executive summaries. Maybe I’ll start there and then, and that’s the guide for me when reading it again. 

Preston Pysh  1:02:01  

Well, Jay, for coming on the show, what we’ll do is we’ll give you the free subscription to our “Intelligent Investor” video course that we have on our website. 

Jay  1:02:08  

Awesome.

Preston Pysh  1:02:09  

Just to say thank you for coming on and asking us questions and being part of the TIP community. We can’t thank you enough.

Jay 1:02:15  

Oh, absolutely. I think the pleasure is all on my side. I’ve been a big fan of your show a heck of a lot. And just look forward to listening to you guys every week. So thank you for having me. 

Preston Pysh  1:02:24  

Great to have you, Jay.

Alright, guys, so that wraps up our 150th episode of doing The Investor’s Podcast. We want to say a special thanks to Brittany and also Jay for coming on the show. That’s always so much fun to do those questions live and have that interaction. We hope you guys really enjoyed the episode and we look forward to doing the next 50, and doing another show like this at episode 200.

Stig Brodersen  1:02:47  

All right, guys, that was all that Preston and I had for this week’s episode of The Investor’s Podcast. We’ll see each other again next week.

Outro  1:02:54  

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