Perfecting the Investing Craft with Caro-Kann’s Artem Fokin

Summary

• Investment Process: The podcast focuses on improving the investment process, emphasizing the importance of continuous learning and iteration in investing as a craft.
• AI and Expert Calls: AI and expert calls are highlighted as valuable tools for enhancing investment research, with AI seen as a way to process large amounts of information and expert calls providing unique industry insights.
• Market Impact of AI: There is a discussion on how AI might make markets more consensus-driven, potentially creating opportunities for investors who can identify non-obvious insights not captured by AI.
• Customer Focus: A key takeaway is the increased focus on understanding customer value propositions and satisfaction, as this can provide critical insights into a company's potential for success.
• Investment Community: The podcast touches on the small cap investment community, emphasizing the importance of networking and sharing ideas while being cautious of groupthink and maintaining independent conviction.
• Risk and Sizing: The conversation includes considerations on risk management and position sizing, with a focus on balancing expected returns with potential risks, especially in leveraged investments.
• Continuous Improvement: Both hosts stress the importance of continuously refining their investment processes and learning from past mistakes to enhance future investment decisions.

Transcript

You're about to listen to the yet another value podcast with your host me, Andrew Walker. Today is a kind of special episode. I have my friend Ardam Finan back on the podcast. Artum is uh one of the most frequent and popular guests on the podcast. He's come on seven or eight times and we do something different. We don't talk about a individual specific stock. This is just Art and I coming on and kind of rambling for about about an hour, over an hour about process improvements, things we're thinking about, ways we've tried to improve as investors over the past 10 years. All sorts of stuff. You know, we start touching on AI and expert calls a little bit. This is this podcast is going to be sponsored by AlphaSense. We actually are doing a separate webinar talking specifically about process improvements and AI and expert calls that I'll include a link in the show notes and talk about more throughout the podcast and stuff. But I I think you know investing is it's a mental sport. It's a to Artem and I I know it's a craft. We're always thinking about how to improve all that sort of stuff. So I think you're going to really enjoy this conversation about just Art and I talking about ways we can improve, ways we think about investing, all that sort of stuff. So it's a little bit different, but I I think you're really going to enjoy it. I had a really really fun time recording this. So we're going to get there in one second, but first a word from our sponsors. Today's podcast is sponsored by Alphacense. Look, Alphas and Satigus are two of my longest time uh subscriptions. They're two of the podcast longest time sponsorships. I I love them both and I I'm so glad they merged. The product is awesome. I've done so much work with them. I consider it probably not probably definitely the most valuable subscription I've got between Alphasense versioning AI tools. They're getting better every month and particularly the expert library on both their uh on both them. Look, I I'll give you a little secret. I I'm always pushing myself to be a better investor. And one of the ways I'm trying to do that is I've pushed myself to once a week I do an expert call on a company or sector that I'm researching come rain or shine. And it's just a really interesting way to be tapping into new ideas, people who are actually operating, get out of the spreadsheets, get out of the SEC filings and actually talk to somebody about what's going on in industry. I I do that myself out of pocket. Alpha doesn't pay. Tiggas doesn't pay. That's just me. But I I I mentioned that because look, I I I think it's really continued to help improve me as an investor. You'll notice it in the podcast when I talk to people. I do expert calls on the companies we're going to discuss and I just show it like I I get real value out of it. And if you're a fundamental investor interested in learning more, diving deeper, I think you will, too. So, Tegan Selfense, I I love the product. They've been a longtime sponsor and I'm happy to keep having them on the podcast. All right. Hello and welcome to the yet another value podcast. I'm your host, Andrew Walker. with me today. I'm excited to have on one of one of my best friends in the industry, one of my favorite guests, Ardan Poken. Ardan, how's it going? >> Hi, Andrew. Great seeing you. I was actually thinking about wearing the same uh polo yet another value podcast uh uh today for the recording, but I decided that maybe it will be one too many. So, I figure out you will be exclusively wearing this. >> Well, that is it because I told you last night I was going to wear this and then you said I might wear my my famous pink polo to go with it. You often wear that for recordings >> sometimes. Uh but we've got a lot to talk about today. Let's just start before we get there. Quick disclaimer. Nothing on this podcast investing advice. Full disclaimer always at the end. And I'll just roll it into look add to disclaimer. Art and I are kind of doing a different podcast here. We are taking Ardum's one of the most popular guests. I believe it's his seventh or eighth time on the podcast. We did a podcast earlier this year that got a lot of uh great feedback where Ardum and I I interviewed him as one of the keynotes at Planet Micro Cap. We're doing this podcast and then I think we're going to do a follow-on webinar with AlphaSense talking about using AI and expert calls in investing. So, I'll include a link to that in the show notes. But this podcast, we're just taking a step back, no real individual securities, and just talking about the investing process, things we learn about, things that Ardum and I talk about while I walk my dog Penny, what two or three nights a week every week. So, uh that's the overall feel of this process. Or anything you want to add before I kind of jump into a first question and we just start, you know, basically rambling for an hour or knowing you three hours. >> Yeah, knowing me and you, it will be not an hour. It will probably run longer. Uh, yes. I think if I were to ask to summarize the theme, the topic, the subject of today's podcast, I would call it perfecting the craft. >> Yes, >> investing is a craft. >> Yes, >> it's a profession. It's a craft. And uh we as craftsmen would like to improve. And you reach that improvement through iteration, through feedback loops, through talking with other people in the field and getting their feedback on your own process, on your own process of conducting that craft and sometimes cloning or stealing their ideas. Not I'm not talking about stock ideas. I'm talking about process ideas. how to play this game at a better level. >> Art, it's like you're in my head. So, I've got a post. It's in draft. I'm going to put it up at some point, but uh if I can ramble for a second. The post is all about, as you know, I ran a high rocks race recently, right? And when you run a high when you run any type of race, it's kind of really clear who's better than you, right? You run and if they finish if they cross the finish line at a time that's faster than you, they're better. And one of the interesting things in all sports when you train hard and you run a race and then you see someone runs it faster psychologically you know that barrier can be broken and you can push yourself harder and beat it. The the most famous example is Roger Banister, right? He runs the four-minute mile and and people think it's physically impossible. Two months later someone else runs the four-minute mile. Now good high schoolers will run four-minute miles, you know? And I always think about that like in investing, what is the thing that pushes you harder? Like I'm sure all of us are internally driven competitive people. What is the thing that pushes you harder? I will tell you what it's not. It is not hey investor A generated 300% returns last year. I generated 4% returns. They're so much better than me. I need to push harder because that has no context. They might have just yoloed call options. For me, what it often is for me if I can try to land this plane is when I talk to people like you and I say, "Hey, Ardum, walk me through this thesis." and you say, "Oh, yeah. As part of this thesis, I, you know, I I did five expert calls on Tikis and one of them uncovered this nugget that no one knew and it it sent me this rabbit hole." It's when I hear someone and they did great research and I'm like, "Oh, I wish I had that insight into an idea I had or I wish I had that in the ideas I had." That's kind of what pushes me and that's like kind of the process improvement for me. And there's lots of other things, but I've kind of rambled. Hopefully, I nailed that plane. I I I you can just respond or tell me if you agree with that. That's interesting for me. Great investor track records do actually motivate and inspire me. But I'm not talking about a single year. I'm talking about an extended period of time with very strong returns over that period. For example, if someone did 25% keer for 20 years, they're probably one of the best in this profession that ever lived, especially if they do something similar conceptually to the style investment I practice. In other words, if it's reinance technologies with medallion fund, sure, they play different game. It's not what I do. It's not what I know how to do and will probably never know how to do. So that's is not that inspiration for me. I'm intellectually curious about how they did it, but it's not something that will be inspiration for me. If you pick someone, let's pick a great investor David who supposedly based on publicly available information had a fantastic track record for many many years. That is inspiration or Joel Greenblood his track record or part of that I think is published in the back cover of front cover back cover of the book you can be stock a genius that's inspiration so single years probably not inspirational for me probably will not push me work harder or think differently but they will probably inspire me in the longer term so >> can I sure can I answer your question so I I generally agree with you, but I've gone a little bit back and forth on this and I'll tell you why. I was talking to someone with a very good track record. I mean, borderline elite track record who runs it also like who runs it very diversified. You know, they're running like 30 to 50 positions plus long shorts. So, they're running diversified lower nets, all this. And I was talking to them about someone who's got a great track track record, right? 14 years, super concentrated, very good track record. I was like, "Hey." And they said, 'Look, I've talked to this person. I've interacted with them. I'm very skeptical that this person is a good investor. I was like, "Oh, well, track record, you know, like scoreboard, bro." Like, look, this person's concentrated over the 14 years they've had 10 positions, right? You don't have statistical significance. They literally could be the the famous coin monkey that flipped the coin and one of the coins came up very heads, right? If 10 years ago you had plowed into Tesla, your returns would be incredible, I don't know if there's still there or not. Now, you know, again, stock price, bro, like scoreboard, bro. But is that statistically significant? Like 10 years and in a concentrated fund, it's not a lot of investments. I think about I think the person is clearly wrong. But the person who said, "Hey, Warren Buffett still doesn't have enough investments to be statistically significant." I think that's wrong. Like 50 years. But I do hear if if somebody started in 2012 and invested today, if they had bought Mag 7, they basically would be a legendary investor. And I'm not sure like, hey, they had the insight to buy Mag 7. Should we give them credit as a legendary investor not? I don't know. But I I I've come to be a little bit of skeptical. And part of that might be because, you know, you see some I read all these business books, me and Burn Hobart are our uh book discussions, and it's like a little bit of a running joke. everyone you read, the person had a near-death experience. And you're like, they created incredible returns, but any return stream times zero is zero. And like in the first 10 to 12 years of their return stream, there was this thing where like if things had broken just a little worse for them, it would have been a zero. And so again, throwing a lot out there, but I've gotten just a little more skeptical of even like longer term track records based on that. How do you think about that? >> I don't think this question is answerable. Meaning we cannot through deduction or induction we can or inference we cannot get to a conclusion that we would feel 95% confident that it's accurate conclusion. It's I don't think it's an answerable question. It's almost a question of belief. Do you believe in XYZ or you don't believe in XYZ? Now if you believe in Santa Claus probably it's a little too much but there are other things that are issues of faith of belief that people do not need proof. So to answer this question and remember I don't know the fund you're talking about. I don't know the fund who a person who is skeptical. I don't know the person who deliver those have literally as much information as anybody who is listening to this podcast right now. So I don't know my logic is what I'm thinking is this very often when people say John and this hypothetical John. So if any John's in our network, we're not talking about you. John is a great investor. What it means more often than not is that the speaker and John are fairly similar in their thought process. And the speaker thinking of himself that all of us are above average drivers and all of us are above average investors and above average runners and swimmers even if you don't know how to swim. So that was a joke and so >> no I I was laughing because in college I was like I'm an above average swimmer and then I hopped in a pool. I was like oh I barely know how to swim. So, and what it means is that it's a similar to bias at play and when the person means Bob again hypothetical Bob who does something different and the person does not fully understand Bob's style or Bob's thought process or decision making. They think that they're not a good investor. Even if the track record may indicate otherwise, I'm not dismissing your argument. It's maybe not statistically significant. I get it. But that is not answerable. I'm just sharing how I view it. And as I said, I cannot prove that my way of thinking about it is right. But I think that it works works for me. For example, some people are superior business analyst. They're just fantastic. They're at the top. Sometimes that translates into money making, sometimes it doesn't. Some people are really good at idea generation. They may be not as good at actually doing analysis, but because they're capable of finding great ideas, they make money. They will be people who are really good at risk management, and that's how they make money. They will be people who just have and that's the one that I understand the least about. But I have some people in my network who I think have this incredible money smell and I talk to them about the position and I think that they don't know this position as well as I do even though I don't own it >> but that person still makes money. They do some analysis and I'm not saying they are bad. I'm saying that that's not where they make money but there's something else about them about their psychic about their process thinking I don't know but they make money they have the money smell and remember I come up with a short money smell because I cannot come up with anything better. So in my my if I were assign probability my base case would be your friend who did not acknowledge the returns being deserved by another friend of yours. My guess is that they're just very different. Remember you and I when we were in Dennis at plant micro cap, we spoke about the superpower. Different people have different superpowers. And I think it's very important to have in your network people with different superpowers. And also just for people who didn't who don't listen to everything that Android I talk about when I when the way I define superpower doesn't mean that you're the best at certain skill in the world. It means that it's your relative strengths meaning Andrew is probably better at lifting weights than running or as we found out right now swimming. So in in exercise weightlifting will be and their superpower in investing different people have different relative strengths and that will be their relative superpower. So that's just definition. So I suspect that those two people you spoke about they have different superpowers that's why and they don't recognize that or at least one of them doesn't recognize that as a result he doesn't speak that highly of the investment talent and acumen of the person with very enviable very impressive track that's my best guess >> no look I think you're let me just propose one more hypothetical and I'm laughing so hard because you and I were like hey it's just Artem and Andrew rambling let's kick off with we've got this buzzy like ESPN would lead it with first question that we're going to get to in a second, but we said we were going to kick off with that and then we got into a conversation on statistical significance of investor returns. Um, let me let me just ask one follow-up question. Somebody who bought Bitcoin 10 years ago and held it till today, I don't think it's crazy to say they have better returns than every investor that we know, right? Bitcoin 10 years ago was 200 and as you and I are talking, it's $115,000, right? So, in 10 years they've got what is that? A 500 plus Xbacker, right? They bought in any size. They've got just absolute groundbreaking returns. Is somebody who bought Bitcoin 10 years ago and wrote it till today, are they a great investor? Because their returns would say that they are literally the best investor of all time. I would say that there is a very high probability that such person is a great asset allocator which is different than an investor. That's number one. Number two, if that person, and the answer I think will be very context specific, if that person in 2012 had $3 million net worth and they put $2.8 million into Bitcoin, I would say, boy, Russian roulette also statistically works, but it's a dumb idea to play it. However, if that person with the same 3 million net worth in our example and by the way, let's imagine also that the person is it 30 years old, healthy, has a good professional career, etc., etc. If the same person put even 10% $300,000 in our example into same Bitcoin in 2012, I would say they're probably a great asset allocator. And I would also say that they're probably they maybe good and I'm saying maybe because here we're speaking about sign statistical sample of one in your example. They're probably good or even incredibly good at envisioning different future states of the world. And one of those potential future states did play out and it played out in an incredibly favorable favorable manner. >> No, that look I I hear you. It's just it's I I've been working with a coach and one of the things they keep telling me is Andrew, you want the you want a you want a definitive answer to all these questions and there are no definitive answers. Like that's one of the I suppose it's the beauty of investing. It's the art of investing. But you know the the logical side of me, I want to I want to read a story and I want to know the ending. And like with investing, there is no right answer unless kind of your Renaissance technology and you run, you know, a thousand trades per day and then you can find statistically significant ones. But like I described the Bitcoin thing, they were kind of a VC and they were right and it's scoreboard, bro. But it's up. Okay. Anything else there? Because I want to get to our first take question. >> Okay. before you get into what you wanted to ask me and somehow 20 minutes later you still have not asked me or 15. So I would also say when you mentioned that your coach told you like oh Andrew you want to know the definitive answers to questions that are not that don't have such answer. I would make things even more complicated because very often if you are investing in companies that commonly called compounds. So I will I will try to maybe narrow the definition a little bit. Company with attractive unit economics with a long growth runway executing that runway and doing it in a very good way because it has strong management that can get execution done. So again I'm not saying that this is classic definition. I'm just oversimplifying here. You are statistically betting on outliers. Meaning most companies will not deliver let's say 10 10 years of 20% revenue growth right or 20% of earnings growth. You pick the numbers >> statistically it's not going to happen. So you are betting on outliers which means that your base rates if you just take all universe of stocks will be against you. Now if you start cutting and recutting that universe and I'm making this criteria up okay so I'm not saying that this is a good criteria if you say I want a found owner operator with at least 20% stake and I want companies that pick margins pick revenue growth pick RIC pick they got backed by squa or Anderson Horitz or any other great VC that we think are great investors whatever your universe is in that case you may be churning base rates in your favor. But even with those, I'm not sure they will be massively in your favor. So you you definitionally from the beginning cannot get the definitive answer. And if you get somewhat definitive answer, somewhat definitive in in quotes right now, then you're basically against you. You're betting on outliers in this in this example, in this style. >> Look, that's a really fascinating way to frame it. I love the uh Warren Buffett had the had the example once where he had like a UN University of Chicago expert who said oh Berkshire you know there are three standard deviation uh outlier there are four standard deviation outlier there are five standard deviation outlier and eventually the the economist just put his money in Berkshire and invested in Bergkshire and like what you're kind of describing is hey an average an investor when you're betting on these great compounders the average company you know what is the stat like uh 80% of the market's returns have been it's it's not the 8020 rule in terms of 80% of the market returns are driven by 20% of the stock. It's like 80% of the market's returns are driven by like 20 stocks or something over the very long run. I'm a little bit >> it was a famous uh academic paper published several years ago by professor I forgot his name I think he's from Texas but I can be wrong and it was like 4% of stocks just% of return etc. that there is this >> I think there was there was some survivorship bias there and stuff but the point was but I love what you're saying the compounders are like you're betting on a company being one of those 4% right it you're betting against base rates it's it's a really interesting way to frame it >> but but another thing that comes here is that and by the way to defend that professor is that any paper of this nature will have some limitations it's probably impossible to make it perfect and obviously many people will say oh you miss this you miss that Sure we're talking about here 80/20 rule meaning the intellectual 8020 rule do you get 80% of the insights even if 20% of situations are not covered so but what is what I and since we got into this topic completely unexpectedly so if you think about if you say I am betting on statistically less likely events from the base rate perspective so probabilities if you do a random th dot throwing are against you. So number one, you need to figure out how to improve the probabilities. Sure, that's obvious. But number two, you need to have I think many investors call it convexity. I don't know whether mathematically it's convexity or not. That's probably somewhat debatable, but let's call it convexity here. You need that convexity of returns on the upside. And this is where I think many investors can learn a lot from venture capital >> with their mindset and how they think about it. And obviously the most famous one is the power law here. I think the first time I learned about it from from fantastic book 0 to1 by Peter Theo. And then there is fant another fantastic book that I read two years ago I believe. Uh the power law by Sebastian Malabi. This is the same author who wrote more money than God. I think actually like the power law even better than like more money than got but that's subjective assessment. So that's a fantastic book about many great venture capitalists. Now I'm not saying that public market investors should become venture capitalists. That's a different game. And by the way by the time that these days public companies companies become public they are way past those early stages where venture can invest. But the overall concept, the matter idea, the matter thought here is that if you're investing where base rates may be against you, number one, CH probability somewhat more in your favor than the base rates. That's number one. So do some filtering, cutting, whatever. And second, you need that explosive upside where if you hold that company for 10 years, for example, it has a shot at becoming five bag or 10 bagger or pick whatever bagger will satisfy >> however many bags you want, you can have. >> So yes, so I think that's another consequence of that framing. >> All right, we're going to hard pivot. All right, let's ask the ESPN first take question. You and I were talking the other day. We're talking about AI again. We're we're going to do a uh webinar with Alpha Sense talking about using AI tools, using expert calls, which I think are I don't want to spoil the webinar. I I I mean I think over the past a little bit. >> Yeah. I I look I just think over 18 months. >> Don't you can spoil the webinar a little bit. Don't do it too much. >> Look, I I've talked to some investors who are a little bit older than me, a little bit older than you, and they're like, "Oh, I haven't used AI at all yet." And I'm like, "Okay, cool." it like you're basically an investor in 2005 who's like oh yeah I'm not using spreadsheets and email like it it's so revolutionary to me and it changes so much and the expert calls you know I just think it's the only way to re not the only way but it's such a useful process for so little upfront to like talk to people in the industry get real insights and everything so they've really evolved anyway we were talking about AI because I I was saying some of this and you told me hey I think AI over time is going to make markets I don't want to put words in your mouth, but I believe you said make markets stupider and in my interpretation that meant less efficient slash easier to generate alpha. And I I kind of disagreed, but I don't want to put words in your mouth. So, I'd love to just ask you, am I remembering this correctly? Did you think AI will make markets less less efficient and kind of easier for active investors to outperform over the long term? >> I first of all, I don't believe I said stupider. >> I think you said stupider. I think super was a correct word. >> I I think I said dumb. >> Dumber. Okay. Okay. >> First of all, I think I would have said more stupid, not stupider if I would use that word. And I think I said dumb. >> Okay. Dumber. Let's go with dumber. >> I think that's what I said. So, let me and that's I'm not sure whether it's consensus view right now among investors. I I I would firm disagree which is I I I would firm disagree and I would think your view is quite non-conensus though I don't think it's completely out of consensus. >> Okay. So let me talk about how I got to that thought and also I want to caveat something. I am not a coder. I'm not software developer. My typical solution to any tech problem is to restart my computer and if that doesn't work plug it out of power for 30 seconds and then plug it back in. >> Yeah. So I want to be very very clear about that and I also want to say that as by the way it applies to anything that I say but here it's even more so I could revise my view six months later or three months later or 12 months later or even tomorrow and I am not a futurist. I am not predicting the technological future. But this is my thought process where we started with you today is that investing is a craft and it takes certain time to master that craft. The best way to master the craft if you have a great mentor you are working directly in front of him for him or her and you are learning and copying that. That's probably the best. If you didn't have that opportunity maybe you figure out it yourself. You probably spend more time figuring it out on your own and you probably got more scars on your back from your mistakes etc etc that sometimes was self-inflicted. But that's how you arrive to your process of insight generation and getting to conclusions. And in order to make strong returns, you need to arrive into some insights into the business, into the investment setup, into something else that I usually fail and nonobvious. And I think there is a danger. I'm not saying it will happen. I'm saying it might happen. Going back to our conversation about Bitcoin, it's one of those future states of the world. It doesn't mean that it will be the state where people especially younger generation of investors they will re outsource their thinking to AI. I would suspect that your parents and my parents generation on average and on average is the key word here are better at navigating a city without a GPS. I expect that our generation are worse. I also suspect that those who are now 25 are probably even worse than us at that. It's a skill of a mispronounced that you will need to correct me. So that muscle is just goes away for people because it's so easy to pluck your GPS. And I think there is a real danger that may happen with how people think, how people do research and how people develop conviction in investing. And AI is incredibly powerful tool. There is no doubt about that. Everybody says that. That's not insightful. But what it will do to our brains is an open question. And I think those people who can figure out how as the eye stands today and remember it can evolve. It can get a lot better. It can do something else that we cannot even think about right now. But as AI stands today in early August 2025, I think people who will succeed to succeed are the people who figure out how to use AI as a supplement and who do not fall intentionally or unintentionally into the trap of outsourcing their thought process to >> well I and also something else you said more you you interpreted My point is more efficient. I think market efficiency or efficient markets it's such a loaded term that everybody means something different that I would rather not use it. >> Okay. >> What I think might happen is that market will become more consensus because people will be asking roughly the same questions to roughly the same large language models. Now there will be some variation in their prompting skills and variation in particular model that they're using some of them is better at any single moment in time because there is a race between them. Sure there will be some variability but I think the answer that will be given will be fair is similar big picture and what it means I think markets will become more consensus and if you figure out where AI is missing either important data points or information is just not out there meaning it has not been written on the internet in articles in expert calls somewhere else your opportunity to generate outsized returns because everybody else is running left and you realize that you need to be running right I think will likely improve that what I meant by dama and dama maybe it's too strong of a board but it will be more consensus driven >> so you know honestly as you described it I I kind of don't know if I've got huge disagreements here with you and I I'd kind of analogize like this like I I like to say hey if somebody comes to me right now with a a P multiplebased investment right they say hey Andrew stock XYZ is trading at eight times price of earnings. I think it's a buy. I'd be like, cool. Like you there's no alpha there. You you've just bought beta and probably negative beta, right? Because 50 years ago, 60 years ago, there was alpha there. There were not computers that were doing that. You could go kind of calculate that and buy something. About 20 years ago, 25 years ago, like computers got so good, they were automatically doing that. It was kind of priced in. But what that meant was in let's call it 2010, that got priced in. and the returns to finding things that were nonobvious values and I would think about many of the compounders you talked about right figure out early Google Facebook all these sort of stuff Amazon yes they did not trade for 10 times earnings so they weren't your traditional value but they had this huge growth one way huge modes lots of ability to compound and you know for many of them I don't think Amazon was guaranteed but like Facebook and Google once they kind of locked in especially Google it was kind of guaranteed that they were going to grow and continue taking share If you could figure that out and you could invest beyond, oh, Google trades at 25 times next year's earnings and you could kind of see the growth runway in the unit economics, you could make a fortune. And I think what you're saying is, hey, AI is going to price out maybe a lot of the medium-term insights, right? Like AI is going to have a lot of insights. Maybe it's going to price out the alpha and buying the compounders and buying the unit economics. But if you can figure out like something that is beyond that, the returns to that, you know, buying Google was exponentially better. If you figured out that insight than buying US steel at four times price earnings in the 80s was if you can figure out kind of the next insight that AI is not going to generate something that it probably we can talk about what it would have to be the returns that actually might be exponentially better. Am am I saying that and summarizing that correctly? >> I wouldn't call it a sum I wouldn't call I wouldn't say that you're summarizing. I would say that you are putting another angle on this issue. >> Okay. >> And some elements I think are fair. Some elements I don't know. I don't have a strong answer. Um whether it will be whether AI will be pricing out medium short term alpha versus long-term alpha. I don't know. Uh I I I'm don't have an answer. I don't think I'm prepared to figure out an answer right now with as time passes by we may figure out. If you were to ask now I would probably say that I think it will be more dispersed. I think it will be more consensus driven. That's kind of how I think about it because if AI will be giving same answers roughly again the same to a bunch of analysts and by the way getting answer from AI in my opinion is very different than reading 15 uh earnings calls or conference transcripts or listening them live if you prefer listening and reading or better yet conducting yourself tons expert calls and and getting slowly to that mosaic and putting it together. I think it's very very different from the way you in terms of process how you get to that conviction and knowledge deep knowledge ingrained in you versus reading a 30 or 40 or 50 page output from AI which can be useful in certain cases but it should not replace your brains and thinking >> and then feeling that I have this knowledge I call it fake knowledge like you don't maybe you memorized it maybe you hidden depending on your quality of your memory and its capacity. But it's not the same as figuring out those things yourself. So that's how I think about that. What I think AI will probably do is that different competitive advantages or competitive strengths would be a better term that people have. We may become obsolete and then you need to reinvent yourself and figure out your new competitive strengths. I'll give you an example. If someone was really good at writing 10 years ago, you're just like brilliant writing. You're engaging. You're convincing. You can figure out how to deliver insights and punchlines. That's a fantastic skill. Not everybody can do it. Guess what? Now you still may be better than everybody else, but everybody else with AI, the gap between you and everybody else who is average with AI has closed dramatically. And I think it's overall theme by the way of technology and technology based investment tools, research tools including AI, including expert library, including expert calls is overall democratization of access to information and knowledge and also I believe closing the gap between investment firms or investors in general with different financial resources. In other words, hypothetically, if let's pick expert library tools for example. If 10 years ago before expert libraries came out, expert call libraries and this is all hypothetical measurements. A person at $2 billion fund has 100 units of utility because they could access someone like bespoke expert calls and pay $1,000 to a provider. That's very expensive. Now, if you're trillion dollar fund, you have the budget. You're fine. >> If you are $5 million fund, for example, I'm potentially taking something very, very small. You couldn't afford it. You're out. Then with Tibus advent and then stream and now it's all under Alpha Sense umbrella you can be subscribed you can have access to bunch of library to a library you can do your own bespoke calls at a lot cheaper price >> yes >> that democratization of access to information knowledge and insights that's fantastic so I think now if before the gap between a small fund and a very big fund was 100 units or 99 units. Gap still exists, don't get me wrong, but now it's maybe 20 or 30. It's a lot smaller. And I think AI is likely to do the same. No. So I I think that's interesting because what you're saying is like one area again 30 years ago, probably more than 30, but 40 50 years ago, your edge could be I can calculate price to earnings, right? Like your edge was basically I can do math better. Yes. And that gets that gets arbitrageed away by a lot of things. Quant fun first Excel so everybody kind of gets it and then quant funds start running and automatically applying it. I think what you're saying is hey the past 10 to 15 years one of the areas of edge might have been I can ingest uh I can ingest information either more or better. Right. As you said with the big funds, and you're 100% right, a big fund now, but especially 10 years ago, could afford to go do 10 expert calls and throw down $10,000 of dollars of research expense on a position, whereas a small fund just couldn't do that. With expert libraries, that's moving away from AI. But, you know, a big fund might have had five analysts who could summarize every sellside model, every sellside note, every expert, all that. That AI can do that for a small fund now. So that summary of information goes away. The new tools is like the the question is going forward what is the thing that will kind of get amplified by AI. And I think I've talked to R about this and I I mean in my view and you can tell me if you disagree or if I'm completely misinterpreted the premise like in my view as that kind of um ability to summarize big things of information gets consumed by AI and maybe simple thesises get spit out by AI. Think the next wave is kind of, hey, can you go find me things that are not on the internet or that are not publicly available? And obviously I'm not talking about MNPI, but I'm talking about, hey, the next wave might be you're researching a you're researching a retail company, like can you find non-obvious sources of data? Or, you know, you're researching a lumber company. Are you the person who can go and like go to a lumber conference and network with 15 people at the lumber conference? So you've got a read on how everything's going that you know literally no one else has because it's bespoke. You created it yourself. Uh I I don't know. Do you agree or disagree there? >> I think we are looking in the same direction. I agree. I will add a couple of examples or wrinkles or new answers. By the way, wrinkle is interesting word. We can speak about it in a second. So I think I I unintentionally created a pun here even though I didn't think about it before before I set it up. >> Wait, say it again. My wife is so much better with puns and word play than me that uh what's the pun? >> No, I remember I said there is there may be a couple of other wrinkles on what you said and then I realize that my example is actually fits nicely into wrinkles. >> Okay. Okay. >> So this is um big picture. I agree with what you said. I think situations where information does not exist in written form at all. That's one of the areas where it will be fascinating and I think what will and also let's step back and as you know mostly Karakan capital the found invest in small and micro cap securities not exclusively but that's what mostly I do this is where I spend most of my time so what it means it means that general if you go into let's say alpha sense expl and again I will use them interchangeably because they're in the process of converging the ch if you go there and you put pick 20 billion market cap company probably there will be I don't know few dozens of calls right that's probably pretty reasonable especially if you pick let's say TMT that are more popular among investors to do expert calls etc there will be a lot my ideal setup I go to the expert call library I put the tika in and it gives me there are no expert calls available. Would you like to request one? Or maybe it's one or two and ideally also it's kind of old. In that case, if someone goes and says and let's pick a real company disclosure, the company that I'm going to mention with uh Kakan Capital LLC and all its affiliates own shares of softwave listed in Israel. So, and by the way, that's the company that sells medical devices for skin tightening has recurring revenue business model razor razor blade and one of the consequences if you are a patient using that you remove wrinkles. So, that's why I was >> there's the >> which I said absolutely accidental and then I like oh I should use this as an example. When I learned about company's existence first and started doing research, there was only one expert call on alpha cells that's the collaborate that I use only one, not many. And by the way, it was somewhat negative in my opinion or at least it was pointing out areas where the company needs to improve itself. And by the way, in my opinion, by the time when I read their call, I thought they already fixed all those things that the former employee was mentioning. So I felt like, okay, I guess probably they were reasonable concerns, but as the company has grown, they fixed it fine. But that's all. So okay, and remember this company listed in Israel. Financials are in Hebrew. I don't speak Hebrew unfortunately. How are you going to be interacting with AI in that situation? one expert call filings and sure different titles will be happily translating those filings for you in fact I use them for that so but it's very different to interact with the in that case there is no information large language model needs to have language to give you answers something in writing as part of my work I've done multiple expert calls I spoke with patients sorry patients I spoke anecdotally that's not expert calls But I spoke with doctors who are the people buying the product and then they will be engaging with patients explain them the benefits of the treatment and using those devices and I spoke also with for about the company culture and market sales process everything what he will be asking if you now go into library and put software as a You can probably will get what by now eight nine expert calls will be my guess roughly at that at this point in time you can use AI to ask thoughtful questions. Now you also need to have thoughtful questions. So you need to have an investment process. AI will not replace your investment process. If you have a good investment process, AI will make it more robust. If your investment process is not robust or you don't have a good process at all, then AI will make things even worse. That's my subjective opinion. So now you can go interact with AI, ask questions, and you will get to those takeaways, conclusions, insights, punchlines a lot faster. What I think it means original ideas with very little information in writing and information were mostly qualitative of course will be more important to find early but then what I think will happen the discovery period of those ideas and market repricing those ideas will probably shorten. Well, look, I I think what you described fits into my thing, right? Like I I was talking about finding non-standard places of information and in my head I was kind of thinking like a $2 billion company where you go and you get cut checks at a an industry conference or something that obviously aren't what you described was finding a company that was small enough that there wasn't much information out there and you went and by doing the you know in this case expert calls and customer talks and everything you created the information for the yourself. Right? Now that doesn't mean it's a good and bad invest or investment but if you have a hundred companies with not a lot out there you go create that all and eventually you know if you're using a public expert called transcript in this case it goes public eventually but you create all the data and then you feed it in you do have edge because you you created it now hopefully you can like create the that data and like kind of refine it and execute on it properly right like that I I I certainly know there have been some undiscovered micro caps that I've invested in that uh you know I thought I had edge on and I kind of wish they had gone undiscovered by me in the long run. But you you are kind of describing um creating you are describing the same thing create creating information and having having a data having an information edge there. Let's talk more about expert calls in our follow-up uh interview tomorrow which again I'll include a link in the show not I I want to ask you something since this is supposed to be a process theme pro process. I I think about process all the time. I'd love to ask you what is something 10 year that you've done over the past like 10 years you know you are I am late 30s you're early 40s theoretically we both should actually be hitting kind of the peaks of our invest investing careers like right around now what is something that you did 10 years ago as you were kind of like prepping for the prime of your career is the generous way I'd put it that uh you've changed that you've improved on anything that you think has made a noticeable difference in your investing process >> massively ly bigger focus on the customer. So massively bigger focus more focus on the company's customers is what >> okay and let's just give me an example early on when I was running kakan I made a very uh painful investment mistake uh in a company investing invested in a company called agrih >> I know a fresh >> significant loser I think you and I spoke about it so back in 2015 uh and with the full benefit of insight if I spoken with a few customers I think I would have probably realized that customer while customers value the product there is they are not as there is a there is a difference between customers satisfied customers and raving fans. Ideally, you want to be investing companies who serve a constituency and that constituency are raving fans. And I think I could have done a substantially better job and avoided a painful mistake both psychological and P&L if I applied that framework to understanding a graph. I could have done a lot better. Now what what it led me to is I need to understand customer value proposition better. And guess what? What's the best way to understand customer value proposition? Talk to customers. Ideally, you could visit them, right? Spend time with them. But sometimes it's an it's an intangible product. So you can speak with them and learn about their why they consume it etc etc. And this is by the way I think the doing expert calls is very very valuable. understanding that customer value proposition and why customers are not switching or switching what the competing solutions what the buying process etc etc who is the decision maker within the custom organization if it's B2B product then need to understand all those things and the old school way would be ask your network now that's the best because you will get unfiltered answers but I have a reasonably large network of people from business school from other venues of my life etc etc. But there are natural limits there. So you need to ask for introductions or introductions etc etc. If you if you could find someone like that that's the best but if you couldn't then either go LinkedIn and start cold calling fantastic or use expert call providers in the past it was very expensive the cost has gone down as you and I discussed five minutes ago. >> Let me ask a couple questions there. I I like that answer. I do. But it I you know, as I said earlier, I I I want one rule, right? I want one rule to rule them all for everything I do. And one of the tough things I found with customer calls is two. Number one is, you know, what's this? I think it was Steve Jobs. He said like the customer doesn't know what they want until we give it to them, right? And sometimes I can think of recent examples. I I don't quite want to disclose disclose the company, but I'm sure people can think of something similar. a company is launching a product, right? And it's an improvement on the current product, but you know, word gets out and people know and I I talk to the the customers and they say, "Oh, you know, whatever. We don't really need that product. We don't think it's that much better. We're not going to upgrade, whatever." And then the product comes out. These are generally B2B products, but exceptions. The product comes out and then you talk to the same customers two weeks later and they're like, "We love it. We're invest. We're upgrading all of our equipment to it." Like that type of stuff. So I I that is one thing I worry about where the customer like they can be so fickle and obviously that is they were talking about something that's yet to be launched versus launch but they can be so fickle with that I I kind of worry that I talk to them and I have one opinion and then the next week if I talk to them I'd have a completely different opinion. Do you want to pause the uh recording, rewind to the place where we spoke with you about uh base rates and how you're trying to recut the universe and how you're figuring out that you're betting on outliers. So this is my response to like I want one rule answer. >> I know I know this >> Andrew this is my one rule answer to you. There are no one rule answers at all. That will be my response. Look, at the end of the day, what we as managers are getting paid for is judgments and decision making. Everything else talking to management, attending investor conference, attending industry events, talking to former employees, uh searching the web, talking to AI, reading, whatever, modeling, whatever you do, that's simply an input. a simp it simply feeds to the output and the output is your decision your judgment and decisions are based on judgments so I think what you're saying is this how can I make the same judgment all the time in similar set of circumstances and be right and the answer is I don't think you can and it boils down to and also remember it's a lot about nuances or wrinkles um in your example You started with Chief Job's famous quote. First of all, it's about B2C. Second of all, it's about the true breakthrough disruptive innovation. >> Mhm. >> When the product does not exist, I don't think that question is no. It's unknown and unknowable. You wouldn't know whether that product will take off with customers or not. And by the way, if you had an insight that this product will be fantastic, even when iPod came out, you would have been probably calling me right now from your BBJ, from your own private island. >> No, you know, let me let me give you the other side of it. I know. Yeah. >> So that's B2C and that's unknown and unknown. And then there's another end of the spectrum where products are already there. It's a B2B software company. Let's pick HubSpot. I don't own HubSpot. I admire the business and what they've done and what they've built etc. If a number of years ago you spoke with 20 customers using Hopspot, you'll probably figure out that it's a very very good CRM Martekch market technology or SAS company and would have probably figure out that the product is good and customers are satisfied and they're happy and maybe they're even more than satisfied. So that's a very different thing than talking to them about if you get this product that doesn't exist but it has this feature. It's very different. So I think you need to calibrate the tools that you're using. Do you play golf? >> Uh I did when I was a kid but right now no. >> Okay. Fantastic. So I >> I know the rules just fine. Yeah. >> Okay. So I don't play golf either. So that's why I will give you analogy from golf because I have no idea how to play it. So, um, in golf, as far as I understand, there are very many different types of cups, right? >> I cannot believe you're giving analogy from a sport you don't play. >> There is. Yes. >> And depending on the terrain, depending on the circumstances, wind, whatever, you are using a different car for each situation. I think with your approach, you have one size answer to all situations. You're trying to go to play golf tournament and you brought only one cup. >> You are correct. >> Work. >> You have all of them and need to figure out which one to use when. >> I can't believe how good of an analogy you just used with a sport that you don't play or apparently know the rules too because that was excellent. >> So now Okay, I'm glad to hear that because otherwise it will be very embarrassing if I give you analogy that was totally be misplaced. >> Let let me go to uh Let me go to a completely different question. >> Okay. >> Uh, one thing you and I talk quite a bit. I I think people can probably hear that. You and I probably talk quite a bit to, you know, the small cap value investor fund community is not large. We probably talk quite a bit to the same people. There are a couple stocks that, you know, if you go read, if there are 20 small cap value investors, you go read 20 of the letters, you know, 12 of the 20 managers are long the same one stock, right? I and I don't need to name names, but I'm sure everyone as soon as I said this who follows the markets closely can think of something. And guess what? It doesn't just apply to small cap managers, right? Like Bill Aman for a long time, he'd go long a stock and then oh, all of a sudden there's 15 other people who run like medium to large size hedge funds who are long the same stock. Like it happens. Tiger club, Tiger Club lies. Oh, look, one of them's long. All of them are long. Like it happens. You you talk to smart people. You share diligence. You all come, you know, that's great. Hopefully, you're talking to really smart investors who have really thoughtful thesises and stuff. But one thing I always worry about is it is very easy to start outsourcing uh conviction, outsourcing thought. Uh it's very easy to get into group think. It's very easy to get into the same names. And even if you like if you gave me one thing I worry about and I know you mentioned Softwave and I I I have looked at the chart recently and I'm kicking myself. you and I talked about quite a bit and there was med device issues and I can talk about those later but you know one thing I always I feel like I have a higher bar for when a friend brings me a name because I'm worried that because I respect them I will have a lower bar for it and group think and then I'll just call them up after I record and say hey what you think and then kind of rely on that. So, I just want to ask you, you know, I'm running yet another value podcast, 330 episodes, 315 of them are individual stock pitches, right? When a listener listens to this and they love an idea and obviously not investing, but they love an idea. When you and I talk, when you talk to the friends, how do you kind of like dial back and avoid the group think, avoid the, hey, I'm outsourced thinking, hey, this person has biased me in an investment, even if you're kind of going to like run the bases and do all the work on it. How do you avoid somebody you respect telling you they they've put their money behind it. They've put their belief behind it and that's not going to influence you. >> So, first of all, when you hit your 400 podcasts, we got to do another interview where I come and interview you. I promised to wear yet another value polo that you kindly gave me. >> There we go. >> Another interview. It will be the second. Remember we did after 210? >> We did. We did. And on this one, you're going to show off the Yet Another Value podcast tattoo that you got as well, right? Oh yeah. Yeah. No, I would not. So, but I can show a bottle. I can show a bottle. It's very, by the way, very nice bottle. Great size. So, um the oneline answer will be in the situation that you describe, I want to make the conviction my own. Don't outsource conviction. That's a dumb idea. But make idea your own. There are some ideas in my portfolio that I probably got from a peer friend uh whom I like and respect their thought process. But by now I may know those some of those ideas. Not all of them but I will know some of those ideas better than they do and even if they still know it better because they've spent longer time researching the company etc etc. I have my own conviction in those. So that's I think what we need to be aspiring to. So that's number one. Number two, remember we said low bar, right? I I don't think it's the right way to frame it. Low bar to invest in an idea because it came from a friend, especially if you like a friend. So I think the low bar should be applied if idea comes for from a friend or respected peer to put that idea on top of your research pipeline. There are some friends in my network whom if they call me today and say I have a great idea. Let me tell you about it. I'm so excited. This is an idea. I'll probably drop almost everything and we'll start researching that idea. I will not go and buy it, but I will go and start researching. It will it will be it will trump over bunch of what I didn't have in my pipeline that I sourced myself or already I got from someone else. So I have a lower bar there. But my bar to invest could be the same. That's what I aspire to. I am a human being. I'm fable. There are probably cases where I did not execute to that vision that I just described and maybe I indeed did lower the investment bar. It's possible but that's my inspiration. That's what I force myself to do. And the way you force yourself to do it is by following your own investment process. If your investment process is for example to read three years of all earnings calls and conference presentations do not shortcut it just because idea came from a friend whom you like and respect. Go and do it. And again, I'm using kind of very simplistic, very rule tools. If your rule of investment process, read five customer expert codes or do your own if they're not available. And by the way, five is a pretty low threshold, by the way, especially if there are 20 in the database. It's a pretty low threshold or 30 or 50. So you go and do the same number of calls that you always do either your own bespoke if you that's your process or if you're okay with reading someone else calls fine go do it you don't cut it if your jaw if your process talk to management and ask them your questions that on top of your mind etc etc do not cut that step out just because idea came from a person who you deeply respect so and again it's one thing to say I want to have the same level of convictions I do on my own ideas Sure. But the way you get it done is via your processes and your routines. That's how you get it done. So, and then also this is very important um about ideas coming from your network. I have friends I'll use myself as an example. If I call you Andrew and say, "Andrew, I got a great idea for you. First of all, I hope you will pick up the phone. So, >> no, I I you know, I'm said I'll call you when I'm walking penny. I'm with Sylvie. I'll call you when I'm walking penny. >> So, if I call you and say, Andrew, I found this company. It has $200 million market cap. It's listed. Pick a country where most people don't look at and there is no sellite coverage and there are no well investments club writeups or maybe there is one but very little information and there are no expert calls and blah blah blah blah blah blah. I wouldn't I would suggest that you listen to me carefully and thoughtfully and maybe put that idea on top of your research plan. If I call you and say, "Andrew, I found this great I found this great investment setup. It's a call company on the East Coast trading at four times earnings, but they're going to pay a big special dividend. I think you should hang up on me." Why? I don't think I know how to do those investment situations. That's not my cost strikes. And most likely what I'm calling you about is a pretty lousy idea. And I don't think >> funny you said special dividend. I was like, I'm here for it. Arun's the company. >> I know. But remember, I usually don't call you with this type of ideas. So you need to calibrate when this an when an investor friend mentions an idea you need to calibrate whether that's a place imagine a hypothetical investor with a very strong track record okay but you need to figure out in my opinion I want to figure out where those returns came from what type of patterns and situations if those ideas came from cold names trading three or four times earnings returning capital doing buyback or doing a tender or whatever I won't probably listen to that person when he pitches those years if that person made money on software as a service names. So software as a service companies uh that are one to two billion market cap and they about to become five or 10 billion dollar company in the next few years. I want to listen to those ideas from another person. So I think that collaboration is very very very important. No, that's super interesting. Especially because there's a company you and I have been talking about uh that fits one of the descriptions and it just rips higher in my face every day and I'm like uh nei here. Uh one of the great things about being podcast host is I can ask completely simple questions under the guise of asking for my listeners. So I I I want to end with one question that has really been on my mind recently in terms of process improvement. We we've talked a lot about ideas and stuff, but in terms of sizing, force ranking, however you do it, your ideas. How has that changed for you over time? That's a process and that's a difficult one. And it's difficult one because you would never get everything perfectly right. And that's difficult. So, and this is just ecologically challenging and and do you know this? I don't know whe the people who listen this will know will know this or not about me. In my prior professional life, I was an international tax law in New York working for a big American law firm. So think about this. I get I'm an associate. I'm getting an assignment from a partner. Research certain situation. Let's say where do our client wants to do a taxfree spin-off. >> Yes. >> Do we have the facts that will support tax-free treatment etc etc. We need to do analysis as an example. Right. So if I come back to a partner and say hey this is my memorandum legal memorandum I wrote let's say 10page memo and that memo is about 60% accurate I think the tax partner should take me and kick me out from the 38th floor of 200 Park Avenue that was our office uh was and they would be right for doing so now they're very nice people I hope they wouldn't but you see my punch time. If you're right 60% of the time in your first ranking your positions or managing your portfolio on your expected IR, you're probably doing pretty well. And that's a very challenging mindset for anybody. That's why I think people for example who play a lot of probabilistic games and come to investing they may have a natural psychological edge because they used to that like playing poker they used to that they may have a good hand and they might still lose it so that's very different mindset and for me personally it has been a challenge to adjust since the time I left legal profession went to start business school then worked for another hedge fund then started Kakan capital that's not easy psychologically so what I want to tell you is that it doesn't mean that I have the perfect answers and it doesn't mean that I get it right and it's work in progress so I think I've become more mindful of looking more carefully at the expected IRS but and I cannot say that I've never done it it's more about doing it a more systemic way and comparing them but it's still very very tough you Know, so expected IRS is an interesting one because I I was talking about this with someone the other day. I I I've gone back and forth so many times on it. My issue with expected IRRs is what I found is when you do it by expected IRRs, and there are other ways to modify this, but it would push me to be into the most levered stuff out there because it the most levered stuff is what gives you the highest upside, right? And that could be the correct answer, right? like uh Todd Wesler who is one of Bergkshire's portfolio manager everybody talks about his IRA right his IRA was two or three bets superlevered companies that survived and went up 100x right so it's possible that we should be taking advantage of the convexity of non-reourse leverage in the stock market by buying companies that are super levered right but it what I was finding was when I would do a force ranking by IRR and I mean at some point I would cover like 50 companies and I would do like little hey here's my fair value I sound like a sellside analyst. Here's my fair value. Here's where the stock is, what trades at the biggest discrepancy. And what I noticed is, oh crap, all of a sudden my portfolio is just the most levered companies I follow in general. Right? So that's why like I've gone back and forth on IR. And then I had somebody say, "Hey, well, charge yourself a volatility factor, right? Or you can do it on an unlevered basis, right? Judge everything on uh the EV, judge everything on an EV basis and how much it trades on discounts of the EV." But when you go that route, what do you end up with? you end up for the most part investing in companies that have huge net cash balances, right? So you've got almost no beta on the upside because yes, they trade their EV is 50, they're trading for 25, but it's all net cash and you're just kind of waiting for the cash to be returned. So I've just gone back and forth so much. Go ahead. Go ahead, please. >> Okay. You want one size answer as you and I >> I know. I know. But I'm also just discussing and being a very handsome podcast host. >> Oh, absolutely. So look, first of all, stylistically, I think you and I were we stylistically diverged the most like philosophically. I do not like le companies and remember you and I were running um informal no recording uh book club that we need to resume doing and we discuss in a particular book one chapter per per conversation and our biggest disagreement on one of the chapters was do not invest in led companies and for me that was very natural like yep I subscribe to that view I rarely invest in led companies again. I put the book down and never read it again. >> You're like, that's nonsense, right? So, you and I disagree on this philosophically and that's totally fine. Now, if you invest in love companies or you invested in a number of them in your portfolio, yes, you cannot if you rank them all purely on expected IR, you will end up indeed with having all those names at the top of the list. what I would encounter and but what is interesting to me is that you said okay then I try to do it on volatility but then I end up with bunch of companies that have very like little EV because they have too much cash >> the volatility was you charge a volatility factor to account for that and I I struggle with that so then I switched to EV and then you just get a bunch of net cash companies >> and and I think this the the in my if I were you if you hired me as your portfolio management coach by the way I don't think you should but if you were to make that dumb decision. In that case, I would say Andrew, you need to apply a penalizing factor to those you you will have simplistically two variable ranking system. One would be expected IRRa, but then you need to add another one that will account and now I will show the uh quotes risk. Risk I'm not talking about volatility here. I am talking about the company going bust. >> When I said volatility, I did kind of mean risk. I wasn't talking about stock market volatility, but please continue. >> Okay. So, and then you would be applying most likely fail significant penalizing factor or downward adjustment because it's a le company. If you tell me I have two stocks, I only imagine the world like now we'll play microeconomics 101. This product A and product B. That's all. There are no other products in microeconomics 101. So there are only two stocks stock A and stock B based on your map and let's assume that you have really good math and really good estimates and everything 25% IRRa over the three-year holding period on each of them. I will say fantastic candidate what's the name well give me a call I want to know the thesis. So but then I will tell you one of them you tell me is has zero bet another one has let's say six times IBIDA four times of bet and two times of equity I will say that you are the these two opportunities are not born equal >> right now I don't know exact part I don't know exact all exact those variables but I think you need to force that and apply some kind of borderline common sense that here IR show my math my Excel my master Excel file spits out the same IRS but they're not born equal and then you adjust for that for me it's probably a little bit easier because I don't invest in as many companies but I have another other issue sometimes for example few months ago you and I were discussing and then I You mentioned this in one of your rumblings without naming me which I appreciate the anonymity but at some point I think you and I chatted about do we as investors take upon ourselves and our portfolios certain level of existential risks and whether we're properly pricing them and that's a fascinating question because it can be 3% probability of something really really really negative happening like imagine if you was selling product And then this product got outlawed by the entire nation. >> Yeah, >> that's a big problem. You all of a sudden go out of business, right? And taken intentionally an extreme case. >> Extreme case, right? >> Huh? >> An extreme case that happens. I mean I mean this does happen. You we there are companies who have their products literally banned. >> Yeah, it it would happen, right? So or imagine if you were investing in a naturally resource company. By the way, don't do that. uh in uh an emerging market country with not very stable government and not very stable political regime that may not necessarily respect bilateral investment treaty. >> Yeah. >> And you may own some the best I'm making this up. Okay. the best copper mine in country X and then when they wake up there is a military coup in that country and now the new leader in it in his ultimate wisdom believes that they now should be running that company instead of your company that is listed in NEO doesn't even have to be a compromine I I've said I think I did a rambling on the podcast things that you say no to and Chinese companies I've I've really struggled with because a I I've never been to China so I the culture and like there's so much more online is difficult but me I just keep thinking of like the Alibaba ant financial like hey it belonged to Alibaba and then it did not and like how do you account for the 2% risk one whatever the risk is of the government just forget the VI structure all the risk the government just deciding hey this company your assets now belong to us right like it has happened in China and I I'm just not sure how to account for that risk >> andrew what I can what I can tell you is that uh you are welcome to build the channel with me I'll take you there and uh >> the second kid is on the way but you you know, I've been planning a trip. May maybe after the second kid's a little older and Alicia won't uh won't throw me out if I'm leaving her around for a 10 week 10day trip over to China. >> Like, as you know, I've been to China many times. I speak some Mandarin. Uh my son speaks massively better Mandarin now, so he fixes my mistakes when I say something incorrectly, which is hilarious. So, yeah, I can take you there. >> I appreciate it. It's going to take the Chinese stuff off my no list. It's going to add so much more to my Okay. Anyway, did you want to have any concluding thoughts here because we're running pretty long. Uh we're gonna I'll I'll say what we're going to do next, but any any concluding thoughts on that or anything else we've talked about today? >> So, going back to what we discussed briefly, I want to ask you remember when you spoke about borrowing the risk of relying on someone else conviction and as a result made an investment mistake and you spoke about there is a relatively small cap. It is a relatively small community of call it small cap managers. >> How many are out there you think in units? >> It's tough because there are bolt-ons there like everyone's doing it a little bit differently but I I mean I think there's a core group of like 50 people who have similar investment styles which I would say is for the most part but not always. Garpy undervalued sub billion dollars let's call it and then there are people who like are alongside the edge of it who might go much smaller much more liquid or might have more like kind of me with maybe a more of an event eventy angle to it is what they focus on but I'd say probably if you're like the core and I think everybody like reads their letters and everybody talks to them and all of us like catch up with each other once every three or six or nine months and like maybe sees each other at Bergkshire the Bergkshire meeting or something But that's kind of what I would say. >> Okay. I got a question. You United States of America has about 330 million people living >> roughly. >> Do you think that the entire nation and let's forget about our peers who may be based in the United Kingdom. Maybe they're based in Asia. They may be based in Singapore, Hong Kong, continental Europe. There are many place in America. There are many play many wonderful investors there. So, but let's put those aside for now. Do you really think that the entire nation of 330 million Americans has only about 50 people 50 who do small cap investing in the >> No, no, no, no, no. This was small cap small cap fund managers running similar styles who are are chatting with each other. I I think there are much >> much more. >> Okay. What fascinates me is this and I don't know the answer. Maybe there are not 50 people like this. Maybe this maybe there are another few hundred people with somewhat similar style but that they're just not chatting very much with this 50 who you and I know. I don't know the answer. I'm genuinely curious. And by the way, so since I Okay, let me do a plug for myself. If you are a small manager, small meaning not your size of M necessarily, but in terms of way you invest like small, micro, even small to midcap and uh we don't know each other like reach out to me on LinkedIn and you can send it it the end. >> How dare you? >> That's what my podcast is for. Reach out to me puff on the podcast. reach out to Andre then reach out to me too because I would like to meet other people in the space especially what is interesting and there is this as you mentioned they're kind of mid-30s and early 40s so what I think is interesting there is a new generation of investors who are now I don't know mid20s very early 30s who are doing what you and I started doing let's say roughly 10 years ago plus minus couple of years but this new generation I know some of them I don't know many of them I would love to get to know They're younger. They are viewing the world differently. They have their own competitive strengths. They are different from ours from their competitive strengths are different from our competitive strengths. So like I'm very I'm always very happy to meet those younger investors. By the way, older too, but older I'm more likely to know because they probably have been in business longer. I probably met with them one way or another. But the younger guys and women, I I don't necessarily know all of them. So, I'd like to meet them, learn what they're doing, talk talk ideas, etc., etc. >> Ditto. Ditto. Always looking for young podcast guests and everything, too. So, cool. Uh, Art, let's wrap it up here. I I I will just again, we you touched on expert calls a little bit. We touched on AI a decent bit, but we are going to do a webinar with the help of Tikas AlphaSense really discussing how we're using expert calls and AI in our research process investments and everything. So, I'll include a link to that in the show notes if anyone's kind of interested in diving further into those topics in particular. I mean, look, I was going to say in particular, expert calls have been a big focus of mine recently, but actually both. I mean, I'm spending so much time using different AI tools and stuff and like I've got so many things I want to talk with you about there, but we're running super long. So, Ardan Folken, one maybe my favorite guest overall. I can't think of anyone off the top manage. One of the most popular guests. Thank you so much for coming on. I'm looking forward to the webinar, including Blink. Oh, Ardum's got one one more thing. There's always one more thing with Ardan. Go ahead. >> Oh, yeah. As you know with me, I think it was Burford number two, number three podcast when we were trying to uh desperately wrap up the podcast. I was like, Andrew, one more point. One more point. Okay. So, one more point on this one. I think it's the last one. When you say, "Oh, >> uh, you're spending more time on expert calls and thinking about the best way of doing them, etc., etc." And but you also think about AI a lot. And I think the interesting thing is this. I almost think that expert call libraries and AI is the match made in Hub. >> Yes. Oh, >> okay. L. >> Don't spoil the webinar. Don't spoil the webinar. But it's interesting. So because you me it's your fault you mentioned that right? So it's it's large language models. The language is the key word here. >> Where else other than SEC filings there is so much density in words. >> Well like what else? So like like they were kind of again it's a perfect match in my opinion. >> You were the one who told me I I mean this alone revolutionized a little bit of of my research project. I hate saying what revolutionized because I don't think it let but it sped it up a lot. You know what I do now when I want to read an expert call? I mean, Alpha Sense does have the summary of it, but what I've started doing if I follow company, it's got five expert calls. I toss all five into an LLM, say, "Summarize it for me." And then I summarize that. And then if I'm still interested in the company and want to learn a little bit more, then I go to the individual expert calls and read the summary there. And then if I'm still interested and like really want to dive in, then I go read the expert call itself. And by doing that uh again I give credit to you. You were the one I believe who told me this by doing that when I'm reading it instead of like you know when you see when you read new information for the first time it's actually very hard to process but if I've kind of already read a summary in that case almost twice I kind of know what's coming. I can really parse the language and I really understand and I found my retention and my absorption is much better. So I mean that is just one way it is so perfect but it is it's been an incredible tool for uh marrying expert calls and AI together. appreciated giving me the credit. That's true. I did tell you that in terms of how I was using AI uh in expert calls. Now what I would say and let's conclude there because I don't want to spoil too much about our second conversation is this uh this is the framework which is very simple and it's not mine. I heard I learned about this framework from Paul and who used to be a portfolio manager at Viking and he did two fantastic podcasts. One with Tatsiders on Capital Locators. Another one is invest like the best with Patakashansi. I believe Patashansi podcast came out first. Both are fantastic. I probably listen to them three times each over the last couple of years. And he Poland right there offered a simple but in my opinion incredibly effective network framework digging, analyzing, deciding. And what I found when I think about my own uses of AI is where AI fits in this three-stage framework digging, analyzing, deciding and where I can use more of it, where I can use very little of it or maybe even zero of it. So, but let's pause here because that's how I will be kind of training. >> Okay, great. >> This is a great pause. We're going to do the webinar links in the show notes talking about AI expert calls. But Ardan, this is awesome. Again, I just wanted to come on and uh we talked about a bunch of stuff. I just wanted to come on and improve the process with you and hopefully uh I've improved my process a little bit, helped you improve your process a little bit and hopefully our listeners are going to improve their process a little bit from listening to this. So, this was awesome. We'll talk soon, buddy. And uh we'll go from there. >> Excellent. >> A quick disclaimer, nothing on this podcast should be considered investment advice. Guests or the hosts may have positions in any of the stocks mentioned during this podcast. Please do your own work and consult a financial adviser. Thanks.