Rules based investing with Methodical Investment's David Kaiser
Summary
Strategy: Emphasizes a rules-based value approach balancing discount and quality, executed with portfolio-level decisions and strict process discipline.
Profitability Filter: Holds only profitable companies (net income excluding one-time items), with quarterly checks and removal if profitability lapses.
Sector Positioning: Currently tilts toward consumer discretionary, limits exposure to financials to avoid factor crowding, and avoids biotech due to volatile earnings.
Rebalancing & Risk: Major rebalance annually (post tax-loss season) to refresh discounts; outliers are excluded and cash can rise if portfolio becomes pricier than the benchmark.
Data & Metrics: Uses Cap IQ data, scrubs one-time items, and triangulates value/quality via PE, P/B, EV/EBITDA, and ROE to build a superior aggregate portfolio profile.
Market View: Sees the 15-year growth dominance as unsustainable, citing concentration and FOMO, and expects eventual reversion favoring value.
Cyclical & Governance Traps: Mitigates cyclical peaks and governance pitfalls through diversification (50–80 names), outlier removal, and consistent rebalancing rather than name-by-name overrides.
AI Stance: Not currently using AI; believes consistency may be a differentiator as others converge on AI-optimized processes, while acknowledging AI’s utility in research.
Transcript
All right. Hello and welcome to the yet another value podcast. I'm your host, Andrew Walker. Uh we've got an interesting one for you today. You know what? I'm a little off because I went to the gym for lunch and the waterline broke. So now I'm just I'm in my head. I am just a a nasty nasty person because there was no shower and I'm an unshered host right now. But we've got a really interesting one for you today. It's David Kaiser from Methodical Investments. David runs a quantitative rules-based uh firm and I think I think it's gonna come through in the conversation. It makes for a really interesting b uh backdrop. It makes for a really interesting discussion when you're saying, "Hey, you're coming up with all of these rules." You know, a lot of the things I've talked about on the podcast, how are these rules getting impacted by AI? How do you think about when I'm doing something that's rules based? Like if it's rules based, can computers copy it? How do you think about evolving or not involve evolving with the times? As you know it, as I'll say on the podcast, Ben Graham, if you read the intelligent investor, he's telling you to buy things for twothirds of networking capital. Well, guess what? You haven't bought anything but Chinese frauds in the past 40 years if that that was the only thing you were buying. So, how do you think about maintaining a a rules and a value based and almost a religion, but you know, evolving with the times or not evolving? So, I think it's a fun conversation. It's it's going to be, you know, I try to start off with if you are a fundamental focused investor, what's one thing you can learn from rules based investing, but I think it's going to make really make you think about investing and sticking to principles and everything. So, we're going to get there in a second, but first, I'm going to stop rambling and go to a word from our sponsors. This podcast is sponsored by AlphaSense. 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Thousands of consistent channel conversations every month deliver comparable signals, helping investors spot inflection points weeks before they show up in earnings or consensus estimate. The best part is that these proprietary channel checks integrate directly into AlphaSense's research platform, which is trusted by 75% of the world's top hedge funds with access to over 500 million premium sources. From company filings and broker research to news, trade journals, and more than 240,000 expert call transcripts, that context turns raw signal into conviction. The first to see wins, the rest follow. Check it out for yourself at alphasense.comyavp. That's alpha-sense.comyavvp. >> All right. Hello and welcome to the yet another value podcast. I'm your host Andrew Walker with me today. I'm happy to have on from Methodical Investments, David Kaiser. David, how's it going? >> Good. Thank you for having me, Andrew. >> Hey, really excited to talk today. Uh before we get started, start this podcast the same way I start every podcast. Quick reminder, we'll remind everyone nothing on this podcast is investing advice. You can see a full disclaimer at the end of the podcast. Um David, super excited to have you on. maybe a little bit of a different chat today, but um you know, you run methodical investments. Uh it's more of a quantitative rules-driven firm and I I I'm always fascinated by rules and quants in markets and stuff. So, actually before I get there, why don't you just give a quick overview of methodical and then we can kind of dive into the conversation. >> Yeah. So, we're fundamentally driven data focused and rules-based value investors. I guess that's the best way to put it. >> Cool. Uh let's we'll dive into that in a second, but you know when I have most of the people on this podcast come and pitch single stock individual uh qualitative focus I I guess let's just start off with a headliner. You know if somebody's listening to this like oh we've got a quant guy on I I want individual stocks. What's just like one thing that you know fundamental qualitative investors, concentrated fundamental investors could take away from rules driven quantitative models that kind of would just improve their investing overall. >> Yeah. So, and also I'll start with you know my background is subjective qualitative research right individual company research. So that's where I come from and and then >> where were you before Methodical? >> I was at Robotian Company. >> Cool. >> Uh actually I'm still at Robotian Company. >> I know. I know. I just, you know. >> Yeah. No, just full disclosure. Bob's a friend, popular podcast guest. You gota got to get the robot name when you can. >> Yeah. No, and I I wouldn't be where I am now, even though this this deviates somewhat without Bob. And so, um, you know, learned so much about, you know, fundamental, qualitative, what drives uh company growth, you know, what what to look for, what causes stocks to go up, what are the important drivers, right? And so um you know I really got focused on to digress a little bit on you know what those drivers are how to exploit them in more of a a rulesbased uh arena right so do what you're comfortable with stick with what you like and I like structure I like organization I like process and that's kind of how I got here so one of the things I think you can take away is qualitative and that subjective way of investing absolutely has place can be excellent to have rules to have process can give you comfort both in how it's performed over time and also in in an A to B right so if X happens you're doing Y it's not about trying to figure out with each individual company with each portfolio however you look at it what the next step is and I think that's a big difference with rules-based and quantity itative investing is that level of comfort and knowing and being able to communicate if you have clients what happens if right let me so I I think this is going to be a recurring theme through the the package let me just riff off that for a second so you said rules base you know if X happens then Y happens and one of my worries just overall as an investor you know for the past 30 years all investors have been worried like hey when is passive going to replace all when are computers going to replace all >> one of my worries is the things that computers and AI are the best at is following rules right if X happens do Y it's replacing humans in all fields all across the board and this is even before AI and software like if you have a rule that can be followed eventually a computer will automate that and when you say having this rules base and having like if X happens then Y the the first thing I worry about both from a quantitative qualitative whatever perspective is like why isn't that something that's just if it's not already being done by AI that's getting done by AI in you know six months two years whenever you want but why isn't this something that like turns us into dinosaurs eventually >> you know I don't have an answer as to how it won't turn us into a dinosaur I think and my understanding and and you certainly have a better understanding of AI I think than I do in this arena it it's learning it's adapting right and one [snorts] of the things with with having rules and being consistent and certainly the way I look at things is that history repeats itself. So, it's not about adapting all the time. It's more about being patient and understanding that there are times when what you're doing may not be uh create the effect you want, but that it will and to have that patience and to have that uh fortitude, whatever you want to call it, hutzba, right? To to say, all right, I'm not adapting in in terms of trying to figure out what's working today. I'm working on what has worked over over time. Look at value investing for 90 years and and that sort of thing. And obviously the different techniques and that sort of thing, but we're looking, you know, methodical. We're looking to exploit those inefficiencies and and actually I would argue that to some extent AI and and uh the inputs probably feed into uh more opportunities and more inequity in stock pricing. >> One thing you said there, right, you said not adapting. I think you used that term three times and >> I I I've written and talked recently about adapting, right? Like >> when you say not adapting, I I could see two schools of thoughts, right? I think of the markets as a competitive game. And in every sport I followed, >> the people who don't adapt, right? In the 2010s, there were the people who say, "Oh, the three-point ball, if you base a team around the three-point ball, you could never win the championship." Those people are out of the league now, right? The NBA is all about three-point ball. If you rewound it, you know, if you went 50 years back in the NFL and you said, "Hey, we're going to run a a passbased offense." They say offense, running base, right? Those people are out of the league. So, on the one hand, I hear not adapt and I say, "Hey, are you Phil Jackson? Hey, how are those threes holding up in the 2010s and you're about to get out of the league?" Or on the other hand, you know, there there is there's the Lindy effect, right? Like, hey, there are these overarching principles and every all the time people say, "Hey, I can get away from these principles." and the the cycle the pendulum always swings back to them and buying things at a discount that that's kind of like the Lenny thing. So like how do I marry those two in my mind where I hear don't adapt don't adapt don't adapt and say markets are really damn competitive. One one more I out there throw like if you go back and read the intelligent investor, right? Ben Graham's whole thing was buy stuff for twothirds of working capital and that's great but those are generally gone and the things that are still in the market they're they're so stressed or so likely to be frauds like there is no off like what Warren Buffett did was he adapted that approach right he said hey let's make an intrinsic value and it doesn't have to be a hard asset. So when I hear not adapt how do I know it's like Lindy versus the guy who refuses to shoot three-pointers. >> Yeah. So okay, two things. one in reverse order. Uh yeah, it's not just about discount, right? As as Buffett ch, you know, changed from what Graham did. It's about quality, too, right? It's it's that balance. And and Graham kind of was a quant in my mind because he was very strict on criteria, right? Now, his criteria was so strict in terms of what you would buy a company at that he he would have no opportunities today, as you say. Right. [snorts] So what I'm talking about not adapting is maybe an approach and and and the rules not that there's no evolution in the portfolio. I don't know if if that's makes sense. So in other words, we don't buy the same exposure, the same pees, everything like that, you know, like metrics like that every year. we're using the same techniques and we're getting different results not just in terms of performance but in terms of the the complexion of the portfolio and so so I think uh you're you're two different things right one is adapting the rules over time and the other is does the portfolio evolve even with the rules the the rules of the NBA haven't changed right to give you example the NBA the rules haven't changed it's the way that teams have approached and and and offenses have evolved, right? And and that sort of thing. And is the game more physical, less physical, is shooting more, you know, there's all sorts of of factors, right? But but the structure, the court's the same size, the rims are the same same height, and the you know, those those type of things, the rules haven't changed in that regard. I think the three-point line came, you know, 23 feet and, you know, stuff like that. >> You are correct. When you said the rules have changed, I was like, well, the three-point line came in in what 40 years, right? It's been it's been consistent. We have mentioned for not the NBA rules but we have mentioned the rules that methodical follows for a long time and I you know in my mind when you say it I I've got an idea of what they are but I could be completely wrong and for my listeners like why don't we talk about what are some of the rules that that that are getting followed here. >> Okay. So uh rules in terms of structure of of portfolio construction right and also rules in terms of risk management and holding holding period things like that right so what are some of our core tenants we're looking for a balance of of quality and discount right probably not in that order discount and quality right so [snorts] uh we uh sorry we consistently apply the same metrics and the way we do that is we take a step back and we look at the portfolio as a whole. Okay, so one of the rules is pretty much everything is done on a portfolio level in terms of of decision making so to speak. Um, two, we only hold profitable companies. And I think that that's an important thing because we rely on metrics and we look at the complexion of the portfolio and how it compares to our benchmark, right? And things like that. Um, other benchmarks, the market, whatever you want to look at. We're looking for a a portfolio that looks better. It's more discounted, has better metrics, right? So, if we're doing that, we need to look at it on a whole. And by doing profitable companies only we are allowing for reliable information. So if you look just as an example if you look at the Russell 2100 value right uh Russell 3000 doesn't matter and it says the PE is 18. I'm just being arbitrary. The PE is 18 but there's a percentage of those companies that aren't profitable that that doesn't go into that right? So it's 18 but they're also unprofitable companies. So one of the the rules one the tenants is to to own profitable companies right so that a they tend to outperform over time and since we're not picking individual companies in the same way as a qualitative subjective concentrated investor would [snorts] we are uh we're wanting that that data to be as reliable as as possible. So I think I'm getting a little off here but >> no no that's great. I actually had a question on data but let's start >> let me start at the smaller profit level and then we can zoom out to you said we only buy profitable companies >> correct >> what is a profitable company is it gap net income profitable is it >> adding back onetime items is it IBIDA how are you getting >> no no we use we use net income and we exclude onetime items >> okay >> so uh let's go to data and then we can come back that >> one of the things when you say rules based and I understand rules based versus quantitative are are different based on what you're saying, but there there's some similar. One of the things like with screeners, I always have this issue and I think I emailed this to you and listen to my news like Gotham ran the little book that beats the market and they had hey you sort by your quality metric is your return on invested capital and then your valuation is EV to I think they use EBIT >> and you kind of blend the two and that's how you get your your blend of quality and value and then they would have this huge aster that said hey we have to exclude biotech stocks because all the biotech so many of the biotechs trade for way below cash, they're too cheap, we have to exclude them. >> Uh with yours, when you've got, hey, we look for profitable companies. Like the first thing that the two things that jumped out to me is a the biotech stock exception, right? And then b a a mining company, right? It feels like if you're saying, hey, we need to buy profitable companies, then you're going to get a lot of mining companies when mining is really effing hot, right? Gold is 5,000 and guess what? Gold miners are profitable and they're thrown in there. And history suggests like the wrong time to buy the gold miners is when gold is 5,000 and they're trading for a five times price earning because it's a super cyclical high. So I I'd love to ask you, you know, let's start with the cyclical and then we go back to the bte. How do you handle that cyclical process, right? Because it does seem like the portfolio could tilt really heavily into cyclicals at the top of the market. If you're just like, hey, we only buy profitable companies cheaply. That's going to push a lot of cyclicals in there. >> Yeah, it it's a good point. So first of all and you talked about rules we we own quite a few companies and we don't have concentrated portfolio in terms of of equity uh individual names. So we will cluster in sectors and we will take uh we we'll invest more heavily in certain sectors than others right based on exactly what you're talking about the clustering right but we're not just looking at two metrics we have a variety of metrics that go into the selection process and it is really looking to a more holistic view right it's not just focusing on A and B it it looks to create a portfolio in aggregate that has better valuation metrics and better quality metrics like return on equity, right? We want that higher. We want lower PE, lower price to book, we want lower enterprise IBA, things like that, right? So to do that, you're not just taking two metrics, although I I'd be lying if I said that, you know, Gotham wasn't uh and what, you know, Greenblat does wasn't a impetus for kind of my thinking about this, right? But I think it it has to be simple but also more complex than than just two metrics. So, do do names get in that maybe shouldn't or they're cyclical and that sort of thing? Can it happen? Absolutely. Do we mitigate it by kind of spreading out the risk in terms of companies? Yes. And we rebalance. So, by rebalancing consistently, if we're wrong, we're wrong for a relatively short period of time. And and again, there's that balance of quality and discount. It's not just about discount. What sectors right now are just like like I'm sure over time different sectors pop up, right? Any anybody's running a value screen or different sectors? What sectors are consistently popping up right now? What sectors is the rules and the factors leaning overweight right now? Because I I think it's really interesting to see what sectors are getting discounted. >> Yeah. So, right now we're we're heavy consumer discretionary uh which is it's such a broad um uh sector, right? There's a lot of different things in there, but right now we're uh we're long we're we're heavy consumer discretionary. We have some energy. Uh not as much as we've had in the past. Uh but this year we're pretty heavy in energy. Financials is up there. Um I think those are the biggest. I think industrials is up there, too. >> So, uh >> I'm going off the top of my head. So, >> no, no, no, that's that's fine. Let me so one question I like to ask every podcast guest right and again normally it's individual stocks but the market is a competitive place what are you seeing that the market's missing let me just ask you like the market especially when you're talking about applying a rulesbased model which uh a rules based or quantitative models which you know that is computer-based you hire one computer programmer and they can go run you know Renaissance runs with 30 people and can manage $40 billion and they've got the best computers in the world and they they can generate 50% alpha forever uh you're talking rules So it can handle a lot more money. It's a lot more scalable. What are you seeing that's kind of your competitive edge that allows you to compete in the market against you know just a the market in general but b all these quant models and quant specific firms that are trying to compete here. >> Yeah. I think uh going back to what I talked about which is my background right. I didn't come at it from a scientific view. I came at it from a fundamental qualitative view. Right? That's my background. And I think that gives me a little bit of a unique perspective in terms of of competing. I go back to and and I I feel like I'm being a dead horse, but the the consistency and and not constantly or even frequently changing your approach and having that patience and having the um the the willingness to to h the confidence that the market will give you opportunity and you'll be able to profit from that opportunity. >> Okay. So you've got a rulesbased system and it it's heavily value based, right? It leans value companies >> very much so. Yes. >> The past, let's call it 10, but I think it's been more like 15 years. >> Yeah. >> Growth has stumped value, right? >> Absolutely. >> And you know, you'll hear a lot of people and it's not just quants, right? You you read the Einhorn letter and he'll say broken market, passive lows, all this sort of stuff. >> But I guess at what point you said the confidence to stick to the rules. At what point do you look and say, "Hey, instead of uh what's the Simpsons thing?" It's like, "Are the kid is it me?" And then he said, "No, it must be the kids, right? It can't be me." At what point do you look in the mirror and you say, "Oh, it's not the market. It's me." Like like how do you >> deviate like uh kind of, hey, I'm insane. The definition of doing insanity is doing the same thing over and over again. 15 years growth being valid versus no, I'm sticking to rules. So, uh, you know, it's a it's a great question. I don't have a a clear answer, right? I'm a I'm stubborn in terms of process, right? Um, and what is my breaking point if that's what you're asking? I don't know. I'm certainly not there yet. And I think um uh historical data and and you know talking about data uh supports the unsustainability of what what's happening now that people are are paying unreasonable prices for for quality at this point. And um so uh I have more confidence today than I probably did three years ago. Uh just because of of where things have have progressed in terms of valuation, in terms of concentration, in terms of you know how much people are betting on the future and not paying attention to what's going on today as much in my opinion. >> Uh we are taping February 3rd, 2026. This is like a borderline black Monday for payments and software. I'm curious have payments and software started popping up in your models recently? >> No, not really. Uh we have very little exposure to uh like it and and things like that. Um and also we we rebalance in January after tax law selling there's a added bump in terms of cheap things getting cheaper, right? discounted companies getting cheaper, uh, more discounted. So, um, what's happened over the past month doesn't really affect so much what we're what we're doing. >> Let me ask corporate governance. And corporate governance has been a a big >> focus for me. And a lot of the stocks I know that are the absolute cheapest are that way because of corporate governance, right? So, you've got a great business, great asset value, all this sort of stuff, and the the CEO just seems determined to light the money on fire through dumb acquisitions or >> pocket everything for himself. >> And one place I could see a rules-based model really failing is that accounting for, you know, you it's very difficult to read a 10K or 10 Q or proxy and say, "Oh, this CEO is going to take everything for himself." But it's pretty easy if you're an investor and you like read two conference calls say, "Oh my god, I'm swimming with sharks here." >> How do you account for corporate governance when you're you're running this? And how do you not just end up in, you know, 15 different hold controlled companies that look very cheap and the CEO is going to pay themselves $50 million per year for all time and shareholders will, you know, take what they can get. >> Yeah. So, uh, we don't have a specific fail safe for corporate governance. you talked about really cheap, right? And one of the things we do and we I guess we're going around a little bit with the rules is we're not buying the cheapest, right? We are uh when we look at the data, we're removing outliers. The things that are really cheap and whatever metric you want to talk about, right? PE, price to book, etc., they probably are for a reason. And then also that combination of metrics is is important, right? It's not just that it's the absolute or even one of the cheapest PE companies, right? that's not enough. So in terms of corporate governance uh it's not something that we we apply and and I think theoretically right and in practice we're we're applying kind of uh law of numbers right even if you take the market and you were to only buy profitable companies over a period of time you would you would outperform right so we're not what what you're talking about I think is more if you had a 15 20% position in a company. It'd be really important to know that. And it's not that it's not important to me. It's that how do you consistently screen uh out companies that don't meet criteria that you're comfortable with? And also, how does that combat what's what's worked over time? >> And and that's the balance, right? You said if you uh in the middle there you said if you only bought companies that were profitable >> you would outperform the market over time and they we mentioned you're referring to gap profitability. >> Yeah. Okay. Uh so what time period like what is the basis for that for saying that? >> Okay. So if you look at uh S&P 600 over the past uh 30 some years, right? It's noticeably outperformed the the Russell 2000. And the main difference between the two benchmarks is profitability. This profitability requirement for the S&P 6. So, um, and there are other studies I I can't think of off the top of my head right now, but, um, generally speaking, if you're buying an index and you're buying profitable companies comparatively, you will outperform in the last 30 years that I've seen. >> You mentioned uh, kind of on the sides of the discussion, rebalancing, you know, and you mainly mentioned it, I think, as December and referring to a little bit of tax loss harvesting. I'll just throw in no one's a tax adviser here, you know, don't take tax advice, all that sort of stuff. >> You mentioned rebalancing. How how do you think about rebalancing when you're running this rulesbased model? >> You mean in terms of like what what the the reasoning is to rebalance when I >> more not the reasoning I think everybody can understand the reasoning, right? You buy a company that's trading a five times fee. It it's a windfield, it's trading 25 times fee, probably time to if you're running rules based model probably. But I I I more meant it in terms of the timing of when you rebalance cuz you know again if I was doing if you and I were running a quantitative book, you know, 3,000 stocks in the in the Russell 3000 or whatever, we're going to be long 1500, short 1500, net neutral, like that's going to and we're going to do it on quantitative value momentum factors. That's going to be re rebalanced basically not just every day, every minute, right? I'm guessing you're not rebalancing every minute. How frequently are you rebalancing and what's the thought process behind that? >> Yeah, so we do a a a big rebalance once a year and that is in in January. Um so the the you you first of all you mentioned one reason why which is the stock goes from 5p to 25p, right? Um and and it's because it's increased in price, right? Well, what if it it does that because it qualitatively falls apart? you know example you gave earlier about you know earnings fall apart that kind of thing so that's another reason right so I I think it's a balance and the reason we do it at the time frame we do between giving things time to be recognized and kind of handing off like a value stock to a growth stock and also uh keeping things uh fresh or uh inexpensive discounted enough that there's a margin of safety and that there's uh some downside protection and not just upside. So when we looked at this, we we looked at more frequent rebalancing and it doesn't give companies enough time to kind of come to fruition. And >> why is that? Because you're you're running a a rules focused quantitative model, right? Why should why isn't the right answer once a month? And if company X reports a bad quarter and it's no longer profitable or you know their their stock trades up, why isn't it better to just kick and and adjust more frequently because you're running a rulesbased model and you said once a year. Why is the answer not once a decade then? Why why is it not once a day? >> Right. >> So it it's first of all we we've looked at this over time, right? It's not an arbitrary number. Um, second of all, we, as I mentioned, hold profitable companies and we do review that more frequently. That's a quarterly review. We make sure that the companies are profitable in the portfolio. So, if a company goes from profitable, not profitable, it's no longer in the portfolio. Um, and another risk tenant is if the portfolio it gravitates to being more expensive than the benchmark for whatever reason, then we're going to be in significantly higher cash. That's not a normal >> Why would that happen? >> Uh, that would happen because of either the portfolio's up noticeably, uh, deterioration in fundamentals or some combination. >> Okay? >> Or or the portfolio holds up and the market falls apart, right? And you know that there there are multiple scenarios where that would happen. They're very unlikely, right? Especially since the discount we look for and the quality metrics we look for, we look for substantial differentiation from from our benchmark where we fish. So um the the time period uh like I said is about not holding the leash so tight uh but also being true to to value. and and you mentioned um being value versus something else in quant like momentum and that sort of thing. We want to consistently be a a value book. And so yeah, we rebalance, but we rebalance frequently enough that the portfolio isn't kind of running away. And what I mean by that is if we held for three years, there's a probably a high probability that things have changed enough in the book that our valuation is not advantageous. We don't have that leverage that we do giving it it let's say a year. Let me let me go back to data. Uh and I I think I asked this but I just want to make sure I'm clear on it. Right? If I do a Yahoo Finance screen, one of the tough things I find with, you know, Yahoo Finance screen, I'm going to sort and I'm gonna say, "Hey, show me the, let's just say the cheapest companies on a price earnings basis, and the first 30 it's going to show me are unusable, right? The first 10, the first 10 had a onetime gain. Okay, you can edit that out. The the next 10 are obvious frauds, you know, Chinese rever reverse merger frauds or something. And then the next 10 is a data error on Yahoo's price, right? Maybe um maybe the company did a reverse split and the the stock hasn't adjusted for that yet or I guess it's more likely they did a split and they you know it's showing hey this company earned $100 per share and it's actually no it should be 10 the stock did a split but it shows 100 so you see that >> how do you guys you know you're doing a rules based investing across basically all the larger US companies how do you guys do data integrity >> so uh data integrity uh we rely on uh Cap IQ and testing over time the validity of their data and the reliability of their data. Now interesting you said Yahoo. Cap IQ feeds into Yahoo. I believe uh one of the things is to have some checks and balances in the uh in in the way we look at the data. We don't just verbatim take it. You mentioned like mergers and acquisitions, right? That's something we look at and if a company is is involved and it's been announced it's not something we'll buy. So like there are things like that that we look at. Um and you know again it can there be an error in data? Yes, of course. Uh but that's another reason why, you know, we spread out the portfolio and we're not if there's a bad apple that gets in because of bad data and certainly if it's with profitability, it's not going to be held long and it's it's should not have a significant impact on the portfolio. >> You think about, you know, this is this has been cleared up a little bit with uh I can't remember when it was like eight years ago bringing operating leases on the balance sheet. But you know, one of the issues I remember Gotham used to run into was retailers looked unbelievable because they used operating leases that was all off the balance sheet. There are other companies that you know it sometimes they do it or look at Facebook right now. One thing I've got a post I'll have to do at some point, but like you know Facebook working these complex JV structures that are like honestly not honestly reminiscent of Enron, right? but working these complex JV structures to keep uh to keep their data centers these huge data center buildouts off their balance sheet. And I'm not accusing them of fraud. I'm just saying like that literally is what Enron did as well, right? They they wanted to keep the they wanted to look asset lighter. >> Uh you you see Intel right now, Verizon, T-Mobile, they're doing these complicated JVS to keep these fiber buildouts off their books. How do you look at like and obviously I've picked a couple cherry picked a couple different samples but I've now hit retailers telecom there's several others how do you look at companies that are maybe structuring things to be offbalance sheet to make their sales look asset light or just accounting rules make them look asset lighter how do you think about th those types of issues? >> Yeah. Uh that's a great question and again it's a combination the way we combat that is a combination of not relying on any one metric like price to book and uh spreading things out and there there you know there are going to be times when a company gets in the portfolio either because there's a profitability error not in terms of necessarily the data but you know it's a onetime item that wasn't scrubbed out it's um in price to book an offshoot something like that. We're not immune but it's not a frequent phenomenon either. So, it's a great question and I think one of the things that I'm I'm thinking about when you're asking a lot of these questions is there's a lot of things to account for, but you it's very difficult kind of to create like a like a perfect system. And one of the ways I think about this when I talk about like the holistic approach and like looking at value from different angles to create a portfolio with a certain complexion. I think one of the things that's important, you know, I'm I'm Jewish and so on we talk about um you know uh the word I'm not remembering the the the Hebrew word at the moment but it means missing the mark, right? And it means like you're human, you're fallible, you are going to make mistakes and you want to do the best you can to come as close to hitting that mark every year and being the best person you can be. And I try to kind of apply that thinking to how I look at the portfolio that I want a good portfolio. If I shoot for the bullseye, I try to create a perfect portfolio, I'm going to miss things too. And like even qualitatively some of the names that have have worked out in the past if I look at them I would have been like h I don't know you know and I would have had other thoughts and by sticking to what works and and and the data um putting my pardon the expression you know faith in that over my own necessar uh necessarily my own expertise and so uh we're not you're you're asking great questions and I think a lot of those things if I was doing qualitative research are all things you check off right they're all the boxes but when you're buying I think you know let's say 50 to 80 companies in a portfolio uh it's not that they're not important but how do you how do you account for all those things and then not exclude things that you would want in the portfolio right and and I think that's where the the complexity uh the the problem occurs with coming up with rules and that's something, you know, we're talking about, right, is how do you consistently find companies that have potential to, you know, pop and and grow and make money for your portfolio? And, uh, how do you do that consistently? And I'm sorry. Yeah. >> No, NO, THAT'S GREAT. WELL, you a lot of it comes back to the rules, right? So, let how do you come up with the rules? So you know the basis for all of this is is things that the investors have looked at over time. Now, um the rules, uh mostly in in testing, uh to see what works, but a a lot of it has to do with um I don't want to say like common sense, but stuff that value investors would think about, right? Like if if my portfolio is upside down in the sense that um the it's not discounted, right? It doesn't create that discount that I want. that's not an exposure I want, right? Things like that. So, uh, they're not out of left field, I guess, is the best way to put it, right? And you talked about some of the data and some of the the ways you look at the data and do I have unique data and that sort of thing. You know, I don't it's how I look at it, right, that that differentiates. It's not that it's unique or you know I have some crazy rule like you know if if I can't think of one but you know if company A does X Y and Z and you know it's the third Sunday and of the month falls on whatever you know I'm not I'm not doing that. Well, let me Okay, so a lot of people are familiar with the Buffett indicator, right? Buffett used to say, "Hey, when the stock market's value trades for in excess of US GDP, >> it's overvalued, right?" And this was you would hear this time and time again from investors. And then you know the that rule if you followed that rule you would literally the only time in the past 15 years you would have been able to buy stocks was like the the absolute depths of the global financial crisis right >> and now you know I I could you could make two arguments and I'm not saying the Buffett GDP indicator is a rule but it was a very useful frame of frame of >> uh you can make two arguments hey we need to stick to this rule right we need to cash and like cash is king and one day we will get a shot you know one day there will be another correct but I think another way of thinking would be like hey if you've got a buy signal that says one time in the past 30 years it was you were good to buy like the buy signal is outdated now >> it's not a good buy signal >> why why is the buffer rule outdated well in part you know the US used to be the public companies were GM Ford and they were selling all their cars in the US so GDP was a good tracker and now it's Apple Facebook you know it's a global and but >> you know how do you think about the rules when I'm guessing some of the rules are as you said profitable trading for low price to earnings trading for ROE I think you're probably like when you say those rules and we back test them was the back test a 100red years like how do we know like the next 10 years aren't different than the last hundred years that it's the rules from the last 100 years are the Buffett indicators right and hey I I could imagine a world where when I say low price earnings good roe that's probably going to push you a little bit heavier into banks a lot of the time right which tend to trade for low price to book, good roses. >> That's historically been a great exposure. But banks have all this fintech risk, right? Like how do I think about the rules evolving and sticking to them even I think I've thrown a lot out there. I I don't know how to quite bring it, but I'm sure people can understand where I'm going based on the buff on that. >> Okay. So, first of all, you you know, we are looking for opportunity in every market. So, we're we're looking for relative opportunity. We don't have and I should be clear about this when we talk about rules and we want discounted P and that sort of that sort of thing. We don't have a cut off you know like five times earnings I'm just being arbitrary right so we're taking what the market gives us at any given point in time like when we balance in January it's what are the opportunities today right so that's number one uh you mentioned financials and earlier you mentioned biotech biotech is not something we invest in there's too much variability in in earnings right uh you can have a drug that hit and it's going to go away next in two months type of thing, right? Uh it's going to go generic or whatever it is. So, uh so that's that's one. And then financials is another one where we limit exposure and we do that because exactly what you said when you're looking for low P or low price to book and high return equity and things you can get a lot of those and those are not necessarily the companies that are going to drive performance uh o over time, right? So we limit exposure, we don't eliminate exposure to financials, but we we do limit it for exactly that reason. That's that's two areas of the market, right? So, I guess you just said, "Hey, we don't do biotech." And I'm with you, right? Like biotech is really effing hard and you've got drug cliffs and you know, up and down, coin flips, safety approvals, like safety approvals are the one where it's like, "Hey, you can have everything right and then you've got sorry, not safety approvals, safety issues. You've got everything right. you've done all the analysis and out of nowhere it could be hey this drug caused liver failure and like how are you going to catch how are you going to catch that as forget individual investor as a big investor like you just don't know and I I understand hey that's a risk but you know those are truly out of left field and you do that the drug goes zero any but you said hey we don't do biotech and we systematically limit our exposure to financials and I'm sure part of that is hey these things aren't going to drive the b up and hey like financials are one of those funny industries where you know Lehman Brothers looked really cheap on Friday in September of 2008 and then on Monday it was zero. So you've got those risks too. But that that's two like pretty big things where you're kind of stepping in and imposing limits and systematic like how do you think about that where you are God imposing limits and overriding these rules versus hey maybe if the system says we should have 15 banks and 24 biotechs right now maybe we should be less that. >> Right. So you talked about and let me go back one sec. We don't have a hard limit on what we limit exposure to financials. It's when we're creating the portfolio, we uh we look at it with financials and then we do a second run actually eliminating financials. >> Okay. >> So um and then therefore there's a lot of redundancy and I'm not going to get the whole whole process of putting the portfolio together, but uh we're open to financials on the first run. On the second run we're limiting it. we we tend to have exactly like we just talked about high exposure to financials more so than uh would help us in terms of performance over time and and that's the answer right so like what I'm doing I don't think is the most complex thing in the world it's kind of how I look at it and the consistency in which I look at it um but again we're using the same metrics everyone else is right but um it's yeah it it's uh in terms of like sorry I lost your train of thought again >> that's great one more question and this has been like d at the heart of it we've touched on some things but it's just one I that keeps popping up >> melting ice cubes right these are investors least favorite things the one that I think of right now is until 2016 when Disney comes out and says hey we're losing ESPN subs if I remember correctly >> linear cable channels are as many people said they're probably the best business in the world I I kind of disagree with them in some but it's hey you know ESPN especially ESPN right you've got scale because of that you can afford to pay for the NFL no one else can you get the ads if a cable channel tries to kick you all their subs are going to turn or they're going to be so angry you've got great pricing power you've got this huge network effect huge scale benefits all this sort of stuff until 2016 it's the best business ever very low capex right after 2016 it's death right go pull up the chart and forget you know the the tiny media companies like AMC, you can look at them. All the regional sports networks, you know, in 2016, they're great. By 2020, they're all going bankrupt left and right. Look at the chart of Disney. You So, media companies, right, are are the shining example of uh of melting ice cubes. And they're near and dear to my heart. And they're also one that, you know, values-based, rules-based models tended to love, right? Again, Capital Light after 2016, a lot of them start trading really damn cheap. and they're justep cheap down down down down down down down down down down down down down down down down down down down down down down down down. Uh we can probably think of other examples of melting ice cubes, but how do you avoid getting a portfolio that because you're using trailing numbers, right? How do you get avoid having a portfolio that looks great on trailing numbers and is just buying left and right, melting ice cube, melting ice cube, melting ice cube? I understand some of that is, hey, mil ice cubes tend to be probably overly discounted, but I I I would just point to the media example and say, hey, you know, if you did these over the past 5 years, you're you're no longer in business because it blow up the price of AMC networks. >> So, you know, we tend to have fairly frequent turnover, I think, for I don't I'm not even going to compare it, but we we generally have fairly substantial turnover when we do a rebalance. So the idea of a company that is not executing the way it should in terms of uh quality metrics as opposed to just uh discounted metrics uh staying in the portfolio over a long period of time is unlikely, right? And also the combination of metrics we look at, right? So, um there can absolutely be falling ice cubes, excuse me, melting melting ice cubes, excuse me. Um it can happen, but you know, also we talked about the year uh rebalancing, right? Uh but it's not uh the focus isn't a year. It's just kind of in the grander scheme. That's how we rebalance. So the idea that again we try to create like a perfect mechanism for one year it's not kind of how we're looking at it. We're looking at consist I don't know maybe to use a sports analogy baseball we're consistently looking for fast balls right uh if we get a curve we're going to hold off right um so the um yeah the the the re the the long-term play is to create alpha over a period of time right so again because of the way we spread out exposure in terms of companies because of the metrics we use. Is is that something that frequently happens that we get a a plethora of melting ice cubes? No. Last question. You know, a rulesbased model, a more quantitative model. It it seems like there's lots of opportunity for AI in the research process, the fundamental. How are you thinking about and using AI not in terms of competition or as a risk to the underlying companies but just in terms of uh assisting or helping with the portfolio construction with the rules with the back testing whatever it is. >> Yeah. So at this point uh we're not really using AI. Uh I think AI is a great tool as you said like subjectively and uh if you're uh gleaning through 10 years of 10ks and trying to you know find a trend or or things that are uh talked about written about consistently things like that I think it's really important. Um is it something that we've thought about? Yeah. And it's something that we could implement potentially, but again, it goes back to uh we believe in the opportunities that we're finding and will continue to find. And so we're not looking to we're not looking to evolve. And I think that's really where AI helps, right? AI helps you evolve a process. And I think that if everyone else is using AI and they evolve, I have the risk of being a dinosaur, but I also have the risk of really being differentiated and sticking with something that will continue to work. >> No, it's you know, AI is something I've thought a lot about. Uh I did a post on market your your podcast and >> you know AI it's funny because when I would say hey you know a lot of people would email me and say hey AI like when you talk about it as a risk to investor you forget that investors can use it and Buffett of course somebody sent it to me Buffett of course had a great quote for this you know it's the standing on your tiptoes at the parade well if you do it everyone else does it so it's a counter and I do think what you said is interesting someone else sent me like uh you know a lot of times what happens is when these games get so optimized, right? So you you think about um the best example, it's a difficult one, but daily fantasy sports, which people used, everyone started using optimizers, which would optimize like, hey, if you're in a competitive thing, it's going to optimize your bracket. Well, when everyone used it, the edge actually went to people who didn't use the optimizers. So they could build good portfolios. In this case, it's daily fantasy sports. they could build good teams but that weren't optimized because you know if everyone buys >> Albert Pool host and Chase Utley >> and every team has that well if you don't have one of them you actually have a huge edge and huge variance and uh yeah it's just interesting because I guess where I'm coming with this is hey if everyone else is using AI they're running into the tiptoes problem and maybe there is alpha on the edges of an old systematic process I'm not 100% sure but that's kind of one of the things >> that I'm not 100% sure either And >> but I do I do think that the opportunity exists uh as you said on the fringes now right because if everyone is using AI excuse me adapting learning trying to kind of keep up with the Joneses and even like you talked about 15 years in the history of the stock market it's not a long period right it's a substantial it's a noticeable period but it's not it's not huge right and and these things do tend to be cyclical in terms of what drives market performance. And right now, safety isn't where it's at. It's it's FOMO, right? It's fear of missing out. And and that, in my opinion, is what's pushing the market. And the idea that there will be a return to caring about uh where you are today and what your uh uh safety level is, right, relative to what you can potentially make. I think, you know, is it it is foreign to me the idea that that will not happen. Can I tell you when? No. Um but I I I I banked on it, right? Like and I think and I think that's the you talk about differentiator and fringe. Yeah, I guess I'm on the fringe now, right? Um value um being consistent in what I do and and it you know what's worked over time and does it work in the future? I don't know. But but I'm I believe it does and and I'm I'm betting on it. Right. >> Last question. So I I think a lot of this just it comes up it is hey I believe in value right I I almost have a a religious type belief in value in these metrics but >> we mentioned back testing yourself a few times. I am curious when you think about back testing and and this was sparked by you're saying 15 years is not a long time in the stock market which I agree. Uh but when you think about back testing how long do you think about that how long do you think about back testing an idea as trying to concept when you're looking thinking about this ideally you know I would say you know several market cycles right so periods where when I say cycles I don't just mean ups and downs in the market but you know different um uh techniques different approaches right growth value whatever you want to say h have excelled or or or worked over time. I think you'd have to look at if you said the past 15 years is more growth oriented, you'd have to go back a lot further to times when value was more in favor, right? I guess the reason I ask is again I I think about this in evolution like if a lot of the let's just hypothetically say a lot of the value outperformance comes from uh 1980 to 2000 >> and a lot of the value out performance comes from 1940 to 1960. Right? So I just use 20-year cycles. Well 1940 to 1960 I'd tell you get out of here. Right? Like that yes Buffett comes along in the ends and but you're buying completely different things. the market is much uh much less efficient. There's lots of pink sheets. Like it's just crazy out there. Right? So if you're doing back test and you're saying, "Hey, you know, I'm back testing to 1940, 1950." I say, "I don't think that's relevant." If you're doing the back test in the 80s, 2000s, well, now we're talking about a more modern market, but you know, computers still aren't around there. There's still a lot I I just wonder like when you're thinking about back testing, how forgetting the market cycles, how are you thinking about how like the market evolution is just think about? >> I'm trying to remember the date. It was in the '9s when everyone had to report digitally, right? What was that? >> I think that's I think SEC >> Right. So I I would think that would be a fairly good period to to kind of be looking at because you have enough information and and the data would be whole, so to speak. >> Cool. Okay, this has been fun. Uh David, where can people find you if they kind of want to learn a little bit more? Oh, um, yeah, methodicalinvestments.com and, uh, davidthodicalinvestments.com is my email and feel free to reach out anytime. >> Perfect. David Ker, Methodical Investments, this has been great. Thanks so much for coming on. >> Thanks, Andrew. I really appreciate it. >> 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.
Rules based investing with Methodical Investment's David Kaiser
Summary
Transcript
All right. Hello and welcome to the yet another value podcast. I'm your host, Andrew Walker. Uh we've got an interesting one for you today. You know what? I'm a little off because I went to the gym for lunch and the waterline broke. So now I'm just I'm in my head. I am just a a nasty nasty person because there was no shower and I'm an unshered host right now. But we've got a really interesting one for you today. It's David Kaiser from Methodical Investments. David runs a quantitative rules-based uh firm and I think I think it's gonna come through in the conversation. It makes for a really interesting b uh backdrop. It makes for a really interesting discussion when you're saying, "Hey, you're coming up with all of these rules." You know, a lot of the things I've talked about on the podcast, how are these rules getting impacted by AI? How do you think about when I'm doing something that's rules based? Like if it's rules based, can computers copy it? How do you think about evolving or not involve evolving with the times? As you know it, as I'll say on the podcast, Ben Graham, if you read the intelligent investor, he's telling you to buy things for twothirds of networking capital. Well, guess what? You haven't bought anything but Chinese frauds in the past 40 years if that that was the only thing you were buying. So, how do you think about maintaining a a rules and a value based and almost a religion, but you know, evolving with the times or not evolving? So, I think it's a fun conversation. It's it's going to be, you know, I try to start off with if you are a fundamental focused investor, what's one thing you can learn from rules based investing, but I think it's going to make really make you think about investing and sticking to principles and everything. So, we're going to get there in a second, but first, I'm going to stop rambling and go to a word from our sponsors. This podcast is sponsored by AlphaSense. 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Thousands of consistent channel conversations every month deliver comparable signals, helping investors spot inflection points weeks before they show up in earnings or consensus estimate. The best part is that these proprietary channel checks integrate directly into AlphaSense's research platform, which is trusted by 75% of the world's top hedge funds with access to over 500 million premium sources. From company filings and broker research to news, trade journals, and more than 240,000 expert call transcripts, that context turns raw signal into conviction. The first to see wins, the rest follow. Check it out for yourself at alphasense.comyavp. That's alpha-sense.comyavvp. >> All right. Hello and welcome to the yet another value podcast. I'm your host Andrew Walker with me today. I'm happy to have on from Methodical Investments, David Kaiser. David, how's it going? >> Good. Thank you for having me, Andrew. >> Hey, really excited to talk today. Uh before we get started, start this podcast the same way I start every podcast. Quick reminder, we'll remind everyone nothing on this podcast is investing advice. You can see a full disclaimer at the end of the podcast. Um David, super excited to have you on. maybe a little bit of a different chat today, but um you know, you run methodical investments. Uh it's more of a quantitative rules-driven firm and I I I'm always fascinated by rules and quants in markets and stuff. So, actually before I get there, why don't you just give a quick overview of methodical and then we can kind of dive into the conversation. >> Yeah. So, we're fundamentally driven data focused and rules-based value investors. I guess that's the best way to put it. >> Cool. Uh let's we'll dive into that in a second, but you know when I have most of the people on this podcast come and pitch single stock individual uh qualitative focus I I guess let's just start off with a headliner. You know if somebody's listening to this like oh we've got a quant guy on I I want individual stocks. What's just like one thing that you know fundamental qualitative investors, concentrated fundamental investors could take away from rules driven quantitative models that kind of would just improve their investing overall. >> Yeah. So, and also I'll start with you know my background is subjective qualitative research right individual company research. So that's where I come from and and then >> where were you before Methodical? >> I was at Robotian Company. >> Cool. >> Uh actually I'm still at Robotian Company. >> I know. I know. I just, you know. >> Yeah. No, just full disclosure. Bob's a friend, popular podcast guest. You gota got to get the robot name when you can. >> Yeah. No, and I I wouldn't be where I am now, even though this this deviates somewhat without Bob. And so, um, you know, learned so much about, you know, fundamental, qualitative, what drives uh company growth, you know, what what to look for, what causes stocks to go up, what are the important drivers, right? And so um you know I really got focused on to digress a little bit on you know what those drivers are how to exploit them in more of a a rulesbased uh arena right so do what you're comfortable with stick with what you like and I like structure I like organization I like process and that's kind of how I got here so one of the things I think you can take away is qualitative and that subjective way of investing absolutely has place can be excellent to have rules to have process can give you comfort both in how it's performed over time and also in in an A to B right so if X happens you're doing Y it's not about trying to figure out with each individual company with each portfolio however you look at it what the next step is and I think that's a big difference with rules-based and quantity itative investing is that level of comfort and knowing and being able to communicate if you have clients what happens if right let me so I I think this is going to be a recurring theme through the the package let me just riff off that for a second so you said rules base you know if X happens then Y happens and one of my worries just overall as an investor you know for the past 30 years all investors have been worried like hey when is passive going to replace all when are computers going to replace all >> one of my worries is the things that computers and AI are the best at is following rules right if X happens do Y it's replacing humans in all fields all across the board and this is even before AI and software like if you have a rule that can be followed eventually a computer will automate that and when you say having this rules base and having like if X happens then Y the the first thing I worry about both from a quantitative qualitative whatever perspective is like why isn't that something that's just if it's not already being done by AI that's getting done by AI in you know six months two years whenever you want but why isn't this something that like turns us into dinosaurs eventually >> you know I don't have an answer as to how it won't turn us into a dinosaur I think and my understanding and and you certainly have a better understanding of AI I think than I do in this arena it it's learning it's adapting right and one [snorts] of the things with with having rules and being consistent and certainly the way I look at things is that history repeats itself. So, it's not about adapting all the time. It's more about being patient and understanding that there are times when what you're doing may not be uh create the effect you want, but that it will and to have that patience and to have that uh fortitude, whatever you want to call it, hutzba, right? To to say, all right, I'm not adapting in in terms of trying to figure out what's working today. I'm working on what has worked over over time. Look at value investing for 90 years and and that sort of thing. And obviously the different techniques and that sort of thing, but we're looking, you know, methodical. We're looking to exploit those inefficiencies and and actually I would argue that to some extent AI and and uh the inputs probably feed into uh more opportunities and more inequity in stock pricing. >> One thing you said there, right, you said not adapting. I think you used that term three times and >> I I I've written and talked recently about adapting, right? Like >> when you say not adapting, I I could see two schools of thoughts, right? I think of the markets as a competitive game. And in every sport I followed, >> the people who don't adapt, right? In the 2010s, there were the people who say, "Oh, the three-point ball, if you base a team around the three-point ball, you could never win the championship." Those people are out of the league now, right? The NBA is all about three-point ball. If you rewound it, you know, if you went 50 years back in the NFL and you said, "Hey, we're going to run a a passbased offense." They say offense, running base, right? Those people are out of the league. So, on the one hand, I hear not adapt and I say, "Hey, are you Phil Jackson? Hey, how are those threes holding up in the 2010s and you're about to get out of the league?" Or on the other hand, you know, there there is there's the Lindy effect, right? Like, hey, there are these overarching principles and every all the time people say, "Hey, I can get away from these principles." and the the cycle the pendulum always swings back to them and buying things at a discount that that's kind of like the Lenny thing. So like how do I marry those two in my mind where I hear don't adapt don't adapt don't adapt and say markets are really damn competitive. One one more I out there throw like if you go back and read the intelligent investor, right? Ben Graham's whole thing was buy stuff for twothirds of working capital and that's great but those are generally gone and the things that are still in the market they're they're so stressed or so likely to be frauds like there is no off like what Warren Buffett did was he adapted that approach right he said hey let's make an intrinsic value and it doesn't have to be a hard asset. So when I hear not adapt how do I know it's like Lindy versus the guy who refuses to shoot three-pointers. >> Yeah. So okay, two things. one in reverse order. Uh yeah, it's not just about discount, right? As as Buffett ch, you know, changed from what Graham did. It's about quality, too, right? It's it's that balance. And and Graham kind of was a quant in my mind because he was very strict on criteria, right? Now, his criteria was so strict in terms of what you would buy a company at that he he would have no opportunities today, as you say. Right. [snorts] So what I'm talking about not adapting is maybe an approach and and and the rules not that there's no evolution in the portfolio. I don't know if if that's makes sense. So in other words, we don't buy the same exposure, the same pees, everything like that, you know, like metrics like that every year. we're using the same techniques and we're getting different results not just in terms of performance but in terms of the the complexion of the portfolio and so so I think uh you're you're two different things right one is adapting the rules over time and the other is does the portfolio evolve even with the rules the the rules of the NBA haven't changed right to give you example the NBA the rules haven't changed it's the way that teams have approached and and and offenses have evolved, right? And and that sort of thing. And is the game more physical, less physical, is shooting more, you know, there's all sorts of of factors, right? But but the structure, the court's the same size, the rims are the same same height, and the you know, those those type of things, the rules haven't changed in that regard. I think the three-point line came, you know, 23 feet and, you know, stuff like that. >> You are correct. When you said the rules have changed, I was like, well, the three-point line came in in what 40 years, right? It's been it's been consistent. We have mentioned for not the NBA rules but we have mentioned the rules that methodical follows for a long time and I you know in my mind when you say it I I've got an idea of what they are but I could be completely wrong and for my listeners like why don't we talk about what are some of the rules that that that are getting followed here. >> Okay. So uh rules in terms of structure of of portfolio construction right and also rules in terms of risk management and holding holding period things like that right so what are some of our core tenants we're looking for a balance of of quality and discount right probably not in that order discount and quality right so [snorts] uh we uh sorry we consistently apply the same metrics and the way we do that is we take a step back and we look at the portfolio as a whole. Okay, so one of the rules is pretty much everything is done on a portfolio level in terms of of decision making so to speak. Um, two, we only hold profitable companies. And I think that that's an important thing because we rely on metrics and we look at the complexion of the portfolio and how it compares to our benchmark, right? And things like that. Um, other benchmarks, the market, whatever you want to look at. We're looking for a a portfolio that looks better. It's more discounted, has better metrics, right? So, if we're doing that, we need to look at it on a whole. And by doing profitable companies only we are allowing for reliable information. So if you look just as an example if you look at the Russell 2100 value right uh Russell 3000 doesn't matter and it says the PE is 18. I'm just being arbitrary. The PE is 18 but there's a percentage of those companies that aren't profitable that that doesn't go into that right? So it's 18 but they're also unprofitable companies. So one of the the rules one the tenants is to to own profitable companies right so that a they tend to outperform over time and since we're not picking individual companies in the same way as a qualitative subjective concentrated investor would [snorts] we are uh we're wanting that that data to be as reliable as as possible. So I think I'm getting a little off here but >> no no that's great. I actually had a question on data but let's start >> let me start at the smaller profit level and then we can zoom out to you said we only buy profitable companies >> correct >> what is a profitable company is it gap net income profitable is it >> adding back onetime items is it IBIDA how are you getting >> no no we use we use net income and we exclude onetime items >> okay >> so uh let's go to data and then we can come back that >> one of the things when you say rules based and I understand rules based versus quantitative are are different based on what you're saying, but there there's some similar. One of the things like with screeners, I always have this issue and I think I emailed this to you and listen to my news like Gotham ran the little book that beats the market and they had hey you sort by your quality metric is your return on invested capital and then your valuation is EV to I think they use EBIT >> and you kind of blend the two and that's how you get your your blend of quality and value and then they would have this huge aster that said hey we have to exclude biotech stocks because all the biotech so many of the biotechs trade for way below cash, they're too cheap, we have to exclude them. >> Uh with yours, when you've got, hey, we look for profitable companies. Like the first thing that the two things that jumped out to me is a the biotech stock exception, right? And then b a a mining company, right? It feels like if you're saying, hey, we need to buy profitable companies, then you're going to get a lot of mining companies when mining is really effing hot, right? Gold is 5,000 and guess what? Gold miners are profitable and they're thrown in there. And history suggests like the wrong time to buy the gold miners is when gold is 5,000 and they're trading for a five times price earning because it's a super cyclical high. So I I'd love to ask you, you know, let's start with the cyclical and then we go back to the bte. How do you handle that cyclical process, right? Because it does seem like the portfolio could tilt really heavily into cyclicals at the top of the market. If you're just like, hey, we only buy profitable companies cheaply. That's going to push a lot of cyclicals in there. >> Yeah, it it's a good point. So first of all and you talked about rules we we own quite a few companies and we don't have concentrated portfolio in terms of of equity uh individual names. So we will cluster in sectors and we will take uh we we'll invest more heavily in certain sectors than others right based on exactly what you're talking about the clustering right but we're not just looking at two metrics we have a variety of metrics that go into the selection process and it is really looking to a more holistic view right it's not just focusing on A and B it it looks to create a portfolio in aggregate that has better valuation metrics and better quality metrics like return on equity, right? We want that higher. We want lower PE, lower price to book, we want lower enterprise IBA, things like that, right? So to do that, you're not just taking two metrics, although I I'd be lying if I said that, you know, Gotham wasn't uh and what, you know, Greenblat does wasn't a impetus for kind of my thinking about this, right? But I think it it has to be simple but also more complex than than just two metrics. So, do do names get in that maybe shouldn't or they're cyclical and that sort of thing? Can it happen? Absolutely. Do we mitigate it by kind of spreading out the risk in terms of companies? Yes. And we rebalance. So, by rebalancing consistently, if we're wrong, we're wrong for a relatively short period of time. And and again, there's that balance of quality and discount. It's not just about discount. What sectors right now are just like like I'm sure over time different sectors pop up, right? Any anybody's running a value screen or different sectors? What sectors are consistently popping up right now? What sectors is the rules and the factors leaning overweight right now? Because I I think it's really interesting to see what sectors are getting discounted. >> Yeah. So, right now we're we're heavy consumer discretionary uh which is it's such a broad um uh sector, right? There's a lot of different things in there, but right now we're uh we're long we're we're heavy consumer discretionary. We have some energy. Uh not as much as we've had in the past. Uh but this year we're pretty heavy in energy. Financials is up there. Um I think those are the biggest. I think industrials is up there, too. >> So, uh >> I'm going off the top of my head. So, >> no, no, no, that's that's fine. Let me so one question I like to ask every podcast guest right and again normally it's individual stocks but the market is a competitive place what are you seeing that the market's missing let me just ask you like the market especially when you're talking about applying a rulesbased model which uh a rules based or quantitative models which you know that is computer-based you hire one computer programmer and they can go run you know Renaissance runs with 30 people and can manage $40 billion and they've got the best computers in the world and they they can generate 50% alpha forever uh you're talking rules So it can handle a lot more money. It's a lot more scalable. What are you seeing that's kind of your competitive edge that allows you to compete in the market against you know just a the market in general but b all these quant models and quant specific firms that are trying to compete here. >> Yeah. I think uh going back to what I talked about which is my background right. I didn't come at it from a scientific view. I came at it from a fundamental qualitative view. Right? That's my background. And I think that gives me a little bit of a unique perspective in terms of of competing. I go back to and and I I feel like I'm being a dead horse, but the the consistency and and not constantly or even frequently changing your approach and having that patience and having the um the the willingness to to h the confidence that the market will give you opportunity and you'll be able to profit from that opportunity. >> Okay. So you've got a rulesbased system and it it's heavily value based, right? It leans value companies >> very much so. Yes. >> The past, let's call it 10, but I think it's been more like 15 years. >> Yeah. >> Growth has stumped value, right? >> Absolutely. >> And you know, you'll hear a lot of people and it's not just quants, right? You you read the Einhorn letter and he'll say broken market, passive lows, all this sort of stuff. >> But I guess at what point you said the confidence to stick to the rules. At what point do you look and say, "Hey, instead of uh what's the Simpsons thing?" It's like, "Are the kid is it me?" And then he said, "No, it must be the kids, right? It can't be me." At what point do you look in the mirror and you say, "Oh, it's not the market. It's me." Like like how do you >> deviate like uh kind of, hey, I'm insane. The definition of doing insanity is doing the same thing over and over again. 15 years growth being valid versus no, I'm sticking to rules. So, uh, you know, it's a it's a great question. I don't have a a clear answer, right? I'm a I'm stubborn in terms of process, right? Um, and what is my breaking point if that's what you're asking? I don't know. I'm certainly not there yet. And I think um uh historical data and and you know talking about data uh supports the unsustainability of what what's happening now that people are are paying unreasonable prices for for quality at this point. And um so uh I have more confidence today than I probably did three years ago. Uh just because of of where things have have progressed in terms of valuation, in terms of concentration, in terms of you know how much people are betting on the future and not paying attention to what's going on today as much in my opinion. >> Uh we are taping February 3rd, 2026. This is like a borderline black Monday for payments and software. I'm curious have payments and software started popping up in your models recently? >> No, not really. Uh we have very little exposure to uh like it and and things like that. Um and also we we rebalance in January after tax law selling there's a added bump in terms of cheap things getting cheaper, right? discounted companies getting cheaper, uh, more discounted. So, um, what's happened over the past month doesn't really affect so much what we're what we're doing. >> Let me ask corporate governance. And corporate governance has been a a big >> focus for me. And a lot of the stocks I know that are the absolute cheapest are that way because of corporate governance, right? So, you've got a great business, great asset value, all this sort of stuff, and the the CEO just seems determined to light the money on fire through dumb acquisitions or >> pocket everything for himself. >> And one place I could see a rules-based model really failing is that accounting for, you know, you it's very difficult to read a 10K or 10 Q or proxy and say, "Oh, this CEO is going to take everything for himself." But it's pretty easy if you're an investor and you like read two conference calls say, "Oh my god, I'm swimming with sharks here." >> How do you account for corporate governance when you're you're running this? And how do you not just end up in, you know, 15 different hold controlled companies that look very cheap and the CEO is going to pay themselves $50 million per year for all time and shareholders will, you know, take what they can get. >> Yeah. So, uh, we don't have a specific fail safe for corporate governance. you talked about really cheap, right? And one of the things we do and we I guess we're going around a little bit with the rules is we're not buying the cheapest, right? We are uh when we look at the data, we're removing outliers. The things that are really cheap and whatever metric you want to talk about, right? PE, price to book, etc., they probably are for a reason. And then also that combination of metrics is is important, right? It's not just that it's the absolute or even one of the cheapest PE companies, right? that's not enough. So in terms of corporate governance uh it's not something that we we apply and and I think theoretically right and in practice we're we're applying kind of uh law of numbers right even if you take the market and you were to only buy profitable companies over a period of time you would you would outperform right so we're not what what you're talking about I think is more if you had a 15 20% position in a company. It'd be really important to know that. And it's not that it's not important to me. It's that how do you consistently screen uh out companies that don't meet criteria that you're comfortable with? And also, how does that combat what's what's worked over time? >> And and that's the balance, right? You said if you uh in the middle there you said if you only bought companies that were profitable >> you would outperform the market over time and they we mentioned you're referring to gap profitability. >> Yeah. Okay. Uh so what time period like what is the basis for that for saying that? >> Okay. So if you look at uh S&P 600 over the past uh 30 some years, right? It's noticeably outperformed the the Russell 2000. And the main difference between the two benchmarks is profitability. This profitability requirement for the S&P 6. So, um, and there are other studies I I can't think of off the top of my head right now, but, um, generally speaking, if you're buying an index and you're buying profitable companies comparatively, you will outperform in the last 30 years that I've seen. >> You mentioned uh, kind of on the sides of the discussion, rebalancing, you know, and you mainly mentioned it, I think, as December and referring to a little bit of tax loss harvesting. I'll just throw in no one's a tax adviser here, you know, don't take tax advice, all that sort of stuff. >> You mentioned rebalancing. How how do you think about rebalancing when you're running this rulesbased model? >> You mean in terms of like what what the the reasoning is to rebalance when I >> more not the reasoning I think everybody can understand the reasoning, right? You buy a company that's trading a five times fee. It it's a windfield, it's trading 25 times fee, probably time to if you're running rules based model probably. But I I I more meant it in terms of the timing of when you rebalance cuz you know again if I was doing if you and I were running a quantitative book, you know, 3,000 stocks in the in the Russell 3000 or whatever, we're going to be long 1500, short 1500, net neutral, like that's going to and we're going to do it on quantitative value momentum factors. That's going to be re rebalanced basically not just every day, every minute, right? I'm guessing you're not rebalancing every minute. How frequently are you rebalancing and what's the thought process behind that? >> Yeah, so we do a a a big rebalance once a year and that is in in January. Um so the the you you first of all you mentioned one reason why which is the stock goes from 5p to 25p, right? Um and and it's because it's increased in price, right? Well, what if it it does that because it qualitatively falls apart? you know example you gave earlier about you know earnings fall apart that kind of thing so that's another reason right so I I think it's a balance and the reason we do it at the time frame we do between giving things time to be recognized and kind of handing off like a value stock to a growth stock and also uh keeping things uh fresh or uh inexpensive discounted enough that there's a margin of safety and that there's uh some downside protection and not just upside. So when we looked at this, we we looked at more frequent rebalancing and it doesn't give companies enough time to kind of come to fruition. And >> why is that? Because you're you're running a a rules focused quantitative model, right? Why should why isn't the right answer once a month? And if company X reports a bad quarter and it's no longer profitable or you know their their stock trades up, why isn't it better to just kick and and adjust more frequently because you're running a rulesbased model and you said once a year. Why is the answer not once a decade then? Why why is it not once a day? >> Right. >> So it it's first of all we we've looked at this over time, right? It's not an arbitrary number. Um, second of all, we, as I mentioned, hold profitable companies and we do review that more frequently. That's a quarterly review. We make sure that the companies are profitable in the portfolio. So, if a company goes from profitable, not profitable, it's no longer in the portfolio. Um, and another risk tenant is if the portfolio it gravitates to being more expensive than the benchmark for whatever reason, then we're going to be in significantly higher cash. That's not a normal >> Why would that happen? >> Uh, that would happen because of either the portfolio's up noticeably, uh, deterioration in fundamentals or some combination. >> Okay? >> Or or the portfolio holds up and the market falls apart, right? And you know that there there are multiple scenarios where that would happen. They're very unlikely, right? Especially since the discount we look for and the quality metrics we look for, we look for substantial differentiation from from our benchmark where we fish. So um the the time period uh like I said is about not holding the leash so tight uh but also being true to to value. and and you mentioned um being value versus something else in quant like momentum and that sort of thing. We want to consistently be a a value book. And so yeah, we rebalance, but we rebalance frequently enough that the portfolio isn't kind of running away. And what I mean by that is if we held for three years, there's a probably a high probability that things have changed enough in the book that our valuation is not advantageous. We don't have that leverage that we do giving it it let's say a year. Let me let me go back to data. Uh and I I think I asked this but I just want to make sure I'm clear on it. Right? If I do a Yahoo Finance screen, one of the tough things I find with, you know, Yahoo Finance screen, I'm going to sort and I'm gonna say, "Hey, show me the, let's just say the cheapest companies on a price earnings basis, and the first 30 it's going to show me are unusable, right? The first 10, the first 10 had a onetime gain. Okay, you can edit that out. The the next 10 are obvious frauds, you know, Chinese rever reverse merger frauds or something. And then the next 10 is a data error on Yahoo's price, right? Maybe um maybe the company did a reverse split and the the stock hasn't adjusted for that yet or I guess it's more likely they did a split and they you know it's showing hey this company earned $100 per share and it's actually no it should be 10 the stock did a split but it shows 100 so you see that >> how do you guys you know you're doing a rules based investing across basically all the larger US companies how do you guys do data integrity >> so uh data integrity uh we rely on uh Cap IQ and testing over time the validity of their data and the reliability of their data. Now interesting you said Yahoo. Cap IQ feeds into Yahoo. I believe uh one of the things is to have some checks and balances in the uh in in the way we look at the data. We don't just verbatim take it. You mentioned like mergers and acquisitions, right? That's something we look at and if a company is is involved and it's been announced it's not something we'll buy. So like there are things like that that we look at. Um and you know again it can there be an error in data? Yes, of course. Uh but that's another reason why, you know, we spread out the portfolio and we're not if there's a bad apple that gets in because of bad data and certainly if it's with profitability, it's not going to be held long and it's it's should not have a significant impact on the portfolio. >> You think about, you know, this is this has been cleared up a little bit with uh I can't remember when it was like eight years ago bringing operating leases on the balance sheet. But you know, one of the issues I remember Gotham used to run into was retailers looked unbelievable because they used operating leases that was all off the balance sheet. There are other companies that you know it sometimes they do it or look at Facebook right now. One thing I've got a post I'll have to do at some point, but like you know Facebook working these complex JV structures that are like honestly not honestly reminiscent of Enron, right? but working these complex JV structures to keep uh to keep their data centers these huge data center buildouts off their balance sheet. And I'm not accusing them of fraud. I'm just saying like that literally is what Enron did as well, right? They they wanted to keep the they wanted to look asset lighter. >> Uh you you see Intel right now, Verizon, T-Mobile, they're doing these complicated JVS to keep these fiber buildouts off their books. How do you look at like and obviously I've picked a couple cherry picked a couple different samples but I've now hit retailers telecom there's several others how do you look at companies that are maybe structuring things to be offbalance sheet to make their sales look asset light or just accounting rules make them look asset lighter how do you think about th those types of issues? >> Yeah. Uh that's a great question and again it's a combination the way we combat that is a combination of not relying on any one metric like price to book and uh spreading things out and there there you know there are going to be times when a company gets in the portfolio either because there's a profitability error not in terms of necessarily the data but you know it's a onetime item that wasn't scrubbed out it's um in price to book an offshoot something like that. We're not immune but it's not a frequent phenomenon either. So, it's a great question and I think one of the things that I'm I'm thinking about when you're asking a lot of these questions is there's a lot of things to account for, but you it's very difficult kind of to create like a like a perfect system. And one of the ways I think about this when I talk about like the holistic approach and like looking at value from different angles to create a portfolio with a certain complexion. I think one of the things that's important, you know, I'm I'm Jewish and so on we talk about um you know uh the word I'm not remembering the the the Hebrew word at the moment but it means missing the mark, right? And it means like you're human, you're fallible, you are going to make mistakes and you want to do the best you can to come as close to hitting that mark every year and being the best person you can be. And I try to kind of apply that thinking to how I look at the portfolio that I want a good portfolio. If I shoot for the bullseye, I try to create a perfect portfolio, I'm going to miss things too. And like even qualitatively some of the names that have have worked out in the past if I look at them I would have been like h I don't know you know and I would have had other thoughts and by sticking to what works and and and the data um putting my pardon the expression you know faith in that over my own necessar uh necessarily my own expertise and so uh we're not you're you're asking great questions and I think a lot of those things if I was doing qualitative research are all things you check off right they're all the boxes but when you're buying I think you know let's say 50 to 80 companies in a portfolio uh it's not that they're not important but how do you how do you account for all those things and then not exclude things that you would want in the portfolio right and and I think that's where the the complexity uh the the problem occurs with coming up with rules and that's something, you know, we're talking about, right, is how do you consistently find companies that have potential to, you know, pop and and grow and make money for your portfolio? And, uh, how do you do that consistently? And I'm sorry. Yeah. >> No, NO, THAT'S GREAT. WELL, you a lot of it comes back to the rules, right? So, let how do you come up with the rules? So you know the basis for all of this is is things that the investors have looked at over time. Now, um the rules, uh mostly in in testing, uh to see what works, but a a lot of it has to do with um I don't want to say like common sense, but stuff that value investors would think about, right? Like if if my portfolio is upside down in the sense that um the it's not discounted, right? It doesn't create that discount that I want. that's not an exposure I want, right? Things like that. So, uh, they're not out of left field, I guess, is the best way to put it, right? And you talked about some of the data and some of the the ways you look at the data and do I have unique data and that sort of thing. You know, I don't it's how I look at it, right, that that differentiates. It's not that it's unique or you know I have some crazy rule like you know if if I can't think of one but you know if company A does X Y and Z and you know it's the third Sunday and of the month falls on whatever you know I'm not I'm not doing that. Well, let me Okay, so a lot of people are familiar with the Buffett indicator, right? Buffett used to say, "Hey, when the stock market's value trades for in excess of US GDP, >> it's overvalued, right?" And this was you would hear this time and time again from investors. And then you know the that rule if you followed that rule you would literally the only time in the past 15 years you would have been able to buy stocks was like the the absolute depths of the global financial crisis right >> and now you know I I could you could make two arguments and I'm not saying the Buffett GDP indicator is a rule but it was a very useful frame of frame of >> uh you can make two arguments hey we need to stick to this rule right we need to cash and like cash is king and one day we will get a shot you know one day there will be another correct but I think another way of thinking would be like hey if you've got a buy signal that says one time in the past 30 years it was you were good to buy like the buy signal is outdated now >> it's not a good buy signal >> why why is the buffer rule outdated well in part you know the US used to be the public companies were GM Ford and they were selling all their cars in the US so GDP was a good tracker and now it's Apple Facebook you know it's a global and but >> you know how do you think about the rules when I'm guessing some of the rules are as you said profitable trading for low price to earnings trading for ROE I think you're probably like when you say those rules and we back test them was the back test a 100red years like how do we know like the next 10 years aren't different than the last hundred years that it's the rules from the last 100 years are the Buffett indicators right and hey I I could imagine a world where when I say low price earnings good roe that's probably going to push you a little bit heavier into banks a lot of the time right which tend to trade for low price to book, good roses. >> That's historically been a great exposure. But banks have all this fintech risk, right? Like how do I think about the rules evolving and sticking to them even I think I've thrown a lot out there. I I don't know how to quite bring it, but I'm sure people can understand where I'm going based on the buff on that. >> Okay. So, first of all, you you know, we are looking for opportunity in every market. So, we're we're looking for relative opportunity. We don't have and I should be clear about this when we talk about rules and we want discounted P and that sort of that sort of thing. We don't have a cut off you know like five times earnings I'm just being arbitrary right so we're taking what the market gives us at any given point in time like when we balance in January it's what are the opportunities today right so that's number one uh you mentioned financials and earlier you mentioned biotech biotech is not something we invest in there's too much variability in in earnings right uh you can have a drug that hit and it's going to go away next in two months type of thing, right? Uh it's going to go generic or whatever it is. So, uh so that's that's one. And then financials is another one where we limit exposure and we do that because exactly what you said when you're looking for low P or low price to book and high return equity and things you can get a lot of those and those are not necessarily the companies that are going to drive performance uh o over time, right? So we limit exposure, we don't eliminate exposure to financials, but we we do limit it for exactly that reason. That's that's two areas of the market, right? So, I guess you just said, "Hey, we don't do biotech." And I'm with you, right? Like biotech is really effing hard and you've got drug cliffs and you know, up and down, coin flips, safety approvals, like safety approvals are the one where it's like, "Hey, you can have everything right and then you've got sorry, not safety approvals, safety issues. You've got everything right. you've done all the analysis and out of nowhere it could be hey this drug caused liver failure and like how are you going to catch how are you going to catch that as forget individual investor as a big investor like you just don't know and I I understand hey that's a risk but you know those are truly out of left field and you do that the drug goes zero any but you said hey we don't do biotech and we systematically limit our exposure to financials and I'm sure part of that is hey these things aren't going to drive the b up and hey like financials are one of those funny industries where you know Lehman Brothers looked really cheap on Friday in September of 2008 and then on Monday it was zero. So you've got those risks too. But that that's two like pretty big things where you're kind of stepping in and imposing limits and systematic like how do you think about that where you are God imposing limits and overriding these rules versus hey maybe if the system says we should have 15 banks and 24 biotechs right now maybe we should be less that. >> Right. So you talked about and let me go back one sec. We don't have a hard limit on what we limit exposure to financials. It's when we're creating the portfolio, we uh we look at it with financials and then we do a second run actually eliminating financials. >> Okay. >> So um and then therefore there's a lot of redundancy and I'm not going to get the whole whole process of putting the portfolio together, but uh we're open to financials on the first run. On the second run we're limiting it. we we tend to have exactly like we just talked about high exposure to financials more so than uh would help us in terms of performance over time and and that's the answer right so like what I'm doing I don't think is the most complex thing in the world it's kind of how I look at it and the consistency in which I look at it um but again we're using the same metrics everyone else is right but um it's yeah it it's uh in terms of like sorry I lost your train of thought again >> that's great one more question and this has been like d at the heart of it we've touched on some things but it's just one I that keeps popping up >> melting ice cubes right these are investors least favorite things the one that I think of right now is until 2016 when Disney comes out and says hey we're losing ESPN subs if I remember correctly >> linear cable channels are as many people said they're probably the best business in the world I I kind of disagree with them in some but it's hey you know ESPN especially ESPN right you've got scale because of that you can afford to pay for the NFL no one else can you get the ads if a cable channel tries to kick you all their subs are going to turn or they're going to be so angry you've got great pricing power you've got this huge network effect huge scale benefits all this sort of stuff until 2016 it's the best business ever very low capex right after 2016 it's death right go pull up the chart and forget you know the the tiny media companies like AMC, you can look at them. All the regional sports networks, you know, in 2016, they're great. By 2020, they're all going bankrupt left and right. Look at the chart of Disney. You So, media companies, right, are are the shining example of uh of melting ice cubes. And they're near and dear to my heart. And they're also one that, you know, values-based, rules-based models tended to love, right? Again, Capital Light after 2016, a lot of them start trading really damn cheap. and they're justep cheap down down down down down down down down down down down down down down down down down down down down down down down down. Uh we can probably think of other examples of melting ice cubes, but how do you avoid getting a portfolio that because you're using trailing numbers, right? How do you get avoid having a portfolio that looks great on trailing numbers and is just buying left and right, melting ice cube, melting ice cube, melting ice cube? I understand some of that is, hey, mil ice cubes tend to be probably overly discounted, but I I I would just point to the media example and say, hey, you know, if you did these over the past 5 years, you're you're no longer in business because it blow up the price of AMC networks. >> So, you know, we tend to have fairly frequent turnover, I think, for I don't I'm not even going to compare it, but we we generally have fairly substantial turnover when we do a rebalance. So the idea of a company that is not executing the way it should in terms of uh quality metrics as opposed to just uh discounted metrics uh staying in the portfolio over a long period of time is unlikely, right? And also the combination of metrics we look at, right? So, um there can absolutely be falling ice cubes, excuse me, melting melting ice cubes, excuse me. Um it can happen, but you know, also we talked about the year uh rebalancing, right? Uh but it's not uh the focus isn't a year. It's just kind of in the grander scheme. That's how we rebalance. So the idea that again we try to create like a perfect mechanism for one year it's not kind of how we're looking at it. We're looking at consist I don't know maybe to use a sports analogy baseball we're consistently looking for fast balls right uh if we get a curve we're going to hold off right um so the um yeah the the the re the the long-term play is to create alpha over a period of time right so again because of the way we spread out exposure in terms of companies because of the metrics we use. Is is that something that frequently happens that we get a a plethora of melting ice cubes? No. Last question. You know, a rulesbased model, a more quantitative model. It it seems like there's lots of opportunity for AI in the research process, the fundamental. How are you thinking about and using AI not in terms of competition or as a risk to the underlying companies but just in terms of uh assisting or helping with the portfolio construction with the rules with the back testing whatever it is. >> Yeah. So at this point uh we're not really using AI. Uh I think AI is a great tool as you said like subjectively and uh if you're uh gleaning through 10 years of 10ks and trying to you know find a trend or or things that are uh talked about written about consistently things like that I think it's really important. Um is it something that we've thought about? Yeah. And it's something that we could implement potentially, but again, it goes back to uh we believe in the opportunities that we're finding and will continue to find. And so we're not looking to we're not looking to evolve. And I think that's really where AI helps, right? AI helps you evolve a process. And I think that if everyone else is using AI and they evolve, I have the risk of being a dinosaur, but I also have the risk of really being differentiated and sticking with something that will continue to work. >> No, it's you know, AI is something I've thought a lot about. Uh I did a post on market your your podcast and >> you know AI it's funny because when I would say hey you know a lot of people would email me and say hey AI like when you talk about it as a risk to investor you forget that investors can use it and Buffett of course somebody sent it to me Buffett of course had a great quote for this you know it's the standing on your tiptoes at the parade well if you do it everyone else does it so it's a counter and I do think what you said is interesting someone else sent me like uh you know a lot of times what happens is when these games get so optimized, right? So you you think about um the best example, it's a difficult one, but daily fantasy sports, which people used, everyone started using optimizers, which would optimize like, hey, if you're in a competitive thing, it's going to optimize your bracket. Well, when everyone used it, the edge actually went to people who didn't use the optimizers. So they could build good portfolios. In this case, it's daily fantasy sports. they could build good teams but that weren't optimized because you know if everyone buys >> Albert Pool host and Chase Utley >> and every team has that well if you don't have one of them you actually have a huge edge and huge variance and uh yeah it's just interesting because I guess where I'm coming with this is hey if everyone else is using AI they're running into the tiptoes problem and maybe there is alpha on the edges of an old systematic process I'm not 100% sure but that's kind of one of the things >> that I'm not 100% sure either And >> but I do I do think that the opportunity exists uh as you said on the fringes now right because if everyone is using AI excuse me adapting learning trying to kind of keep up with the Joneses and even like you talked about 15 years in the history of the stock market it's not a long period right it's a substantial it's a noticeable period but it's not it's not huge right and and these things do tend to be cyclical in terms of what drives market performance. And right now, safety isn't where it's at. It's it's FOMO, right? It's fear of missing out. And and that, in my opinion, is what's pushing the market. And the idea that there will be a return to caring about uh where you are today and what your uh uh safety level is, right, relative to what you can potentially make. I think, you know, is it it is foreign to me the idea that that will not happen. Can I tell you when? No. Um but I I I I banked on it, right? Like and I think and I think that's the you talk about differentiator and fringe. Yeah, I guess I'm on the fringe now, right? Um value um being consistent in what I do and and it you know what's worked over time and does it work in the future? I don't know. But but I'm I believe it does and and I'm I'm betting on it. Right. >> Last question. So I I think a lot of this just it comes up it is hey I believe in value right I I almost have a a religious type belief in value in these metrics but >> we mentioned back testing yourself a few times. I am curious when you think about back testing and and this was sparked by you're saying 15 years is not a long time in the stock market which I agree. Uh but when you think about back testing how long do you think about that how long do you think about back testing an idea as trying to concept when you're looking thinking about this ideally you know I would say you know several market cycles right so periods where when I say cycles I don't just mean ups and downs in the market but you know different um uh techniques different approaches right growth value whatever you want to say h have excelled or or or worked over time. I think you'd have to look at if you said the past 15 years is more growth oriented, you'd have to go back a lot further to times when value was more in favor, right? I guess the reason I ask is again I I think about this in evolution like if a lot of the let's just hypothetically say a lot of the value outperformance comes from uh 1980 to 2000 >> and a lot of the value out performance comes from 1940 to 1960. Right? So I just use 20-year cycles. Well 1940 to 1960 I'd tell you get out of here. Right? Like that yes Buffett comes along in the ends and but you're buying completely different things. the market is much uh much less efficient. There's lots of pink sheets. Like it's just crazy out there. Right? So if you're doing back test and you're saying, "Hey, you know, I'm back testing to 1940, 1950." I say, "I don't think that's relevant." If you're doing the back test in the 80s, 2000s, well, now we're talking about a more modern market, but you know, computers still aren't around there. There's still a lot I I just wonder like when you're thinking about back testing, how forgetting the market cycles, how are you thinking about how like the market evolution is just think about? >> I'm trying to remember the date. It was in the '9s when everyone had to report digitally, right? What was that? >> I think that's I think SEC >> Right. So I I would think that would be a fairly good period to to kind of be looking at because you have enough information and and the data would be whole, so to speak. >> Cool. Okay, this has been fun. Uh David, where can people find you if they kind of want to learn a little bit more? Oh, um, yeah, methodicalinvestments.com and, uh, davidthodicalinvestments.com is my email and feel free to reach out anytime. >> Perfect. David Ker, Methodical Investments, this has been great. Thanks so much for coming on. >> Thanks, Andrew. I really appreciate it. >> 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.