Rules based investing with Methodical Investment's David Kaiser

All right. Hello and welcome to the Yet Another Value Podcast. I'm your host, Andrew Walker. Uh Uh we've got an interesting one for you today. Uh 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 I'm in my head, I am just a a nasty, nasty person because there was no shower and I I'm an unshowered 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 slash rules-based uh firm. And I think yeah, I think it's gonna come through in the conversation. It makes for a really interesting battle.

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 involving evolving with the times as you know?

It uh as I'll say in the podcast, Ben Graham, if you read the intelligent investor, he's telling you to buy things for two thirds of networking capital. Well, guess what? You haven't bought anything but Chinese frauds in the past forty years if that that was the only thing you were buying. So how do you think about maintaining a a rules and a value base 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 gonna be, you know, I try to start off with if you are a fundamental focus investor, what's one thing you can learn from rules based investing? But I think it's gonna 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 sponsor.

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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 will 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 run methodical investments. Uh it's more of a quantitative slash rules driven firm. And I I I'm always fascinated by rules and quants and 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. 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, qualitative focus.

I I guess let's just start off with a headliner. You know, if somebody's listening to this, they're like, oh, we've got a quant guy on, I 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 where were you before Methodical? I was at Robotic Company. Cool. Uh actually I'm still at Roboti and Company as well. I know, I know. I just you know just full disclosure. Bob's a friend, popular podcast guest. You gotta you gotta 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 uh without Bob. And so um, you know, learn 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 rules based 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. So one of the things I think you can take away is qualitative and that subjective way of investing absolutely has a 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 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 quantitative 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 gonna be a recurring theme through the the package. Let me just riff off that for a second. So you said rules based, 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 saw? When are computers going to replace saw?

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 based 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 uh and my understanding and and you certainly have a better understanding of AI, I think, than I do in in this arena.

It it's learning, it's adapting, right? And one 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, Hutzpah, 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. And look at value investing for 90 years and that sort of thing. And obviously the different techniques and that sort of thing. But we're we're looking at 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 have written and talked uh 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 put base a team around the three point ball, you could never win the championship. Those people are going to the league now, right? The NBA is all about three point ball. If you rewound it, you know, if you went fifty years back in the NFL and you said, Hey, we're gonna run a a pass based offense, they say,

Offense a 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 were those threes holding up in the 2010?

And you're about to get around the league. Or on the other hand, you know, there there is there's the Lindy effect, right? Like, hey, there 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'em and buying things.

At a discount that that's kind of like the Lindy 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 more one more out there. Like, if you go back and read the intelligent investment.

Right. Ben Brand's whole thing was buy stuff for two-thirds 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's no off of.

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, d two things. One in 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? So what I'm talking about non-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 PEs, everything like that, you know, like metrics like that every year. We're using the same technique. 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 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? And to give your example of the NBA, the r the rules haven't changed. It's the way that teams have approached it and and and offenses have evolved, right? And and that sort of thing. And as the game more physical, less physical, is shooting more, you know, there's all sorts of of factors, right? But but the structure, though the court's the same size.

The rims are the same s uh the same height. And the you know, those those type of things, the rules haven't changed in that regard. I I think the three point line came, you know, twenty three feet and yeah, stuff like that. You are correct. I when you said the rules have changed like well the three point line came in. But in in what, forty 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 I 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?

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 we're looking for a balance of of quality and discount, right? Probably not in that word discount and quality, right? So uh we 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. 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 of the market, whatever you want to look at. We're looking for 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 the 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 twenty five hundred value, right? Uh Russell three thousand doesn't matter. And it says the P is 18. I'm just being arbitrary.

The PE is 18, but there's a percentage of those companies that aren't profitable that doesn't go into that, right? So it's eighteen, but they're also unprofitable companies. So one of the the rules on 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 a qualitative, subjective, concentrated investor would. We are uh we're wanting that.

that data to be as reliable as as possible. So I 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 l let me start at the smaller profit level and then we can zoom out today. You said we only buy profitable companies. Correct.

What is a profitable company? Is it GAAP net income profitable? Is it adding back one time items? Is it Ebidah how how are you gonna no, we use we use net income and we exclude one time items. Okay. Yeah. So uh let's go to data and then we can come back to that. One of the things uh when you say rules based and I'm just saying rules based versus quantitative are are are different based on what you're saying, but they're 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 be listening 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 qu

Good quality and value. And then they would have this huge asterisk 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 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 F and hot, right? Gold is 5,000. And guess what? Gold miners are profitable and they're throwing in their And history suggests like the wrong time to buy the gold miners is when gold is 5,000 and they're trading for five times price earnings 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 can go back to the biotech. 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 uh 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 uh concentrated portfolio in terms of of equity uh individually. So we will cluster in sectors and we will take uh we will 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 uh 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 P, lower price to book, we want lower enterprise ID, things like that, right?

So to do that, you you're not just taking two metrics, although I I'd I'd be lying if I said that, you know, Gotham wasn't uh and what you know Greenblatt does is 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 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? And you anybody who's running a value screener, different sectors are

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 uh 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 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 guess, 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 rules-based model, which a 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 dollars and they've got the best computers in the world and they they can generate 50% alpha forever. Uh you're talking rules so 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 all these quant models and quant-specific firms that are trying to compete here?

Yeah, I think uh uh going back to what I talked about, which is m 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, uh 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 have the confidence that the market will give you opportunity and you'll be able to profit from that opportunity.

Well okay. So we've got a rules based system and it it it's heavily the value based, right? It leans value. Probably companies very much so, yes.

But the past let's call it 10, but I think it's been more like 15 years. Yeah. Growth has stomped value, right? Absolutely. And You know, you'll hear a lot of people, and and it's not just quants, right? You you you read the Einhorn letter and he'll say broken market, passive flows, 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 kids is it me? And then he said, No, it must be the kids, right? It can't be me. And what would you look in the mirror and you say, Oh, it's not the market, it's me. Like, like we 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 value versus no, I'm sticking to rules.

So uh you know it it's a it's a great question. I don't have a clear answer, right? I'm uh I'm stubborn in terms of process, right? Um and Uh, 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 borderblind black Monday for payments and software. I'm curious, are have payments and software started popping up in your models recently?

No, not really. Uh we in in 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. Corporate governance has been a 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 the accounting for, you know, you're

It's very difficult to read a 10K or 10Q 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 s sharks here.

How do you account for corporate governance when you're or you're running this? And how do you not just end up in, you know, 15 different hold co-controlled companies that it 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 uh we don't have a specific failsafe 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 we look at the data we're moving out. The things that are really cheap and whatever metric you want to talk about, right? PE, price book, et cetera, 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 P companies, right? That's not So

In terms of corporate governance, uh it's not something that we we apply. And and I think uh 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 uh we mentioned earlier, 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 six hundred over the past uh thirty semi 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. So um and 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 uh an index and you're buying profitable companies, uh comparatively, you will outperform in during the last 30 years. So I

You mentioned uh kind of on the sides of the discussion, rebalancing. You know, and you may mainly mention 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 advisor here, you know, don't take tax advice, all that sort of stuff. Yeah. But you mentioned rebalancing. How do you think about rebalancing when you're running this rule space model? You mean in terms of like what what the the reasoning is to rebalance when I do

Uh more not the reasoning. I I think everybody can understand the reasoning, right? You buy a company that's treating it at five times fee, it hits a wind fuel, it's treating at twenty five times fee, probably time to if you're running a rules based model, probably time to but

I I I more meant to in terms of the timing of when you rebalance'cause, you know, uh again, if I was doing if you and I were running a quantitative book, you know, uh three thousand stocks in the in the Russell three thousand or whatever.

We're gonna be long 1500, short 1500, net neutral, like that's gonna and we're gonna do it on quantitative value momentum factors. That's gonna rebound rebalance basically not just every day, every minute. Right. I'm guessing you're not rebalancing every minute. And how frequently are you rebalancing and what's the thought process behind that?

Yeah. So we do a a our 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 five P to twenty five P, right? Um And and it's'cause it's increased in price, right? Well what if it it does that because it qualitatively falls apart?'Ca y 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 timeframe 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 W 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 though? Because you you're you're running a qu uh a rules focused quantitative model, right? Why shouldn't 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 i their their stock trades up? Why isn't it better to just kick and and adjust more frequently because you're running a rules based 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 uh y it it's

Well, 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, all 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 to not profitable, it's no longer in the portfolio. Um and another risk tenant is if the portfolio is gravitates to being more expensive than the benchmark for whatever reason.

then we're gonna be in significantly higher cash. That's not a normal why would that happen? That would happen because of either the portfolios up noticeably, uh deterioration in fundamentals, or some combination. Okay. Or or the portfolio holds up and the market falls apart, right? And

Yeah, the 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 i 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 of 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 I'm clear on it, right? If I do a Yahoo finance screen, one of the tough things I find with, you know, a Yahoo finance screen, I'm going to sort and I'm going to say, hey, show me the, let's just say the cheapest companies on a price earnings based. And the first Thirty it's gonna show me are unuseful, right? The first ten Um the first ten had a one time gain. Okay, you can edit that out.

The the next ten are obvious frauds, you know, Chinese rever reverse merger frauds or something. And then the next ten is a data error on Yahoo's price. Like 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 chose 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 by q. and testing over time the validity of their data and the reliability of their data. Now, interesting, you said Yahoo, CapIQ 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 and 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 uh, you know, again, it 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 n should not have a significant impact on the port.

is 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 it got the measurement into was

uh uh 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 uh honestly reminiscent of Enron, right? But working these complex JV structures to keep uh

to keep their data centers, these huge data center build outs off their balance sheet. And I'm not accusing them of fraud. I'm just saying like that literally is what MON did it as well, right? They they want it to keep the head they want it to look asset like.

Uh, you see in telecom right now, Verizon, T-Mobile, they're doing these complicated JVs to keep these fiber build-outs off their books. How do you look at like Uh and obviously I've picked a couple the Cherry picked a couple of different samples, but I've now hit retailers, telecomma, there's several others.

How do you look at companies that are maybe structuring things to be off balance sheet to make their sales look asset light or just accounting rules make them look asset light? Or how do you think about those types of issues? Yeah, uh that's a great question. And uh again, it's a combination, the way we combat that is a combination of not relying on any one metric.

price the book and uh spreading things out. And there there uh 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 one-time item that wasn't scrubbed out. It's um uh in price to book and off balance sheet, something like that. We're not immune.

But it's not a frequent phenomenon either. So uh 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. 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 Yom Kippur we talk about um you know uh The word I 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 gonna 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, ah, 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 necessary uh necessarily my own expertise. And so uh or not

You 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 fifty to eighty 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 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 Yeah, I'm sorry. Yeah. No, no, no, that's great. Well, you it a lot of it comes back to the rules, right? So how do you come up with the rules?

So uh 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 a c time again from investors. And then, you know, the that rule, if you follow that rule, you would literally the only time in the past. Fifteen years you would have been able to buy stocks was like the the absolute debt.

of the global financial crisis, right? Yeah. 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 it was a very useful frame of frame of them. Uh You can make two arguments. Hey, we need to stick to this rule, right? We need to be 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 it another way of thinking would be like, hey, if you've got a buy signal that says one time in the past thirty years it was you were good to buy, like the buy signal is outdated. No why why is the buffer rule outdated? Well, in part you know, the US used to be

It the public companies were GM forward 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 may 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 earnings, trading for ROE? I think you're probably like when you say there's rules and we back test them, was the back test 100 years? Like, how do we know like the next

Are different than the last hundred years. The rules from the last hundred years are the Buffett indicators, right? And hey, I I could imagine a world where when I say, Low price earnings, good ROEs, 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 the book, good ROEs.

That that's historically been a great exposure, but banks have all the spintach risks, right? Like, how do I think about the rules evolving and sticking to them even I I think I've thrown a lot out there. I I don't know how to quite frame it, but I'm sure people can understand where I'm going based on the buffer to be on that. Okay. So first of all, y 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 cutoff, you know, like five times earnings of 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? 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 gonna go generic or whatever. 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 the book and high return equity things, you can get a lot of those. And those are not necessarily the companies that are going to drive performance. Uh oh 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 clips and you know, up and down coin flips, uh safety approvals. Like safety approvals are the one where it's like, hey, you can have everything right.

And then you've got or sorry, not safety approval, safety issues. You've got everything right, you've done all the analysis. And out of nowhere could be, hey, this drug caused liver failure. And like, how are you gonna catch how are you gonna catch that as forget individual investors as a big investor, like

You just don't know. And I I understand, hey, that that's a risk, but you know, those are truly out of left field. And you do that, the drug goes to zero. Anyway. 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 are gonna drive the boob up. And hey, like financials are one of those funny industries where, you know, Lehman Brothers looked really cheap on Friday in September of two thousand eight and then on Monday it was zero. So you've got those risk two.

But that that's two like pretty big things where you're kind of stepping in and imposing limits and systematics. 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 Fifteen banks and twenty four biotechs right now, maybe we should be leaked to that. Right. So

You you talked about and I'll 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 financial Okay. So um and then therefore there's a lot of redundancy and I'm not getting in 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 uh 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 uh in terms of like

Sorry, I'm also sure I thought again. That's great. One more question. And this has been like draw at the heart of it. We've touched on some things, but it's just one I uh that keeps popping up. Melting ice cubes, right? These are investors' least favorite.

Uh the the one that I think of right now is until twenty sixteen 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 phrase, but it's hey. You know, ESPN, uh 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 gonna turn or they're gonna 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 are, 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 just cheap, cheap, cheap, cheap, cheap, cheap, cheap, 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 Trillion 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. And I understand some of that is hey, melting 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 five years, you're you're no longer in business because it pulled up the price of AMC networks. So you know We tend to have fairly frequent turnover, I think, for well, I don't I'm not even gonna compare it, but we we generally have fairly substantial turnover when we do a research. So The idea of a company that is executing the way it should in terms of uh Uh discounted metric.

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, uh excuse me, melting melting ice cubes, excuse me. Um the it can happen, but it 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 uh 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 consistent looking for fastballs, right? Uh if we get a curve, we're gonna hold off. Right. Um so The re the the long-term play is to create alpha over a period of time. Right. So

Again, uh because of the way we spread out exposure in terms of companies, because of the metrics we use, i is that something that frequently happens that we get a a plethora of melting ice cubes? No.

Last question. A rules based model, a a qua more quantitative model. 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 a assisting or helping with the portfolio construction, the with the rules, with the backcessing, whatever it is. Yeah, so at this point uh we're not really using it.

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 it's you know, AI is something I've thought a lot about. Uh I did a post on weird markets. But your your podcasts and uh you know, AI is funny because when I would say, Hey 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 Uh the best example, it's a a difficult one, but daily fantasy sports, uh which people use Everyone started using optimizers, which would optimize, like, hey, if you're in a competitive thing, it's gonna 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 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 Pulhos 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 say 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 a hundred percent sure either. And but I do I do think that

The uh 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 stock markets, 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 FOMA, 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

uh you know, is it it it is foreign to me the idea that that will not happen. Can I tell you when? No. But I I I I banked on it, right? Like and I think and I think that the you talk about differentiated 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 always have a a a religious type belief in value in in these measures. But we mentioned back testing this up a few times. I am curious when you think about back testing, and and this was sparked by your saying 15 years is not a long time in the stock market, which I agree.

But when you think about backtesting, how long do you think about back how long do you think about backtesting 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 uh 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, ha have excelled or or or worked over time. I think you'd have to look at if you said the past fifteen 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 Devolution. Like if a lot of the let's just hypothetically say a lot of the value out performance comes from

To 2000, and a lot of the value out performance comes from 1940 to 1960, right? So I just use 20 year cycle.

Well, nineteen forty to nineteen sixty, 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 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 nineteen forty, nineteen fifty, I say, I don't think that's relevant.

I if you're doing the back test in the eighties, two thousands, well now we're talking about a more modern market, but you know, computers still aren't around. There they're still a lot. I I just wonder like when you're thinking about back testing how you're Forgetting the market cycles, how are you thinking about how like the market evolution is just something I've been thinking about? I'm trying to remember the data was in the 90s when everyone had to report. Digital, right?

What was that? I think that's I think uh SEC after S C 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.

Okay, this is been fun. Uh David, where can people find you if they kind of want to learn a little bit more? Oh, um yeah, methodical investments dot com and uh David at Methodical Investments dot com is my email. And feel free to reach out anytime. Perfect. David Kaiser, 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 advisor. Thanks.