VALUE: After Hours (S08 E13): Mark Cooper on global small cap value, AI and managing small cap long/short at MAC Alpha

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TRANSCRIPT

[Tobias] I think we’re live. I’m Tobias Carlile. This is the Acquirers Podcast joined, as always, by my co-host, Jake Taylor.

Our special guest today is Mark Cooper of Alpha Mac. I got that wrong, didn’t I? Mac Alpha Capital Management.

Mark’s got one of the more fascinating value backgrounds that I’ve seen. He was a Columbia professor. He’s worked at First Eagle.

He’s running a global value fund. How are you, Mark? Welcome.

[Mark] Good afternoon. Thanks for having me, Tobias. All’s good.

[Tobias] My pleasure. Let’s start with a little bit. Tell us about your strategy, your philosophy at Mac Alpha.

Inside a Global Small Cap Long/Short Strategy: How MAC Alpha Finds Opportunities

[Mark] Sure. We have two strategies, really focused one long only and one long short, but we’re really focused on global small caps. If I were to simplify it as much as possible, we’re focused on global small caps because that’s where we see the best opportunity on the long side, which is primarily international small cap value stocks, so small cap value stocks outside of the United States.

We are short more than not small cap, high growth, high valuation stocks that have never earned their cost of capital within the US. We’re doing that because that’s where we’re finding the best opportunities. Looking at a long bit of history, 50 to 100 years of data show that these areas are the most attractive they’ve ever been.

The long side, international small value is much more attractive than it’s been historically. On the short side, we think the opportunity is better today than it was the peak of the dot-com bubble by a serious margin.

The Most Overvalued Stocks Since the Dot-Com Bubble? A Data-Driven Warning

[Jake] Mark, does that end up being a lot of science fair projects and stuff that are in the Russell 2000 today?

[Mark] Some of that stuff, yeah. Companies that have never earned their cost of capital that trade crazy valuations. By our estimation, there were about 400 companies that traded over 10 times enterprise value to sales in March of 2000.

Now, when the bubble burst, the median return on those the next year was down about 79%. Today, there’s only 300 companies that are over 10 times enterprise value to sales, last time we looked at it. But as you probably well know, there’s only about half as many public companies today as there was in 2000, so the percentage is higher.

But the other interesting nuance is, so that’s just the cutoff level at 10 times enterprise value to sales. The valuations today and the leverage, number one, the companies have much more leverage today than they had then, so they’re substantially more leveraged. But number two, the average valuation is about 3x what it was then.

So we look out there and there’s a lot of companies that traded 50, 100 or more. And yeah, some of them probably qualify as science projects. But historically, they probably haven’t earned their cost of capital or generated any free cash flow and don’t have, in our opinions, necessarily any sustainable competitive advantage.

[Tobias] What’s your universe, Mark? What are you looking at developed?

[Mark] So it’s really the global small cap universe, we would say is around 20,000 companies. Our focus tends to be more developed. So we’re probably 95% developed.

I mean, you hear people talk about EM, but we’re only finding small pockets in EM right now that are interesting. So from a country perspective, it leads to us having large positions in the UK and Japan, as well as some in the US. We find some global businesses in the US that are attractive.

But again, on the other side, it’s the overvalued, expensive companies. And then we’re in about 20 countries, and we have exposure probably in almost every sector. Although by design, we do not look like any benchmark.

[Tobias] What is the portfolio just in broad terms? You don’t have to tell us names, just in terms of industry, country, diversification, industry concentration, any of that sort of thing. Position sizing.

[Mark] Sure. So we do structure the portfolio to be quite diversified. And it’s because we believe that if you’re looking at a universe of 20,000 stocks, we’re going to end up owning or being short in our long short strategy, less than probably one half of 1% of the universe, right?

So we’re going to be long or short, somewhat less than 100 single securities on either side, right? So we can afford to be extremely picky in doing so. From a country perspective, again, our biggest weights tend to be, again, Japan, the UK and the US, the biggest kind of overweight relative to what a lot of people would think is reasonable is probably the UK.

Sector wise, because we focus on competitive advantage so much, we want to go where industries tend to have longer lived competitive advantage than not. So what it causes us to do is typically favour certain sectors at the expense of others. So we tend not to be invested as much in financials, utilities, or real estate.

Why is that? Well, they’ve got characteristics we tend not to like. Number one, we don’t think a lot of them have competitive advantage.

Number two, they tend to have a lot of leverage. Number three, the regulatory environment, I mean, maybe you have semi-monopolies and some utilities, but that’s a small portion of the small cap space. Real estate, we tend to think that a lot of people can, a lot of investors have a lot of exposure to real estate anyway, outside of maybe an investment they would choose with us.

So we think we’re a little bit more diversifying to be outside of that realm. And we don’t think the tax treatment is necessarily as favourable. And we think we can get better returns without using substantial leverage.

So we tend to avoid those areas. Areas we tend to like over time, we tend to like industrials because we think the competitive advantage period lasts a lot longer there than it does in many other industries where you’ve got better visibility. We have companies there that have better visibility for earnings the next five or 10 years than a lot of other sectors.

We try to, we’ll probably, you know, we will episodically be in technology or healthcare when we see appropriate. We’ve seen consumer discretionary hit so much, and we’re not a fan of the consumers. We think the consumer’s got a lot of issues these days, but some of these stocks we think have been beaten down enough to where we’re finding interest there.

You like staples, but you can only buy those occasionally when they get to be cheap enough for us. Because we like quality businesses and high return businesses without leverage, but they often traded a pretty high multiple.

[Tobias] So- I thought Japan was a little bit, Japan versus UK is a little bit interesting because I would have thought that the narrative for most people is that Japan is just stonkingly cheap and the UK, I’ve also heard the UK is cheap, but I think that most folks who I talk to think that Japan is cheaper. So what are you guys seeing that’s a little bit different there?

Why Value Investing Still Works: The Case for Quality Compounders Over Net-Nets

[Mark] Yeah, I think we agree Japan is really cheap. And if I think about the markets as a whole, it’s probably the cheapest. And we’re value investors.

I do have a long history with Columbia as do many members of our team, but our portfolio is probably more Buffett-like than Graham-like. So we tend to own, especially in a small cap space, I think you can buy a lot of high quality businesses. And we talk about this later, but a lot of quality stocks have been beaten up pretty good, but they’re not paying the premium you used to pay for quality.

And so in my in that environment, you want to favour those investments. We also like businesses that we think are high quality. People have called them compounders, the platform businesses, but we just have a limitation on what we’re willing to pay.

We don’t think that a great business is an excuse to pay 30, 40, 50 times for something, right? So we want the great businesses, we just want to buy them when they’re cheap. And we will and have owned net nets in the past, and we will continue to own those.

But we think one of the key components of being an effective analyst over time is using your time wisely. We think return on time is extremely important. One of the problems with buying a lousy business that trades at half a book value, okay, so you’re right, you do your analysis, it goes up to book value, then you’re going to sell it, you’re going to go find something else.

Whereas if we’ve got a business we think is super attractive, that’s compounding at very high rates, that is still cheap, that research we do today might last us 10 years, 15 years longer, because we’re going to end up holding that position for a lot longer period of time. So we think that’s actually a better use of time than kind of constantly turning over new rocks to find the newest stock that’s trading at half a book value.

[Jake] Sometimes those net nets can sit as a net net for 10 years straight too.

[Mark] Sorry?

[Jake] I said sometimes those net nets can sit as a net net for 10 years as well, can be quite irritating.

[Mark] Absolutely. So we would like the business to be growing in value over time. So we’ve looked at net, we’ve owned net nets and we’ve also passed on net nets where we felt like they were not going to do anything with the cash or it was not growing.

If the business is decaying fundamentally or losing money, it might be trading at half a book value, but if they’re bleeding value over time, then time works against you. We want time to be on our side and we figure if we own a good business that’s growing value at 6, 7, 8, 10, 15% a year, whatever the number is, at least it’s getting more valuable through time. So there time works on our side and it works, if nothing else, it should increase our margin of safety over time.

[Jake] Activism stuff in Japan, have you been looking for increasing the chances of a catalyst happening if you know that maybe somebody else is sniffing around there?

[Mark] Yeah. We’re generally not activist investors the way most people describe it. We do engage with management.

We talk to management, but we keep it all private. We’re never public with our disputes with management. We think it’s better to build a relationship for the long-term.

That’s not our expertise. It’s not been our history, either at First Eagle or at Omega or PIMCO or Pequot, anywhere else I’ve worked. So we will try to help educate management on our view on strategy.

We’ll do it on capital allocation and we tend to have a lot of good conversations with managements or boards on capital allocation, but we don’t go public with it and we don’t try to garner other support from other investors, et cetera, to make it happen.

[Tobias] How often do you find them receptive to those ideas or you’re the first person who’s telling them those sort of things? How often do you find that? Because I’ve found that a little bit in small cap land.

[Mark] Yeah. There’s definitely cases where you’re the first person to tell somebody something. I think generally, where we’ve had the biggest impact is both in Japan and in the UK.

I think they are pretty receptive to it. I think that unfortunately, they also, if you’re sitting in the company seat, or if you’ve got a hedge fund coming in, encouraging them to say, capital allocation, it means just buy back stock. That’s generally not a good ploy to get the company to act as you want to act.

My view is they’ve got to live with the consequences of their actions 10 years from now, whereas if a hedge fund owns it and wants them to buy back stock, reduce the stock price 20% or 30% this quarter, and they’re going to be gone when it’s over, that doesn’t go very far. I think they see through that quite a bit. So if you really think about it, it’s a long-term relationship and it’s about educating and hopefully informing.

We don’t tell them what to do, but we walk them through our thought process. We’ve talked to many companies about this. I talked to companies as big as Apple 13 or 14 years ago about capital allocation before they started on their dividend payment and share repurchase back 2012, 2013, whenever that was.

I think it’s about thinking that we want to lay out the flow chart, if you will, the things we would consider, the things we think they should consider. It’s not do X or Y, but if we were in your seat, this is the stuff we would want to consider and want you to consider in thinking about any form of capital allocation, whether it’s share repurchase or acquisitions. It never ceases to amaze me, companies will tell you they have no view what their business is worth.

I understand they don’t need to tell us what the number is, but I would like them to think they know what their business is worth, but they’ll go out and do a lot of acquisitions. I always ask the question, if you’re not sure what your business is worth, how do you think you’re going to be able to identify what some other business is worth? You should have more information about your own business and you should know where all the good parts are and all the works and problems that the seller is not going to tell you about.

We think companies need to have a view of its own value before they should consider acquiring anything else.

[Tobias] You said that there’s this opportunity in global small value. Can you put some numbers around that or just articulate the view to us?

Why International Small Caps May Need to Triple to Reach Historical Averages

[Mark] Sure. So we’ve looked at historical data and if we break international small and value into factors, if you will, and think about it like a quantitative analyst would kind of think about it, we believe international stocks today are cheapest to the S&P and all of the data we use for our charts go back, one of them is just a little bit less than 50 years, the other charts are probably 55 years or so. We think international small caps or international stocks need to triple to get back to the 55 year average versus the S&P.

So they are much cheaper than they’ve ever been historically. Maybe adjusting for a little bit around this level the last couple of years, right? But they’ve gotten cheaper and they’ve gotten cheaper for, they’ve gotten cheaper really since the peak of the Japan bubble in 1989 era, right?

But it’s been a long time coming and they are much cheaper than they’ve ever been historically. So that would be suggestive that international stocks need to compound at about 25% per year for five years ahead of the S&P to get back to their long-term average.

[Jake] What if we just cut the S&P in half? What would that change the math?

[Mark] Then those numbers go down substantially, right? And you can think about how that convergence may happen, right? There is absolutely, and we will get to that point.

I’ll say quickly, we think that the S&P is probably flattish for the next 10 years, but you could see a 30, 50% haircut at some point in the not too distant future. So we think that there is a reality that is a significant risk in our opinion. If I go to value as a factor, it’s almost as attractive as international on a relative basis.

So value versus growth, that is about, I think we need to compound at about 20 something percent a year for five years to get back to long-term average. And then small versus large, our data set, and I can share this with you later, but our data, we really focus on the US because we don’t have it broken out as well internationally. But you would say small caps are about as cheap as they’ve ever been.

Now, international and value are much cheaper than they’ve ever been historically. So they’ve got to go up three X and two, two and a quarter times or something like that to get the long-term average. Small versus large is not as cheap, but that’s in the US.

And again, there’s a couple of nuances here about the data series we look at. That series goes back to the late seventies. If you look at the chart we have in 2000, small versus large are about the same as it is today.

And you say, but it’s not as attractive. And I agree with that. However, I mentioned the fact that there’s half as many public companies today that were around in 2000, but on the extreme end, the stuff that we are typically short is much more expensive.

So you’ve got a greater percentage that are expensive and they’re much more expensive. So that kind of raises the average a little bit, but forget it. So that would imply that small probably should outperform large by seven to 8% a year for five years or so.

Okay. That’s all well and good. What’s it mean in total?

Right? If you add these factors together and you look at it compounded, if you do international small and value, the question in my mind is like, how fast does this mean revert? And I’ll say full stop.

I believe these time series will mean revert. I think there’s one of the valuations of one of the most mean reverting trend time series in finance. I absolutely believe it will mean revert.

Historically, it’s mean reverted within kind of three to five years. Now this cycle has taken longer, it’s gone further. So does that mean it mean reverts over a longer period of time, or is it the same shorter period of time?

Why Global Small Cap Value Could Outperform the S&P by 25% Per Year

I don’t know the answer. And I don’t think anybody knows the answer to that, obviously. So we kind of look at it and say, historically, it’s mean reverted in three to five years.

What if we look at 10 years? And frankly, we choose 10 because it’s, I don’t know, nice round number. But the numbers are insane if you look at it on a shorter term basis, it sounds even more unbelievable.

But international small and value, if those factors are mean revert to their long term average, which we think they will, would suggest that international small and value would outperform the S&P by about 25% per year for the next 10 years to get to the long term average.

[Jake] Now- Mark, you’re filling Toby’s head with all kinds of confirmation. Absolute fireworks going on over here.

[Mark] It sounds crazy, but the math is, again, I don’t think you can dispute the math. You can say it’s not going to mean revert, that’s fair. But the math is pretty clear.

And we’ll share the data series with anybody. You can look at the data series and that’s pretty clear. Now, a lot can happen, a lot can change it.

What I would also say is that if you assume that the S&P does zero, which we kind of assume, or maybe 5%, which is like the most bullish 10 year forecast we’ve seen of any of the large investment banks is 5% a year for the next 10 years. So 5% a year would be about 62% if you compound that out for 10 years, total return for the S&P. And again, our starting point today, valuations about as high or as high as it’s ever been would be suggestive of a market that has zero total return or maybe negative, probably with a big drawdown at some point in the middle.

And we agree with that. If the market were to do 5% and compound total return 62% over 10 years, that would imply that a long only investor in international small cap value, just with those exposure to those factors could expect about a 30% per year gross return.

[Tobias] That’s acceptable. That’ll do.

[Mark] Which, yeah, I think that’s more than adequate. How we want to determine, again, and we think historically, we think we’ve been able to deliver alpha, hence the name, part of the name of the firm. And we think we do it with low correlation and low beta and less downside and less true risk of permanent impairment of capital.

So that diversification benefit, we think is substantial. And so in our long short portfolio, we actually, we structure the long short very different than most. We use a lot less gross leverage than most long short hedge funds, but our strategy has much higher net exposure.

And it’s the nature of what we’re long versus short, which drives that. But we’re basically fully invested or more than 100% invested. And we end up with a beta to the NASDAQ of, I think last year was slightly negative, and the S&P was about 0.1. So it’s a very different portfolio by design of our longs and shorts, which gives you a different stream. And hopefully, we can add value in the short side, hopefully we can add value on the long side as well, and being in the right place. But I think the biggest story by far, if I could leave listeners with anything is, you need to pay attention to this area. And whether it’s with us or somebody else or Tobias or your business, it is a great opportunity.

And it looks like from our perspective, the asymmetry is phenomenal at this point, where we think we should get worst case, we get pretty decent returns on an absolute basis, and best case you get outstanding relative and absolute returns, depending on how you structure it.

[Tobias] Mark, let’s just talk a little bit about the US bubble and the AI probably is driving a big part of that. My own figures are that we’re probably slightly negative on the index over a decade, total return is slightly positive. And so the difference between the two is dividends, and that the dividend yield at the moment is like 1.4% or something. So that’s the margin. So the returns are expected fairly low. And then if you look at the index, it’s almost it’s dominated by mag seven.

That’s the big AI play. So how do you see? That’s really the million dollar question, whether we’re paying just way too much for these firms, even though they’ve all come down pretty substantially since November last year.

Right.

Why the Mag 7 Dominance Could Signal Rising Market Risk

[Mark] We would agree. And again, I mean, our focus is all on the small end, because it just seems that’s where we’re finding both the best opportunities on both sides. But I would agree.

I think, I mean, obviously, the concentration is at or near all time high levels of concentration. Historically, that has not worked out well. Again, I’m not trying to tell everybody to sell all their NASDAQ or whatever, people are going to do what they do.

But we do think the risk is rising. And we think that some diversification away from that makes a lot of sense. Right.

As far as the mag seven goes, yeah, I think I think last we looked, the average mag seven stock is down 15 or so percent from October or thereabouts, maybe more. And some of them are down 20 or 30. Are we in the process of seeing that bubble burst today?

Possibly. I mean, we’re seeing in other areas, we’ve seen massive speculation like we haven’t seen in 25 years last year, kind of from starting in April last year, once the tariff ended. Some of the metrics we look at when we look at kind of expensive stocks versus cheap stocks, high volatile stocks versus low volatile stocks.

And, you know, they’ve outperformed by a greater degree than they have ever in the past, which shows us there’s just more speculation in the market. But with the mag seven, one thing I kind of wonder, and this is not a maybe fully formed out thought, but it wouldn’t surprise me with the talk of the two big IPOs, maybe there’s more, but talk of OpenAI coming public this year and SpaceX at some crazy valuations. And then the talk that they’re changing the way you do the index construction methodology to allow them to be part of the index faster.

Obviously, we think part of what’s changed over time in the markets is, you know, the increased passive money flows, right? So it’s going to drive more money there. So is money leaving mag seven now in anticipation of buying OpenAI and SpaceX later this summer?

Maybe. But could that be, you know, could that be the top, the top? I don’t know.

I mean, it doesn’t matter for us that much. But I just, I like to think about what risks could exist that could go wrong to upset everything, right? And I think that’s an issue.

You know, we, as far as AI goes, we’ve done a lot of work on, we think on understanding the timeline for OpenAI and the promises and the spending. And we think there are a lot of parallels. Like we study a lot of history and financial history to understand what’s similar to this event today versus the dot-com bubble 25 years ago or the 70s.

What’s similar and different about these cycles? What about prior bubble periods or, you know, the conglomerate phase of the 60s, or we can go back in time and look at, you know, we can look at the railroads, we can look at radio, we can, you know, you know, going back further in time, but human nature doesn’t change in our opinion. Human nature is the same.

And so we get some of these same behaviours. Everyone says it’s different this time. We don’t believe it is.

We don’t think humans evolved that quickly. We think we’ve evolved very little in the last 2000 years. I mean, you know, humans have been around in current form about 200,000 years.

So we study history back to Roman times to understand, you know, how have the markets behaved? And the product is different, but we think you kind of get the same outcome. And at the end of the day, our analysis of looking at AI is that even the money that people talk about is going to be hard to come by.

I mean, I was talking with some people, it’s probably been four or five months ago, they’re talking about open AI saying, well, I said, do you realise they promised what 500 billion in revenue the next few years? How much revenue did they do last year? I think last year, the first half of last year, they did 4 billion or so in revenue.

The second half, they did eight something. So I think they did 13 billion in revenue. If they double every six months, that’s outstanding growth, right?

It’d be the fastest growing company in history, right? And others, Michael Mobison’s written about this as well. Like their promises would be the fastest growing company in history.

And maybe they achieve it. But if they do 50 billion in revenue, somebody said, well, they’ll just borrow the money. And I said, they’ll borrow a trillion dollars.

You realise the biggest bond offering in history until maybe recently was Verizon in 2014 borrowed $50 billion to build out their network. So again, all the promises, we’re just sceptical that they can grow as fast as they want on a money perspective. Number two, we think there’s a limitation on people.

And it’s not the guys programming the LLMs. It’s actually the engineers and constructions to build the facilities. But oh yeah, then we’ve got to get permitting. We’ve got to get them connected to the grid, right?

Which is another problem. So we’re sceptical. And I think we’ve been this way.

We just understand the realities of making this happen. Then we also know commodities were in shortage before AI became topic of everyday conversation. So if you go back five years ago, when most of every conversation you were involved with didn’t include AI, right?

People were worried about commodity shortages for everything going green and all the EV stuff. There was, I mean, the IEA and EIA put out warnings about commodity shortages then. And now you’ve had AI come in when they can probably pay more than the governments can to produce the commodities.

But can you produce all these commodities in the quantities needed to build AI as fast as everybody talks about? And again, we’re sceptical, right? This is a complex system.

And what do we know about complex systems and construction projects? They tend to be late and over budget, right? Morgan Stanley put out a piece, I don’t know, maybe a few months ago saying we need 48 gigawatts of nuclear power in the next three years.

And I thought about that. I said, so that’s a lot, right? And they determined this 48, one gigawatt plants.

Well, how many nuclear power plants are under construction in the United States today?

[Tobias] I would say zero.

[Mark] Zero, right. How many have we built in the last 25 years?

[Tobias] I’m guessing the same number.

The Hidden Limits of AI Growth: Energy, Commodities, and Reality Check

[Mark] Actually, I think it’s three. Okay. So we built three in 25 years.

The fastest one of those from our research, it was from the time they started construction, right? So forget permitting. Construction was 10 years.

So if you ask me, are we going to build 48 gigawatts in the next three years? I’d say absolutely not, right? So there are constraints to the system that are outside everybody’s hopes and dreams.

[Jake] And listen, we hope- Not on my spreadsheet. It looks like it’s just a cell that says 48 gigawatts.

[Mark] Exactly. So again, I don’t try to be the… We just tell you what we believe, right?

And we could be wrong, but our analysis would say it’s going to be very, very difficult to do this, right? And the amount of commodities you need, whether it’s copper, platinum, palladium, their arid elements, nickel, go down the list, right? There’s a long list of commodities where the production amounts needed in the next few years are astronomical.

You need copper. You’ve got the biggest country in the world, copper-producing country, Chile, is restricting copper production. But you need the equivalent of the six biggest mines in the world coming online every couple of years to grow, right?

And if this was oil, if we said, you need three Gowars coming on, the biggest field in Saudi Arabia, right? Which by the way, now is shut down and we’ll have a tough time getting back to the level of producing anytime soon. If you can’t bring commodities on fast enough.

So it’s not even a function of price, right? It doesn’t matter if copper is $5 a pound or $50 a pound. There’s a limitation to how fast this can be produced.

And so we think that’s going to temper everybody’s enthusiasm. So we’re a little sceptical from that perspective.

[Tobias] I saw a good stat the other day that the biggest copper mine in the world is Escondida, which means hidden in Spanish. Somebody on Twitter told me. And by 2030, we need eight more Escondidas, which is a lot.

And I don’t know if there are eight more Escondidas in the world.

[Mark] And by the way, even in an environment now where copper is up, I may be a little bit older than this, maybe a couple of months old, but I think three of the largest six mines are going to produce less copper, including Grasberg, which is the second biggest copper mine in Indonesia, Freeport owns Grasberg, the second biggest copper mine in the world. Three of the biggest six are going to be down production over the course of the next year. So again, you need to grow the overall production rate at double digits, mid-teens, whatever the number is, maybe more.

If you don’t get any growth from the biggest guys, it’s going to be quite difficult to get it from the smallest.

[Tobias] It’s going to be hard to hit.

[Jake] China wasn’t in a real estate collapse right now. I mean, it’d be a different world.

[Tobias] Top of the hour. So I’m going to just do a quick shout out and then JT is going to give us some veggies. What’s up?

Valparaiso, Breckenridge, Jetpack Gully in the New South Wales. Boise, Brisbane, Australia. Good effort.

Early start for you. Lawrence, Kansas. Tumble, Texas.

Tallahassee, San Diego, Snohomish. Mittersill, Austria. What’s up?

Spilley, Gothenburg, Sweden. Fairfax, Virginia. Transylvania.

Barrow-in-Furness, England. Thanks, Mike. JT, give us some veggies.

[Jake] All right. So this is entitled Mercator Projection for Markets. And at the centre of both maps and markets is the same paradox.

The best tools can be wrong, even on purpose. And every map distorts reality. It has to, right?

It can’t just be perfect representation of the territory. And every valuation shortcut does as well. So it published the projection that changed Navalegian and there was a reshaping that was happening due to trade and exploration.

And maps were not neutral objects at that point. They shaped who could move, who could trade, even who could survive in some cases. And Mercator found himself, he’d already spent several months in prison after being arrested on suspicion of heresy in 1544.

So this was not, you know, some detached scholarship that he was engaged in. This was work in the real world where uncertainty was real and mistakes had consequences. And at that time, exploration was accelerating and ships were travelling farther.

And at that time, ocean navigation was really unreliable, obviously. So Mercator was not trying to show the earth as it really looked. He was trying to make his maps usable.

So sailors needed a flat map where a straight line represented a constant compass bearing. So he solved that problem. And later, you know, he created atlases, which is a term he invented, reflected that kind of same instinct.

Like it’s not a mirror of the world perfectly, but it makes the world more legible for a specific purpose. But of course, their trade-offs were very severe. To keep that bearing and make it fit across, you know, a curved earth, it had to distort the scale, of course.

And as you all well know, like it moved things, as you move towards the poles in the Mercator projection, the land masses get bigger than they actually are. So Greenland looks as the same size as Africa, even though it’s about, you know, Africa is about 14 times larger. So this was not a flaw in the design.

It was the design. Like this is what he was trying to accomplish. And he was optimising for navigation, not for showing the correct size of continents.

The problem came later when everyone kind of forgot about all that. And this specialised tool that he created escaped the purposes of the sailors and ended up in classrooms. And now that distortion stayed, and the context behind it completely disappeared.

And people stopped seeing that trade-off, and they started just thinking that that map looked like truth instead. So as investors, we often do the same thing. The P-E ratio, I think, is the Mercator projection in markets.

Helps you navigate, but also can distort what matters. And this is not really the bug, like it’s kind of the point. We take something extraordinary complex, you know, business with its future cash flows, its competitive positioning, its capital needs, and we compress it down into this one number, price divided by earnings, simple, fast, comparable.

But just like Mercator’s map, there’s a flattening that’s happening. And that multiple hides duration, hides reinvestment needs. It hides returns on incremental capital.

It hides balance sheet risk, cyclicality, management quality, et cetera. And a company at 25 times earnings might be expensive, or it might be this durable, high-return business with a really long runway, very little capital needs to grow. And maybe 10 times could be cheap, quote-unquote, or might be slowly deteriorating and wildly expensive.

The number itself doesn’t really tell you. So of course, there’s a little example of this. Buffett bought See’s Candy in 1972, paid about $25 million for business earning, call it $4 million or so pre-tax.

And on the surface, this looks not like super classically cheap. And in fact, Buffett said that he would have walked away if they’d asked for an additional $100,000. But the real asset was not living in the multiple there.

It was the economics underneath that multiple. See’s had pricing power, required very little incremental capital, could send cash upstream for decades on end. And over time, Berkshire’s pulled north of, I think, $2 billion at this point out of the business.

So a richer entry multiple than whatever he paid, call it six times or something, would have reduced the return, of course, but would have been completely irrelevant for the underlying lesson was that the business economics did most of the work here. So this is a common mistake I think we see, is you hear it constantly, like, this stock is cheap at 10 times X, or this stock is expensive at 30 times X. But a multiple has real no standalone meaning.

And I think Michael Mobison said it well. He was right when he said you have to earn the right to use a multiple. A PE is the simplicity that’s on the other side of the understanding and the inherent complexity in the work that you need to do.

So at this deepest level, the PE ratio is just a compact expression of all of these hidden variables. And just like two places on the Mercator’s map can look similar in size while being radically different in the real world, the same thing can happen in markets where a 15 PE stock looks the same. So just wrapping this all up, you know, useful models, of course, are going to have to simplify.

But every simplification brings with it some kind of bias to it. That’s not really a problem, necessarily. The problem is, is when you forget about what that thing was originally built for.

And then that’s when you go on to make mistakes.

[Mark] I just want to check, too. Can I ask a question on that as a follow up? Do you mind?

[Jake] I may not have an answer, but I’ll help you to feel it.

[Mark] If you look at some of the indices and how they account for PEs, it’s my understanding that many of the popular indices, how they deal with companies that don’t have earnings, right?

[Jake] You drop it to zero or you cap if it’s like an infinite or a big number over 50, we’ll just, nothing’s higher than 20, cut it off.

[Mark] Right. But that’s massively distorting, right? Again, I agree with you.

Your points are very valid, right? It’s not a single number itself doesn’t tell you anything. But when the Russell 2000, I think, you know, again, it’s roughly a little over 2000 companies.

If half those companies don’t earn any money and maybe the range of PEs is one to 100, right? And they just get rid of them. They’ll tell you that the average PE is 40, which still versus history is about as high as it’s ever been.

But I would argue it’s more distorting because they don’t try to adjust for those other thousand companies other than just ignoring them.

[Jake] Yeah. That’s probably where price to sales is a smarter way to do some of that, right? Because then you, at least revenue is a somewhat cleaner number on this.

[Tobias] It does presuppose some sales for some of these companies and many of them don’t have sales. I have looked through the top 50 of the Russell 2000. That’s hilarious.

How many of them don’t have sales? Most of them actually, when I went through. Oh shit.

Quite a few of them are sort of science experiments.

[Mark] Yeah, go ahead. Sorry.

[Tobias] I was just going to say, what do you think, Mark? That’s near your universe, right?

[Mark] I mean, we don’t look at the benchmarks for lots of reasons because we think that we’re not set up to look like a benchmark on purpose. So, I mean, we are aware people will compare us that way. My view about something like the Russell where you’ve got called half the companies don’t have a PE multiple.

A quick and dirty approximation, again, still wrong, but closer to ballpark would be if your range of companies is, you know, PE is one to a hundred and then you’ve got another thousand companies that are effectively don’t have a PE because they’ve got negative. The least they could be is a hundred. Maybe they’re 150.

Maybe they’re a thousand. Maybe they’re infinite, right? Whatever.

But if you want to adjust for it to normalise it, I’d say at least throw them at some premium to the highest multiple you’ve got out there. But at the bottom line, it doesn’t really matter. Like I’m talking about kind of how cheap we see these factors are versus the market.

They could get a little cheaper. People have asked me, oh, international stocks have worked last year. Is it over?

Like, look at the chart we have. You can’t tell on the chart it’s moved, right? So I think it directionally would put you in a better direction, but again, it’s still inaccurate, right?

But it would be my way.

[Tobias] Can you take us through one of your names just so we can get an idea of how you think about one of these stocks?

[Mark] Sure. So I’ll mention one today that I really wasn’t intending to talk about, but they got taken out today. So they’ve got an agreement.

We’ll see. It may not be all done, but Senior PLC is a UK-based supplier of components and equipment for commercial aircraft, for military applications, for both fighter planes and transport planes. They may make products that are used for heavy-duty trucking.

They make products that are used for a Caterpillar tractor or John Deere bulldozer or like a John Deere tractor. What they do at the end of the day is their expertise is managing thermal management and fluid conveyance. So deal with heat flow and cooling in engines, in a cabin, et cetera.

They also make specific products for components for engine mounts and things like that, right? But that’s their bread and butter. That’s their expertise.

That’s their competitive advantage. It’s a company that I followed for over 20 years. We’ve owned it since inception of our firm.

We launched with Outside Capital about five and a half years ago. We’ve owned it since inception. It’s the second go-around I’ve seen a takeover bid in the last five years or so.

We definitely see a lot of that. We’ve seen a lot of acquisitions in our space, and that’s part of our thesis on small versus large. And part of it’s strategic buyers, part of it’s financial and private equity.

But the bottom line is they’ve got products that without which any commercial aircraft, Airbus or Boeing would not fly. We wouldn’t have our F-35 fighters. You wouldn’t have a C-130 transport plane, which is aircraft that airborne uses to jump out of, and they’ll transport all sorts of equipment.

Other aircraft, again, heavy duty trucks, so class eight trucks, I think, like trucks that are on the highway, class eight, 18 wheelers, those trucks, and again, products like a John Deere tractor or a Caterpillar bulldozer. So their speciality is manufacturing. They do it very well.

I mentioned before, I think that one reason we like industrials, they have a pretty long runway. We think seniors had one of the longest runways for quite some time. I mean, it suffered on the back of COVID before we launched the firm.

And so we had a good chance to buy initial position at very attractive prices when people were really worried about where we were going to fly again. And much like we talk about looking at history, look at the past. I remember post 9-11, everybody thought we weren’t going to ever travel again, and everybody was going to stay home.

And I’ve got millions of frequent flyer miles to say that I don’t believe that’s the case. I think humans are social animals. They’ll still continue to travel.

Yes, commercial air traffic suffers at times when there’s uncertainty like now, but we’re transporting more cargo and people are more global than ever. So that’s typical of a business that we have liked. I mean, it’s roughly speaking about a billion to a billion and a half market cap, US dollars, small amount of net debt, been run by a great management team we’ve known for a long time.

But one advantage that we’ve had is we’ve been to visit this company many times. We’ve been to many facilities that they have. And part of the way we do research is we go visit facilities.

And it’s interesting that people don’t. I mean, we’ve been to a couple of facilities this company has where they have 30 something facilities globally, but like some of their biggest facilities are based in the United States. Not that hard to get to.

And a few years ago, I go visit one of them and they’re like, nobody’s ever been here. And we go to another one or another analyst goes to visit one. We’ve had two people visit this facility in the last year.

So much like there’s fewer analysts on the sell side covering stocks, we think there’s a lot of people on the buy side are not going to visit facilities. And it’s something we’d like to do after we’ve done a lot of research.

[Jake] I thought you just asked AI on your, is this a good company?

[Mark] We use AI, but we use AI for purely time-saving things, but definitely not decision-making things. And now we’re, we still believe that, you know, we believe a lot in the numbers we’re looking at, but once we do enough work, we want to go visit facilities and we want to visit, not just the senior management. And again, we’ve other companies we’ve owned for quite a long time.

We had another company in the portfolio that was taken out a couple of years ago. Again, that I first visited over 20 years ago. And so we’ve got a long history with all these companies.

We’ve owned them here at MacAlpha. We owned them at a prior firm or maybe two or three firms ago, 15, 20 years ago, I’ve owned the company or followed them. So we’ve got a long history with a lot of companies.

And we think that is, it creates a different relationship because again, we’re not focused on the quarter or the next six months necessarily. Most of our focus is much longer, right? We care what’s happening short-term, but only as an indication of what’s the long-term competitive advantage look like.

And this was a company that, you know, they were investing through COVID in early 2021, 2022. And so they’re putting up the capital today and everybody’s like, well, the cashflow is going away and there’s no free cashflow, et cetera. But you could see they had contracts and they were going to deliver and they were executing, they were getting more business, not less business.

So, you know, it’s a time when we looked at investing when the investments were being made. But again, we had an issue, I think it was 2022, summer of 2022, I believe. I have to look at the chart, but we, there was a takeover bid for the company.

So it went, you know, it spiked on the takeover bid. They said no. Around the time it spiked, we tried to, you know, reduce the position size.

We thought the upside was not substantial at that point in time. We took it down. They said no.

The buyer walked away, private equity firm walked away. Stock drops like 30 or 40%. Gives us a chance to re-add a position.

And then, you know, a few years later, it’s being sold probably for about, you know, twice that price. So anyway.

[Tobias] Tell us a little bit about, just without naming names, but just your process for shorting, what you’re looking for, how you manage it.

[Mark] Sure. So our process for shorting, our short process is mostly all quantitative and it’s the nature of kind of how, but we use a lot of the same kind of tools we think about on the long side, right? We use a lot of quantitative tools to narrow down the universe, right?

So kind of using, kind of paraphrasing Charlie or Warren, we’re trying to find a well stock pond to fish in, right? And it’s not, you know, how do you search for names where you’ve got a universe of 20,000 stocks to look for and a handful of analysts? Oh, you know, that’s the search process is something that Bruce focused on at Columbia teaching and we taught our students at Columbia, but we’ve got to figure out a way to narrow down the universe.

When I was a sector specialist, I felt like I knew all the companies in the sector, right? I didn’t have to worry about, like a screen was not really an option or it wasn’t really, you didn’t think it was adding much value, but where we’re looking at the entire universe, we’re first trying to filter out things that are not likely to end up in the portfolio. So things that we do not want to own, we’re going to try to get rid of as quickly as possible.

Things that because the characteristics of the business, they’ve never earned their cost of capital, they’re highly levered, they’re pre-production mining, pre kind of pre, you know, phase three or pre-production biotech companies, things like that, we’re not likely to own. So we try to eliminate those as quickly as possible. So then we narrow, we use all time, some of them use epicyclic, depend on the environment we’re in that we think work better at certain points in time.

And on the short side, we’re looking for, you know, on the long side, we want competitive advantage. On the short side, we want absence of competitive advantage, no evidence they’ve earned their cost of capital, no evidence they’ve really generated any free cash flow, a very high valuation, that’s helpful, right? But then we want to see starting to see cracks in the business.

So we’re looking for fundamentals in the business that are starting to deteriorate. Because we think that those companies, if companies eventually end up going to zero or going down a lot, it just happens to be that that’s where the, you know, the area of small cap is where the greatest opportunity is today. In our long short strategy, we could go up in cap, but we’re going where we see the best opportunity.

But if companies eventually go to zero, they’ve kind of got to go through 5 billion, 2 billion, a billion, 500 million on their way to zero, right? So we have a very, you know, an approach that leading to what we think has worked over a long period of time, it’s worked throughout my career, going back over 20 years at previous firms, we think it will continue to work, we just think that the current environment is very attractive and likely to be more fruitful than it’s been historically. But again, we’re looking for companies that don’t have competitive advantage, high valuation and cracks in the business.

[Tobias] You’re not looking for sort of matching short for a long, you’re just looking for purely alpha shorts?

[Mark] No, we don’t. We’re really trying to make money in the shorts. I mean, a lot of people talk about alpha on the shorts.

If the market goes up 15% and we lose 10, I don’t think we’ll be that happy with our shorts. We think that this approach historically has made absolute dollars over time. Obviously, the current environment is better than it was 25 years ago or so ago, when you used to pay a short stock rebate, as opposed to earning, you used to have to pay to borrow.

Most of our companies and our portfolio as a whole actually pays us at this point in time, because we’re not we try to avoid most of the super concentrated stuff that, again, everybody else is involved with. So rarely do we ever pay to borrow the shortest stock. So but we do believe that in a normal environment, we can earn a positive return.

And therefore, you know, if the market goes up single digits over time, in a normal environment, hopefully we would earn the stocks would go down at some single to double digit rate. So the alpha should be pretty strong. But the absolute return is what we’re really focussing on.

And the nature of our longs and shorts is so different. It leads to a portfolio construction that’s very different than most long short hedge funds, we tend to manage with a much lower gross leverage than about everybody I’m aware of that does fundamental long short, but a higher net. And the reason is, we’ve kind of come to that higher net over time, because it doesn’t make a lot of intuitive sense to have a higher net.

But it actually reduces the risk in our portfolio. If we have a higher net, if we if we shorted more and took the dollar net closer to zero, we would effectively be massively short. And I think, you know, we’ve been short the bubble in the US for a bit now, it would be very difficult, like some periods of time, like last year, when I think from call it mid April around the lows to the end of the year, or maybe late, maybe six months or so afterwards, somewhere between October the end of the year, like the Goldman Sachs and profitable tech index was up like 100 and something percent, right? Pretty bad environment, if you’re short those types of companies, what we look at, you know, quality, definitely kind of high ROE stocks underperform massively low ROE stocks, again, adjusted for leverage in this small cap universe, right? high volatile stocks, high beta stocks, outperform massively, all those signs are, from our perspective, are of very high speculation.

And the degree of outperformance through the last half or the last two thirds of last year was significantly greater than it’s been at any point in the last 25 years. And so that, again, is indication to us that, you know, there’s a lot of speculation, I mean, you know, the argument about quality, and we can define quality however you want, but most people all else equal would prefer high quality versus low quality, you don’t want to buy a low quality business, if you can buy a high quality business with the exact same characteristics, you know, at the same valuation, right?

I don’t think people, you know, it’s like, why would you be searching for that, you know, the the low quality, you wouldn’t want that. But today, a lot of the quality stocks, and we’ve seen it throughout last year, where a lot of quality, depending on how it’s defined, but a lot of quality underperformed, which, again, tells us there’s a lot of speculation in the market. We have seen the reversal on the shorts in the first quarter this year, where they’ve gone down on average substantially.

So maybe it’s turning, I don’t know, I haven’t really seen, I haven’t seen the quality working so much yet. And definitely, you know, we’ve seen it, we saw a lot, I guess, in, in March of more of the AI threat has damaged a lot of software businesses that people think are under a severe threat from AI. And while we recognise that that’s probably the case for a lot of them, especially if they started at 30 times earnings or something like that, there’s a lot of stocks that are already down 70 or 80% that have seen Google try to enter their space or seen Amazon try to enter and fail to enter their space and no evidence that the business is suffering from AI or threats from other competitors, yet the stock still goes down substantially. So we’ve seen some of that recently. And, you know, if, if we do, if our analysis is good, maybe we’ll be corrected.

And we’ll be, we’ll be right that in some cases, maybe it’s overdone. And if we’re wrong, we’ll be wrong and lose money.

[Tobias] I tracked two data series that I think are kind of interesting. One is the high beta versus low volatility, because there’s the, there’s a paper that shows that low volatility and some industry research that came out to like 2015 or something that shows that basically low volatility pretty reliably outperforms high beta, but that’s not been true since the 2009 low. And it’s been particularly not true over the last five years.

There’s been massive high beta outperformance and it’s still close to all time highs. Although it has sold off a little bit since November last year. And the other one that I track is just the S&P 600 versus the Russell 2000, because the 600 has the profitability filter and the 2000 doesn’t.

It’s a slightly different universe, but there is some overlap there. And you can see there’s these two marked peaks on that chart. Like basically the 600 consistently outperforms the 2000, except for the run-up to 2020.

And then it sold off very violently after that. And then the run-up to 2025, and it’s sold off pretty violently since then. I think it’s still selling off.

So I do think that that’s sort of in process, but I agree that it’s got a long way to go. It hasn’t really started yet.

[Mark] Yeah. And I wonder, you think about kind of how the markets have changed over our careers and clearly the prevalence of passive and momentum is something that, I think momentum is a much bigger component today and it’s passive flows, et cetera. So as a value investor, you think, okay, you think a stock’s worth a hundred, maybe you want a 30% margin of safety.

It gets to 70. If you’d read old literature from Seth Klarman or Buffett, they’d be like, buy your position at 70. And I guess what we would have done 20 years ago, whereas now you’re like, okay, I’ll buy a little bit 70.

I’ll probably buy a little bit 65, buy a little bit 60, buy a little bit 50. So I think what it’s caused people to do is be a little bit more, from my perspective, I know one thing we’ve changed is a little bit more cautious about how fast you buy or exit a position, especially a quality business. Because then they can tend to go much further than you think if you have the positive momentum behind it.

[Tobias] It’s just been amazing to have so much negative momentum for such an extended period of time. All of my metrics are just placed at the absolute bottom of negative momentum and just can’t get up off that.

[Mark] And we find it very upsetting because we’ve, as I said, we’ve suffered, we’ve had, I think 20, today we’ll make, if this is completed, it’d be 21 deals that’ll be completed in the last five years of takeouts. And that’s like a quarter of our portfolio, roughly speaking. And the problem in my mind, I call it already a take under, because if you have a stock that goes from a hundred to 20, and then they bid 35 or, oh, we give you a big premium.

No, you bought it at a 65% discount to where it was a few years ago. Now, again, I recognise the business can change, but if we believe the fundamentals are somewhat the same as they were or better, maybe eventually we’ll get back to that point. So we think that there, in many cases, it’s enabling strategic buyers or financial buyers to steal some of these businesses at short-term premiums.

And we’ve seen some big premiums, seen some big premiums in Japan recently. There’s been a couple of hundred percent premiums. There’s definitely, I mean, we see 50, this deal day, over 50% where it was two months ago, three months ago.

But that’s a little bit of a concern for us as investors. And we have pushed back against one deal, but unfortunately that didn’t, we weren’t able to do much there at the time. We weren’t big enough to do a whole lot, but- I mean, congrats to the buyers if you can get it done.

[Tobias] Sorry, JT.

[Jake] Well, I was just saying, you get this feeling of like, gosh, I have to buy more of this to lower my cost basis to mitigate some of that take-under risk.

[Mark] Yeah. People say, because I remember the first one we had, somebody, this was actually a previous firm, but one of the first takeovers, somebody said, congratulations, XYZ got taken out at a 30% premium. I said, actually, I mean, yes, today from a market-to-market basis, it’s good for the portfolio, but actually for our investors over the long-term, I’m not happy because I don’t think it was a full value.

And if it had been a half a book value, then I’d been happy to exit. But this business, we still thought was going to grow value over time. So I thought, yeah, we get a small premium today, but I think our investors actually do worse over time.

So I’m definitely in favour of companies kind of doing the right thing to make it harder from that perspective to have the companies taken out too cheaply. If it’s fully valued, happy to sell it. But we fear that after a long period of time where some of these stocks have suffered, but the problem is a lot of funds have marked their fund-to-market at the end of the year or last quarter, and they’re like, oh, it was at 100, now it’s at 150.

Thank you very much. But we think long-term, it’s worth a lot more. We don’t want that to happen.

[Tobias] Hey, Mark, we’re coming up on time. If folks want to get in contact with you or follow along with what you’re doing, what’s the best way of doing that?

[Mark] I guess it would be our website or email me. Should I get my email address?

[Tobias] If you’d like to.

[Mark] Sure. So mcooper, M for Mark, C-O-O-P-E-R at macalphacapital.com.

[Tobias] Perfect. So thank you. Well, thanks very much for spending time with us today.

It’s a fascinating conversation. I like talking to someone who agrees with everything that I say.

[Mark] We’ll have to find something to disagree about next time.

[Tobias] Yeah, we will. Next time.

[Mark] We just haven’t gotten to it yet, right? That’s right.

[Tobias] Yeah, small value. But JT, any final words?

[Jake] No, thanks for coming on, Mark. Much appreciated.

[Mark] Thanks, guys.

[Jake] Appreciate it.

[Mark] Thanks, JT. Thanks, guys.

VALUE: After Hours (S08 E13): Mark Cooper on global small cap value, AI and managing small cap long/short at MAC Alpha

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