(Ep.103) The Acquirers Podcast: Drew Dickson – Alpha Europe: Finding Alpha Through Behavioral Investing In Europe

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In this episode of The Acquirers Podcast Tobias chats with Drew Dickson of Albert Bridge. During the interview Drew provided some great insights into:

  • Hunting Alpha In Europe
  • The DCF is the Randy Watson of Valuation
  • Voting Machine Or Weighing Machine
  • How To Build A Debiasing Strategy
  • Narrative Driven Markets
  • The Math On Tesla Just Doesn’t Add Up
  • Modelling For A Global Pandemic
  • Fama vs Thaler
  • Asness Early On Momentum
  • Compensation For Risk
  • The Underreaction Thing That Drives Momentum
  • Short Sellers Are A Paragon Of Virtue
  • What’s A Gamma Squeeze!?
  • Behavioral Dynamics That Drive Value Or Growth
  • Alpha Can’t Be Extracted From A Diversified Portfolio
  • Finding Opportunities Through An Avalanche Of Information
  • Building Shadow Models
  • 35% – 50% Of The AUM In The Top Five Positions
  • Getting Impact On Your Winners
  • When The Unsinkable Berkshire Was Down Lower Than The Market

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Full Transcript

Tobias: Hi, I’m Tobias Carlisle. This is The Acquirer’s Podcast. My special guest today is Drew Dickson of Albert Bridge. We’re going to be talking about his Alpha Europe strategy studying at the Chicago Graduate School of Business under some of the biggest names in behavioral and efficient markets theory right after this.

Tobias: First job out of college was commodities?

Drew: Yeah, I was basically working with a group in Atlanta, Georgia. We did risk management work for folks that had exposure to commodity prices. The bulk of the business was for grain elevators in the Midwest, these were farmers and grain elevators, or mostly elevators that had exposure to corn beans, or wheat prices that they posted for farmers, so they’re longer or shorter, depending on which side they’re on.

We help them analyze the price which they had, but my boss at the time wanted to do the same thing in the energy markets, the oil markets. That’s when I came down there, didn’t know anything, but started working with him to basically help oil companies and jobbers and wholesalers and retailers to take a look at their balance sheet and see where they might be impacted by price volatility. The classic one could be a refiner who’s buying food and selling products. then he’s got this crack spread risk.

It was pretty natural. It’s pretty early days for the NYMEX back then, this is the early 90s. A lot of learning myself, obviously, but a lot of education for some relatively sophisticated companies who hadn’t really used– did a lot of OTC stuff, but not a lot in the futures market. It was all the basis trading principles you have in in the traditional commodities. You had oil in that, gas, [unintelligible [00:02:12] and then natural gas subsequently came on.

I spent six years doing that with him, but always had this passion, obviously, for financial markets, but for stocks, and for stock picking, and going back to my time at Purdue. I was there during the whole– ‘87 happened right in the middle of my experience. I started investment clubs with my buddies, and I was writing investor newsletters and always been really just interested in the way financial markets work, particularly equity markets.

At the Purdue printer library, there was an old copy of security analysis, and originally I should have lifted it but I did not, I checked that out and everything that I can get my hands on. I was always had a passion for that. After doing the commodity trading off the floor, I really wanted to get back into more– take my career in the equity side markets again.

Fama vs Thaler

I spent a bit of time out in Korea before going to business school. For me, that was where the– I was really starting to put things together in terms of how I wanted to think. I’m still learning but was just very intrigued by this whole– Well, at the time, this emerging conflict between efficient markets and behavioral finance and I was reading everything I could about the psychology of markets, and at the same time really had an appreciation for the rigor of what the efficient market guys were doing.

For me, the only choice to try to get into business school was at the University of Chicago where Gene Fama was there and Merton Miller was still alive. There was this upstart, slightly younger economist that was up in Cornell, who had been poking holes in efficient market theory. Well, there’s Bob Shiller, but this is Richard Thaler. Fama famously was really intrigued by these guys attacking these notions of what drives the value premium, what drives returns and how rational are markets.

Gene said to Merton Miller, who is the kind of the school, “I think we need to get that Thaler guy down here and make him part of the faculty.” Mert says, “Well, Gene, I’ll let the next generation make their own mistakes.”

[laughter]

Drew: With that, Fama made sure that Dick came down and from– that was in 95-96, maybe it was 94, before I got there, but it’s just been fascinating, and it was fascinating watching the two of them, complete opposite sides of the spectrum.

Good friends, tennis buddies, golf buddies, they play at Beverly together. But they just go at it over these notions of what drives share prices, and can you beat markets or can you not. There was actually a lot more agreement there than people realize. There’s also a lot of disagreement, but I wanted to try to get into it and be a part of that, and learn what I could. That was–

Tobias: It’s very open-minded of Fama to have invited probably his greatest critic to come and work with him and to learn from him.

Asness Early On Momentum

Drew: Well, he was that way. Cliff Asness will tell you that when he was a PhD student, again before my time, he wrote one of the early papers on momentum. This was long before Mark Carhart added it. There’s a fourth factor to the models, and I can’t remember if it was– I’m spacing out if it was LSV, or who it was, about the initial momentum paper.

Asness had written the same PhD paper, just saying, “Hey, look, I’m seeing this weird stuff where stocks have gone up over the last 12 months, keep going up. Then, stocks that went down over the last 12 keep going down.” Did the proper work on it and proposed it to Gene. Gene said, “Well, if it’s in the data, write the paper.” He’s open to criticism, and that’s the one anomaly that he really struggles with. Even today, he’s just like, “Uh, I don’t know what’s this compensation for.”

Maybe he can come up with a story for value, maybe we can have debates about, is it the behavioral or the risk of explanation, but that momentum one, it’s a tough one to come up with from an efficient market perspective as it needs some compensation for. Maybe it’s a discontinuous jump risk that you might get one day and so you need to be paid for that in the meantime, but I think it’s a lame post hoc look back reason why factors should work. It needs to be a state variable in the spirit of Bob Merton, sort of this ICAPM stuff.

Compensation For Risk

If you want to have an efficient market store for why value works? Well, it has to be compensation for risk you’re taking, or for that matter of small caps or market exposures, but in the behavior explanation is, “Hey, this has nothing to do with the compensation for risk. This is due to glamour versus value anchoring and excited this and hurting and all these behavioral factors that impact the way people make decisions.” I ended up a little bit more philosophically aligned with Thaler. But I’ve got to say I’m still learning today about finance because of Fama. He just teaches you how to think. It was a great experience.

Tobias: How do you go from– so the old GSB, now it’s called Booth, probably the best quant school in the States, maybe in the world. You’ve got some of the biggest names on the efficient market side, also on the behavioral side. How do you get from there? You’re not a quant in your approach, are you?

The Underreaction Thing That Drives Momentum

Drew: No, I’m not. I’m intrigued by the notions of it all. But at the heart of it, I’m more interested in idiosyncratic firm-specific side of what it is stock pickers do. Now, I do think that it’s a little bit more difficult at a specific company level, but it’s I think it’s still practicable. Some of these things, same reasons to help explain why there are opportunities, these behavioral overreactions, these underreaction.

The underreaction thing that drives momentum, effectively what it is in my mind, it’s people underreacting to changes in the business model. As more people cottoned on as the narrative changes, this is one of the things that helps to explain why momentum works over the long run. People don’t like to process information, which is different than their existing view, the confirmation bias thing.

I think you can apply that at the company level as well. It’s more difficult, a lot of other things are introduced when you do that. For me, if we can do that deep dive, fundamental research, trying to understand what a business model looks like, who’s running it, what their policies are for managing their capital, and then try to develop a view of–

The DCF is the Randy Watson of Valuation

Drew: Not only is our view different from what the market thinks, in terms of what the business might look like, in two or three years, but why.

That’s the big one, because you can always say, “Oh, I’m building a model. Look, I’m 20% ahead of the street.” Anyone could do that. If you already have a preexisting notion you like this company, you will come up with whatever you want. The more complicated the model you’re using, the easier it is to get to the number you want.

In one of my blog posts, I wrote about the DCF thing, the Randy Watson of valuation. Randy Watson, he was the singer in Coming to America 1, which Eddie Murphy said was good and terrible. That’s what to me the DCF is. It’s perfect. It is the perfect tool for a completely unbiased mind.

But if you introduce any notions of bias into your analysis, any predilections, any disdain or belief in the management team, you can make that model sing baby, and you can spit out whatever number you want. I try to use proxies for the DCF, it might be a little less biased, and you can have a debate about what they might be. In some cases, I think it’s different for different companies.

Some companies, they’re going to be much more driven, depending on the balance sheet by EV metrics, some will be driven by some of the [unintelligible [00:11:05] value. Basically, what do we think the market will think? That’s a bit of a Keynesian beauty contest analysis, but what do we think the market will think about this company in two years?

How different is that than what the market thinks now? If we can spot hurting confirmation bias, anchoring something which is explaining why they’re not reacting to how positive things are, or overreacting in the short term about how negative things are. As we work through the pandemic, a lot of what we were doing was more of that. I’m getting ahead of myself in the whole career thing.

A lot of what we’re doing is okay. This stock should be down 20%, this thing is heavily levered, it’s going to see a trough, they’re going to have to refinance debt because the markets are closed, and that should put some pressure on things, so it should be down 20. Not 70, but 20. We found ourselves selling things that were only down 20 to buy things down 70 kind of behavior. Anyway, that’s getting ahead of things. Back to Chicago. That was a great foundation for me. I stayed pretty close and still have with Dick over the years and continue to learn from him. My whole goal is to try to merge the behavior with the fundamentals when you’re thinking about stock picking.

Tobias: When did you get to Och-Ziff?

Drew: I started off with Fidelity right after business school. I spent a summer in Hong Kong with them, and then full time in London and moved there ‘99. Then three years later, I joined Och-Ziff. That was my introduction to the long short. At the time– they’ve gone through their surge in the fall and perhaps recovery now, but at the time, it was much more of an RV shop, much more merger arbitrage place that was getting– it was becoming more of a multi-strategy firm at the time. I came in to do more traditional equity stock picking. Whereas most of the desk was more focused on some of the M&A stuff. Great experience.

Any Stock Can Be A Buy And A Sell

Drew: At Fidelity, you’re driving the supertanker. You’re massive, and you own 10% of a company, and if you want to change your mind about it, it’s hard to, and if it’s hard to change your mind, I think that’s a little bit poisonous. That can be something that prevents you from doing the right work. That helped to shape me that this notion of– and I think it also helped having been a commodity trader beforehand, and selling first and buying second, that was something I had to unlearn, that was just natural to me.

Whichever way you were doing, it didn’t matter. To me any stock– and even Ben Graham said this, in Security Analysis, maybe it was Intelligent Investor. Any stock price can be dear at one range and cheaper in another. Which is interesting to see the environment we’re in now where people just think that you buy good stocks, they go up forever. This whole quality compounding discussion we’ve been having for three or four years, it’s accelerated in the last 12 months.

I really do believe that any stock can be a buy, any stock can be a sell. There is a difference between price and value. That’s the job of– if I’m good at that or any of my peers are good at that, that can be a great thing for a portfolio. If we’re not or if I’m not, that money should be in an index fund, and if you want your factor exposures to– if you don’t want any factor exposures, fine. If you do want to have exposures to value, quality, and momentum or in the last year, not value, anti-momentum, or sorry, not value, and for some period, it’s not momentum, but that’s your decision.

Behavioral Dynamics That Drive Value Or Growth

Drew: This residual in the regression equation, this alpha that we’re all trying to capture, that is the goal. To the extent that the world has evolved to be able to provide some of these– Prince, the Artist Formerly Known As Prince. You’ve got this this thing that the formerly known as alpha thing which we can get now, you can get into value factor fund. You can it with Cliff’s products at AQR, a host of these guys that do great work. Is there anything left after that?

Is there anything left? Is there idiosyncratic risk in the economic sense? Is there firm-specific risk that you can take advantage of? Obviously, I’m biased, I do this for a living, so I think the answer is yes. I will say that to do so, there are limited and rare opportunities where there is that obvious mismatch. I don’t think you can capture a whole lot of alpha in a big diversified portfolio. You can capture factor risks, and if you want to call that factor betas, instead of alpha, the artist formerly known as, that’s fine, it’s probably what they are.

I do think that a lot of factors that people look at going beyond the value, going beyond momentum, going beyond size, which is a debatable one itself. A lot of times people will call something a factor in hindsight, this is after the fact. Well, and this all worked at the same time, that’s a factor. Maybe I’m just a bit too grounded in the whole theoretical notion of what factor risk is supposed to be, but it’s supposed to be compensations for risk.

They’re supposed to be offering you something that is a state variable, hedging concern. You can hedge it out if you want to. The fact that betting against beta, it works. “What’s that? What’s the theoretical one for that? What’s the behavioral one for that?” I don’t have an explanation for it. But I’m pretty comfortable– not during all regimes, but I’m pretty comfortable believing that it’s actually behavioral dynamics that drive momentums, behavioral dynamics that drive value or growth. Less so behavioral on the size stuff, that could be a liquidity risk thing.

Alpha Can’t Be Extracted From A Diversified Portfolio

Back to your question, no, I want to be fully aware of what those factor exposures I’m taking and also philosophically focused on what remains as what we can try to capture. To do so though, it must be in a concentrate– in my view, it must be a very concentrated portfolio, which brings risks. This thing will naturally have periods of deep downdrafts. But overtime, if there is alpha to extract, it can’t be done from a diversified portfolio mathematically.

Finding Opportunities Through An Avalanche Of Information

Tobias: Let’s talk a little bit about Albert Bridge. How do you characterize the philosophy there? Then how is that expressed in the strategy or strategies?

Drew: Yeah. Well, basically, it’s a process that– we try to be bottom-up, we try to be firm specific. We try purposely not to take a top-down view about anything. Even within factors, and I’ll tweet out a lot of things or some things, “Hey, look, how much growth outperformed value hasn’t happened like this since ‘98-99,” blah, blah, blah.

Broadly, we’re going to have a value bias, but it’s not what you might have told me this super deep value bias that really dive in and buy the stuff that there’s a big margin of safety. For us, it’s almost this two- to three-year window.

What can we own today where the business that’s either not deteriorating as much as people think, or it’s improving more than people think, or maybe it’s even turning that the market doesn’t want to see yet, that the market will have a completely different view about in a few years’ time?

That’s one aspect of it. You’ve got to break that down into the fundamental part and the behavioral part. This is just following from the way we did things at Fidelity. You just do a deep dive. You speak to the management, the CEO or the CFO. You do plant tours and visits. You learn about the sector and all that, everything you need to know.

Then, you realize that you’re one of a gazillion people doing the same thing. Sometimes, you’ll see folks that think they have the inside edge, because they just met with management. I think that’s naïve. I think you’ve got to realize that you’re one of many sell-side and buy-side analysts doing the same thing. I think the real value added for us and for anyone who’s picking stocks is to see what you can pick out of that avalanche of information and see if any of it actually matters to the investment thesis.

With that, we’ll try to do a pretty rigorous modeling of those key factors, whatever they are, could be certain products, could be spinoffs of businesses, it could be lines within a software company or maintenance line, what’s happening? Is that accelerating or deteriorating? What sort of licenses are translating to that? What it means if it spills down?

Whatever we think the market will think is the thing that drives value, that’s what we try to focus on. If we have to be a little bit ahead of the market in that where we think they’ll go, we can then marry that deep fundamental dive to this whatever behavioral bias we think’s being committed. Is it a representative bias? Is it an availability bias? Is it something that is preventing people from seeing that this business might look very different to everybody in two or three years? Those things are exciting. They’re wobbly, they’re volatile, but they’re exciting.

The goal for the Alpha Europe process is to focus on sectors which are less macro exposed. You’re still going to have macro exposures everywhere, industrials, even technology. Broadly, they’re a little more secular, a little more stern firm-specific than, say, utilities or real estate or different consumer defensives. These things that are ebb and flow more with this market appetite for that kind of stock.

How To Build A Debiasing Strategy

Drew: Whereas you can find winners and losers within the healthcare equipment space or within media or technology or industrials pretty easily. Easily, you can identify them, it’s going to be dispersion of returns and that gives you the chance to do stock picking.

We focus on those groups and try to gel it up to a portfolio or actually to a focus list for things that look really interesting and dynamic. Then, we start this debiasing process. Okay, what can we do to make sure we’re not being affected ourselves? We’re not immune, just because we know about behavioral finance, studied under Richard Thaler.

Danny Kahneman will say himself, “I came up with all these things, I still commit the same errors.” Just because you know about them, doesn’t mean you can prevent them. What can we do ourselves to insulate our emotions and recognize at least that we’re biased people, biased analysts, biased [unintelligible [00:23:13]? Well, we can write short cases on everything we want to buy, not just the one paragraph, “these are the rest of the long case but the deep dive short case and how are you going to make money on this thing on the short side.”

Building Shadow Models

Then, I should say that backing things up when we launched Alpha Europe back in 2008, our main product was a long short fund. Then we were bought by Perella Weinberg in 2012. It pretty quickly launched a long only fund alongside it, and then as we spun off Perella’s platform to launch Albert Bridge back in 2016, it was a long only fund that we lead with, and but still bringing those long, short principles I think helps. If we can come in there and build– we call them shadow models or black sky models.

“Okay, here’s a business that we think’s got great ROICs, and they’re going to beat numbers and no one’s paying attention because this, this, and this.” “Okay, now flip yourself around and represent the defense, and tell me why this thing’s a dog and why it’s going to go lower and what’s going to happen.” It’s a great debiasing exercise, and then each of those that work for both long and the short work on each of these names become our constraints.

Okay, well, if we’re right about company X, Y, Z, or X, Y, Zed as you might say in Australia, or we would say in England. We can then say, okay, if we’re broadly right about what the stock will be worth, if we’re right, and if we’re broadly right about what the stock will be worth if we’re wrong, then we can start to develop this notion of risk and reward.

We can start to develop this notion of expected returns, and then we could ask ourselves, “Okay, well, how long is this going to take for the market to wake up to this thesis? Is it going to take a year? Is it going to take two years? How volatile is this thing naturally? We should penalize it, if it’s naturally more volatile.”

We could put all these things into a mix. Then, effectively, using a bit of Kelly criterion math come up with the right size we think these positions should be. Obviously, that’s going to be somewhat dependent on the expected returns of the other things that we’ve found that have gelled up. Then the goal for us is to basically get a 15-, 20-stock portfolio.

35% – 50% Of The AUM In The Top Five Positions

Then within that portfolio– and this is in a long-only portfolio. Within that portfolio, despite in nature of those expected returns, typically get 35% to 50% of the AUM in the top five positions. Their duration in the portfolio will be a function of not only how the fundamentals do develop over the next few years, but also just their own volatility that stocks could– they can go up to Goldman Sachs upgrades the stock and it rallies 12% over three days.

Well, we lost a bit of the expected return, that we might even trim some of that. Wait for it find its equilibrium later and add back to it. This stock selection, the managing the positions, and then the sizing of them, all of those things are factors that help contribute to this alpha proposal.

Basically, since 2010– it’s a tough time to be a value investor. You’ve been talking about this every podcast. We’ve been really proud of being able to outperform the markets, despite us not owning any Tesla or anything remotely close to it. That would have been impossible if I had a 75-stock book, it really needs to be concentrated, it needs to be high conviction, deep-dive stuff, especially because you want to be able to hold on to it when everything does hit the fan. You also wouldn’t be able to say, “Hey, I screwed this up.” We have a culture where you can mess things up.

That’s another key device– I’m jumping all over the place here. You want your analysts, you want yourself, not to the R-WSB point of posting your losses and saying how great they are, but certainly to the point of being able to say, “No, I messed this one up.”

Getting Impact On Your Winners

Drew; This is a big thing, I use a lot of baseball analogies in the UK, and you’ve been in the US long enough, you’ll get them, but they’re lost a bit when we talk to our British investors. It’s not just a batting average game. It’s a slugging percentage game. We’re going to have all these ways to try to get that batting average up so you get more stocks right, and then you get wrong.

Within those ones that you get right, you have this notion of impact. For us, for things that where there’s either make money or lose money relatively or absolutely, it’s a mid-50s hit rate, batting average if you will. But if you look at the things that had more than 100 basis points impact, or more than 200 basis points impact, or more than 300 basis points of impact over the last however many years, that batting average becomes a slugging percentage, and it gets up into the 60s and the 70s, which is what we want, what we want to see.

Have A Process To Make It Ok To Make Mistakes

We throw all that stuff in the mix in terms of how we size the positions, and have this culture where, because we’ve written that short note, we’re looking for the bad stuff. If we see the bad stuff, you just hold your hand up and say, “Hey, this is one of those 4 out of 10 that were going to screw up.” It’s one of those things that offsets that whole Kahneman & Tversky loss aversion thing. If it’s okay to have a loss, it’s no fun, especially if you’ve been public about it, if your investors know it’s a big idea, and you think you’re smart because you picked the right stock, you don’t want to find information, which makes you look stupid. But that’s what we should do. Have that process and make it okay to make those mistakes.

Hunting Alpha In Europe

Tobias: What’s your universe, in terms– so it’s Europe, but it’s anywhere in Europe, and then do you care about your geographic concentration or diversification or that’s just an irrelevant consideration?

Drew: Well, it may not be irrelevant, but I don’t care. We’re basically a Western European focused product. It depends on what ideas make their way through the process and through our universe into this focus list. We typically have a lot of exposure in the UK or Germany or France, sometimes Sweden, Norway, Finland, Spain, very little in Portugal or Austria, bit in Holland, bit in Italy, just depends on the ideas and the nature of them. But no, we’re not– arguably, it’s become less important after we all moved to the Euro in terms of FX risk, but from a geographic perspective, we monitor but we don’t have any constraints on it.

If it turns out that we have half the portfolio in one country, as long as we think we’re doing things that are idiosyncratic, and they’re not that related to each other, we’re totally fine with it. Similarly, I say the same thing about our sector exposures. We’ve got a lot of consumer stuff. We have a lot of industrial stuff. Very little in tech in Europe. We haven’t found things we thought they were– we had a few IT services exposures over the years where we thought people are missing out on things.

Tobias: What’s the limiting there? You just don’t think that they’re cheap enough. They’re just not underfollowed enough.

Drew: Well, there are some that are, but you don’t have these global dominating businesses in tech, like we have in the US. We had one, this is not a value stock at all, but we held it because this is a great example actually, Toby. It was Arm Holdings was the company– Basically, they’re the inside all these phones. The Arm architecture, it’s a globally dominated business. SoftBank bought it a few years ago. We lost one of our potential world dominating tech companies. Of course, we have SAP and the big IT services companies like Capgemini, Aptose and things.

We’ve had different positions in a lot of these things over the years. I should mention too, sometimes we’ve had names in the portfolio for six months. Usually, when we get six months into it, no, we screwed that up, that’s wrong. Sometimes, it’s because the thesis changed, and sometimes there can be something in the portfolio for years. But even then, it’s not a static size, it can be a 5% position and that can grow to 8% and fall to 4%.

This all very much driven by what is expected returns. Here’s what we’re worth if it goes up. Here’s what it’s worth, it’s if it goes down. Where’s this stock and how does that compare to other things in the portfolio? As the expected returns fall for certain things, we will shift that capital into other things that have higher expected returns. That drives a bit of turnover, which has a bad name. I think it can actually be a positive thing in a concentrated book if you’re doing it from without bias. Obviously, easier said than done, that’s part of the process for us, too.

Tobias: How are you hunting for what you’re looking for? How are you tracking them down, then, how are you going–? What’s the process for validating and making sure they fit for the portfolio?

Drew: We start with a defined universe of billion-dollar market cap companies in the sectors we focus on and the analysts, including myself, will be in charge of doing the work in those– [crosstalk]

GAME, Gather, Analyze, Model, Evaluate

Tobias: How big is that universe roughly?

Drew: It’s a 300-stock universe, basically, and you can have– call it five different sectors that we’re focusing mostly. Like I mentioned, we don’t look at the utilities or the telecoms, or the interest rate sensitive stuff, real estate. But in the stock-picking sectors, these are ones with the highest dispersion, it becomes a matter of– we call our process the GAME, Gather, Analyze, Model, Evaluate. At the beginning of the process, we’re just gathering information.

We’re going to conferences and we’re meeting with companies. You’re just trying to hear things that you didn’t expect to hear. If you don’t hear anything you didn’t expect to hear, you move on to the next sector or the next idea. But if you hear that stuff that, “Hey, I didn’t expect that,” if you see management change its tone from what they used to say six months ago or a year ago.

Well, let me dig a little deeper to this and then move into the A stage, you start to analyze all the information you’ve gathered. The most important thing in that A stage is to get rid of information, get rid of stuff, which is noisy, and people are going to think it’s news, or it doesn’t matter and try to really hone in on the stuff that does matter. In the M stage, we’re just modeling it. Okay, what’s this thing going to look like?

What’s down the road, given the restructuring that they’re doing or the products that they’re launching or the margins that they’re seeing or the demand that we’re hearing about? Then, in the E stage, the evaluation stage, we’re evaluating consensus expectations. Okay, Where is Mr. Market? What do they think about this? It’s hard, but we try not to know that stuff at first. We don’t talk to sell-side analysts until the very end to see what their views are. We don’t want to be biased ourselves. We just want to be fairly open and objective to this notion that company X, Y, Z is a buy or to sell or it’s a nothing.

Once we decided something in that E stage, then we’re trying to understand why. Okay, why does the market not see the things that we see? What are we getting wrong? What are they getting wrong? If we can then marry those things, then we have candidates for the focus list. Then the whole expected return thing is what then helps me downselect to a more concentrated portfolio of our very best ideas.

Modelling For A Global Pandemic

Tobias: When you’re looking at upside and downside, if something is a potential zero, is it still potentially in the portfolio? Or, that’s never going to get a consideration, even though the upside might be so vast?

Drew: Yeah. This is a great question. I wonder if I would answer the question differently now than I would have a year ago. From my career, it’s always been this notion of– I don’t mind asymmetry. Theoretically, Toby, we can have situations where we think there’s only a 30%, 40% chance of it being a winner. If it’s a three-bagger, if it wins, almost call optioning, and there’s only 20% downside if it doesn’t win, well, you’ll press forward. But typically, we don’t have that situation. Usually, it’s a 60% to 80% conviction name. We’ll have downside, and the bigger balance sheets potentially have more downside when things go pear-shaped.

Fast forward into the way markets can behave in these extreme periods, like a lot of our stuff that I totally misestimated what the downside was, for a lot of our names in March of 2020. Stuff that we thought might have fallen 30% in the worst case, literally was down 60%, 70%. You can mess things up on the upside too because you want to be conservative, you don’t want to look stupid. “Hey, I think company X, Y, Z could quintuple.” There’s no upside to saying that to your boss, or to your investor.

If you say, “There’s great upside we’re seeing, we’re ahead of the street by 25%. We think it’s 80% of growth. We think they can go up 80%.” Okay, that’s getting out there, that’s still reasonable, but you can’t– you’ve got to be careful in terms of being objective yourself. The question becomes now, after we saw what could happen to companies in March last year, how will the market react as it marches forward and thinks about how to value upside and downside of certain kinds of things?

Should people model for a global pandemic that will shut down the economy? As it turns out, markets really didn’t care that much about it ultimately, which I’m still very intrigued by. That’s a whole another discussion, policy reaction and things like that. It does beg the question, what is the actual downside now that we’ve been introduced to this idea that economists can be ground to a halt?

Tobias: It’s not something that I’ve done any work on, but it’s just something that I anecdotally observed, as we went through that there were a lot of companies that had healthy balance sheets with plenty of cash on the balance sheet. You would think that with a business that’s reasonably strong through that period, it should have been– I don’t want to say low beta, but it should have moved less than the market. Then there were companies on the other side that were pretty heavily levered and weren’t making any money.

When The Unsinkable Berkshire Was Down Lower Than The Market

You would think that there would be a little bit more volatility than the market. It was an unusual period, because I don’t think that that if anything, it was the other way around. It was some of the ones that I thought were a bit junkier, didn’t react as much, and some of the ones that were a little bit safer, reacted more. I think Berkshire Hathaway is a pretty good example of that. Just like an absolute battleship that’s just unsinkable, and then it was down more than the market.

Drew: Yeah, that’s a great point. What I think happened with Berkshire and actually what happened to a host of names, it kind of depended what factor box you were in. We were even seeing that before the pandemic started. If you’re in the growth [unintelligible [00:39:20] box, you get a different constituency than you’re from the value [unintelligible [00:39:28] box. It became so– well, I think historically, significant by the middle of, I guess, late March/early April, that even in our portfolio, we typically– we will tilt value. We’re not a growth shop, we own a lot of that other stuff, but we’re happy to own Arm Holdings as I mentioned back in the day.

Parallels Between Today’s SPACs And Free Money Back In ’98-99

Drew: But we found ourselves tilting way more valuable just because it was silly. You see it even still now. If you’re in this box, you’re in this mean box or if you’re in this growth box, or if you’re in this FAMANG box, you have flows and that has this self-sustaining narrative until it doesn’t, the parallels– I’m sure this one’s been beaten to death but the parallels between what we’re seeing now with the SPACs and the free money back in ‘98-99, or the R-WSB versus the message boards and chat rooms, there’s so many similarities to the behavior in why people want to own things and the trick for folks to do what I do is, you have to be aware of that.

You’re scouring your portfolio, making sure you’re not short things that they might decide they love, even if it’s probably zero. At the same time, you have to realize that ultimately– and this is the ultimate question, I’ve had this debate with some good mates of mine about this notion of the voting machine and the weighing machine, this notion of how things work.

Voting Machine Or Weighing Machine

Drew; Going back to this [unintelligible [00:41:19] being in college and reading everything I could, My favorite quote from him was, “The market’s a voting machine, whereon countless individuals register their votes. Partly the product of reason, partly of emotion.” That’s what drives things. Part of it is reason, part of it is emotion. That’s a time-varying thing. It’s not like everyone’s always crazy, it’s not like everyone’s always calm, but reason’s always there. It’s either a big part of things or a small part of things.

That gets us to this notion of the voting and weighing machine. Ben Hunt, Epsilon Theory, a friend of mine, he thinks it’s a voting machine from here to eternity. I think that it depends. It eventually becomes a weighing machine. In some cases, it becomes a weighing machine very quickly. You have a market overreact to a bad earnings print, and then find equilibrium. Or, that could take years, but eventually we get to the fundamentals.

Then, you’ve got to make sure you’re structuring your investments, your business so that you have that ability to weather that storm between now and then. Also, you can’t be steadfast in your [unintelligible [00:42:36] just because you bought a stock and it has lost money, it doesn’t mean it’s necessarily going to come back. It might be a bad idea, might be one of those 4 out of 10 that wasn’t going to work as the thesis changed.

Let’s go back and read the short case, does that actually look stronger now? Let’s go back and read your buy case, and has some of those pillars to the buy foundation broken down? Just constantly be as addictive as you can about it. Hopefully, that makes you more clear thinking than the next guy, which is what we’re trying to do.

Tobias: I think it always looks like a voting machine that will never stop being a voting machine when it has been a voting machine for a long time. That’s what Lakonishok, Shleifer, Vishny, they would say, “Naive extrapolation investors are always going to assume that you just continue on with this trend in earnings or stock prices or so,” whatever.

Then the better bet has typically been to assume that there’ll be some mean reversion at some point, so I’ve been a little bit resistant. Michael Green also has that argument that the flows totally dominate the market now and will until there’s this crack-up boom, [crosstalk] bust. It’s hard to argue otherwise in a market that is going to do that until it doesn’t.

Drew: I know. I had a few discussions with him as well. I disagree, but it lays out a very compelling argument about how flows are the dominating feature and a lot of the theory that we’ve all learned on how things work and why they should work is inapplicable, if at best from his perspective, but when I take a look at it, it is the case that ultimately– we own shares, not because of some belief that we can sell them at a higher price to someone else, but because we have a belief that eventually there’s cash flows and dividends, and either through share price appreciation or return of capital that we’ll decide– that’ll be what drives when things are ultimately worth.

The question becomes is ultimately 20 years from now, or is it six months from now? Obviously, we prefer it to be something that’s quicker rather than longer, and you get that validation, and you don’t have as much volatility.

At the same time, I think to the point of the guys who focus more on flows, you do have to be cognizant of it. If I were to go back and diagnose some things where my big mistakes have been, not only do I never buy the bottom, I don’t think anyone does. I’m always too early, I always said, “Oh, shoot this thing down 12% for the stupidest reasonable time, let me go buy a bunch of it.” Then, it just keeps going and going and going. I’m letting myself think that the market’s going to get reasonable and rational, and the weighing machine will show up tomorrow or they might not. It might be six months from now.

Now, the trick is rewiring your circuits and it’s hard to do, because sometimes the thing to do is to buy that stock, because tomorrow, the weighing machine will show up. I think a lot of that comes back to the kinds of ideas you have and how similar in thesis they are, not in terms of what the companies do, but actual is this an overreaction thesis? Is this an overreaction thesis? Or, is this an under– and how they might behave? How might they behave in different market regimes, but it’s interesting to watch this whole narrative, to think this whole notion that narratives are dominating, and driving things.

Narrative Driven Markets

For every GameStop, that obviously was to just get a bunch of people on board. I think hedge funds on both sides of that were probably the bigger players than anyone wants to realize, but it was interesting to see, and then, of course, it’s still 900% higher than where it was a year ago. This whole move from 40 to 450, and then back to 40 or 50, wherever it is now, that all happened in its craziest week, I can remember. I was involved in the Volkswagen thing back in ‘08. This, I think felt certainly in percentage terms, it was much quicker.

Not in terms of total, I think Volkswagen gained 300 billion euros of value in the space of three days. This wasn’t that big in total, but it was bigger move in percentage terms. That was a narrative thing. Let’s take it up because people believe in it. Then you had, I think, a lot of professionals who followed that momentum, and maybe played that a bit in some of the short squeeze activity that we saw. I think some of the people that knew they were buying it probably didn’t think it was worth what they were paying, but they’d be able to sell it higher.

You have things like Tesla, which to me, and I’ve written a few things about this. I’ve tried to de-bias myself, I’ve tried to come up with the most bullish potential assumptions, not only for the automotive business, but trying to do it for the automotive business and then see what remains and what’s the market paying for the Elon Musk option. I don’t want to say it’s a GameStop because they’ve got real business, they have real things that they do, but it’s the narrative that’s driving that one too, but it just continues. It’s so strong and so powerful.

So much so that when Elon tweets out he likes bitcoin or GameStop or anything, you– Matt Levine is writing a lot about this right now. Here’s a billion dollars, whatever he says, it goes. That stuff, it’s narrative-driven, it’s a bit more– Some people say investing in stocks is gambling, but it’s certainly a lot more like gambling than it is pure stock picking when you sort of guess, “Will I be able to sell this at a higher price to someone else because the [unintelligible [00:49:02] working.” Some guys are very good at that. It’s not my skill set.

The Math On Tesla Just Doesn’t Add Up

Mine is would keep me away from owning something like Tesla, unfortunately, because I can’t get there, even in the most– Toyota and Volkswagen both were founded in 1937, and they’re just incredible global-scale businesses. They, after decades, have arrived to the point where they have 10% or 7% global market share and are extremely profitable. You can make all these fast forward assumptions about EV being 90% of every car that’s sold in 15 years and you can start to flex on what kind of margins these players will have in that.

You look at the capex that Toyota itself is spending, add up all the capex of all the auto companies and it’s over $100 billion dollars and Tesla will spend $4 billion. I think it’s going to be a rude awakening. You’ve heard these arguments before.

Let’s say that I’m wrong. Let’s say that Tesla does become a Toyota or a Volkswagen, let’s say they become twice the company that those two, but let’s say they have 20% market shares of all EV sold. They do net margins that are higher than what Tesla does today, because of the software add-ons and things like that. Even doing that, you can’t get to more than $350-$400 billion market cap, which means even in that incredibly, almost impossible scenario, you’re paying another $600 billion for whatever it is he’s going to do next. Yes, it’s been great for Cathie Wood and everyone else to have bought this thing and have it rip and build a business out of it but philosophically, I couldn’t do that.

Tobias: To what extent is this driven by the option speculation, which seems to be the tail that wags the dog a little bit where there’s some delta hedging going on by the folks on the other side of that trade?

What’s A Gamma Squeeze!?

Drew: Yeah. There is a lot of talk about the gamma squeeze and you get this– whenever someone’s out, buying a call option, the hedgers are going to have to go out and buy stock, the guys that sold them this stuff. Now, they’ve sold it at a very nice bid-offer spread. These guys aren’t going to be losing money when they do this. They go out and they build a hedge and stock goes higher, and if they got to buy a bit more the delta, it works back the other way. I think that might have driven some of the craziness. I think what drove it more crazy than it might have been warranted, is that everyone started talking about it. It wasn’t just the technicalities of a gamma squeeze. It was that everyone learned what a gamma squeeze was, and everyone’s like– people never heard the term, and they’re like, “That was a gamma squeeze.” Geez, what?”

[laughter]

Drew: It just became this wonderful, self-fulfilling feedback loop. I think the retail guys thought they were fighting the hedge funds when, in fact, it was probably hedge funds fighting hedge funds, and just playing the narratives. A lot of misdirection and talking about front running and coordination. It was just a speculative mania, which we’ve seen time and time again, and this time, it’s everyone’s talking to each other in real-time, and so you come up with these notions of politics or of screwing the man, and let’s get these hedge funds back for their bailout-ing their way, I’m thinking to myself, “Mate, hedge funds were bailed out in a way it was the banks and the hedge funds found out a lot of this stuff, and a lot of these egregious situations.”

Short Sellers Are A Paragon Of Virtue

These things– short-sellers are paragon of virtue. Yes, they can be spivey and dodgy, some, but most are not. Most are good folks who are helping people construct portfolios that give them a little bit of uncorrelated return to the rest of what they own. They’re out there making markets efficient. They’re out there exposing situations so that mom and pops don’t pay too much for stuff, because no one’s doing the work. There’s a value that they add. It’s a tough place to have been since 2009 when everything’s ripping. But for those that have been able to sustain it, and stay with it, it’ll come back in vogue, believe me. As soon as market’s falling out, everyone’s going to want long-short again.

With all the narratives that were flying around the last two weeks, it was just nuts, they were just crazy and it was wild. We’re not out of the woods, either, that things are going to happen, we’re in this environment now, we could tell ourselves is because interest rates are low and money’s free so you can discount terminal values with 100 years’ duration at whatever price you want and pay infinity for a thing. Or, you can say that’s a bit of a post hoc explanation for why things are the way they are.

We had a bubble in 1999 when interest rates were 5%, that wasn’t the story. It was just people got excited and psychology took off. I do wonder if a lot of that is what’s hitting us now. The unpredictability of all that is, if it’s happening now, if things are twice as expensive as they should be, they could become three times as expensive. Back to the voting and weighing, eventually market weighs. We saw that after the tech bubble, even great companies fell 80% to where they should have been and then they’ve marched higher since. We’ll see. We’ll see how it all plays out, but the timing of it, who knows?

Tobias: I think that’s a great sentiment to leave it on. Drew, if folks want to get in contact with you, or follow along with what you’re doing, how do they go about doing that?

Drew: Just send us an email at info@albertbridgecapital.com.

Tobias: And your Twitter account.

Drew: If folks want to follow us on Twitter, and if they’re interested in learning more about how I think and how we think and my philosophy, we do have this Drew’s Views blog on our website. I usually will post some of that stuff into Twitter as well. It’s a fun thing to scroll through and read some– a bit about the way we think the world works in terms of stock picking valuation, with all these crises that we’re having, the impact of flows and of factor investing on stock picking and what gets squeezed out, what doesn’t, how do you make better decisions, and as you go about this.

It’s a bit of cathartic thing for me to do just to write, and I enjoy doing it. I think a lot of our subscribers now and a lot of folks or folks are enjoying, and hopefully learning a bit. I’m learning too, this whole experience of trying to be a bit more out there, whether on Twitter or with our blog, a lot of great people, and learn a bunch of myself. It’s been great. And meet guys like you, Toby.

Tobias: [chuckles] On that note, Drew Dickson, Albert Bridge, thank you very much.

Drew: All right, mate. Cheers.

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