The Exchanges

Q As the market is moving around, how do you adjust your position sizing within say a group of the same names in the portfolio?

A So even if we look at the things that have been our biggest contributors over many years, our biggest contributors have been in the book for four to five years, but they might be a five percent position and it might go up to eight and back down to four and out to nine. That's all driven by their expected returns and by the expected returns of the things around it in that portfolio. It's this notion of making sure that we have the mindset that this is the portfolio we would own today if we launched the fund today. And so if you find a security that's, you think it's worth a 150 euros a share and it's trading at a hundred and it's got downside to 80, you can come up with the expected return metric. And if the stock goes from 100 to one 20, well, the expected return just fell. By definition, it must be due less capital than it was before. And that capital can be moved somewhere else.

AI assessment note: “That's all driven by their expected returns and by the expected returns of the things”

Q And where did you get the formative education beyond paying 25% of the cost of the option for commissions?

A I've always been interested in financial theory. Why do things work the way they work and interested in psychology? And in the mid eighties, late eighties, early nineties, there was this heretic group of economists, one of them being Richard Thaler, who was up at Cornell at the time. That was, they were poking holes in this, what was known as the efficient market theory still is. And Eugene Fama, this paragon and pillar of efficient market theory thought it was really interesting what he was doing. And he had an idea in the mid nineties that let's try to get Richard Thaler down at the university of Chicago. Let's have this place be the battleground for this efficient market versus behavioral debate. And I wanted to go back to business school. And as soon as I saw that happen, I said, well, if I can get into Chicago, that's where I want to go. I want to be a part of that. I was lucky enough to be one of the MBAs that was able to take Fama's course, which allowed me to take Dick Thaler's course on behavioral economics. He also taught a course of the MBAs that was more decision making. I took that too. So I got pretty close to him there. It was during the tech bubble by now. So this is 98, 99. And so we worked a little bit together outside of class on some other things and got to know each other. And so from that point forward, it was sort of the Morpheus Neo moment where you take…

AI assessment note: “I was lucky enough to be one of the MBAs that was able to take Fama's course”

Q And so what was that plan of attack at the time?

A Well, at the time, Imprella, they have a big brand in the banking business, and at the time, they didn't have a huge brand in asset management, but it was a known group, particularly here in the U.S., and our target audience for what we do is the U.S. university and endowment cadre of long-term investors. And with the front office, they had some very good guys on the marketing team and, and a really big platform that was going to take some of the operational burden off of us. We made the decision to not be independent anymore. But with a sort of independent flair, we turned Dixon Capital's office into Perella Weinberg's European asset management office, and with that, began having conversations with some of these longer-term thinkers. And one of the first things we did, as a lot of other London-based funds and even funds over here had done, is make the Longbook its own investable vehicle. The combination of having discussions with the longer-term thinkers and having this vehicle where people could get exposure to Europe And best ideas without paying for the beta component of those returns was aligned with how we think the world should work. And very much aligned with how they think in terms of their long-term goals. So that was one of the first things we did there.

AI assessment note: “We made the decision to not be independent anymore... make the Longbook its own investable vehicle.”

Q What are the other ones that you incorporate into your work?

A The biggest one, and this is Kahneman and Tversky one-on-one is confirmation bias. So we all tend to find information which supports views that we already have. It's almost echo chamber kind of stuff. And I did it as an analyst at fidelity and I catch myself doing it now. An example, again, this is a hypothetical example, but if you're long SAP, uh, Big enterprise resource planning software manufacturer in Germany. And let's say I'm short SAP. And we have our reasons why we're long or short. And then we see Oracle have a profit warning competitor in the space. If you're long SAP and you're short SAP, you might have two completely different interpretations of that same exact data point. If I'm shorted, I'll be like, oh, this is great. Enterprise application spending's falling. These guys are seeing negative like for likes year on year. This foretells bad news for their biggest competitor in the space. But if you're long it, you'd be like, this is awesome. I knew it. They're finally taking share from Oracle, and I've got data points from these investors that are, they're switching from Oracle to SAP, and that's why Oracle missed. It's about us being objective about the information that comes to us, and that's one of my favorite parts.

AI assessment note: “The biggest one, and this is Kahneman and Tversky one-on-one is confirmation bias.”

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A There's one of these biases that's called ambiguity aversion. Well, you combine that with availability bias, but it's more of an overreaction thing that happens in the short term. So if you remember BP and the Deepwater Horizon, stock cratered, and it was terrible, and it was bad news. Volkswagen and the Dieselgate scandal in 2015, stock was killed. And that's a great example too. The stock sells off to 90, 95 euros a share from a 160, and the worst fears of what kind of fines they would end up having to pay turn out to be true. But by the time they wrote the checks, the stock's back to one 45, one 51 55. People double and triple count bad news. They get really, really scared. And very recently, we thought we had a potential situation like that with bear, which we say buyer in the UK. So I might flip back and forth and say it the wrong way here. But growing up, it's bear aspirin. Over there, it's buyer. But it was a very similar kind of move. The stock goes down about 40% peak to trough, just like BP did, just like Volkswagen did. And we thought to ourselves, well, this is another potential ambiguity aversion case where people are just selling this thing down. And it is unknowable. It's hard to know what will the ultimate litigation liabilities be from these California courts or elsewhere over Roundup, glyphosate, which they acquired those liabilities when they bought Monsanto.…

AI assessment note: “Volkswagen and the Dieselgate scandal in 2015, stock was killed.”

Q When you take the lessons you learned from Dick Thaler, your various investment experiences, and then you go to apply it at Albert Bridge, What have you internalized in terms of how behavior impacts the way you invest?

A Well, it's twofold. And this is again, hopefully a positive evolution in my career. If you had asked me that question in 2008, I would have rattled off a lot of important things, but mostly to do with Mr. Market. Here's the confirmation bias they're suffering from. Here's the ambiguity aversion. Here's the representative bias. Here's, here are the things that are preventing them from seeing what we see. And we want to take advantage of that. And that would be our approach. And it still is, but we've now I realized, and actually reading through Thinking Fast and Slow, Danny Kahneman's book, this is Dick Thaler's mentor, and he's the one that came up with a lot of these things that we all do as human beings, and I remember the most interesting passage to me in the whole book was talking about how even he still commits these same errors himself, and so if Danny Kahneman still commits these errors himself, how is Drew Dixon not going to? So what can I do? I can Try to set up a culture where it's okay to make mistakes, it's okay to recognize those weaknesses, and have investors with similar time horizons so that you're not affected by other folks as much as, even if you don't think you're being troubled by someone that's asking you how you're doing the first week of the month, it's affecting you. So if you have folks that don't ask you those questions, that just interested in the pr…

AI assessment note: “Try to set up a culture where it's okay to make mistakes”

Q Do you have biases in terms of the kinds of stocks you're looking for?

A Yeah, I probably do have a little value bias when I'm looking for it. Maybe that's the time that we all grew up and the kinds of things that we read at a certain age. And I'm sure someone that started their careers in 2011 has the opposite bias. Why would you do that? Why wouldn't you buy all these great businesses which are growing ROICs At an exhilarating rate. So I have to guard for that. And even though I do guard for it, we still end up having a value-y kind of portfolio. But we've been able to outperform not just value, but the market overall. But I think that's just a consequence of A, having a very concentrated best ideas portfolio rather than something that's more diversified and sensitive to those factors, and B, it's having this, back to this culture thing, where if we've defined where we might lose money in particular positions, then we're looking for that information, and if it's okay for me or for the guys on my team to hold their hand up and say, you know what, my conviction of this is lower. I just saw this thing happen. We wrote about this as a potential threat to the To the case, and I wouldn't have 75% conviction in this. It'd probably be closer to 65 now. What does that mean for expected returns? And if it turns out it means that we shouldn't own as much of the stock, or any of it, we'll go. And that doesn't matter to us if we bought it five years ago or fiv…

AI assessment note: “Yeah, I probably do have a little value bias when I'm looking for it.”

Q It sounds like a lot of the conviction that will lead to position sizing within the portfolio is very subjective. So how do you come up with position weights for these names?

A It can be subjective. I mean, at the end of the day, I think everything's always more subjective than we think it is. So what can we do to make it sort of less so? One is to build this short model and this long model so that we have a reasonable gauge of what the upside and downside could look like in a great or a terrible scenario. Now, those are kind of binary. I'm not talking about a distribution of different outcomes. I'm talking very simply, here's what it's worth if we're right, here's what it's worth if we're dead wrong. And then it's about asking ourselves, okay, how long will it take Mr. Market to wake up to this thesis? Is it going to take 24 months? Or maybe there's some events coming. It might take 15 or 18. It might take 36 because it's a long burn. But once we have those factors in, we can come up with this notion of annualized potential expected returns. And that's how we basically rate the companies that are in the focus list and make sure we're allocating capital to the ones with the highest returns. And by design, we do not care about overweights or underweights in particular sectors or countries. If it turns out that we're finding no healthcare equipment ideas in Switzerland, we don't own any healthcare equipment ideas in Switzerland. It's just It's just the ideas that come through and germinate through. We are paying a little bit more attention now, obviousl…

AI assessment note: “we can come up with this notion of annualized potential expected returns.”

Q Where do you get that information from to sort of gather that information, analyze the information when the information is, what does the market think? What is the market getting different from what you see?

A Yeah, so we can bring in sell-side coverage, so we have a strong sense of the number of analysts covering a stock, the number of buys, sells, and holds. We can weight each of those differently. It's actually quite different in Europe. A hold doesn't have the same flavor as a hold here in the U.S., which is what the analysts say, but we can Make some adjustments for that, and we'll come up with the notion if the sell side broadly likes or dislikes the company. We do something similar with the buy side. Obviously, there's a buyer for every seller, but we can at least get a sense of what's happening by looking at short interest, how stale is it getting, which kind of money is long or short certain companies, and as we aggregate those things, we're able to, I think, develop a pretty good sense of the kinds of things that people are paying attention to, and one point I would make, and this has been just a change in the market, and it might even be More exacerbated by Mifid II now, which has kind of decreased the amount of folks that are covering companies. Increasingly, I think there's almost been more of a melding between the sell side and the sell side's clients. So when we see broker notes, we call it reverse broking in the UK, it almost feels like it's one of their big clients that has pushed this analyst to convince them that here's the thesis that matters, and they're out mark…

AI assessment note: “we can bring in sell-side coverage, so we have a strong sense”

Q What was it that got you to an option before a stock?

A I didn't have enough money to buy enough shares of stock, so I thought that this thing was going up, might as well just buy some calls. Literally the first trade. And that was all during this sort of, this is going way back that when I'm in college and the market's going crazy. It's 86, it's 87. And then when the market crashed, at that point I was hooked. We had like an original copy of security analysis at Purdue's library and go back and read through that and trying to build all these models to try to see where markets are going to go and all this silly stuff, which in hindsight is stupid and naive, but it was always something that captivated me. And so as I progressed in my career, that was always Broadly the focus.

AI assessment note: “I didn't have enough money to buy enough shares of stock”

Q Let's start breaking down the strategy. You're playing in Europe. What's different about stock picking in Europe from say the US?

A The behavioral stuff's all the same. We all make the same mistakes. I have the same biases that I try to shed and my team tries to shed. Mr. Market has the same biases. They overreact to bad news and vivid recent information. They underreact to things which disconfirmed their previous theses. That's as good in Asia or Europe or the US. And from a company level, we tend to focus on more mid to large cap companies, and so when you have these multinational businesses, very little difference in stock picking from that fundamental perspective. I will say there's some nuance across different regions in terms of when you do have conversations with management teams or with suppliers or competitors. If someone says maybe in Sweden, it means yes. If someone says maybe in the UK, it means no. So you do have, you have a little bit of experience with that over the years, and we've been doing it for so long that You know, in some cases we're on our fourth or fifth management team, so that helps to some degree. But broadly, accounting systems are fairly reasonably harmonized. I used to spend a lot of time diving down these rabbit holes of trying to figure out the exact specific line item that was going to make my, some of the parts model look good or bad, but the more you're in this business, the more you realize your success in these positions is more different by what's happening to the fun…

AI assessment note: “very little difference in stock picking from that fundamental perspective. I will say there's some nuance”

Q Is there a particular factor you hate the most right now that people are calling a factor that you don't think is?

A No, no, no, no. It's just the number, like, I don't know who it was, John Cochran maybe talks about the factor zoo, and, and there's some new factors which are, to me, fascinating. Betting against beta. This is flies in the face of single factor CAPM, and that's what the guys at AQR call it. It's similar to the low vol kind of factor, where people, theoretically, stocks with a high beta are supposed to move more higher than the market does in the market. So it turns out it's the other way around, and And this is something for Gene Fama and the official market crew to have to grapple with. And it does beg the question of, in which you'll have plenty of folks say that the cap M and the whole structure was wrong in the first place. From my perspective, if Fama and French introduce value and introduce the small cap bias in a three factor model, and then Mark Carhartt a few years later introduces momentum, those are the key ones. Really momentum is maybe more important, certainly more important than size and maybe more important than value. And then you get this slow vol, this betting against beta stuff, and the theory is tougher for me to come up with why that might work. Quality. Quality is another one. Is that a behavioral story, or is that a, is that a risk story? It's tough. They seem to work. The momentum stuff, I am convinced there's no risk story for, and that is an underrea…

AI assessment note: “No, no, no, no. It's just the number, like, I don't know”

Q What do you constitute a thorough analysis of a company?

A It's basically the whole game process. So it's, you have to have a strong sector construct, knowing what drives the competition, knowing the dynamics of who's competing against two and how each of these companies in the group makes money. And then it's a matter of just staying on top of that and maintaining this framework as competition happens and as businesses evolve and as management teams come and as management teams go. And then when we find things which Are basically just changes. Hey, this is the way things used to be. They're going to be different now. That is the kind of thing that makes us want to dive in and understand what it is that's going to be different. And as we do that, ultimately, we want it to be expressed in some change in a financial metric. It could be sales line. It could be EBIT margins. It could be earnings. Something, you know, a year from now, two years from now, two and a half years from now, where we see earnings change. Or cash flows or whatever's going to drive Mr. Markets appetite. If we see them potentially markedly surprising the consensus investor, then we have a chance to take advantage of that. So that's going to be a lot of financial modeling. We build financial models for all the companies in the focus list. That's the M. That's the modeling. And that's a fidelity thing. It's, I think, a lot of managers think, but that's certainly someth…

AI assessment note: “you have to have a strong sector construct, knowing what drives the competition”

Q What was it like launching your own fund?

A Well, it's exciting. I had kind of been doing it in something similar in smaller versions previously with DocSif and with the guys from Fidelity. And the whole goal was just to, and it still is actually, is there a way we can do this a bit better, a bit smarter? And I hope, actually, I hope in 10 years I can look back to this day and say, well, I've, look how stupid I was 10 years ago. And if you can stay on that path to try to get better and learn more. And so, And with that though, there's still always been this overriding view that, hey, we're in the business of generating alpha. We're not market timers. We're not going to be dialing our gross up and down because we have a view of the market. This is about bottom-up idiosyncratic stock picking. Can we identify businesses where we can objectively analyze information we're gathering and see if they're going to beat numbers? Let the fundamentals lead you, and then let valuation come in to help you size the positions. We started off with a long, short fund. I have the worst Track record of when to launch funds. I launched Alpha Europe originally as an independent company three months before the financial crisis showed up. We launched Albert Bridge three and a half years ago, two months before Brexit. But as it turned out, we did reasonably well back in the day, and we made money in oh eight and oh nine, and grew the business nic…

AI assessment note: “Well, it's exciting. I had kind of been doing it in something similar”