The Exchanges

Q So in your years at IAS, what would you say worked and what didn't work?

A I would say that what really worked was, it was a small portfolio, so we could actually do very interesting things with it. We had a tremendous committee, and I was quite experienced before getting there, so that worked well. I really thought about who in my committee is good at what, and then used them, collaborated with them for that particular purpose, and so it was quite unique to have Jim, Marty Leibovitz, Nancy Pertzman, and then, you know, a whole host of other distinguished people that I won't mention all the names. I think that what doesn't work is, I'm not clear that the entire ecosystem of the Swenson model that had become so super institutionalized really works any longer. The fees are high, the fees are asymmetric, the LPGP risks are different, and I think we should explore different models, and I think Vanguard Constantly puts us to shame. Huh.

AI assessment note: “what really worked was, it was a small portfolio... what doesn't work is”

Q All right, we're going to have to come back to that seminal insight because it's so pervasive across the investment landscape. So where did you go from there off the trading desk?

A Eventually, I ended up at JP Morgan in the asset management division, and around 99, there was something very interesting going on in the world, and it was the early stages of the internet. This was causing seismic changes in the entire industry, and I believe, if I have my facts right, that the market value of Schwab exceeded The market value of JP Morgan, and Morgan, in some sense, was in an existential crisis, especially the private bank, because this was the old JP Morgan private bank. You came to JP Morgan, they didn't come to you, and they had a few great offices for very wealthy people, and now suddenly, all of these internet millionaires were being minted by the day. You had to find a way to service them, and the market was Was discounting traditional banks and providing tremendous valuations to the new entrance. So JP Morgan went in and said, what is it that we can do to, like, reinvent ourselves? And they looked at that in each division, and the private bank came back and said, we can provide financial advice in a scalable way using machines and the internet. Today, people call it RoboAdvisor, but that's not a great name for it, because it's really not a question of RoboAdvisor. It's a question of, can people plus machines plus some form of AI or rules create a scalable, cost-efficient way of providing differentiated service all over the world? So this is 1909, 2000. …

AI assessment note: “Eventually, I ended up at JP Morgan in the asset management division”

Q What caused you to go from the high net worth facing side to the institutional side?

A So, I wouldn't say that I wasn't only in the high network side. I was in the retail side of Merrill, so we saw all kinds of clients. It was 2006, and I didn't like the markets at all. The framework was quite popular. I was traveling all over the world. Merrill was under new leadership, and my kids were five years away from college, and I did the calculation that In five years, probably they'd just fire me because I was getting tired of the markets and the job, and my kids would be gone in college and no one would be talking to me. I thought it would be great if I just hung out with my kids for five years rather than do these crazy commutes, and somebody mentioned to me that the Institute for Dwan's study in Princeton, and I lived in Princeton, which is like 10 minutes away, was looking for a CIO, that they'd never had a CIO, And the chair of the investment committee was a famous guy called Jim Simons. And I'm a physicist by training. The institute is where Albert Einstein and Kurt Gödel were faculty members, John von Neumann. I mean, this is a place that, you know, it's like you had me at hello. So I went and I said, let me go find out. So that was the genesis of the transition.

AI assessment note: “I thought it would be great if I just hung out with my kids”

Q So how in the world do you know you want to become a physicist when you're a kid?

A I didn't know. I had a good friend whose father had a PhD in physics and worked at the National Physical Laboratory in India. And so, I think I got introduced to the books by Asimov, and I just knew I wanted to be a physicist, and obviously, Einstein was writ larger than life. I remember reading as a kid about how Einstein was working on relativity, and he sort of imagined himself sitting on a light wave, and how the world would look that way, as opposed to just sitting on the earth. And for some reason, it burned something in my brain. And I said, That's really interesting. There are two points of view in life. One, the way you see it, and one, if you're not a human, how would you see it? And in that sense, that duality has actually stuck to me, and you'd be amazed how useful it is in investing.

AI assessment note: “I think I got introduced to the books by Asimov, and I just knew”

Q What was that first year, that transition like for you?

A I think it's a growing experience. I think people who are very, very deep in academia may not have a Grasp on the real world or how it works, and within three months, actually, of being what we'd call a quant, they were very good to me. They said, you want to be a trader, eventually. Quants are supporting traders. We could give you a trading book, like a small trading book, and you can start taking some risk. It was quite an honor, because I was very green, and I looked at the whole situation, and I said, no, I don't want to do that, and they said, why? I said, because the traders have a free option, and On the firm capital, and so you're just going to induce me to take a lot of risk, and if it works out well, I'll make a lot of money if it blows up. There was something wrong with that whole structure, and so I just stayed away from it, and so eventually I moved away from the trading floors because I didn't have the risk-return mentality that that ecosystem needed and flourished and lived by.

AI assessment note: “I think it's a growing experience. I think people who are very, very deep”

Q So, you start studying physics, and why don't you take me through where that brought you?

A So the second thing that you have to understand is I wasn't very good at school. It sounds a little weird given that I have reasonable academic qualifications, but I guess now you would say that one was differently abled in learning. I just had a really hard time. I'd sit in the class and get spewed masses of information. You're supposed to memorize them and then regurgitate them in three hours, and it was a disaster. The one thing I was pretty good at was playing chess. My father introduced me to chess, and he and I would play every weekend. For fun, and that sort of made it clear that at least I had some brains. When I graduated from school, I entered the state junior championships and tied for the first four places, and that actually got me into the best college. So in some sense, chess got me into the best college, St. Stephen's, and I did physics there, and I captained the chess team. Happy to note we won the intercollegiate championship, just as a note. But I did physics at Stevens in Delhi, and then I got a scholarship, and I went and did graduate work first at the University of Georgia in Athens, where I got lucky, and I worked with a very distinguished person, David Landau, who was a pioneer in Monte Carlo simulations, and so I did my master's thesis with him, and then I did my PhD at Yale in chaos theory, where I got to work with some more distinguished People, Benoit…

AI assessment note: “I did physics there... went and did graduate work first at the University of Georgia”

Q I'd love to walk through a couple different applications of this. So at the time, where were you sitting and how did you apply it?

A So, as I said, the early work, really, the genesis was the work we did at J.P. Morgan. By then, I had moved to Merrill, and I had the Thundering Hood to work with, and that was a great experience, and I developed, I wrote Beyond Markowitz there, and we began to apply it. There was great resonance because in many ways, there was a disconnect between modern portfolio theory and how people really invested. And, you know, this is well known. Even Markowitz doesn't invest as per Markowitz, and nobody really does mean variance optimization. Otherwise, you put all your money in emerging markets. You put constraints. But this was the first time this was a framework where people of all different styles of investing could look at it and say, yeah, I already do that. I do that sort of in my head, or I've never quite formalized it. So I knew that I was onto something good, because I always think the good ideas are sort of obvious in retrospect. The idea that everybody needs to put an index, a call, is actually the essence of investing. It's also a way of then connecting between things that I want that are certain, and things that I'm willing to have some flexibility on, and how do I connect them with the market, That is very uncertain, but is also my best bet for extracting return.

AI assessment note: “By then, I had moved to Merrill, and I had the Thundering Hood”

Q What are your signposts of what you constitute as a good person?

A I think that most people are capable of both good and bad behavior in their lifetime, and people will manifest that. So I don't think of any one person as good or bad. I'm asking myself, what are the circumstances that we have? Is this going to engender good behavior, or is this going to engender behavior that's not aligned with what I want? What I would define as bad behavior, and the way fees are structured, how they behave when things are going badly, are they raising as much money as possible, or are they being capacity constrained? It's actually not that hard. What is hard is that you're always looking at managers who have done well recently. That's why they're raising capital. So you have that behavioral bias, you want to get in, And you're willing to overlook things that in retrospect were always there.

AI assessment note: “I don't think of any one person as good or bad... what are the circumstances”

Q So in that seat, you're facing everything from retail to high net worth clients. What's a good example of what someone's portfolio might have looked like putting that framework to work?

A It really is a tremendous span of examples you can give, but let's start with high net worth individuals, because being in that seat, that's sort of the first one that you're paying attention to. At some level in a, so take a business owner. They've been very successful, and 95% of their portfolio in the past didn't even exist under the Markowitz framework. So they would work with a financial advisor, and the financial advisor would say, you need to take some of the profits that the business is generating and give them to me. And the business owner would look somewhat suspiciously and say, what rate of return are you promising? Because I'm making 20, 25, 30% a year compounding. You can offer me six, seven, 10, and by the way, what are your fees? Why am I doing this? So in general, they would stay away from the market, and they would barbell. They would have a lot of cash and some real estate, and then it would become very inefficient over time because they didn't need such a big safety net. So now you have a middle bucket that's missing, and over time, it's costing you a lot. So the idea of thinking that you're buying insurance is And if you need it instantly, you need it in the form of cash and bonds, but if you need it over time, then the market is your insurance, because it compounds at a very healthy rate, and you're giving up market return. So, just the idea of rebalancing…

AI assessment note: “let's start with high net worth individuals... take a business owner.”

Q So how did you think about your framework, the safety portfolio, the index, the upside portfolio, aspirational portfolio in the context of IAS?

A So I think that you want to take one step back and say, remember, it's not just the three buckets, it's your goals. You always go back and you ask yourself, why do you have this money? What is the purpose? And in fact, that is what the interesting piece is. Jim had really thought that through for the Institute. The idea that the Institute has no students, and therefore, the only source of funding is the endowment. Now, think of it another way. If you're taking a lot of market risk, and the market goes to hell, and the Institute gets into deep trouble, the next Einstein doesn't come there or do their work because the S&P didn't return the right amount. It's the same thing with individuals. Your kids didn't go to college because the S&P, 500 underperformed. There's something wrong with that. So the idea about having low beta is not to have low returns. It's simply saying, I recognize the returns of the market and the risk that comes with them, and one of the risks is volatility, and that volatility can be very painful for The Institute, because there's no other source of funding, while on the other hand, for Yale or Princeton, they could just double their tuition. They still fill every seat. So the low beta portfolio was a challenge. It was the right thing to do for the Institute. Therefore, also when markets are riding high, you don't end up spending too much because you're not …

AI assessment note: “The idea that the Institute has no students, and therefore, the only source of funding”

Q All right, Ashton, I want to turn to a couple of fun closing questions. So let's start with what is your favorite hobby or activity outside of work and family?

A I like hanging out with my wife and just, we read, watch TV, go see places. There's nothing special. I, I, I occasionally read a hard math book just to see if my brain still works, which normally I come to the conclusion it doesn't. And so that maybe that qualifies as an unusual activity. Sometimes I'll have an interesting conversation with Jim and he'll talk about a mathematical concept and I'll go look it up. I also love looking at original papers. On anything. So, on a technology, there's a lot of fun in going back to the original source. I'm also in a bunch of committees, Rockefeller University, National Academy of Sciences, Stony Brook Foundation, the Institute for the One Study, and I think each of these institutions represent something special. The boards are interesting.

AI assessment note: “I occasionally read a hard math book just to see if my brain still works”

Q So let's dive into that a little bit. Vanguard puts us to shame, and you don't think the endowment model will be as effective. What's the alternative?

A I don't think there's a silver bullet. I think people are doing the best they can. Everybody exists within a certain framework, and I think that's a nice article that both you and I have read by Graham Duncan. It's on infinite games, and I think you have to understand the games that everybody is playing, including the game that you are playing. And I mean that in a serious way, not necessarily that it's a game, but what are the rules of whatever you're doing, and where is value coming from? Where's the return coming from? Why are you at the table? Why are you being given permission to participate in the gains? And in that sense, the fundamental value managers are playing a different game than the momentum managers. The quants are playing a different game than either of those two. Yale, for example, would never invest in quantitative managers, at least as far as I know, and I believe the answer was, Swenson said, I like to invest in things I know. My view was, give me any large cap stock, JP Morgan, Merrill Lynch, IBM, Microsoft, I still don't know what I'm investing in. To know is to be able to predict something, especially from physics. You're talking about multinationals, you're talking about the world. So, You need to go back and ask yourself, what are the different ecosystems that coexist in the investing world? And which are the ones that you can participate in, and which …

AI assessment note: “I don't think there's a silver bullet... ask yourself, what are the different ecosystems”

Q What was it like meeting Jim the first time?

A The Institute, for those who don't know, the Institute is a few hundred acres next to Princeton University, completely independent, 30 faculty members for life, and then a couple of hundred visitors each year. 30 faculty members can do whatever they want for life. That's why you had Einstein there, you had Kurt Gödel, John von Neumann, you have Ed Witten today, you have a whole bunch of very distinguished people really pushing the edges of the Frontier and brilliant people. So prior to Jim was a man called Leon Levy, who was the chair of the investment committee. Brilliant investor. Ran the portfolio himself pretty much. Probably took risks that today under an institutional setting you could not take. Worked out well. And I think the feeling always was that it was not a huge portfolio, and with all of these billionaires, if something went wrong, they'd fix it. So Leon unfortunately died suddenly and And they looked at the next who would take it over, and of course, Jim's. Jim, who had been at the institute, I think, as a mathematician briefly, a long time early in his career, became chair of the investment committee. So finally, I did get an interview with Jim, and we spent an hour, and Marty Liebowitz was there. So it was Marty Liebowitz and Jim interviewing me. I had this view that I was a managing director at Merrill. I had Chaired the asset allocation committee. I was a pre…

AI assessment note: “Jim spent an hour asking me very precise questions about how I do due diligence”

Q What was the process of getting into Sequoia?

A I cannot tell you. I don't think that they would want me to reveal that, and I would just say I was grateful that they gave us capacity. The Institute is a wonderful, wonderful cause, and I think we do them proud, and their returns have done us proud. But then the question was, and this is where I think I had some fun, because I had a very interesting committee, and I very quickly determined Jim was setting the strategy. He was easy to work with, as far as I was concerned. I was on the same page. Marty Leibovitz was there, and he was terrific in terms of understanding risk return, betas, stress betas, and then there was Nancy Peretzman, who just Is a genius at Emerging Managers, and she sent me to Union Square Ventures, and she said, go talk to Fred Wilson, and I went and talked to Fred, and I really, really thought they were very good. This is 2006, so, you know, they have the 2004 fund, which is already doing well, but he's talking about something called networking, and that's interesting. Networking is an interesting concept, but who knows? It's like eyeballs in 99, and I'm very concerned about the bubble I've seen and gone through. In 1909, 2001. I don't see how this connects with the low beta, low risk strategy at the institute. I do feel like I need to get returned from somewhere, and venture is a persistent source of return if you can get there with the right people. And…

AI assessment note: “I cannot tell you. I don't think that they would want me to reveal that”