Transcript: Brian Hurst, ClearAlpha
The transcript from this week’s, MiB: Brian Hurst, ClearAlpha, is below.
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00:00:02 [Speaker Changed] Bloomberg Audio Studios, podcasts, radio News. This is Masters in business with Barry Riol on Bloomberg Radio
00:00:17 [Speaker Changed] This week on the podcast. Yet another extra special guest, Ryan Hurst is founder, CEO and CIO of Clear Alpha. They are a multi-manager, multi-strategy hedge fund that has put up some pretty impressive numbers. His background is really fascinating. Cliff Asness plucked him out of the ether to be one of his first hires at the Quantitative research group at Goldman Sachs. He was the first non founding partner at a QR, the hedge fund that Asna set up. And Brian worked there for a couple of decades before launching Clear Alpha. He has a fascinating perspective on where Alpha comes from as well as the entire hedge fund industry. Few people have seen it from the unique perspective he has, and I think he understands the challenges of creating Alpha, where it comes from, and managing the risk and looking for ways to develop non-correlated alpha that is both sustainable and manageable from a behavioral perspective. I, I thought this conversation was absolutely fascinating and I think you will also, with no further ado, my interview with Clear Alphas Brian Hurst.
00:01:38 [Speaker Changed] Thank you Barry. Appreciate it.
00:01:40 [Speaker Changed] Good to have you back here. Last time you were on a panel, we were talking about the rise of, of some emerging managers, including yourself. But let’s go back to the beginning of your career. Wharton School at the University of Pennsylvania. You graduate with a bachelor’s in economics. Was quantitative finance always the career plan?
00:02:01 [Speaker Changed] That’s a great question. I think when I went to school, I didn’t even know quantitative finance was a thing and frankly at that point in time it really wasn’t much of a thing. I was taken by my dad. He was an accountant and CFO of a commercial real estate company. He would take me to the office and I was really fascinated by business. I really wanted to get into that. I was into computers. I, I really learned how to teach myself how to program and things like that. But I wanted to get into business and I said, dad, I wanted to get into real estate. And my dad gave me some really good advice. He said, Brian, if you think about finance as an org chart, real estate is like one of the divisions and if you start in real estate, it’s hard to move up and go to other divisions and, and try other things out. You should really learn corporate finance and you can always switch to real estate if you wanted to. And corporate finance is kind of the, the top of the, the umbrella or the org chart. And I said, okay, well what’s corporate finance and, and where do I go to learn that? And he’s like, well, you should go to Warden. And then I said, well, what’s Warden? So that’s how it started.
00:02:57 [Speaker Changed] That’s hilarious. You finish up at Pennsylvania and you begin your career at DLJ. What sort of work were you doing and what were your classmates doing? This is the early nineties you start at DLJ.
00:03:09 [Speaker Changed] Yeah, I did DLJ. It was interesting. That was my summer year between junior and senior at, at Warden. And they kept me on throughout my senior year to finish up an interesting project, which is basically automating the job of the investment analyst, this, that, that we’re doing all the company work, getting all the, you know, 10 Ks, 10 Qs, all the information. At the time there was a new company starting up, and I know I’m on Bloomberg, but it was called FactSet at the time. Sure, of course. And there was a sales person walking around trying to get anyone to talk to them. ’cause this is a brand new company and I was a summer analyst and I was like, I’ve got time, I’ll talk to you. And he showed me, first of all two things. He showed me this thing called Microsoft Excel. At the time everybody was using Lotus 1, 2 3.
00:03:53 And he showed me basically how you can type in a ticker and it pulls in all of the financial information right into this spreadsheet for you before the internet. But you know what was kind of the internet at the time, I was like, wow, this is amazing. I was like, this could save me hours and hours of work. And so I went to the MD at the time and I said, Hey, I think I can automate most of what the analysts are doing. He said, you’re a summer intern, we’re not paying you much. Go at it. And that’s what I did. So I I, I started off in that, but I mainly learned that I didn’t really wanna do investment banking because it didn’t hit on my core skillset, which was like engineering back down quantitative techniques and tools.
00:04:29 [Speaker Changed] That sounds really interesting. It’s amazing to have that sort of experience As an intern. How did you land at Goldman Sachs?
00:04:36 [Speaker Changed] Like everything in life that works out well. That’s, you know, a lot of hard work, but mostly luck because of the DLJ experience. That was a good thing to have on my resume. Cliff Asus, founder of a QR capital managing partner there, at the time, I think it was late twenties, he was finishing up his PhD at the University of Chicago and was working for Goldman Sachs Asset Management. He got the mandate to launch a new quantitative research group. And so he wanted to hire someone who had both the finance background and the computer science background. I had started with a couple of friends, a software business in high school and at Penn. One of the things I did with my roommate was we started up a hardware business, kinda like Michael Dell building and selling computers to faculty and students on campus. So I had the computer science background.
00:05:23 Cliff had gone undergrad at Penn, at Wharton also. So he knew that we’d taken the same kind of courses, we spoke the same language from that perspective and had that, that technology background. So I was his first hire. He was building out that new team, what my other colleagues did back then you had basically three choices come outta Wharton. It was accounting, investment banking and consulting. There was really no jobs for asset management, but those are the courses I love the most at Penn and really wanted to pursue that. So it was, it was a great opportunity.
00:05:50 [Speaker Changed] So, so you spend three years or so at Goldman with Cliff by that point. He had been there for a while and decided, Hey, I think I, I have a little more freedom and opportunity if I launch a fund on, on our own. You were there day one, you left with him. Right. Tell us a little bit about what it was like standing up a QR with Asness.
00:06:12 [Speaker Changed] It was great. We started off just a little, little background there as a research group within GS a m, so think cost center and just putting some timeframes around this. This is 1994, which is one of the toughest years in Goldman’s history. Even going back to the Great Depression, it was, it was kind of year where to me and a partner had to put in money. Wow. Which was, you know, was it
00:06:33 [Speaker Changed] That bad a year? I don’t remember. 94 is a terrible market year.
00:06:36 [Speaker Changed] That was the, the year where the, the Fed had the surprise significant rate hike in Feb. I was actually on the floor.
00:06:42 [Speaker Changed] I think bonds took a whack, but I, equities also wobbled a bit, if that is that right. Wobbled
00:06:47 [Speaker Changed] Bit. But yeah, it was really a bad year for fixed income and, and the firm had a lot of risk in fixed income, I presume, which led to the tough year, huh? Yep. So we were a research group cost center, and then left and right. People were disappearing week by week as they were, you know, cutting down really headcount. And so quickly we realized we’ve gotta start generating some revenue if we wanna stay alive. And Cliff went to them and said, Hey, we’ve been, we’ve built some interesting models. We think we’re good at picking stocks and futures and things like that. We think we can trade on this and make some money. And he convinced the partnership to give us some money. So it was basically a prop trading effort for a little while. It did very well. They kept adding money to it and then we opened it up and turned it into a fund. And it was really Goldman’s first real hedge fund coming outta GSAM that funded very well, which really opened the door for us to be able to leave and start up and, and raise money as a, as an independent hedge fund.
00:07:40 [Speaker Changed] What were the specific strategies Cliff was running at GSAM with the partners money? It
00:07:46 [Speaker Changed] Was a multi-strategy approach, but it was all quantitative. And, and, and when I say quantitative, that means a lot of things to different people. I think about every good investment process is really a process and whether people would label it as quantitative or not is really how automated it is. And so by quantitative, I mean like really automated, downloading public data for the most part, pumping it through some systems and that causes you to want to buy and sell different instruments around the world. But
00:08:14 [Speaker Changed] You’re still creating, or Cliff at the time was creating models and the models would give him a, a ranked list of, hey, the top 10 stocks on this list of a thousand are really, or whatever the number is, are things you wanna look at either getting long or short based on whatever that model is.
00:08:30 [Speaker Changed] That’s right. So that you’d have many different signals and we’re trading many different asset classes. And so it’s, it’s like you’re saying all those signals you would give different weights, different signals and those would add up to you. Like these things, you don’t like these things. We would trade global equities in a bunch of different countries, but market neutral. So long as much as you are short. So you’re not taking a bet on is the market gonna go up or down? You’re really taking a bet on this group of stocks is gonna outperform this other group of stocks by looking at a bunch of different characteristics. We did that for stocks, we did that for currencies, for commodities, you name it. It was, it was tradable and we had data. We wanted to be trading it and that that’s really what the genesis of that fund was. How
00:09:09 [Speaker Changed] Long were you guys doing that before you realized, hey, this is really gonna be a successful model? And then how much longer was it before? Maybe we should do this out from under the compliance regulations of a broker dealer?
00:09:23 [Speaker Changed] We started that as a fund really in 1995. It had been trading prop for a little time with Goldman’s money and we made money almost every month. Basically it traded as a fund and, and I think we left in terms of a timing perspective. You know, this started in 1995. We left early 1998, so it was only a couple years in change that we were trading this within GS a before leaving to, to start up a QR.
00:09:47 [Speaker Changed] So, so let’s talk a little bit about a QR you there from, from inception, from day one. What was that transition like from, you know, I imagine at Goldman Sachs you have access to lots of support, lots of tools, lots of data, lots of everything. What’s it like starting over again from scratch in a standalone hedge fund?
00:10:08 [Speaker Changed] I’ll tell you a funny story. So I got into a few different battles with the administration folks at Goldman Sachs Asset management, if you remember like in, in college I had a computer business where we’d like buy parts, build computers and sell them. And so I knew how to build my own computers. Goldman Sachs at the time, the standard computer that everybody had was what was called an 8 0 86. This was like the first real PC that that IBM had out there. And, and you know, they were good but they weren’t the most advanced available machines. Basically I went to the administration and I said, look, we need the most advanced machines because we’re trying to run a lot of computationally intensive models. And this machine we have now is very slow. It’s taking very long to run our models. You can buy the latest machine at half the price of what Goldman was paying right. And get twice the performance. What I didn’t realize at the time is that when you’re trying to run an organization that large and complex,
00:10:58 [Speaker Changed] They want everything standardized and
00:11:00 [Speaker Changed] You can’t support it unless everything’s standardized. And so there was a reason for it, which I didn’t understand at time, but
00:11:04 [Speaker Changed] You, you guys can support your own hardware. That’s not that hard.
00:11:08 [Speaker Changed] Cliff eventually persuaded them to give, let us get the, the new machines. But one of the big changes as you talk about leaving a place, you know you have lots of resources and and whatnot at large organizations, but you have limited resources at every place. No matter how big you are. There’s always trade offs that you’re making when you start off as a new firm. One thing that was a big change is that at Goldman we had to support lots of other groups. You know, we were providing research advice, investment advice, talk to clients, help them raise money in other products. When we launched our own hedge fund, all that matter was making money in that hedge fund. So helping that focus was important and we were able to buy the latest computers at half the cost.
00:11:47 [Speaker Changed] I’m gonna bet that you did something a little beefier than those IBM 8 0 80 sixes.
00:11:52 [Speaker Changed] Yeah, I was overclocking the machines. I was doing all the, pulling all the ways to get things to go as fast as possible. Huh.
00:11:57 [Speaker Changed] Really, really interesting. So at A QR you juggled a, a lot of responsibilities. You were a portfolio manager, researcher head of trading, and apparently tech geek putting machines together. What was it like juggling all these different responsibilities?
00:12:13 [Speaker Changed] There’s a couple things I’ll say about that. So one thing, just from a personal perspective, my wife and I, we have five children together and that’s a lot to deal with. My wife is amazing and there’s no way I would be able to do all the stuff I do at work if it weren’t for her being amazing and handling everything at home. So that’s the the first thing. In terms of how I get so many things done at work, I’m also, from a personality perspective, I get bored very quickly. I like learning and doing a lot of different things. I like being able to jump around. So to me that’s just fun. The consequence is sleep. I don’t sleep very much.
00:12:45 [Speaker Changed] What do you mean not very much? And you know, that only gets worse as you get older, right?
00:12:51 [Speaker Changed] We usually get to sleep around 1:00 AM and wake, wake be up, you know, 6, 6 30, something like that. Alright,
00:12:56 [Speaker Changed] So five hours. That’s not terrible. Yeah, that’s not too terrible. I’ve lived on six hours most of my life. Yeah. And it’s, and you get older that that shrinks. I thought you were referencing the five kids ’cause it’s like hey, when you have five kids you learn how to juggle a lot of different things at once. ’cause something is always on
00:13:12 [Speaker Changed] Fire. That’s right. There’s always something going on, that’s for sure.
00:13:15 [Speaker Changed] What was it like working with Cliff back in in the days?
00:13:19 [Speaker Changed] It was fun. I think Cliff’s great at a lot of different things, but one was he hired, well he was able to attract really talented people and then he just let them do what they do. So he is not a micromanager, he just lets them run with it. And so that was a very fortunate thing for me right place, right time in terms of being able to get a lot of responsibility early on. And that’s how I was able to not just be a researcher building models and creating new strategies that I’d run by Cliff. And he would say, okay, you’re doing this dumb or doing that dumb and you gotta improve this. But also doing all the trading by myself for the firm for the first several years and then eventually saying, Hey Cliff, you know, I need some help here. We need to hire, you know, someone to run technology other than me. We need to, you know, hire more traders than just me so that I could actually sleep. So that’s how he ran it and it was a lot of fun. I mean you mentioned it earlier on, I mean, Cliff’s hilarious and
00:14:09 [Speaker Changed] He’s a funny guy and it’s rare to find someone who is a quants who can communicate as eloquently as he can and at the same time has such a devilish sense of humor. Like that’s an unusual trifecta right there.
00:14:24 [Speaker Changed] And it’s part of what makes him fantastic as an individual, but also fantastic to work, work with and work for it. It made the place fun even in the tough times. And so that’s a big reason why I think a lot of people stuck through lots of the ups and downs that any organization has.
00:14:41 [Speaker Changed] Let’s talk a little bit about the A QR experience. The firm seems very, I I almost wanna say academic. They publish a lot of white papers, they do a lot of research, they have very specific opinions on different topics that seem to come up in the world of finance. How much of this intellectual firepower is part think tank and how much of it is just, hey, if you’re gonna have an investment perspective, you need to have the intellectual underpinnings to justify it.
00:15:14 [Speaker Changed] So I think one thing that makes acro very powerful is its ability to attract top talent. Specifically on the academic side. The, you know, smart people wanna hang out with other smart people. That there’s a definitely a network effect that happens there. And I would say part of the compensation you’re getting indirectly by being in an organization like that is getting exposure to all these great minds that you can learn from. You can bounce ideas off of. So is it a think tank? Yeah, I think it is a think tank from that perspective, but at the end of the day, it’s a business and they’re there to make money, make money for their investors. So I think there is a lot of focus on that as well. So the publications, you know, you see a lot of white papers ensure it, I would say it rhymes with a lot of things they do, but they obviously keep a lot of the special sauce unpublished and and use that within their funds.
00:16:05 [Speaker Changed] But they’re still writing about broad strokes. So let’s talk about a white paper that you wrote titled The Evolution of Alpha. Tell us how has Alpha evolved over the past few decades?
00:16:17 [Speaker Changed] Sure. This is a white paper I wrote from my clear alpha C-I-O-C-E-O hat. And it really talks about the history of the hedge fund industry, why different models of delivering alpha, starting with let’s say single strategy, hedge funds, fund of funds, multi-strategy funds, and now multi strategy multi-manager or multi PM funds. And that that’s the latest evolution. And then we talk about what we think might, might be the next step, part of which we think we will, we will drive. So that’s the point of the paper and there’s reasons why you went from different models from one to the next and it has to do with a variety of things. I’d encourage you to read the paper, it’s on our website, but,
00:17:02 [Speaker Changed] So let’s, let’s follow that up. What were the drivers of the shift from a single manager to multiple managers to multi-strategy, to multi-manager, multi-strategy? What was the key driver of that?
00:17:16 [Speaker Changed] Starting back, this is around 2000 let’s say. Obviously hedge funds existed before that, but that’s really the point at which at least a meaningful amount of institutional investors actually started having investments in hedge funds as like a normal course of business. That was the year obviously that the market sold off a lot. There was the Enron fiasco and whatnot. A lot of Wall Street was let go. So a lot of talent was being let go and much of that talent was investment analysts, research analysts that covered stocks, new stocks, deeply knew the management of those companies deeply. So if you’re a investment analyst at a Wall Street bank, you go off and hang up a shingle, start a single strategy hedge fund where you’re picking stocks. You had an argument that why you’d have an edge because you knew these managers and these stocks deeply and that’s really was like a Cambrian explosion of hedge funds at at that moment in time. And even to this day, I think in terms of like sheer number count, the vast majority of hedge funds are really stock picking hedge funds, long,
00:18:12 [Speaker Changed] Short 11,000 hedge funds out there today.
00:18:14 [Speaker Changed] Yeah, yeah. Long short discretionary equity stock picking hedge funds. That model survived for a little while. But as investors were investing in these individual kind of single strategy, single style hedge funds, what they realize is that any one single approach is not very consistent. You know, it’s gonna go through its good periods and its bad periods and was hard to hang on to what I would call the the or be exposed to what the line item risk is. You know, when you have these quarterly reviews of what’s going in the portfolio, invariably the discussion is let’s talk about the things that are down the most. And that leads to, you know, firing managers when they’re down usually just after a, a environment that was just bad for their approach right before it rebounds and does well, you know, in the next year. So that model, well it still exists today is tough from an investment to stick with.
00:19:06 Then you switch to fund of funds institutional investors, you know, one stop shop, buy into a fund to fund, you can get exposure to many different strategies and styles in one vehicle. That’s what came out of that and was to address this inconsistency. So fund to funds were more consistent than a single strategy fund. But I would say the consequence and it’s, or the issue really is both for fund to funds and really for portfolios of hedge funds that investors have. It’s cash inefficient, it’s capital inefficient because most hedge funds have a lot of cash on their balance sheet. Typical hedge fund, it varies, but depending on the type of style and strategy we’ll have between 40 and 90% of the money you give them just sitting in cash.
00:19:50 [Speaker Changed] Really? That’s a giant number. Half is a giant number. I I thought you were gonna go in a different direction. I have a friend who’s an allocator at a big foundation and, and he calls the funder funds funder fees ’cause you’re paying layers on top of layers of fees and it definitely acts as, as a long-term drag. But I never would’ve guessed that 50 plus percent of assets handed to hedge funds are in cash at any one time. I always assumed it was the opposite that alright, they’re, you know, like the 1 30 30 funds or whichever variation you’re looking at, I always assume that they’re leveraged up and even if they’re long, short, all that money’s put to work. You’re saying that’s not the case?
00:20:33 [Speaker Changed] Well technically all the, you know, they will put the money to work in in the sense of it’s not pure cash sitting there, but really there’s a lot of borrowing power. You’ll, a lot of assets that you’re holding. There’s a tremendous amount of borrowing power you can borrow against those assets that you hold to then create a more efficient portfolio. And that’s where kind of multi-strategy funds evolved. So multi-strategy funds gave you the benefit of many different strategies and styles yet put into the same vehicle, all these positions held in the same vehicle to get much more cash efficiency, capital efficiency, higher return on capital plus the consistency.
00:21:06 [Speaker Changed] So I’m assuming if you’re using a multi-manager, multi-strategy approach, any one strategy at any given time is either gonna be doing well or poorly, but the overall performance of a multi-strat will offset that. So it’s not like, hey, this guy has a bad quarter ’cause what they do is out of favor and the clients pull out their cash just before the recovery. Is there a tendency to leave money with a multi-strat multi-manager approach for longer? And so you don’t have those sort of bad quarter, bad month, whatever it is because this just isn’t working now, but it’ll start working eventually. I is that the underlying thinking
00:21:50 [Speaker Changed] That that’s really the approach? In fact, a lot of successful single manager businesses evolve to the multi-strategy approach because they recognize that that lack of consistency for a single approach, a single investing style was a, a threat to their own business. And so expanding into other strategies and styles is how a lot of these more successful single strategy funds evolved.
00:22:14 [Speaker Changed] So it sounds like if you’re running either a multi-manager or a multi strategy or both, everything needs to be very non-correlated. You don’t want everything down at the same time. How, how do you approach picking various strategies that are not correlated?
00:22:31 [Speaker Changed] That’s a great question. I I think it’s helpful. I don’t like the gambling angle, but I think it’s helpful analogy. ’cause most people are con are are used to the, are used to the, the analogy, if you think about the casino, people go to the casino knowing that if they play the games long enough, they’re gonna lose their money. I think most people think that the multi-strategy hedge fund is really like the house where each table or each game in the casino in their house has a slight edge. And if they make sure that there’s not gonna be massive losses at different tables on the same night, same weekend, same month, over time, they will just, just statistically accrue profits in a, in a more consistent manner. So that is a big focus and if you think about what risk managers would do at a casino, it’s the same thing. They’re gonna make sure that these, these tables, these games are not gonna be making or losing money at the same time.
00:23:27 [Speaker Changed] So let’s talk about some of these diversified non-correlated strategies. I’m assuming some include momentum, long, short, any other sort of approaches that people would really readily understand? Sure.
00:23:43 [Speaker Changed] When I think about most hedge fund strategies, the ones that people know about, the ones that there are, if you look at hedge fund indices, there’s a category for it, right? You know, so it could be long short stock picking. It could be merger arbitrage, it could be index free balance arbitrage or basis trading. There’s a variety and there’s like dozens of these kind of well-known well under strategies.
00:24:06 [Speaker Changed] Activist is another
00:24:07 [Speaker Changed] Activist. Exactly. These are all out there. They’re, they’re, they’re well known. When you look at each one of those, you can break it down between kind of cheap passive beta. So let’s take an example. Long short discretionary stock picking most of these hedge funds, the way they’re implemented is the managers net long, the, the stock market. And so some portion of their returns, and it’s actually a pretty significant portion, is just being gonna be driven by whether the stock market’s up or down, just
00:24:31 [Speaker Changed] Pure beta,
00:24:31 [Speaker Changed] Pure beta. And that’s, that’s a, I think about the, the scarce resource is your risk budget and how do you wanna allocate that risk budget If you’re allocating a lot of your risk budget to just pure beta, that might work for the manager. But for an investor that doesn’t make a lot of sense because I can go and get pure beta, I can buy an index fund for, you know, single digit basis points at this point. It’s effectively free these multi-strategy funds in order to reduce the correlation across their managers. They don’t wanna have all these managers long, pure beta. That’s a common risk that will cause ’em to make and lose money at the same time. And so when you’re running a multi-strategy fund, it’s really about looking at these common risks. Beta is the simplest example. It could be sector exposure, it could be factor exposure like momentum you mentioned earlier. And there’s a lot of other less well known, but known in the industry risks that take place. You know, people talk about crowding, there’s reasons why crowding happens. So being able to be aware of those and look for signs of that and trying to mitigate those commonalities across your different strategies is a really key component to managing risk for these multi-strategy funds.
00:25:36 [Speaker Changed] Huh. There’s so many different ways to go with this. So you’re, you’re implying with these crowded funds that there’s a way to identify when, when you’re in a crowded fund. I, I recall the quant quake a couple of years back where all these big quant shops post GFC really seemed like they were having the same sort of exposure and the same sort of problems. How can you identify an event like that before it takes your fund down 10, 20%?
00:26:07 [Speaker Changed] That’s a great question. And I would say a more recent example might be covid March of 2020 when there, so I talked about a, a couple different common risks. One is beta one, another one might be factors, a simple other one is just, there’s a well-known strategy, let’s say merge arbitrage. You know, there are plenty of funds that are running merge arbitrage is one of their strategies within the fund. Okay. Simply because a lot of people are doing something that in a sense, when there is some other exogenous event that causes people to de-risk, it actually makes it bad to be in well-known, well understood trading strategies so that you know ahead of time that this is something that is crowded. You know, that there are other players that are doing the same kind of trades as you going in.
00:26:54 [Speaker Changed] Huh. That’s really interesting. And, and just to put some meat on the bones, multi strategy, multi-manager, multi-model funds have really gained prominence lately. Names like Citadel, point 72, millennium, lots of other larger funds have very much adopted this approach. Fair statement.
00:27:15 [Speaker Changed] That’s very fair. I I do think it’s the best way to deliver alpha.
00:27:20 [Speaker Changed] So you’re reducing correlation, you’re reducing risk, you’re increasing the odds of about performance at how broad are firms like, I dunno, citadel or or Millennium, that they don’t run into that crowded trade risk. You would think given their size and their tens of billions of dollars, a crowded trade becomes increasingly more likely. Right?
00:27:42 [Speaker Changed] Right. And there, there’s a reason for why that’s the case. There are literally thousands of different types of ways to make money in the markets. Thousands. But there’s only dozens of ways of making money in the markets that have lots of capacity. Means you can put a lot of dollars and generate a lot of dollars of
00:27:57 [Speaker Changed] Panel to scale up.
00:27:58 [Speaker Changed] To scale up. And if you’re gonna be a very large fund, you by definition have to put more and more of your money into the well-known large trading strategies. And so they have to be particularly attuned to the fact that they’re large and their competitors are also large and then they’re same kind of trades. So it is at risk. And when these things, you know, when one of these shops sells auto or reduces risks in one of these common strategies, it’s going to affect the other ones. It’s, it’s hard to avoid that, but they are fairly well diversified across many different types of strategies. So that’s why you see still very consistent returns. But there is this exogenous risk element of of having, being big in the crowded, the way you avoid that is by being smaller, focusing on smaller strategies that are a little bit different.
00:28:40 [Speaker Changed] Huh. Really, really interesting. So you mentioned earlier, early days of hedge funds, the fund to funds were popular, it feels like they’re kind of going away. You certainly hear much less about ’em these days. Is that a fair assessment? Just because you don’t hear about stuff doesn’t mean it’s disappeared. But I certainly read much less about funder funds. They, they are in the news much less have multi-manager, multi-strat, multi-model broad funds replace the concept of of funds.
00:29:12 [Speaker Changed] I think it’s an evolution. It doesn’t mean that the fund of funds model is going away entirely. There’s certain managers out there who have commingled vehicles that only you know that they won’t run an SMA for you. They won’t trade their strategy into your account. Fund of funds can access that. So there’s a reason for that. And you know, they, they’re nice one-stop shops and they can maybe a little more transparent. But there are, you talked about this earlier, the, the fees being an issue and it’s really about the fee is a percentage of the dollars of p and l being earned. There was an academic paper recently published that did a really interesting study over 10 years of looking at institutional hedge fund portfolios. What it showed is that for every dollar of p and l being generated by these hedge fund strategies, at the end of the day, the institutional investor took home about 37 cents.
00:29:59 [Speaker Changed] Really.
00:30:00 [Speaker Changed] Which is I think a shocking number for a lot
00:30:02 [Speaker Changed] Of people. Right, right. So you’re saying almost two thirds of the money never e either it’s fees or costs or, or some other factor but only le a little more than a third ends up with the actual investor.
00:30:15 [Speaker Changed] That’s right. And it’s, it’s, they actually, it’s really interesting. It breaks down the sources of all these things. Part of it is fees and double layers of fees and things like that. A big part of it is the behavioral nature, which I think is driven by governance of investing organizations where
00:30:31 [Speaker Changed] Filled with humans. Yeah. Yes.
00:30:34 [Speaker Changed] Strategy is down. What’s been down, let’s get out of that. Let’s get into the thing that’s been up recently that costs about a third of, of your
00:30:40 [Speaker Changed] Alpha. That doesn’t surprise me at all. Even though you expect big endowments and foundations and hedge funds to be smarter than that. Fill ’em with people and you’re gonna get those behavioral problems, aren’t you? Yeah,
00:30:52 [Speaker Changed] Well there’s agency issues in between and I think investors are, well, well aware of these. So that causes part of it too. But a big thing and then the thing that kind of the multi- manager, multi-strategy approach tackles that a fund of funds can’t, is you get a lot of netting benefits both from, you know, one manager’s long Apple, another manager’s short apple, right? And a fund to fund approach where you’re investing in two different funds. Well, A, they don’t know that, right? And B, the managers who long Apple, they’re paying a financing spread to go, you know, leverage long apple and the managers’ short is paying a financing spread to go short apples. A lot of costs built in. You’re paying a lot of extra costs there
00:31:28 [Speaker Changed] Just to be net flat. Just
00:31:29 [Speaker Changed] To be net flat. So if those two managers instead traded those positions into the same vehicle, you’re getting that efficiency and that’s worth, you know, on the order of like two to 3% per year, just that alone, the enhanced risk management you can get by having daily position transparency and all the trades of all the different PMs they’re doing, being able to hedge out all these beta risk factor risk sector risks, things like that allows you to be much more efficient with how you deploy that capital. And so you, you see that these multi-manager funds tend to be a little more invested than a hedge fund portfolio typically could be. And that creates a lot of efficiencies. And so when you look at the returns that they’re generating, you know, it’s closer to like 50 50, we’re like for every dollar that’s generative p and l 50 cents is going for the investor. So it’s a much more efficient delivery mechanism of alpha.
00:32:18 [Speaker Changed] So we were talking earlier, and I mentioned off air that the funny element of individual investors tending to underperform their own investments. I know you’ve done some research on that. Tell us a little bit about what you see.
00:32:34 [Speaker Changed] Yeah, this is really something that’s very important to me in terms of when I think about the industry and like what are the big problems that are, that are facing the industry, what’s really causing investors not to get as much money in their retirement accounts as we possibly could get there. One of them is this behavioral issue, which I think also ties to like incentives and governance and agency issues with within investing organizations. Morningstar does a study that they call Mind the Gap and they do it on a regular basis. Some of your listeners might have heard, heard this and it’s definitely worth reading. I’ll quote some numbers off the top of my head. I I might be remembering it incorrectly. But what it does is it’s measuring the time weighted returns of funds, which is the returns that funds report. These are the returns that if you invested a dollar at the beginning and you held it all the way through the returns you would’ve gotten if you never went to or went outta that fund, then they compare that to the asset weighted returns, right? And that is gonna, the asset weighted returns are, you know, counting for the fact that, you know, the fund does well, everybody gets excited, money comes in larger assets and then it maybe does not as well after that. And so the larger assets earn less return. And so the asset way to return minus the time way to return is a really good way to measuring what’s the actual i in impact of this behavioral element of investing, which is a really critical part of investing.
00:33:55 [Speaker Changed] And, and the gap refers to the behavior gap, which is the difference between what the fund generates and what the actual investors are getting. Yeah, please continue.
00:34:04 [Speaker Changed] And, and so what you find is that for six, like 60 40 balance funds, which typically are in retirement accounts where people maybe aren’t looking at them every single day, they get statements once a quarter that are delayed
00:34:17 [Speaker Changed] Set and forget, just leave it alone for
00:34:18 [Speaker Changed] Decades. It’s kind of set and forget. Yeah. That, that gap is on the order of 60 basis points. Relatively
00:34:23 [Speaker Changed] Small,
00:34:23 [Speaker Changed] Relatively small, but it costs still, it costs 60 basis points per year for the average investor of this beaver for those simple funds. Now for alternative funds, when they look at those, that gap is 170 basis points a year.
00:34:35 [Speaker Changed] Okay. That’s starting to add up that
00:34:36 [Speaker Changed] Really, I mean if you think about that compounding over a decade, sure that’s a massive hit to wealth. Why is there such a big gap for alternatives and not as much of a gap for the 60 40? I think it has a lot to do with investor understanding of what those products are and therefore the confidence people invest in alternatives, they don’t necessarily understand them. And so you’re setting yourself up for failure a little bit there because when it has bad performance you don’t understand what it does, you’re more likely to redeem. That
00:35:06 [Speaker Changed] Makes a lot of sense.
00:35:07 [Speaker Changed] So to me, investor education really understanding what they’re investing is, is a critical component to being a successful investor.
00:35:13 [Speaker Changed] Huh, really, really interesting. So you talk a lot about idea meritocracy, it’s on your site, you’ve written about it. Explain a little bit what is idea meritocracy?
00:35:24 [Speaker Changed] This is a really important part and it’s a part of our culture at Clear Alpha. The idea is to get all ideas surfaced so that the organization can make the best decisions. How do you, you know, what prevents good ideas from surfacing one is that people may not know that, you know, a question’s even being asked. So many organizations are run fairly siloed, different groups and, and a lot of that happens, especially large, large organizations, it’s hard for everybody to be constantly communicating with one another. So just not even knowing a question exists. So what the way we address that is that we use Microsoft teams at, at the office and most people are in various channels and we’re seeing questions going on all the time. I really discourage people from asking me a one-on-one question and I will usually re redirect a question. Someone ask me to, here’s the broad company, here’s the question that was asked, here’s the answer.
00:36:17 So then immediately the entire company learns, you know, what this topic was. And very often that says, oh someone else, I have another idea about that that I want to now share. So getting accessibility for people to deliver. But the most important about idea of meritocracy is really from a leadership standpoint, people have to feel safe bringing up ideas that they’re not gonna get, you know, yelled at. You know, there’s no, there’s no bad questions there. There’s only people not asking questions. That’s, that’s what bad. And the only way that that for people to feel safe about that is that they need to see me as the leader and my, my other partners as the leaders to be willing to take in feedback, be challenged even publicly and say, you know what? That’s a really good idea, let’s go with that. And so just having them feel that safe environment so that people can always ask and bring questions up.
00:37:10 [Speaker Changed] Huh. You that, that’s really interesting. Also, you’ve discussed generating less common ideas. Earlier we were talking about crowded trades. How do you generate less common ideas? How do you find non-correlated sources of return when you’re, you know, in a hypercompetitive marketplace?
00:37:29 [Speaker Changed] Great question. So I’ll, I’ll use an example here. There’s a common strategy that people might be familiar with. It’s called merge arbitrage. And basically company A is gonna buy company B, whether it’s for cash consideration or stock for stock type transaction. And you know, merge arbitrages look at that and they might go, you know, long the company that’s being acquired short, the company that’s doing the acquirer and then make money if that deal ultimately closes. That’s a, that’s a very common well known strategy that would be the common version of implementing this strategy. A less common version to implement is you try to find ones that you like more than others. So you might think they all are like the vast majority are going to close, but some you might like better than others. And so you could go long half of them and short half of them. So you’re not exposed to this common element of merge arbitrage deals closing, you’re neutral to those. So if a large pod shop, you know, one of these large multi managers, if they decided to get out of merger arbitrage and they’re selling all these positions down half your portfolio will get helped and half your portfolio will get hurt. But you’re less exposed to that crowding risk and that common, what I would say risk factor that these other common strategies have. So that’s a niche version of how we might implement that kind of a strategy.
00:38:46 [Speaker Changed] You, you mentioned niche, I never heard the phrase prior to reading something you had written called Niche Alpha. Tell us a little bit what Niche Alpha is.
00:38:56 [Speaker Changed] That’s a great question. The simple answer is you’re unlikely to have any or, or much of it in your hedge fund portfolio. That, that’s how I would describe it. And so it’s looking for people that are either implementing common strategies in a very different way that makes them less susceptible or more immune to people getting out of that strategy. Or people have a completely different idea of how to make money that I haven’t heard of before. And I’ve interviewed hundreds if not thousands of portfolio managers and worked with develop many strategies of my own. So it’s trying to find things that people aren’t doing. Huh.
00:39:31 [Speaker Changed] Is there, given what we know about the efficient market hypothesis and Gene Fama was Cliff Asness doctoral advisor, is that what or MBA advisor
00:39:42 [Speaker Changed] Cliff Cliff was Gene’s ta.
00:39:43 [Speaker Changed] Yeah. So given how mostly efficient the market is, is are the really nies left that have not been discovered, how, how many more opportunities are out there that we don’t know about?
00:39:57 [Speaker Changed] That taps into something we talked about earlier, which is there are thousands of ways to make money in the markets. There’s only dozens of ways to make money in big dollar size in the markets at scale. At scale.
00:40:09 [Speaker Changed] So these smaller ideas, is that where the mostly kind of eventually efficient market do hasn’t quite reached yet?
00:40:18 [Speaker Changed] Well it’s what I think about is the amount of dollars you can make. This is the ratio ratio I think about the amount of dollars you can make divided by the complexity or how much brain damage you have to inflict upon yourself to actually implement the strategy. A lot of these small strategies, they’re complex and, and and difficult to do. They might require, you know, some kind of new technique that is, is difficult or or rare to implement. And the actual p and l that you can generate profit loss you can generate is small, valid for that effort.
00:40:47 [Speaker Changed] Small in terms of percentage returns or small in terms of dollars. Hey there’s only a hundred million to arbitrage away with this. And once that is mined, that’s it. It’s, it’s done. It’s
00:40:57 [Speaker Changed] About dollars of p and l you can extract from the markets per year. Percentage returns can be very high for these strategies. But I’ll give you a sense, you know, most other large shops, they’re gonna look for strategies that can generate at least a hundred million dollars of p and l to make it worth their while to, to invest. We’re looking at strategies that are generating 10, 20, 30, $40 million per year.
00:41:16 [Speaker Changed] Huh. That’s really kind of intriguing. So what sort of demand is there for lower capacity strategies? I mean, so you guys are less than half a billion dollars, you’re not a a an enormous fund. Yep. Are there more hedge funds looking to swim in these ponds or is this something that hey, once you cross a certain size you just have to leave behind and stay with those larger capacity scalable strategies?
00:41:44 [Speaker Changed] Yeah, I think this is a general thing for all investors, not just other hedge funds. Everybody wants to be in the interesting things. They want to be in the lower capacity things. They know that they’re less crowded. The difficulty, and really what I think a kind of our business model is, is you’re paying for us to go out and search the world and source them because it’s expensive, it’s expensive exercise to do. People might not have the expertise or the the background to underwrite these types of strategies. It just takes a lot of work. And at the end of the day, alpha is either about being smarter or working harder. The being smarter can work in the short term, but eventually that does get our way. Eventually someone smart enough comes by. The working harder to me is the thing that actually stays.
00:42:23 [Speaker Changed] Huh, that’s really interesting. You would think if the incentive was there enough, people would just eventually grind away in that space. I mean
00:42:31 [Speaker Changed] The incentive’s there, it’s just not enough to be worth the time. And so if you are a very large invest organization, you do have to prioritize. You still have limited resources and time to, to look for things. So you’re gonna have, you know, thresholds, I’m not gonna invest at least, you know, at this amount of dollars. And that’s, that’s where we step in is kind of fill that gap.
00:42:51 [Speaker Changed] So you’re very much a student of what’s going on in in the hedge fund world. What are you seeing in terms of strategies, driving costs down and the question of where fees are, they’ve certainly pulled back from the days of two and 20. What’s happening in terms of efficiency and cost?
00:43:09 [Speaker Changed] There’s a bunch of things to talk about there. So first thing I would say is the higher capacity strategies that have become well known, I think that those costs are going down because there’s a lot of people who can implement those strategies. And so you think just simple supply and demand, lots of portfolio managers who can do them. And so then it’s just a competition of who’s gonna be able to do it most efficiently. Then there’s unique alpha. I think that’s harder. And actually the cost of that has gone up over time. It’s not gone down. The, the cost it takes to compete in in the space has increased over time. And so there’s a bifurcation that’s been going on. We think that there’s still a lot of efficiencies you can carve out of the system that exists now that we’re attacking a lot, a lot of lot through technology, a lot of through ways of working that can just make the organization more efficient and deliver more net returns to investors.
00:43:56 [Speaker Changed] So we’ve seen some motion towards fees for Alpha, not beta, some people call it pivot fees. There’s like a lot of different names for this. I haven’t heard much about that recently. What are your thoughts on where hedge fund fees are going in the future?
00:44:13 [Speaker Changed] I’ll answer that with a different story that will draw an analogy here. With the rise of indexing, which has been happening for decades now and thank God for indexing, it’s a fantastic invention that has helped a lot of investors. The original thought was, well as the market goes more and more indexing and I dunno what the number is, it’s probably 70% is indexed of the invested dollars. Then it makes the markets, you know, it’s easier to make money ’cause there’s less people trying to compete for that. But that’s not what actually happens. What actually happens is it’s, it’s become more and more difficult to make money. ’cause the talent pool is of higher quality now than it used to be. That’s searching for that alpha and just like sports when there’s a zero sum game, right? Right. And it’s just, it’s very small differences between, you know, the number one person and the number five person. What you see is the, the, the rewards and the compensation tends to be a power law, meaning that it, the, the very few get get paid a lot. And I see for pure alpha where there’s real competition that the the investment talent will actually get paid more and more over time and it’ll get more and more difficult to be that person. Whereas for the common stuff, the well-known things that have higher capacity, I think you’re gonna see fees keep going down on that side.
00:45:37 [Speaker Changed] Michael Mobin calls that the paradox of skill that the more skillful the players are, whether it’s sports investing business, the more of a role luck plays, which is really, really kind of, kind of fascinating. Before I get to my favorite questions that I ask all my guests, I I just have to throw you a little bit of a curve ball. So you are a member of the Yale New Haven Children’s Hospital Council. Tell us a little bit about what you do with that.
00:46:08 [Speaker Changed] Sure. So just how we got involved, my wife and I, we, we have the five kids, three of which had severe peanut allergies and we were very concerned about that. You know, that’s become a, a rising epidemic within society over time. And we wanted to see if we could solve that, invest in basically research, try to, to solve this problem. So we worked with both Yale and our local hospital to can we, you know, fund a research effort and a clinical effort to basically collect data. ’cause a lot of the research really needs data. So we worked with them and that’s how we got originally involved with, with Yale as an organization. And then they have this council that’s focused on children’s health issues. And what it is, it’s a collection of individuals who are interested in this topic. We meet typically quarterly, they’ll have, you know, some of their top researchers from Yale come in and talk about whatever research they’re working on and and their clinical experiences with, you know, children as patients. And that usually generates ideas, okay, how can we make this more effective? How can we get more funds directed toward this activity?
00:47:13 [Speaker Changed] You’ve also written about portable alpha discuss, discuss portable alpha, what is that and how can we get some,
00:47:20 [Speaker Changed] So I think portable alpha is a, is a great way for investors to get exposure to alternative return streams. What portable alpha is, is mixing a beta like s and p 500 exposure with an alpha stream and really just plopping that alpha stream on top of the s and p 500 returns. So it lets investors get exposure to s and p, which most investors already have, but now exposure to a different type of return stream. Usually people historically at least have tried to be the s and p by picking a manager who’s trying to pick stocks, overweighting stocks they like versus the index and underweighting stocks they don’t like. But that comes with a lot of constraints. One is the manager can only overweight and underweight stocks in the index. They can’t trade other asset classes, they can’t, you know, utilize any kind of sophisticated investment techniques to try to beat that benchmark portable alpha, get rid of all of those constraints. And so what you typically see is portable alpha programs are much better at, in consistently beating traditional active programs. I,
00:48:21 [Speaker Changed] I like the phrase Cory Hte uses for that return stacking is that same concept that right as portable alphas. That’s right. Yeah. Really, really interesting. Alright, we only have you for a, a couple of minutes. Let’s jump to my favorite questions that we ask all of our guests. Starting with what are you streaming these days? What’s keeping you entertained? Either Netflix podcast, Amazon, whatever.
00:48:45 [Speaker Changed] My wife and I, after going through the litany of all the kids and their issues each day, it’s usually very late. And so we don’t get to watch as much TV as you probably would like. There’s a lot of great content out there. Lately we’re watching Lioness on Paramount, which is,
00:48:58 [Speaker Changed] I just finished season one a few weeks ago and taking a break before season two. But it’s fantastic.
00:49:03 [Speaker Changed] It’s fantastic. Yeah, we’ve really enjoyed it so far. But I would say Are you,
00:49:08 [Speaker Changed] Are you up to season two
00:49:09 [Speaker Changed] Yet? No, we’re three or four episodes in. Oh well to season one
00:49:12 [Speaker Changed] Brace Yourself, you have quite a ride.
00:49:14 [Speaker Changed] Okay, great. But in terms of like favorite shows, one of my favorites was the remake of Battlestar Galactica, which was a show when I was growing up as a kid with a
00:49:24 [Speaker Changed] Re with terrible special effects in the old one. Yes. And the new one is great, right?
00:49:28 [Speaker Changed] That’s right. And there’s, there’s a scene that’s actually relevant to our conversation a little bit today. The leader of the cy, which is like the robots is talking with a human. He is one of the, the fighter pilots and they’re watching a video of one of the battles and the humans win this battle. But then the cylon says, this is how we’re gonna beat you. And human’s like, what do you mean? Because they just watch, like one of the humans kill one of the, the robot fighter pilots and she says, well, every time that we make a mistake and, and we lose a battle, every single other silo learns from that. And so inevitably we will learn every way that we, you know, can avoid dying and we will take you over. And that has a lot to do with how we approach the business on the investing side. Always learn from mistakes, get the communication out there and constantly improve. If you improve by a few percent a year, that really compounds over time.
00:50:32 [Speaker Changed] Well what does it matter? If the AI silences eventually are gonna kill all of us, it won’t, won’t make any difference. Al Alpha is only here until the, the Cy beat us in a space battle. Yeah.
00:50:43 [Speaker Changed] We, we, we view it
00:50:45 [Speaker Changed] That’s way off in the distance anyway.
00:50:47 [Speaker Changed] That’s it. We, we like intelligence augmentation versus artificial intelligence. Okay. So IA instead of AI using these tools to be more effective.
00:50:55 [Speaker Changed] That, that makes a lot of sense. Let’s talk about your mentors who helped to shape your career.
00:51:02 [Speaker Changed] Well, I would say, of all the ones I could think of, cliff would be the, the top mentor. And Cliff wasn’t the kind of guy who would you know, put your brand, his, his arm around you and say, Hey, you know, this is how you do X, Y, and Z and you should do this differently. He did have a good several conversations with me like that. Most of his mentorship was through his actions. Cliff’s extremely principled, very ethical, and it’s, it’s a very fortunate thing to be able to be in business with someone like that where you can be successful at business but do it in a very ethical, principled way that’s always doing right by the client. And that’s something, some of the biggest things I’ve taken away from working with them. Let,
00:51:40 [Speaker Changed] Let’s talk about books. What are some of your favorites and what are you reading right now?
00:51:44 [Speaker Changed] I like history, specifically financial history. The one I’m reading right now is called The World For Sale. It’s actually written by a couple of journalists that cover the commodity industry and it’s really about the physical commodity traders and the whole history of that, which is, which is kind of interesting. I love biographies. One of particular I liked was the Michael Dell one played nice, but Win where it’s kind of chronologically, it’s his whole story. I really connected with the building computers in his dorm and selling them. Obviously he was much more successful at that than I was. Hmm,
00:52:15 [Speaker Changed] Really interesting. Any chance you read McCullough’s Wright Brothers?
00:52:19 [Speaker Changed] I have not
00:52:20 [Speaker Changed] Really Fascinating. I like it’s, it’s unusual to read something that you think, oh, I know that history. And then it’s like, no, you have no idea what’s going on in that history. Yeah. And it, he’s just a great writer. Really, really, really interesting. Our final two questions. What sort of advice would you give to a recent college grad interested in a career in either quantitative or investment finance?
00:52:45 [Speaker Changed] I dunno if the advice would be specific to those things, but talk less and listen more is what I would say. I, there’s a curve, I forget the name of the curve, but it’s, you know, you start thinking, you know, a lot, especially Dunning Kruger. Yeah. Dunning Kruger. That’s what it’s, yeah. That is such a true effect. I, I thought I knew everything being, and if I just listened to those around me, who knew a lot more people are trying to help you more than you realize as a young person. And I should have just listened to more advice. I would’ve been more successful, much more earlier if, if I had
00:53:22 [Speaker Changed] So, so here’s the funny thing about the Dunning Kruger curve, and this comes straight from David Dunning. They did not create the Dunning Kruger curve. It kind of came from just pop psychology and social media. And then when they went back and tested it, I think the paper was like 99 or 2004, something like that, when they went back and tested it, it turned out that the Dunning Kruger Curve turned out to be a realistic, measurable effect. And it’s mount stupid. The Valley of despair and the slope of enlightenment are just sort of the, the pop terms of it. But, but it’s really, really funny. And our final question, what do you know about the world of investing today? You wish you knew back in the early nineties that would’ve been helpful to you over those decades?
00:54:15 [Speaker Changed] There’s a lot of smart people out there. As smart as you might be, there’s a lot to learn from everybody else. Everybody has some insight, some perspective that you don’t have, don’t presume how that, you know, what people are thinking. So ask questions and, and listen. Sounds
00:54:36 [Speaker Changed] Like good advice for everybody. We have been speaking with Brian Hurst, he’s the founder and CIO of Clear Alpha. If you enjoy this conversation, well be sure to check out any of the 530 we’ve done over the past 10 years. You can find those at iTunes, Spotify, YouTube, Bloomberg, wherever you find your favorite podcasts. Be sure to check out my latest podcast at the Money Short, 10 minute conversations with experts about topics that affect your money, spending it, earning it, and most importantly, investing it at the money wherever you find your favorite podcasts. I would be remiss if I did not thank the correct team that helps us put these conversations together each week. Sarah Livesey is my audio engineer. Sage Bauman is the head of podcasts. Sean Russo is my researcher. Anna Luke is my producer. I’m Barry Ritholtz. You’ve been listening to Masters in Business. I’m Bloomberg Radio.
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