Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Masters in
Speaker 1: Business with Barry Ritholt on Bloomberg Radio.
Speaker 2: This week on the podcast, yet another extra special guest.
Speaker 2: Brian Hurst is founder, CEO, and CIO of Clear Alpha.
Speaker 3: They are a.
Speaker 2: Multi manager, multi strategy hedge fund that has put up
Speaker 2: some pretty impressive numbers. His background is really fascinating. Cliff
Speaker 2: Astness plucked him out of the ether to be one
Speaker 2: of his first hires at the Quantitative Research Group at
Speaker 2: Goldman Sachs. He was the first non founding partner at AQR,
Speaker 2: the hedge fund that Asna set up, and Brian worked
Speaker 2: there for a couple of decades before launching Clear Alpha.
Speaker 2: He had as a fascinating perspective on where alpha comes
Speaker 2: from as well as the entire hedge fund industry. Few
Speaker 2: people have seen it from the unique perspective he has,
Speaker 2: and I think he understands the challenges of creating alpha
Speaker 2: where it comes from and managing the risk and looking
Speaker 2: for ways to develop non correlated alpha that is both
Speaker 2: sustainable and manageable from a behavioral perspective. I thought this
Speaker 2: conversation was absolutely fascinating and I think you will also
Speaker 2: with no further ado my interview with Clear Alpha's Brian Hurst.
Speaker 4: Thank you very appreciate it.
Speaker 3: Good to have you back here.
Speaker 2: Last time you were on a panel, we were talking
Speaker 2: about the rise of some emerging managers, including yourself. But
Speaker 2: let's go back to the beginning of your career Wharton
Speaker 2: School at the University of Pennsylvania. You graduate with a
Speaker 2: bachelor's in economics. Was quantitative finance always career plan?
Speaker 4: That's a great question. I think when I went to school,
Speaker 4: I didn't even know quantity of flants was a thing,
Speaker 4: and frankly, at that point in time, it really wasn't
Speaker 4: much of a thing. I was taken him by my dad.
Speaker 4: He was an accountant and CFO of a commercial real
Speaker 4: estate company. He would take me to the office, and
Speaker 4: I was really fascinated by business. I really wanted to
Speaker 4: get into that. I was into computers. I learned how
Speaker 4: to teach myself how to program and things like that.
Speaker 4: But I wanted to get into business, and I said, Dad,
Speaker 4: I want to get into real estate. And my dad
Speaker 4: gave me some really good advice. He said, Brian, if
Speaker 4: you think about finance as an org chart, real estate
Speaker 4: is like one of the divisions and if you start
Speaker 4: in real estate, it's hard to move up and go
Speaker 4: to other divisions and try other things out. You should
Speaker 4: really learn corporate finance and you can always switch to
Speaker 4: real estate if you wanted to. And corporate fans is
Speaker 4: kind of the top of the umbrella or the org chart.
Speaker 4: And I said, okay, well what's corporate finance and where
Speaker 4: are I go to learn that? He's like, well, you
Speaker 4: should go to Wharton And then I said, well, what's Wharton?
Speaker 4: That's how it started.
Speaker 3: That's hilarious.
Speaker 2: You finish up at Pennsylvania and you begin your career
Speaker 2: at DLJ.
Speaker 3: What sort of work.
Speaker 2: Were you doing and what were your classmates doing? This
Speaker 2: is the early nineties.
Speaker 3: You started DLJ.
Speaker 4: Yeah, I did DLJ. It was interesting. That was my
Speaker 4: summer year between junior and senior at Warden, and they
Speaker 4: kept me on throughout my senior year to finish up
Speaker 4: an interesting project, which is basically automating the job of
Speaker 4: the investment analyst that we're doing all the company working,
Speaker 4: all the tank k's, tank q's, all the information. At
Speaker 4: the time, there was a new company starting up and
Speaker 4: I know on Bloomberg, but it was called fact Set
Speaker 4: at the time. Of course, and there was a salesperson
Speaker 4: walking around trying to get anyone to talk to them
Speaker 4: because this is a brand new company. And I was
Speaker 4: a summer analyst and I was like, I've got time,
Speaker 4: I'll talk to you. And he showed me, first of
Speaker 4: all two things. She showed me this thing called Microsoft Excel.
Speaker 4: At the time, everybody was using Lettus one, two three,
Speaker 4: and he showed me basically how you can type in
Speaker 4: a ticker and that pulls in all of the financial
Speaker 4: information right into this cheat for you before the internet,
Speaker 4: but you know what was kind of the internet at
Speaker 4: the time. I was like, wow, this is amazing. I
Speaker 4: was like, this could save me hours and hours of work.
Speaker 4: And so I went to the MD at the time
Speaker 4: and I said, hey, I think I can automate most
Speaker 4: of what the analysts are doing. He said, you're a
Speaker 4: summer intern. We're not paying you much. Go at it.
Speaker 4: And that's what I did. So I started off in that,
Speaker 4: but I mainly learned that I didn't want to do
Speaker 4: investment banking because it didn't hit on my course skill set,
Speaker 4: which was like engineering back down quantitative techniques and tools.
Speaker 2: That sounds really interesting. It's amazing to have that sort
Speaker 2: of experience as an intern, How did you land at
Speaker 2: Goldman Sachs.
Speaker 4: Like everything in life that works out well, that's you know,
Speaker 4: a lot of hard work but mostly luck. Because of
Speaker 4: the DLJA experience, that was a good thing to have
Speaker 4: on my resume. Cliff Asnas founder of AQR Capital, managing
Speaker 4: partner there at the time. I think it was late twenties.
Speaker 4: He was finishing up his PhD at the University of
Speaker 4: Chicago and was working for Goldman Asset Management. He got
Speaker 4: the mand to launch a new quantitative research group, and
Speaker 4: so he wanted to hire someone who had both the
Speaker 4: finance background and the computer science background. I had started
Speaker 4: with a couple of friends a software business in high
Speaker 4: school and at Penn. One of the things I did
Speaker 4: with my roommate was we started up a hardware business,
Speaker 4: kind of like Michael Dell, building and selling computers to
Speaker 4: faculty and students on campus. So I had the computer
Speaker 4: science background. Cliff had gone undergrad at Penn at Wharton also,
Speaker 4: so he knew that we'd taken the same kind of courses.
Speaker 4: We spoke the same language from that perspective, and I
Speaker 4: had that technology background. So I was his first tire
Speaker 4: as he was building out that new team. What my
Speaker 4: other colleagues did back then, you had basically three choices
Speaker 4: come out of Warden. It was accounting, investment, banking, and consulting.
Speaker 4: There was really no jobs for asset management, but those
Speaker 4: are the courses I love the most at Penn and
Speaker 4: really wanted to pursue that. So it was a great opportunity.
Speaker 2: So you spend three years or so at Goldman with Cliff.
Speaker 2: By that point he had been there for a while
Speaker 2: and decided, hey, I think I have a little more
Speaker 2: freedom and opportunity to find launch a fund on our own.
Speaker 2: You were there day one, you left with him, right,
Speaker 2: tell us a little bit about what it was like
Speaker 2: standing up AQR with aastness.
Speaker 4: It was great. We started off this little background there
Speaker 4: as a research group within g SAM so think cost
Speaker 4: center and just putting some timeframes around this. This is nineteen
Speaker 4: ninety four, which is one of the toughest years in
Speaker 4: Goldman's history, even going back to the Great Depression. It
Speaker 4: was the kind of year where trem and a partner
Speaker 4: you get to put in money. Wow, which was was
Speaker 4: it that bad a year?
Speaker 3: I don't remember. Ninety four is a terrible market year.
Speaker 4: That was the year where the Fed had the surprise
Speaker 4: significant rate hike in feb I was actually on the floor.
Speaker 2: I think bonds took a whack, but equities also wobbled
Speaker 2: a bit.
Speaker 4: Is that a well a bit? But yeah, it was
Speaker 4: really a bad year for fixed income and the firm
Speaker 4: had a lot of risk and fixing, I presume, which
Speaker 4: led to the tough year. Yeah. So we were a
Speaker 4: research group, cost center, and then left in people were
Speaker 4: disappearing week by week as they were cutting down really headcount,
Speaker 4: and so quickly we realized we've got to start gendering
Speaker 4: some revenue. We want to say, alive. And Cliff went
Speaker 4: to them and said, hey, we've been we built some
Speaker 4: interesting models. We think we're good at picking stocks and
Speaker 4: futures and things like that. We think we can trade
Speaker 4: on this and make some money. He convinced the partnership
Speaker 4: to give us some money. So it's basically a prop
Speaker 4: trading effort. For a little while, it did very well.
Speaker 4: They kept adding money to it, and then we opened
Speaker 4: it up and turned it into a fund. It was
Speaker 4: really Goldman's first real hedge fund coming out of g
Speaker 4: SAM that funded very well, which really opened the door
Speaker 4: for us to be able to leave and start up
Speaker 4: and raise money as an independent hedge fund.
Speaker 2: What were the specific strategies Cliff was running at g
Speaker 2: SAM with the partner's money.
Speaker 4: It was a multi strategy approach, but it was all quantitative.
Speaker 4: And when I say quantitative, that means a lot of
Speaker 4: things to different people. I think about every good investment
Speaker 4: process is really a process, and whether people would label
Speaker 4: as quantitative or or not is really how automated it is.
Speaker 4: And so by quantity of I mean like really automated
Speaker 4: downloading public data for the most part, pumping it through
Speaker 4: some systems, and that causes you to want to buy
Speaker 4: and sell different instruments around the world.
Speaker 2: But you're still creating or Cliff at the time was
Speaker 2: creating models, and the models would give him a ranked
Speaker 2: list of Hey, the top ten stocks on this list
Speaker 2: of a thousand are really or whatever the number is,
Speaker 2: are things you want to look at, either getting long
Speaker 2: or short based on whatever that model is.
Speaker 4: That's right. So that you'd have many different signals, and
Speaker 4: we're treading many different asset classes, and so it's like
Speaker 4: you're saying all those signals you would givefferent weights different signals,
Speaker 4: and those would add up to you like these things,
Speaker 4: you don't like these things. We would trade global equities
Speaker 4: in a bunch of different countries, but market neutral so
Speaker 4: long as much as you are short, so you're not
Speaker 4: taking a bet on is the market going to go
Speaker 4: up or down. You're really taking a bet on this
Speaker 4: group of stocks is going to perform this other group
Speaker 4: of stocks by looking at a bunch of different characteristics.
Speaker 4: We did that for stocks, We did it for currencies,
Speaker 4: for commodities, you name it was. It was tradable, and
Speaker 4: we had data we wanted to be trading it. And
Speaker 4: that's really what the genesis of that fund was.
Speaker 2: How long were you guys doing that before you realized, hey,
Speaker 2: this is really going to be a successful model, And
Speaker 2: then how much longer was it before maybe we should
Speaker 2: do this out from under the compliance regulations of a
Speaker 2: broker dealer.
Speaker 4: We started that as a fund really in nineteen ninety five.
Speaker 4: It had been trading prop for a little time with
Speaker 4: Goldman's money, and we made money almost every month. Basically
Speaker 4: it traded as a fund, and you think we left
Speaker 4: in terms of a timing perspective, you know, they started
Speaker 4: nineteen ninety five We left early nineteen ninety eight, so
Speaker 4: it's only a couple of years in change that we
Speaker 4: were trading this within g SAM before leaving to start
Speaker 4: at BAQR.
Speaker 2: So let's talk a little bit about AQR. You there
Speaker 2: from inception, from day one. What was that transition like
Speaker 2: from you know, I imagine at Goldman Sachs you have access
Speaker 2: to life, lots of support, lots of tools, lots of data,
Speaker 2: lots of everything. What's it like starting over again from
Speaker 2: scratch in a standalone hedge fund.
Speaker 4: I'll tell you a funny story. So I got into
Speaker 4: a few different battles with the administration folks at Goldman
Speaker 4: Sachs size management. If you remember, like in college, I
Speaker 4: had a computer business where we'd like buy parts, build
Speaker 4: computers and sell them, and so I knew how to
Speaker 4: build my own computers. Goldman Sachs. At the time, the
Speaker 4: standard computer that everybody had was what was called an
Speaker 4: eight eighty six. This is like the first real PC
Speaker 4: that IBM had out there, and you know, they were good,
Speaker 4: but they weren't the most advanced available machines. Basically, I
Speaker 4: went to the administration and I said, look, we need
Speaker 4: the most advanced machines because we're trying to run a
Speaker 4: lot of computationally intensive models and this machine we have
Speaker 4: now is very slow at taking very long to run
Speaker 4: our models. You can buy the latest machine at half
Speaker 4: the price of what Goldman was paying and get twice
Speaker 4: the performance. What I didn't realize at the time is
Speaker 4: that when you're trying to run an organization that large
Speaker 4: and complex.
Speaker 3: I want everything stand you.
Speaker 4: Can't support it unless everything's standardized. And so there was
Speaker 4: a reason for it which I didn't understand.
Speaker 2: That you guys can support your own hardware.
Speaker 3: That's not that hard.
Speaker 4: Cliff eventually persuaded them to give let us get the
Speaker 4: new machines. But one of the big changes as you
Speaker 4: talk about leaving a place, you know you have lots
Speaker 4: of resources and whatnot at large organizations, but you have
Speaker 4: limited resources at every place, no matter how big you are.
Speaker 4: There's always trade offs that you're making when you start
Speaker 4: up as a new firm. One thing that was a
Speaker 4: big change is that at Goldman we had to support
Speaker 4: lots of other groups. We were providing research advice, investment advice,
Speaker 4: talk to clients, help them raise money in other products.
Speaker 4: When we launched you own hedge fund. All that matter
Speaker 4: was making money in that hedge fund, so helping that
Speaker 4: focus was important, and we were able to buy the
Speaker 4: latest computers that have the cost.
Speaker 2: I'm going to bet that you did something a little
Speaker 2: beefier than those IBM eight to eighty six is.
Speaker 4: Yeah, I was overclocking the machines. I was doing all
Speaker 4: the pulling, all the ways to get things to go
Speaker 4: as fast as possible.
Speaker 3: Huh.
Speaker 2: Really interesting. So at AQR you juggled a lot of responsibilities.
Speaker 2: You were a portfolio manager, researcher, head of trading, and
Speaker 2: apparently tech geek putting machines together. What was it like
Speaker 2: juggling all these different responsibilities.
Speaker 4: There's a couple things I'll say about that. So one thing,
Speaker 4: just from a personal perspective, my wife and I we
Speaker 4: have five children together, and that's a lot to deal with.
Speaker 4: My wife is amazing, and there's no way I would
Speaker 4: be able to do all the stuff I do at
Speaker 4: work if it weren't for her being amazing and handling
Speaker 4: everything at home. So that's the first thing, and how
Speaker 4: I get so many things done at work. I'm also
Speaker 4: from a personality perspective, I get bored very quickly. I
Speaker 4: like learning and doing a lot of different things. I
Speaker 4: like being able to jump around, So to me, that's
Speaker 4: just fun. The consequence is sleep. I don't sleep very much.
Speaker 2: What do you mean, not very much? And you know
Speaker 2: that only gets worse as you get older.
Speaker 4: We usually get to sleep around one am and you know,
Speaker 4: six six thirty something like that.
Speaker 2: All right, so five hours, that's not terrible, not too terrible.
Speaker 2: I've lived on six hours most of my life and
Speaker 2: it's and you get older that that shrinks. I thought
Speaker 2: you were referencing the five kids, because it's like, hey,
Speaker 2: when you have five kids, you want how to juggle
Speaker 2: a lot of different things at once because something is
Speaker 2: always that's fine.
Speaker 4: There's always something going on, that's for sure.
Speaker 3: What was it like working with Cliff back in the days.
Speaker 4: It was fun. I think Cliff's greatd a lot of
Speaker 4: different things, but one was he hired well. He was
Speaker 4: able to attract really talented people and then he just
Speaker 4: let them do what they do. So he's not a micromanager.
Speaker 4: He just lets them run with it. And so that
Speaker 4: was a very fortunate thing for me right place, right
Speaker 4: time in terms of being able to get a lot
Speaker 4: of responsibility early on, and that's how I was able
Speaker 4: to not just be a researcher building models and creating
Speaker 4: new strategies that I'd run by Cliff and he would say, Okay,
Speaker 4: you're doing this dumb or doing that dumb, and you
Speaker 4: got to improve this, but also doing all the trading
Speaker 4: by myself for the firm for the first several years,
Speaker 4: and then eventually saying, hey, Cliff, you know I need
Speaker 4: some help here. We need to hire, you know, someone
Speaker 4: to run technology other than me. We need to hire
Speaker 4: more traders than just me so that I can actually sleep.
Speaker 4: So that's how he ran it. And it was a
Speaker 4: lot of fun. I mean you mentioned it earlier on.
Speaker 4: I mean Cliff hilarious and he's.
Speaker 2: A funny guy. And it's rare to find someone who
Speaker 2: is a quant who can communicate as eloquently as he
Speaker 2: can and at the same time has such a devilish
Speaker 2: sense of humor. Like that's an unusual trifecta right there.
Speaker 4: And it's part of what makes him fantastic as an individual,
Speaker 4: but also fantastic to work with and work for. It
Speaker 4: made the place fun even in the tough times. And
Speaker 4: so that's a big reason why I think a lot
Speaker 4: of people stuck through lots of the ups and downs
Speaker 4: that any organization has.
Speaker 2: Let's talk a little bit about the AQR experience. The
Speaker 2: firm seems very I almost want to say academic. They
Speaker 2: publish a lot of white papers, they do a lot
Speaker 2: of research, They have very specific opinions on different topics
Speaker 2: that seem to come up in the world of finance.
Speaker 2: How much of this intellectual firepower is part think tank
Speaker 2: and how much of it is just Hey, if you're
Speaker 2: going to have an investment perspective, you need to have
Speaker 2: the intellectual underpinnings to justify it.
Speaker 4: So I think one thing that makes acar a very
Speaker 4: powerful is its ability to attract top talent, specifically on
Speaker 4: the academic side. The smart people want to hang out
Speaker 4: with other smart people. That there is definitely a network
Speaker 4: effect that happens there. And I would say part of
Speaker 4: the compensation you're getting indirectly by being in an organization
Speaker 4: like that is getting exposure to all these great minds
Speaker 4: that you can learn from, you can bounce ideas off of.
Speaker 4: So is it a think tank? Yeah, I think it
Speaker 4: is a think tank from that perspective, But at the
Speaker 4: end of the day, it's a business and they're there
Speaker 4: to make money, make money for their investors, so I
Speaker 4: think there is a lot of focus on that as well.
Speaker 4: So the publications, you see a lot of white papers,
Speaker 4: and sure, I would say it rhymes with a lot
Speaker 4: of things they do. But they obviously keep a lot
Speaker 4: of the special sauce unpublished and use that within their funds.
Speaker 2: But they're still writing about broad strokes. So let's talk
Speaker 2: about a white paper that you wrote titled the Evolution
Speaker 2: of Alpha. Tell us how has alpha evolved over the
Speaker 2: past few decades.
Speaker 4: Sure, this is a white paper I wrote from my
Speaker 4: clear Apha Cio CEO hat and it really talks about
Speaker 4: the history of the hedge fund industry, why different models
Speaker 4: of delivering alpha, starting with let's say single strategy hedge funds,
Speaker 4: fund of funds, multi strategy funds, and now multi strategy
Speaker 4: multi manager are multipm funds and that's the latest evolution.
Speaker 4: And then we talk about what we think might be
Speaker 4: the next step, part of which we think we will drive.
Speaker 4: So that's the point of the paper. And there's reasons
Speaker 4: why you went from different models from one to the next,
Speaker 4: and it has to do with a variety of things.
Speaker 4: I can Curg. You to read the paper, it's on
Speaker 4: our website.
Speaker 2: But so let's follow that up. What were the drivers
Speaker 2: of the shift from a single manager to multiple managers
Speaker 2: to multi strategy to multi manager multi strategy.
Speaker 3: What was the key driver of that?
Speaker 4: Starting back this is around two thousand, let's say. Obviously
Speaker 4: hedge funds existed before that, but that's really the point
Speaker 4: at which at least a meaningful amount of institution investors
Speaker 4: actually started having investments in hedge funds as like a
Speaker 4: normal course of business. That was the year obviously that
Speaker 4: the market sold off a lot. That was the Enron
Speaker 4: fiasco and whatnot. A lot of Wall Street was let go,
Speaker 4: so a lot of talent was being let go, and
Speaker 4: much of that talent was investment analysts, research chants. The
Speaker 4: covered stocks new stocks, deeply knew the management of those
Speaker 4: companies deeply. So if you're an investment analyst at a
Speaker 4: Wall Street bank, you go off and hang up a shingle,
Speaker 4: start a single strategy hedge fund where you're picking stocks.
Speaker 4: You had an argument why you'd have an edge because
Speaker 4: you knew these managers these stocks deeply. And that's really
Speaker 4: was like a Cambrian explosion of hedge funds at that
Speaker 4: moment in time, and even to this day, I think
Speaker 4: in terms of like sheer number count, the vast majority
Speaker 4: of hedge funds are really stock picking hedge funds.
Speaker 2: Long short eleven thousand hedge funds out there too.
Speaker 4: Yeah, yeah, long short discretionary equity stockpicking hedge funds. That
Speaker 4: models survived for a little while, but as investors were
Speaker 4: investing in these individual kind of single strategy, single style
Speaker 4: hedge funds, what they realize is that anyone single approach
Speaker 4: is not very consistent. You know, it's going to go
Speaker 4: through it's good periods and it's bad periods, and it's
Speaker 4: hard to hang on to what I would call be
Speaker 4: exposed to what the line item risk is. When you
Speaker 4: have these quarterly reviews of what's going on the portfolio,
Speaker 4: invariably the discussion is, let's talk about the things that
Speaker 4: are down the most, and that leads to, you know,
Speaker 4: firing managers when they're down, usually just after a environment
Speaker 4: that was just bad for their approach, before it rebounds
Speaker 4: and does well, you know, in the next year. So
Speaker 4: that model, well it still exists today, is tough from
Speaker 4: an investment to stick with. Then you switch to fund
Speaker 4: of funds and soucial investors. You know, one stop shop,
Speaker 4: buy into a fund of funds. You can get exposure
Speaker 4: to many different strategies and styles in one vehicle. That's
Speaker 4: what came out of that and was to address this inconsistency.
Speaker 4: So fund of funds were more consistent than a single
Speaker 4: strategy fund. But I would say the consequence and its
Speaker 4: or the issue really is both for fund of funds
Speaker 4: and really for portfolios of hedge funds that investors have.
Speaker 4: It's cash inefficient. It's capital inefficient because most hedge funds
Speaker 4: have a lot of cash on their balance sheet typical
Speaker 4: hedge fund. It varies, but depending on top of style
Speaker 4: and strategy, will have between forty and ninety percent of
Speaker 4: the money you give them just sitting in cash.
Speaker 2: Really, that's a giant number. Half is a giant number.
Speaker 2: I thought you were going to go in a different direction.
Speaker 2: I have a friend who's an allocator at a big foundation,
Speaker 2: and he calls the fund of funds fund of fees
Speaker 2: because you're paying layers on top of layers of fees,
Speaker 2: and it definitely acts as as a long term drag.
Speaker 2: But I never would have guessed that fifty plus percent
Speaker 2: of assets handed to hedge funds are in cash at
Speaker 2: any one time. I always assumed it was the opposite
Speaker 2: that all right there, you know, like the one thirty
Speaker 2: thirty funds or whichever variation you're looking at. I always
Speaker 2: assume that they're leveraged up and even if they're long short,
Speaker 2: all that money is put to work. You're saying that's
Speaker 2: not the case.
Speaker 4: Well, technically all the you know, they will put the
Speaker 4: money to work in the sense of it's not pure
Speaker 4: cash hitting there. But really there's a lot of barring power.
Speaker 4: You love assets that you're holding, there's a tremendous amount
Speaker 4: of barring power you can borrow against those assets that
Speaker 4: you hold to then create a more efficient portfolio. And
Speaker 4: that's where kind of multi strategy funds evolved. So multi
Speaker 4: strategy funds gave you the benefit of many different strategies
Speaker 4: and styles, yet put into the same vehicle all these
Speaker 4: positions held in the same vehicle to get much more
Speaker 4: cash efficiency, cap efficiency, higher return on capital, plus the consistency.
Speaker 2: So I'm assuming if you're using a multi manager, multi
Speaker 2: strategy approach, anyone strategy at any given time is either
Speaker 2: going to be doing well or poorly, but the overall
Speaker 2: performance of a multi strat will offset that. So it's
Speaker 2: not like, hey, this guy has a bad quarter because
Speaker 2: what they do is out of favor and the clients
Speaker 2: pull out their cash just before the recovery. Is there
Speaker 2: a tendency to leave money with a multi strat multi
Speaker 2: manager approach for longer and so you don't have those
Speaker 2: sort of bad quarter, bad month, whatever it is, because
Speaker 2: this just isn't working now, but it'll start working eventually.
Speaker 2: Is that the underlying thinking.
Speaker 4: That's really the approach? In fact, a lot of successful
Speaker 4: single manager businesses evolve to the multi strategy approach because
Speaker 4: they recognize that lack of consistency for a single approach,
Speaker 4: a single investing style was a threat to their own business,
Speaker 4: and so expanding into other strategies and styles is how
Speaker 4: a lot of these more successful single strategy funds evolved.
Speaker 2: So it sounds like, if you're running either a multi
Speaker 2: manager or a multi strategy or both, everything needs to
Speaker 2: be very non correlated. You don't want everything down at
Speaker 2: the same time. How do you approach picking various strategies
Speaker 2: that are not correlated.
Speaker 4: That's a great question. I think it's helpful. I don't
Speaker 4: like the gambling angle, but I think it's a helpful
Speaker 4: analogy because most people are used to the analogy. If
Speaker 4: you think about the casino, people go to the casino
Speaker 4: knowing that if they play the games long enough, they're
Speaker 4: going to lose their money. I think most people think
Speaker 4: that the multi strategy hedge fund is really like the
Speaker 4: house where each table or each game in the casino
Speaker 4: in their house has slight edge, and if they make
Speaker 4: sure that there's not going to be massive losses at
Speaker 4: different tables on the same night, same weekend, same month,
Speaker 4: over time, they will just just stashysically accrue profits in
Speaker 4: a more consistent manner. So that is a big focus.
Speaker 4: And if you think about what risk manners would do
Speaker 4: at a casino, it's the same thing. They're going to
Speaker 4: make sure that these tables, these games are not going
Speaker 4: to be making or losing money at the same time.
Speaker 2: So let's talk about some of these diversified, non correlated strategies.
Speaker 2: I'm assuming some include momentum, long, short, any other sort
Speaker 2: of approaches that people would really readily understand.
Speaker 4: Sure, when I think about most hedge fund strategies, the
Speaker 4: ones that people know about, the ones that there are.
Speaker 4: If you look at hedge fund indicies, there's a category
Speaker 4: for it, you know. So it could be long short
Speaker 4: stock picking, it could be merger arbitrage, it could be
Speaker 4: index rebound arbitra, or basis trading. There's a variety, and
Speaker 4: there's like dozens of these kind of well known, well
Speaker 4: understand activists exactly. These are all out there, they're they're
Speaker 4: well known. When you look at each one of those,
Speaker 4: you can break it down between kind of cheap passive beta.
Speaker 4: So let's take an example long short, discretionary stockpicking. Most
Speaker 4: of these hedge funds, the way they're implemented is the
Speaker 4: manager's net long the stock market, and so some portion
Speaker 4: of their returns, it's actually a pretty sniffing portion is
Speaker 4: just being going to be driven by whether the stock
Speaker 4: markets separate down there just pure data, pure beta, and
Speaker 4: that's that's a I think about the scarce resources your
Speaker 4: risk budget, and how do you want to allocate that
Speaker 4: risk budget. If you're allocking a lot of your risk
Speaker 4: budget to just pure beta, that might work for the manager,
Speaker 4: but for an investor that doesn't make a lot of
Speaker 4: sense because I can go and get pure beta. I
Speaker 4: can buy an index fund for you know, single digit
Speaker 4: basis points. At this point, it's effectively free these multi
Speaker 4: strategy funds in order to reduce the correlation across their managers.
Speaker 4: They don't want to have all these manager's long pure beta.
Speaker 4: That's a common risk that will cause them to make
Speaker 4: and lose money at the same time. And so when
Speaker 4: you're running a multi strategy fund, it's really about looking
Speaker 4: at these common risks. BITA is the simplest example. It
Speaker 4: could be sector exposure, it could be factor exposure like
Speaker 4: momentum you mentioned earlier, and there's a lot of other
Speaker 4: less well known but known in the industry risks that
Speaker 4: take place. You know, people talk about crowding. There's reasons
Speaker 4: why crowding happens. So being able to be aware of
Speaker 4: those and look for signs of that and trying to
Speaker 4: mitigate those common allies across your different strategies is a
Speaker 4: really key component to managing risk for these multi strategy funds.
Speaker 2: Huh, there's so many different ways to go with this.
Speaker 2: So you're implying with these crowded funds that there's a
Speaker 2: way to identify when when you're in a crowded fund,
Speaker 2: I recall the quant quake a couple of years back,
Speaker 2: where all these big quant shops post GFC really seem
Speaker 2: like they were having the same sort of exposure in
Speaker 2: the same sort of problem problems. How can you identify
Speaker 2: an event like that before it takes your fun down
Speaker 2: ten twenty percent.
Speaker 4: That's a great question, And I would say a more
Speaker 4: recent example might be COVID March of twenty twenty when
Speaker 4: they're so I talked about a couple of different common risks.
Speaker 4: One is beta one. Another one might be factors, a simple.
Speaker 4: Other one is just there's a well known strategy. Let's
Speaker 4: say merge arbatrage. You know there are plenty of funds
Speaker 4: that are running merge arbatrage is one of their strategies
Speaker 4: within the fund. Okay, simply because a lot of people
Speaker 4: are doing something that in a sense, when there is
Speaker 4: some other exogenous event that causes people to de risk,
Speaker 4: it actually makes it bad to be in well known,
Speaker 4: well understood trading strategies, so that you know ahead of
Speaker 4: time that this is something that is crowded. You know
Speaker 4: that there are other players that are doing the same
Speaker 4: kind of trades as you going in.
Speaker 2: Huh, that's really interesting, And just to put some meat
Speaker 2: on the bones. Multi strategy, multi manager, multi model funds
Speaker 2: have really gained prominence lately, names like Citadel, Point seventy two, Millennium,
Speaker 2: lots of other larger funds have very much adopted this approach.
Speaker 3: Fair statement, that's very fair.
Speaker 4: I do think it's the best way to deliver alpha.
Speaker 2: So you're reducing correlation, you're reducing risk, you're increasing the
Speaker 2: odds of about performance. At how broad are firms like
Speaker 2: I don't know, Citadel or Millennium that they don't run
Speaker 2: into that crowded trade risk? You would think given their
Speaker 2: size and they're tens of billions of dollars, a crowded
Speaker 2: trade becomes increasingly more likely, right.
Speaker 4: Right, And there's a reason for why that's the case.
Speaker 4: There are literally thousands of different types of ways to
Speaker 4: make money in the markets, thousands, but there's only dozens
Speaker 4: of ways of making money in the markets that have
Speaker 4: lots of capacity. And you can put a lot of
Speaker 4: dollars in general, a lot of dollars to scale up,
Speaker 4: to scale up, and if you're going to be a
Speaker 4: very large fund, you by definition have to put more
Speaker 4: and more of your money into the well known large
Speaker 4: trading strategies and so they have to be particularly attuned
Speaker 4: to the fact that they are large and their competitors
Speaker 4: are also large, and then the same kind of trades.
Speaker 4: So it is at risk. And when these things, you know,
Speaker 4: when one of these shops sells out or reduces risks
Speaker 4: and one of these common strategies, it's going to affect
Speaker 4: the other ones. It's hard to avoid that. But they
Speaker 4: are fairly well diversified across many different types of strategies,
Speaker 4: so that's why you see still very consistent returns. But
Speaker 4: there is this exogenous risk element of having being big
Speaker 4: in the credit. The way you avoid that is by
Speaker 4: being smaller, focusing on smaller strategies. They're a little bit different.
Speaker 3: Huh.
Speaker 2: Really interesting. So you mentioned earlier early days of hedge funds,
Speaker 2: the fund of funds were popular. It feels like they're
Speaker 2: kind of going away. You certainly hear much less about
Speaker 2: them these days. Is that a fair assessment. Just because
Speaker 2: you don't hear about stuff doesn't mean it's disappeared. But
Speaker 2: I certainly only read much less about fund of funds
Speaker 2: that they are in the news much less. Have multi manager,
Speaker 2: multi strat multi model broad funds replaced the concept of
Speaker 2: fund of funds.
Speaker 4: I think as an evolution, it doesn't mean that the
Speaker 4: fund of funds model is going away entirely. There's certain
Speaker 4: managers out there who have commingled vehicles that only you know.
Speaker 4: They won't run an SMA for you, they won't trade
Speaker 4: their strategy into your account. Fund of funds can access that,
Speaker 4: So there's a reason for that. And you know they're
Speaker 4: nice one stop shops and they can maybe a little
Speaker 4: more transparent. But there are You talked about this earlier,
Speaker 4: the fees being an issue, and it's really about the
Speaker 4: fee is a percentage of the dollars of P and
Speaker 4: L being earned. There's an academic paper recently published that
Speaker 4: did a really interesting study over ten years of looking
Speaker 4: at institutional hedge fund portfolios. What it showed is that
Speaker 4: for every dollar of P and L being generated by
Speaker 4: these hedge fund strategies, at the end of the day,
Speaker 4: the institutional investor took home about thirty seven cents, really,
Speaker 4: which is I think a shocking number from right right.
Speaker 2: So you're saying almost two thirds of the money never
Speaker 2: either it's fees or costs or some other factor, but
Speaker 2: only let a little more than a third ends up
Speaker 2: with the actual investor.
Speaker 4: That's right, and it's actually it's really interesting breaks down
Speaker 4: the sources of all these things. Part of it is
Speaker 4: fees and double layers of fees and things like that.
Speaker 4: A big part of it is the behavioral nature, which
Speaker 4: I think is driven by governance of investing organizations.
Speaker 3: Where filled with humans.
Speaker 4: Yes, strategy is down. What's been down, Let's get out
Speaker 4: of that. Let's get into the thing that's been up
Speaker 4: recently that costs about a third of your offha.
Speaker 2: That doesn't surprise me at all, even though you expect
Speaker 2: big endowments and foundations and hedge funds to be smarter
Speaker 2: than that. Fillm with people and you're going to get
Speaker 2: those behavioral problems, aren't you.
Speaker 4: Yeah, Well, there's agency issues in between, and I think
Speaker 4: investors are well aware of these, so that causes part
Speaker 4: of it too. But a big thing and the thing
Speaker 4: that kind of the multi manager, multi strategy approach tackles
Speaker 4: that a fund of funds can't is you get a
Speaker 4: lot of netting benefits both from you know, one manager's
Speaker 4: long apple another manager's short apple. Right in a fund
Speaker 4: to fund approach where you're investing in two different funds, well,
Speaker 4: a they don't know that. And b the managers who
Speaker 4: long Apple, they're paying a financing spread to go leverage
Speaker 4: long Apple, and the managers's shortest paying financing spread to
Speaker 4: go short Apples. You're paying a lot of extra cost
Speaker 4: there just to be net flat, just to be net flat.
Speaker 4: So if those two managers instead traded those positions into
Speaker 4: the same vehicle, you're getting that efficiency and that's worth
Speaker 4: you know, in the order of like two to three
Speaker 4: percent per year just that alone. The enhanced risk management
Speaker 4: you can get by having daily position transparency and all
Speaker 4: the trades, if all the different pans are doing, being
Speaker 4: able to hedge out all these beta risk factor, risk
Speaker 4: sector risks, things like that allows you to be much
Speaker 4: more efficient with how you deploy that capital. And so
Speaker 4: you see that these multi manager funds tend to be
Speaker 4: a little more invested than a hedge fund portfolio typically
Speaker 4: could be, and that creates a lot of efficiencies. And
Speaker 4: so when you look at the returns that they're generating,
Speaker 4: you know, it's closer to like fifty to fifty, where
Speaker 4: like for every dollar that's generative P and L, fifty
Speaker 4: cents is going to the investor. So it's a much
Speaker 4: more efficient delivery mechanism of alpha.
Speaker 2: So we were talking earlier and I mentioned off air
Speaker 2: that the funny element of individual investors tending to underperform
Speaker 2: their own investments. I know you've done some research on that.
Speaker 2: Tell us a little bit about what you say.
Speaker 4: Yeah, this is really something that's very important to me
Speaker 4: when I think about the industry and like, what are
Speaker 4: the big problems that are facing the industry. What's really
Speaker 4: causing investors not to get as much money in their
Speaker 4: retirem accounts as we possibly could get there. One of
Speaker 4: them is this behavioral issue, which I think also ties
Speaker 4: to like incentives and governance and agency issues within investing organizations.
Speaker 4: Morning Star does a study that they call Mine the Gap,
Speaker 4: and they do it on a regular basis. Some of
Speaker 4: your relitiers might have heard this, and it's definitely worth reading.
Speaker 4: I'll quote some numbers off the top of my head.
Speaker 4: I might be remembering incorrectly, but what it does is
Speaker 4: it's measuring the time weighted returns of funds, which is
Speaker 4: the returns that funds report. These are the returns that
Speaker 4: if you invested a dollar at the beginning and you
Speaker 4: held it all the way through, the returns you would
Speaker 4: have gotten if you never went to or went out
Speaker 4: of that fund. Then they compare that to the asset
Speaker 4: weighted returns, right, and that is going to be the
Speaker 4: asset weight returns are counting for the fact that you know,
Speaker 4: the fund does well, everybody gets excited, money comes in
Speaker 4: larger assets, and then it maybe does not as well
Speaker 4: after that, and so the larger assets earn less return.
Speaker 4: And so the asset way to return minus the time
Speaker 4: way to return is a really good way to measuring
Speaker 4: what's the actual impact of this behavioral element of investing,
Speaker 4: which is a really critical part of investing.
Speaker 2: And the gap refers to the behavior gap, which is
Speaker 2: the difference between what the fund generates and what the
Speaker 2: actual investors are getting.
Speaker 3: Yeap, please continue.
Speaker 4: And so what you find is that for like sixty
Speaker 4: to forty balanced funds, which typically are in retirement accounts
Speaker 4: where people maybe aren't looking at them every single day,
Speaker 4: they get statements once a quarter that are delayed.
Speaker 3: Set and forget just it's kind of a set of Yeah.
Speaker 4: That gap is on the order of sixty basis points,
Speaker 4: relatively small, relatively small, but it costs still. It costs
Speaker 4: sixty basis points year for the average investor. This beaver
Speaker 4: for those simple funds. Now for alternative funds, when they
Speaker 4: look at those, that gap is one hundred and seventy
Speaker 4: basis points a year.
Speaker 3: Okay, that's starting it up.
Speaker 4: That really I mean, if you think about that compounding
Speaker 4: over a decade, that was a massive hit to wealth.
Speaker 4: Why is there such a big gap for alternatives and
Speaker 4: not as much of a gap for the sixty forty
Speaker 4: I think it has a lot to do with investor
Speaker 4: understanding of what those products are and therefore the confidence
Speaker 4: people invest in alternatives. They don't necessarily understand them, and
Speaker 4: so you're setting yourself up for FI. You're a little
Speaker 4: bit there, because when it has bad performance you don't
Speaker 4: understand what it does, you're more likely to redeem.
Speaker 3: That makes a lot of sense.
Speaker 4: So to me, investor education, really understanding what they're investing
Speaker 4: is is a critical component to being a successful investor.
Speaker 2: Really really interesting. So you talk a lot about idea meritocracy.
Speaker 2: It's on your site, you've written about it. Explain a
Speaker 2: little bit what is idea meritocracy?
Speaker 4: This is a really important part and it's part of
Speaker 4: our culture at clear Alpha. The idea is to get
Speaker 4: all ideas surfaced so that the organization can make the
Speaker 4: best decisions. How do you know what prevents good ideas
Speaker 4: from surfacing. One is that people may not know that
Speaker 4: you know, a questions even being asked. So many organizations
Speaker 4: are run fairly siloed different groups, and a lot of
Speaker 4: that happens associally large large organizations. It's hard for everybody
Speaker 4: to be constantly communicate with one another, so just not
Speaker 4: even knowing a question exists. So the way we address
Speaker 4: that is that we use Microsoft Teams at the office
Speaker 4: and most people are in various channels and we're seeing
Speaker 4: questions going on all the time. I really discourage people
Speaker 4: from asking me a one on one question. I will
Speaker 4: usually redirect a question someone asked me to here's the
Speaker 4: broad company, here's the question that was asked, here's the answer.
Speaker 4: So then immediately the entire company learns you know what
Speaker 4: this topic was, and very often that says, oh, someone else,
Speaker 4: I have another idea about that that I want to
Speaker 4: now share. So getting accessibility for people to deliver. But
Speaker 4: the most important about idea meritocracy is really from a
Speaker 4: leadership standpoint. People have to feel safe bringing up ideas
Speaker 4: that they're not going to get you know, yelled at.
Speaker 4: You know, there's no bad questions, there's only people not
Speaker 4: asking questions. That's not bad. And the only way that
Speaker 4: that for people to feel safe about that is that
Speaker 4: they need to see me as the leader and my
Speaker 4: other partners as the leaders, to be willing to take
Speaker 4: in feedback, be challenged even publicly and say, you know what,
Speaker 4: that's a really good idea, let's go with that. And
Speaker 4: so just having them feel that safe environment so that
Speaker 4: people can always ask and bring questions up.
Speaker 2: Huh, that's really interesting. Also, you've discussed generating less common
Speaker 2: ideas earlier, we were talking about crowded trades. How do
Speaker 2: you generate less common ideas? How do you find non
Speaker 2: correlated sources of return when you're you know, in a
Speaker 2: hyper competitive marketplace.
Speaker 4: Great question. So I'll use an example here. There's a
Speaker 4: common strategy that people might be familiar with. It's called
Speaker 4: merge arbitrage. And basically, company A is going to buy
Speaker 4: company B, whether it's for cash consideration or stock for
Speaker 4: stock type transaction. And you know, merge arbitragers look at
Speaker 4: that and they might go, you know, long the company's
Speaker 4: being acquired, short, the company's doing the acquire, and then
Speaker 4: make money if that deal ultimately closes. That's a that's
Speaker 4: a very common, well known strategy. That would be the
Speaker 4: common version of implementing the strategy. A less common version
Speaker 4: implemented is you try to find one that you like
Speaker 4: more than others. So you might think they all are
Speaker 4: like the vast majority are going to close, but some
Speaker 4: you might like better than others, and so you could
Speaker 4: go long half of them and short half of them,
Speaker 4: so you're not exposed to this common element of merger
Speaker 4: arbitrage deals closing. You're neutral to those. So if a
Speaker 4: large pod shop, you know, one of these large multi managers,
Speaker 4: if they decided to get out of merger arbitrage and
Speaker 4: they're selling all these positions down, half your portfolio will
Speaker 4: get helped and half your portfolio will get hurt, but
Speaker 4: you're less exposed to that crowding risk, and that common
Speaker 4: what I would say, a risk factor that these other
Speaker 4: common strategies have. So that's a niche version of how
Speaker 4: we might implement that kind of a strategy.
Speaker 3: You mentioned niche.
Speaker 2: I never heard the phrase prior to reading something you
Speaker 2: had written called niche alpha. Tell us a little bit
Speaker 2: what niche alpha is.
Speaker 4: That's a great question. The simple answer is you're unlikely
Speaker 4: to have any or much of it in your hedge
Speaker 4: footy portfolio. That's how I would describe it. And so
Speaker 4: it's looking for people that are either implementing common strategies
Speaker 4: in a very different way that makes them less susceptible
Speaker 4: or more immune to people getting out of that strategy,
Speaker 4: or people have a completely different idea of how to
Speaker 4: make money that I haven't heard of before. And I've
Speaker 4: interviewed hundreds, if not thousands of portfolio managers and worked
Speaker 4: with developed many strateges of my own. So it's trying
Speaker 4: to find things that people aren't doing.
Speaker 2: Huh is there given what we know about the efficient
Speaker 2: market hypothesis? And Gene Fama was Cliff Astness's doctoral advisor,
Speaker 2: is that what or mba Cliff was Gensta Yes? So,
Speaker 2: given how mostly efficient the market is, is are there
Speaker 2: really Nietzsches left that have not been discovered? How many
Speaker 2: more opportunities are out there that we don't know about?
Speaker 4: That taps into something we talked about earlier, which is
Speaker 4: there are thousands of ways to make money in the markets.
Speaker 4: There's only dozens of ways to make money and big
Speaker 4: dollar size at scale at scale.
Speaker 2: So these smaller ideas is that where the mostly kind
Speaker 2: of eventually efficient market hasn't quite reached yet.
Speaker 4: Well, it's what I think about is the amount of
Speaker 4: dollars you can make. This is the race. I think
Speaker 4: about the amount of dollars you can make, divided by
Speaker 4: the complexity or how much brain damage you have to
Speaker 4: inflict upon yourself to actually implement the strategy.
Speaker 3: Uh huh.
Speaker 4: A lot of these small stranges, they're complex and difficult
Speaker 4: to do. That might require, you know, some kind of
Speaker 4: new technique that is difficult, are rare to implement, And
Speaker 4: the actual P and L that you can generate profit
Speaker 4: less you can generate is small villid for that effort.
Speaker 2: Small in terms of percentage returns or small in terms
Speaker 2: of dollars. Hey, there's only one hundred million to arbitrage
Speaker 2: away with this, and once that is mined, that's it.
Speaker 3: It's done.
Speaker 4: It's about dollars of P and L you can extract
Speaker 4: from the markets. Percentage returns can be very high for
Speaker 4: these strategies, but I'll give you a sense. You know,
Speaker 4: most other large shops they're going to look for strategies
Speaker 4: that can generate at least one hundred million dollars at
Speaker 4: P and L to make it worth their while to invest.
Speaker 4: We're looking at strategies that are generating ten, twenty thirty
Speaker 4: forty million dollars per year.
Speaker 3: Huh.
Speaker 2: That's really kind of intriguing. So what sort of demand
Speaker 2: is there for lower capacity strategies? I mean, so you
Speaker 2: guys are less than half a billion dollars, You're not
Speaker 2: an enormous funds. Are there more hedge funds looking to
Speaker 2: swim in these ponds or is this something that hey,
Speaker 2: once you cross a certain size, you just have to
Speaker 2: leave behind and stay with those larger capacity, scalable strategies.
Speaker 4: Yeah. I think this is a general thing for all investors,
Speaker 4: not just other hedge funds. Everybody wants to be in
Speaker 4: the interesting things. They want to be in the lower
Speaker 4: capacity things. They know that they're less crowded, the difficulty
Speaker 4: and really what I think are kind of our business
Speaker 4: model is is you're paying for us to go out
Speaker 4: and search the world and source them because it's expensive.
Speaker 4: It's expensive exercise to do. People might not have the
Speaker 4: expertise or the background to underwrite these types of strategies.
Speaker 4: It takes a lot of work, and at the end
Speaker 4: of the day, alpha is either about being smarter or
Speaker 4: working harder. The being smarter can work in the short term,
Speaker 4: but eventually that does get our way. Eventually someone smart
Speaker 4: enough comes by. The working harder, to me is the
Speaker 4: thing that actually stays.
Speaker 2: Huh, that's really interesting. You would think if the incentive
Speaker 2: was there enough, people would just eventually grind away in
Speaker 2: that space.
Speaker 4: I mean, the incentive is there, it's just not enough
Speaker 4: to be worth the time. And so if you are
Speaker 4: a very large investor of organization, you do have to
Speaker 4: prioritize you still have limited resources in time to look
Speaker 4: for things, so you're going to have you know, thresholds.
Speaker 4: I'm not going to invest at least, you know, at
Speaker 4: this amount of dollars, and that's where we step in
Speaker 4: is kind of fill that gap.
Speaker 2: So you're very much a student of what's going on
Speaker 2: in the hedge fund world. What are you seeing in
Speaker 2: terms of strategies driving cost down and the question of
Speaker 2: where fees are. They've certainly pulled back from the days
Speaker 2: of two and twenty. What's happening in terms of efficiency
Speaker 2: and cost.
Speaker 4: There's a bunch of things to talk about there. So
Speaker 4: The first thing I would say is the higher capacity
Speaker 4: strategies that have become well known. I think that those
Speaker 4: costs are going down because there's a lot of people
Speaker 4: who can implement those strategies and so that you think
Speaker 4: just simple supply and demand, lots of portfolio managers you
Speaker 4: can do them, and so then it's just a competition
Speaker 4: of who's going to be able to do it most efficiently.
Speaker 4: Then there's unique alpha. I think that's harder, and actually
Speaker 4: the cost of that has gone up over time. It's
Speaker 4: not gone down. The cost it takes to compete in
Speaker 4: the space has increased over time. So there's a bifurcation
Speaker 4: that's been going on. We think that there's still a
Speaker 4: lot of efficiencies you can carve out of the system
Speaker 4: that exists now that we're attacking lot through technology, a
Speaker 4: lot of three ways of working that can just make
Speaker 4: the organization more efficient and deliver more net returns to investors.
Speaker 2: So we've seen some motion towards fees for alpha and
Speaker 2: not betos. Some people call it pivot fees. There's like
Speaker 2: a lot of different names for this. I haven't heard
Speaker 2: much about that recently. What are your thoughts on where
Speaker 2: hedge fund fees are going in the future.
Speaker 4: I'll answer that with a different story that we'll draw
Speaker 4: on analogy here with the rise of indexing, which has
Speaker 4: been happening for decades now, and thank god for indexing.
Speaker 4: It's a fantastic invention that has helped a lot of investors.
Speaker 4: The original thought was, well, as the market goes more
Speaker 4: and more indexing, and I don't know what the number is,
Speaker 4: it's probably seventy percent is indexed of the invested dollars,
Speaker 4: then it makes the markets, you know, it's easier to
Speaker 4: make money because there's less people trying to compete for that.
Speaker 4: But that's not what actually happens. What actually happens is
Speaker 4: it's become more and more difficult to make money because
Speaker 4: the talent pool is of higher quality now than it
Speaker 4: used to be. That's searching for that alpha. And just
Speaker 4: like sport, it's when there's a zero sum game right right,
Speaker 4: and it's just it's very small differences between you know,
Speaker 4: the number one person and the number five person. What
Speaker 4: you see is the rewards and the compensation tends to
Speaker 4: be a power law, meaning that the very few get
Speaker 4: get paid a lot. And I see for pure alpha,
Speaker 4: where there's real competition that the investment talent will actually
Speaker 4: get paid more and more over time, it will get
Speaker 4: more and more difficult to be that person. Whereas for
Speaker 4: the common stuff, the well known things that have higher capacity,
Speaker 4: I think you're gonna see fees keep going down.
Speaker 2: On that side, Michael Mobison calls that the paradox of
Speaker 2: skill that the more skillful the players are, whether it's sports,
Speaker 2: investing business, the more of a role luck plays, which
Speaker 2: is really really kind of kind of fascinating. You've also
Speaker 2: written about portable alpha. Discuss discuss portable alpha. What is
Speaker 2: that and how can we get some.
Speaker 4: Think portal alfa is a great way for investors to
Speaker 4: get exposure to alternative return streams. What portal alfa is
Speaker 4: is mixing a beta like s and P five hundred
Speaker 4: exposure with an alpha stream and really just pop in
Speaker 4: that offa stream on top of the SMP five hundred returns.
Speaker 4: So it lets investors get exposure to SMP, which most
Speaker 4: investors already have, but now exposure to a different type
Speaker 4: of return stream. Usually people historically at least have tried
Speaker 4: to beat the SMP by picking a manager who's trying
Speaker 4: to pick stocks, overweighting stocks that they like versus the
Speaker 4: index and underwaitting stocks that they don't like. But that
Speaker 4: comes with a lot of constraints. One is the manager
Speaker 4: can only overweight underweight stocks in the index. They can't
Speaker 4: trade other asset classes, they can't utilize any kind of
Speaker 4: sophisticated investment techniques to try to beat that benchmark. Portal
Speaker 4: alpha get rid of all of those constraints, and so
Speaker 4: what you typically see is portal alpha programs are much
Speaker 4: better and consistently beating traditional active programs.
Speaker 2: I like the phrase Corey Hofstein uses for that return stacking.
Speaker 2: Is that same concept for portable alpha? That's right, Yeah,
Speaker 2: really really interesting. Before I get to my favorite questions
Speaker 2: that I ask, well, my guests, I just have to
Speaker 2: throw you a a little bit of a curveball. So
Speaker 2: you're a member of the Yale New Haven Children's Hospital Council,
Speaker 2: tell us a little bit about what you do with that.
Speaker 4: Sure. So just how we got involved, My wife and
Speaker 4: I we with the five kids, three of which had
Speaker 4: severe peenaut allergies, and we were very concerned about that.
Speaker 4: You know, that's become a rising epidemic within a society
Speaker 4: over time, and we wanted to see if we could
Speaker 4: solve that invest in basically research, try to solve this problem.
Speaker 4: So we work with both Yale and our local hospital too.
Speaker 4: Can we fund a research effort and a clinical effort
Speaker 4: to basically collect data because a lot of the research
Speaker 4: really needs data, So we work with them. That's how
Speaker 4: we got originally with yellows an organization, and then they
Speaker 4: have this council that's focused on children's health issues and
Speaker 4: what it is. It's a collection of individuals who are
Speaker 4: interested in this topic. We meet typically quarterly. They'll have,
Speaker 4: you know, some of their top researchers from Yale come
Speaker 4: in and talk about whatever research they're working on and
Speaker 4: their clinical experiences with you know, children as patients, and
Speaker 4: that usually generates ideas, Okay, how can we make this
Speaker 4: more effective? How can we get more funds directed towards
Speaker 4: this activity?
Speaker 2: All right, we only have you for a couple of minutes.
Speaker 2: Let's jump to my favorite questions that we ask all
Speaker 2: of our guests, starting with what are you streaming these days?
Speaker 2: What's keeping you entertained? Either Netflix, podcast, Amazon, whatever.
Speaker 4: My wife and I, after going through the litany of
Speaker 4: all the kids and their issues each day, it's usually
Speaker 4: very late and so we don't get to watch as
Speaker 4: much TV as probably would like. There's a lot of
Speaker 4: great content out there. Lately, we're watching Lionis on Paramount,
Speaker 4: which is.
Speaker 2: I just finished season one of few weeks ago and
Speaker 2: taking a break before season two.
Speaker 3: But it's fantastic.
Speaker 4: It's fantastic. Yeah, we've really enjoyed it so far.
Speaker 3: But I would say, are you up to season two yet?
Speaker 4: No, we're three or four episodes in. Oh, this season one?
Speaker 3: Brace yourself, you have quite right?
Speaker 4: Okay, great, But in terms of like favorite shows, one
Speaker 4: of my favorites was the remake of Battlestar Galactica, which
Speaker 4: was a show when I was growing up as a kid.
Speaker 2: With a terrible special effects in the old one, yes,
Speaker 2: and the new one is great.
Speaker 4: Right, that's right. And there's there's a scene that's actually
Speaker 4: relevant to our conversation a little bit today. The leader
Speaker 4: of the sidelines, which is like the robots, is talking
Speaker 4: with Human is one of the fighter pilots, and they're
Speaker 4: watching a video of one of the battles and the
Speaker 4: humans win this battle. But then the sieline says, this
Speaker 4: is how we're going to beat you, and Human's like,
Speaker 4: what do you mean? Because they just watched, like one
Speaker 4: of the humans kill one of the robot fighter pilots,
Speaker 4: and she says, well, every time that we make a
Speaker 4: mistake and we lose a battle, every single other Cylon
Speaker 4: learns from that, and so inevitably we will learn every
Speaker 4: way that we can avoid dying and we will take
Speaker 4: you over. And that has a lot to do with
Speaker 4: how we approach the business on the investing side, always
Speaker 4: learn from mistakes, get the communication out there, and constantly improve.
Speaker 4: If you improve by a few percent a year, that
Speaker 4: really compounds over time.
Speaker 2: Well, what does it matter if the AI silon is
Speaker 2: eventually going to kill all of us, It won't make
Speaker 2: any difference. Alpha is only here until the cylons beat
Speaker 2: us in a space battle.
Speaker 3: We view it that's way off in the distance.
Speaker 4: We like intelligence augmentation versus artificial intelligence IA instead of
Speaker 4: AI using these tools to be more effective.
Speaker 2: That makes a lot of sense. Let's talk about your
Speaker 2: mentor who helped to shape your career.
Speaker 4: Well, I would say of all the ones I could
Speaker 4: think of, Cliff would be the top mentor. And Cliff
Speaker 4: wasn't the kind of guy who would you know put
Speaker 4: your brand? Is his arm around you say hey, you
Speaker 4: know this, you do X, Y and Z, and you
Speaker 4: should do this differently. He did have a good several
Speaker 4: conversations with me like that. Most of his mentorship was
Speaker 4: through his actions. Clip's extremely principled, very ethical, and it's
Speaker 4: it's a very fortunate thing to be able to be
Speaker 4: in business with someone like that, where you can be
Speaker 4: successful at business but do it in a very ethical,
Speaker 4: principled way that's always doing right by the client, and
Speaker 4: that's something some of the biggest things I've taken away
Speaker 4: from working with him.
Speaker 2: Let's talk about books. What are some of your favorites
Speaker 2: and what are you reading right now?
Speaker 4: I like history, specifically financial history. The one I'm reading
Speaker 4: right now is called The World for Sale. It's actually
Speaker 4: written by a couple of journalists that cover the commodity industry,
Speaker 4: and it's really about the physical commodity traders and the
Speaker 4: whole history of that, which is which is kind of interesting.
Speaker 4: I love biographies. One of particularly liked was the Michael
Speaker 4: Dell one Played Nice but When where it's kind of
Speaker 4: chronologically it's this whole story. I really connected with the
Speaker 4: building computers in his dorm and selling them. Obviously, he
Speaker 4: was much more successful at that than I was really interesting.
Speaker 2: Any chance you read McCullough's Wright Brothers, I have not
Speaker 2: really fascinating. I like, it's unusual to read something that
Speaker 2: you think, oh, I know that history, and then it's like, no,
Speaker 2: you have no idea what's going on in the history.
Speaker 2: And he's just a great writer, really really really interesting.
Speaker 2: Our final two questions, what sort of advice would you
Speaker 2: give to a recent college grad interested in a career
Speaker 2: in either quantitative or investment finance.
Speaker 4: I don't know if the advice would be specific to
Speaker 4: those things. But talk less and listen more, that is
Speaker 4: what I would say. There's a curve. I forget the
Speaker 4: name of the curve, but it's you know, you start
Speaker 4: thinking you know a lot, especially Unny Kruger. Yeah, Dunning Kriger,
Speaker 4: that's what it is. Yeah, that is such a true effect.
Speaker 4: I thought I knew everything, and if I just listened
Speaker 4: to those around me who knew a lot more people
Speaker 4: are trying to help you more than you realize as
Speaker 4: a young person, and I should have just listened to
Speaker 4: more advice. I would have been more successful, much more
Speaker 4: earlier if I had.
Speaker 2: So here's the funny thing about the Dunning Kruger curve,
Speaker 2: and this comes straight from David Dunning. They did not
Speaker 2: create the Dunning Kruger curve. It kind of came from
Speaker 2: just pop psychology and social media. And then when they
Speaker 2: went back and tested it, I think the paper was
Speaker 2: like ninety nine or two thousand and four, something like that.
Speaker 2: When they went back and tested it, it turned out
Speaker 2: that the Dunning Kruger curve turned out to be a realistic,
Speaker 2: measurable effect. And it's mount stupid. The valley of Despair
Speaker 2: and the slope of enlightenment are just sort of the
Speaker 2: the pop terms of it, but it's really really funny.
Speaker 2: And our final question, what do you know about the
Speaker 2: world of investing today? You wish you knew back in
Speaker 2: the early nineties that would have been helpful to you
Speaker 2: over those decades.
Speaker 4: There's a lot of smart people out there, as smart
Speaker 4: as you might be. There's a lot to learn from
Speaker 4: everybody else. Everybody has some insight, some perspective that you
Speaker 4: don't have. Don't presume how you know what people are thinking.
Speaker 4: So ask questions and listen.
Speaker 2: Sounds like good advice for everybody. We have been speaking
Speaker 2: with Brian Hurst. He's the founder and CIO of Clear
Speaker 2: Alpha If you enjoy this conversation, well, be sure and
Speaker 2: check out any of the five hundred and thirty we've
Speaker 2: done over the past ten years. You can find those
Speaker 2: at iTunes, Spotify, YouTube, Bloomberg, wherever you find your favorite podcasts,
Speaker 2: be sure and check out my latest podcast, At the Money,
Speaker 2: short ten minute conversations with experts about topics that affect
Speaker 2: your money, spending it, earning it, and most importantly, investing it.
Speaker 2: At the Money. Wherever you find your favorite podcasts, I
Speaker 2: would be remiss if it and not thank the crack
Speaker 2: team that helps us put these conversations together each week.
Speaker 2: Sarah Livesey is my audio engineer. Sage Bauman is the
Speaker 2: head of podcasts. Sean Russo is my researcher. Anna Luca
Speaker 2: is my producer.
Speaker 3: I'm Barry Retolts.
Speaker 2: You've been listening to Masters in Business on Bloomberg Radio.