WEBVTT - From AQR Quant to Founder & CIO with Brian Hurst 0:00:02.600 --> 0:00:11.959 Bloomberg Audio Studios, Podcasts, radio News. This is Masters in 0:00:12.039 --> 0:00:15.560 Business with Barry Ritholt on Bloomberg Radio. 0:00:17.280 --> 0:00:20.960 This week on the podcast, yet another extra special guest. 0:00:21.480 --> 0:00:25.720 Brian Hurst is founder, CEO, and CIO of Clear Alpha. 0:00:26.040 --> 0:00:27.040 They are a. 0:00:27.120 --> 0:00:31.080 Multi manager, multi strategy hedge fund that has put up 0:00:31.120 --> 0:00:36.320 some pretty impressive numbers. His background is really fascinating. Cliff 0:00:36.360 --> 0:00:39.880 Astness plucked him out of the ether to be one 0:00:39.880 --> 0:00:43.279 of his first hires at the Quantitative Research Group at 0:00:43.320 --> 0:00:49.239 Goldman Sachs. He was the first non founding partner at AQR, 0:00:49.479 --> 0:00:54.320 the hedge fund that Asna set up, and Brian worked 0:00:54.320 --> 0:00:59.560 there for a couple of decades before launching Clear Alpha. 0:00:59.640 --> 0:01:03.640 He had as a fascinating perspective on where alpha comes 0:01:03.680 --> 0:01:07.679 from as well as the entire hedge fund industry. Few 0:01:07.720 --> 0:01:11.240 people have seen it from the unique perspective he has, 0:01:11.720 --> 0:01:16.240 and I think he understands the challenges of creating alpha 0:01:16.280 --> 0:01:19.959 where it comes from and managing the risk and looking 0:01:19.959 --> 0:01:24.120 for ways to develop non correlated alpha that is both 0:01:24.200 --> 0:01:29.560 sustainable and manageable from a behavioral perspective. I thought this 0:01:29.600 --> 0:01:33.319 conversation was absolutely fascinating and I think you will also 0:01:33.440 --> 0:01:38.000 with no further ado my interview with Clear Alpha's Brian Hurst. 0:01:38.280 --> 0:01:39.400 Thank you very appreciate it. 0:01:40.360 --> 0:01:41.399 Good to have you back here. 0:01:41.520 --> 0:01:43.680 Last time you were on a panel, we were talking 0:01:43.760 --> 0:01:48.840 about the rise of some emerging managers, including yourself. But 0:01:49.160 --> 0:01:52.440 let's go back to the beginning of your career Wharton 0:01:52.480 --> 0:01:55.760 School at the University of Pennsylvania. You graduate with a 0:01:55.960 --> 0:02:00.680 bachelor's in economics. Was quantitative finance always career plan? 0:02:01.320 --> 0:02:03.840 That's a great question. I think when I went to school, 0:02:03.840 --> 0:02:05.560 I didn't even know quantity of flants was a thing, 0:02:05.800 --> 0:02:08.000 and frankly, at that point in time, it really wasn't 0:02:08.080 --> 0:02:12.480 much of a thing. I was taken him by my dad. 0:02:12.520 --> 0:02:14.560 He was an accountant and CFO of a commercial real 0:02:14.680 --> 0:02:17.079 estate company. He would take me to the office, and 0:02:17.120 --> 0:02:19.079 I was really fascinated by business. I really wanted to 0:02:19.080 --> 0:02:22.200 get into that. I was into computers. I learned how 0:02:22.200 --> 0:02:24.280 to teach myself how to program and things like that. 0:02:24.480 --> 0:02:26.040 But I wanted to get into business, and I said, Dad, 0:02:26.080 --> 0:02:28.320 I want to get into real estate. And my dad 0:02:28.440 --> 0:02:31.320 gave me some really good advice. He said, Brian, if 0:02:31.320 --> 0:02:34.560 you think about finance as an org chart, real estate 0:02:34.680 --> 0:02:37.000 is like one of the divisions and if you start 0:02:37.040 --> 0:02:39.040 in real estate, it's hard to move up and go 0:02:39.080 --> 0:02:41.920 to other divisions and try other things out. You should 0:02:41.960 --> 0:02:44.400 really learn corporate finance and you can always switch to 0:02:44.440 --> 0:02:46.280 real estate if you wanted to. And corporate fans is 0:02:46.320 --> 0:02:49.480 kind of the top of the umbrella or the org chart. 0:02:49.880 --> 0:02:52.600 And I said, okay, well what's corporate finance and where 0:02:52.600 --> 0:02:53.760 are I go to learn that? He's like, well, you 0:02:53.760 --> 0:02:56.000 should go to Wharton And then I said, well, what's Wharton? 0:02:56.639 --> 0:02:57.520 That's how it started. 0:02:57.680 --> 0:02:58.560 That's hilarious. 0:02:58.720 --> 0:03:01.680 You finish up at Pennsylvania and you begin your career 0:03:01.720 --> 0:03:02.400 at DLJ. 0:03:03.480 --> 0:03:04.400 What sort of work. 0:03:04.200 --> 0:03:06.959 Were you doing and what were your classmates doing? This 0:03:07.000 --> 0:03:08.080 is the early nineties. 0:03:08.080 --> 0:03:08.920 You started DLJ. 0:03:09.280 --> 0:03:11.520 Yeah, I did DLJ. It was interesting. That was my 0:03:11.680 --> 0:03:17.120 summer year between junior and senior at Warden, and they 0:03:17.160 --> 0:03:19.040 kept me on throughout my senior year to finish up 0:03:19.080 --> 0:03:24.120 an interesting project, which is basically automating the job of 0:03:24.120 --> 0:03:28.240 the investment analyst that we're doing all the company working, 0:03:28.240 --> 0:03:31.160 all the tank k's, tank q's, all the information. At 0:03:31.200 --> 0:03:33.800 the time, there was a new company starting up and 0:03:33.880 --> 0:03:35.960 I know on Bloomberg, but it was called fact Set 0:03:35.960 --> 0:03:39.240 at the time. Of course, and there was a salesperson 0:03:39.280 --> 0:03:41.520 walking around trying to get anyone to talk to them 0:03:41.520 --> 0:03:44.240 because this is a brand new company. And I was 0:03:44.280 --> 0:03:47.040 a summer analyst and I was like, I've got time, 0:03:47.120 --> 0:03:49.160 I'll talk to you. And he showed me, first of 0:03:49.200 --> 0:03:51.320 all two things. She showed me this thing called Microsoft Excel. 0:03:51.480 --> 0:03:53.400 At the time, everybody was using Lettus one, two three, 0:03:53.680 --> 0:03:55.920 and he showed me basically how you can type in 0:03:55.920 --> 0:03:58.840 a ticker and that pulls in all of the financial 0:03:58.840 --> 0:04:01.840 information right into this cheat for you before the internet, 0:04:01.880 --> 0:04:03.120 but you know what was kind of the internet at 0:04:03.160 --> 0:04:05.280 the time. I was like, wow, this is amazing. I 0:04:05.320 --> 0:04:07.880 was like, this could save me hours and hours of work. 0:04:08.280 --> 0:04:10.400 And so I went to the MD at the time 0:04:10.600 --> 0:04:12.240 and I said, hey, I think I can automate most 0:04:12.240 --> 0:04:14.560 of what the analysts are doing. He said, you're a 0:04:14.560 --> 0:04:16.640 summer intern. We're not paying you much. Go at it. 0:04:16.880 --> 0:04:20.120 And that's what I did. So I started off in that, 0:04:20.400 --> 0:04:21.960 but I mainly learned that I didn't want to do 0:04:22.480 --> 0:04:25.039 investment banking because it didn't hit on my course skill set, 0:04:25.040 --> 0:04:29.520 which was like engineering back down quantitative techniques and tools. 0:04:29.920 --> 0:04:32.240 That sounds really interesting. It's amazing to have that sort 0:04:32.279 --> 0:04:35.000 of experience as an intern, How did you land at 0:04:35.000 --> 0:04:36.240 Goldman Sachs. 0:04:36.839 --> 0:04:39.400 Like everything in life that works out well, that's you know, 0:04:39.480 --> 0:04:41.920 a lot of hard work but mostly luck. Because of 0:04:41.960 --> 0:04:44.960 the DLJA experience, that was a good thing to have 0:04:45.000 --> 0:04:48.640 on my resume. Cliff Asnas founder of AQR Capital, managing 0:04:48.680 --> 0:04:51.919 partner there at the time. I think it was late twenties. 0:04:52.440 --> 0:04:54.960 He was finishing up his PhD at the University of 0:04:55.000 --> 0:04:59.120 Chicago and was working for Goldman Asset Management. He got 0:04:59.160 --> 0:05:02.440 the mand to launch a new quantitative research group, and 0:05:02.480 --> 0:05:05.040 so he wanted to hire someone who had both the 0:05:05.080 --> 0:05:09.719 finance background and the computer science background. I had started 0:05:09.760 --> 0:05:11.760 with a couple of friends a software business in high 0:05:11.800 --> 0:05:14.680 school and at Penn. One of the things I did 0:05:14.760 --> 0:05:16.960 with my roommate was we started up a hardware business, 0:05:17.240 --> 0:05:19.479 kind of like Michael Dell, building and selling computers to 0:05:20.720 --> 0:05:23.320 faculty and students on campus. So I had the computer 0:05:23.360 --> 0:05:26.560 science background. Cliff had gone undergrad at Penn at Wharton also, 0:05:26.680 --> 0:05:28.559 so he knew that we'd taken the same kind of courses. 0:05:28.600 --> 0:05:30.880 We spoke the same language from that perspective, and I 0:05:30.880 --> 0:05:33.760 had that technology background. So I was his first tire 0:05:33.760 --> 0:05:36.400 as he was building out that new team. What my 0:05:36.440 --> 0:05:39.120 other colleagues did back then, you had basically three choices 0:05:39.120 --> 0:05:42.479 come out of Warden. It was accounting, investment, banking, and consulting. 0:05:43.320 --> 0:05:46.000 There was really no jobs for asset management, but those 0:05:46.000 --> 0:05:48.080 are the courses I love the most at Penn and 0:05:48.400 --> 0:05:50.520 really wanted to pursue that. So it was a great opportunity. 0:05:50.680 --> 0:05:54.920 So you spend three years or so at Goldman with Cliff. 0:05:55.480 --> 0:05:57.680 By that point he had been there for a while 0:05:58.360 --> 0:06:01.120 and decided, hey, I think I have a little more 0:06:01.160 --> 0:06:05.320 freedom and opportunity to find launch a fund on our own. 0:06:06.080 --> 0:06:08.080 You were there day one, you left with him, right, 0:06:08.120 --> 0:06:09.840 tell us a little bit about what it was like 0:06:10.520 --> 0:06:12.719 standing up AQR with aastness. 0:06:13.240 --> 0:06:16.880 It was great. We started off this little background there 0:06:17.480 --> 0:06:20.280 as a research group within g SAM so think cost 0:06:20.360 --> 0:06:22.799 center and just putting some timeframes around this. This is nineteen 0:06:22.880 --> 0:06:26.080 ninety four, which is one of the toughest years in 0:06:26.080 --> 0:06:28.560 Goldman's history, even going back to the Great Depression. It 0:06:28.600 --> 0:06:30.640 was the kind of year where trem and a partner 0:06:30.680 --> 0:06:33.359 you get to put in money. Wow, which was was 0:06:33.400 --> 0:06:34.240 it that bad a year? 0:06:34.240 --> 0:06:36.599 I don't remember. Ninety four is a terrible market year. 0:06:36.680 --> 0:06:39.120 That was the year where the Fed had the surprise 0:06:39.279 --> 0:06:42.040 significant rate hike in feb I was actually on the floor. 0:06:42.160 --> 0:06:46.159 I think bonds took a whack, but equities also wobbled 0:06:46.160 --> 0:06:46.400 a bit. 0:06:46.839 --> 0:06:48.159 Is that a well a bit? But yeah, it was 0:06:48.200 --> 0:06:50.599 really a bad year for fixed income and the firm 0:06:50.640 --> 0:06:53.440 had a lot of risk and fixing, I presume, which 0:06:53.520 --> 0:06:56.120 led to the tough year. Yeah. So we were a 0:06:56.120 --> 0:07:00.640 research group, cost center, and then left in people were 0:07:00.680 --> 0:07:04.359 disappearing week by week as they were cutting down really headcount, 0:07:04.880 --> 0:07:06.840 and so quickly we realized we've got to start gendering 0:07:06.920 --> 0:07:09.640 some revenue. We want to say, alive. And Cliff went 0:07:09.680 --> 0:07:11.680 to them and said, hey, we've been we built some 0:07:11.840 --> 0:07:14.840 interesting models. We think we're good at picking stocks and 0:07:14.920 --> 0:07:17.480 futures and things like that. We think we can trade 0:07:17.480 --> 0:07:20.040 on this and make some money. He convinced the partnership 0:07:20.040 --> 0:07:21.520 to give us some money. So it's basically a prop 0:07:21.560 --> 0:07:24.280 trading effort. For a little while, it did very well. 0:07:24.320 --> 0:07:26.600 They kept adding money to it, and then we opened 0:07:26.600 --> 0:07:28.080 it up and turned it into a fund. It was 0:07:28.080 --> 0:07:31.040 really Goldman's first real hedge fund coming out of g 0:07:31.160 --> 0:07:34.480 SAM that funded very well, which really opened the door 0:07:34.640 --> 0:07:37.080 for us to be able to leave and start up 0:07:37.160 --> 0:07:40.040 and raise money as an independent hedge fund. 0:07:40.160 --> 0:07:43.880 What were the specific strategies Cliff was running at g 0:07:44.080 --> 0:07:46.000 SAM with the partner's money. 0:07:46.280 --> 0:07:48.800 It was a multi strategy approach, but it was all quantitative. 0:07:48.800 --> 0:07:51.360 And when I say quantitative, that means a lot of 0:07:51.360 --> 0:07:55.600 things to different people. I think about every good investment 0:07:55.640 --> 0:07:58.960 process is really a process, and whether people would label 0:07:59.000 --> 0:08:01.880 as quantitative or or not is really how automated it is. 0:08:02.440 --> 0:08:06.040 And so by quantity of I mean like really automated 0:08:06.200 --> 0:08:09.160 downloading public data for the most part, pumping it through 0:08:09.200 --> 0:08:11.960 some systems, and that causes you to want to buy 0:08:12.000 --> 0:08:14.480 and sell different instruments around the world. 0:08:14.360 --> 0:08:16.760 But you're still creating or Cliff at the time was 0:08:16.800 --> 0:08:19.960 creating models, and the models would give him a ranked 0:08:20.000 --> 0:08:22.840 list of Hey, the top ten stocks on this list 0:08:22.880 --> 0:08:25.440 of a thousand are really or whatever the number is, 0:08:26.000 --> 0:08:28.120 are things you want to look at, either getting long 0:08:28.200 --> 0:08:30.720 or short based on whatever that model is. 0:08:30.880 --> 0:08:33.480 That's right. So that you'd have many different signals, and 0:08:33.520 --> 0:08:35.760 we're treading many different asset classes, and so it's like 0:08:35.760 --> 0:08:38.640 you're saying all those signals you would givefferent weights different signals, 0:08:38.679 --> 0:08:40.920 and those would add up to you like these things, 0:08:40.920 --> 0:08:43.640 you don't like these things. We would trade global equities 0:08:43.679 --> 0:08:46.160 in a bunch of different countries, but market neutral so 0:08:46.240 --> 0:08:47.800 long as much as you are short, so you're not 0:08:47.800 --> 0:08:49.679 taking a bet on is the market going to go 0:08:49.720 --> 0:08:52.240 up or down. You're really taking a bet on this 0:08:52.280 --> 0:08:54.320 group of stocks is going to perform this other group 0:08:54.360 --> 0:08:57.120 of stocks by looking at a bunch of different characteristics. 0:08:57.720 --> 0:09:00.680 We did that for stocks, We did it for currencies, 0:09:00.760 --> 0:09:03.680 for commodities, you name it was. It was tradable, and 0:09:03.720 --> 0:09:06.640 we had data we wanted to be trading it. And 0:09:06.840 --> 0:09:09.080 that's really what the genesis of that fund was. 0:09:09.160 --> 0:09:12.560 How long were you guys doing that before you realized, hey, 0:09:12.600 --> 0:09:15.240 this is really going to be a successful model, And 0:09:15.280 --> 0:09:18.160 then how much longer was it before maybe we should 0:09:18.240 --> 0:09:22.200 do this out from under the compliance regulations of a 0:09:22.200 --> 0:09:23.000 broker dealer. 0:09:23.480 --> 0:09:26.559 We started that as a fund really in nineteen ninety five. 0:09:26.600 --> 0:09:28.680 It had been trading prop for a little time with 0:09:28.720 --> 0:09:32.559 Goldman's money, and we made money almost every month. Basically 0:09:32.960 --> 0:09:35.559 it traded as a fund, and you think we left 0:09:35.640 --> 0:09:37.640 in terms of a timing perspective, you know, they started 0:09:37.720 --> 0:09:40.800 nineteen ninety five We left early nineteen ninety eight, so 0:09:40.840 --> 0:09:43.280 it's only a couple of years in change that we 0:09:43.280 --> 0:09:46.680 were trading this within g SAM before leaving to start 0:09:46.720 --> 0:09:47.280 at BAQR. 0:09:48.040 --> 0:09:50.160 So let's talk a little bit about AQR. You there 0:09:50.200 --> 0:09:54.400 from inception, from day one. What was that transition like 0:09:54.600 --> 0:09:58.960 from you know, I imagine at Goldman Sachs you have access 0:09:59.000 --> 0:10:02.439 to life, lots of support, lots of tools, lots of data, 0:10:02.480 --> 0:10:05.960 lots of everything. What's it like starting over again from 0:10:06.080 --> 0:10:08.320 scratch in a standalone hedge fund. 0:10:08.679 --> 0:10:11.040 I'll tell you a funny story. So I got into 0:10:11.160 --> 0:10:15.079 a few different battles with the administration folks at Goldman 0:10:15.120 --> 0:10:18.440 Sachs size management. If you remember, like in college, I 0:10:18.440 --> 0:10:21.000 had a computer business where we'd like buy parts, build 0:10:21.000 --> 0:10:23.319 computers and sell them, and so I knew how to 0:10:23.360 --> 0:10:26.000 build my own computers. Goldman Sachs. At the time, the 0:10:26.040 --> 0:10:28.520 standard computer that everybody had was what was called an 0:10:28.559 --> 0:10:32.240 eight eighty six. This is like the first real PC 0:10:32.720 --> 0:10:36.080 that IBM had out there, and you know, they were good, 0:10:36.120 --> 0:10:39.880 but they weren't the most advanced available machines. Basically, I 0:10:39.920 --> 0:10:41.360 went to the administration and I said, look, we need 0:10:41.360 --> 0:10:43.079 the most advanced machines because we're trying to run a 0:10:43.120 --> 0:10:46.840 lot of computationally intensive models and this machine we have 0:10:46.880 --> 0:10:48.680 now is very slow at taking very long to run 0:10:48.679 --> 0:10:51.760 our models. You can buy the latest machine at half 0:10:51.800 --> 0:10:54.280 the price of what Goldman was paying and get twice 0:10:54.320 --> 0:10:56.640 the performance. What I didn't realize at the time is 0:10:56.679 --> 0:10:58.360 that when you're trying to run an organization that large 0:10:58.360 --> 0:10:59.360 and complex. 0:10:59.000 --> 0:11:00.800 I want everything stand you. 0:11:00.760 --> 0:11:02.920 Can't support it unless everything's standardized. And so there was 0:11:02.920 --> 0:11:04.400 a reason for it which I didn't understand. 0:11:04.400 --> 0:11:06.720 That you guys can support your own hardware. 0:11:06.760 --> 0:11:07.640 That's not that hard. 0:11:08.440 --> 0:11:11.000 Cliff eventually persuaded them to give let us get the 0:11:11.240 --> 0:11:13.440 new machines. But one of the big changes as you 0:11:13.480 --> 0:11:15.640 talk about leaving a place, you know you have lots 0:11:15.679 --> 0:11:19.360 of resources and whatnot at large organizations, but you have 0:11:19.440 --> 0:11:22.000 limited resources at every place, no matter how big you are. 0:11:22.080 --> 0:11:24.920 There's always trade offs that you're making when you start 0:11:25.000 --> 0:11:28.000 up as a new firm. One thing that was a 0:11:28.000 --> 0:11:30.280 big change is that at Goldman we had to support 0:11:30.360 --> 0:11:34.400 lots of other groups. We were providing research advice, investment advice, 0:11:35.120 --> 0:11:37.400 talk to clients, help them raise money in other products. 0:11:37.760 --> 0:11:39.960 When we launched you own hedge fund. All that matter 0:11:40.080 --> 0:11:43.360 was making money in that hedge fund, so helping that 0:11:43.400 --> 0:11:45.839 focus was important, and we were able to buy the 0:11:45.880 --> 0:11:47.360 latest computers that have the cost. 0:11:47.280 --> 0:11:49.560 I'm going to bet that you did something a little 0:11:49.600 --> 0:11:52.319 beefier than those IBM eight to eighty six is. 0:11:52.679 --> 0:11:54.880 Yeah, I was overclocking the machines. I was doing all 0:11:54.920 --> 0:11:56.800 the pulling, all the ways to get things to go 0:11:56.840 --> 0:11:57.680 as fast as possible. 0:11:57.760 --> 0:11:58.000 Huh. 0:11:58.400 --> 0:12:03.000 Really interesting. So at AQR you juggled a lot of responsibilities. 0:12:03.040 --> 0:12:06.360 You were a portfolio manager, researcher, head of trading, and 0:12:06.440 --> 0:12:10.920 apparently tech geek putting machines together. What was it like 0:12:11.160 --> 0:12:13.280 juggling all these different responsibilities. 0:12:14.000 --> 0:12:15.840 There's a couple things I'll say about that. So one thing, 0:12:15.920 --> 0:12:17.920 just from a personal perspective, my wife and I we 0:12:17.960 --> 0:12:21.040 have five children together, and that's a lot to deal with. 0:12:21.559 --> 0:12:23.320 My wife is amazing, and there's no way I would 0:12:23.320 --> 0:12:24.640 be able to do all the stuff I do at 0:12:24.679 --> 0:12:27.040 work if it weren't for her being amazing and handling 0:12:27.080 --> 0:12:30.800 everything at home. So that's the first thing, and how 0:12:30.840 --> 0:12:33.360 I get so many things done at work. I'm also 0:12:33.600 --> 0:12:36.760 from a personality perspective, I get bored very quickly. I 0:12:36.880 --> 0:12:39.480 like learning and doing a lot of different things. I 0:12:39.559 --> 0:12:41.800 like being able to jump around, So to me, that's 0:12:41.840 --> 0:12:45.200 just fun. The consequence is sleep. I don't sleep very much. 0:12:46.000 --> 0:12:50.120 What do you mean, not very much? And you know 0:12:50.160 --> 0:12:51.600 that only gets worse as you get older. 0:12:51.880 --> 0:12:55.120 We usually get to sleep around one am and you know, 0:12:55.280 --> 0:12:56.360 six six thirty something like that. 0:12:56.360 --> 0:12:58.880 All right, so five hours, that's not terrible, not too terrible. 0:12:59.080 --> 0:13:01.280 I've lived on six hours most of my life and 0:13:01.280 --> 0:13:04.719 it's and you get older that that shrinks. I thought 0:13:04.760 --> 0:13:07.160 you were referencing the five kids, because it's like, hey, 0:13:07.160 --> 0:13:09.000 when you have five kids, you want how to juggle 0:13:09.000 --> 0:13:11.560 a lot of different things at once because something is 0:13:11.600 --> 0:13:13.079 always that's fine. 0:13:13.080 --> 0:13:15.280 There's always something going on, that's for sure. 0:13:15.800 --> 0:13:18.480 What was it like working with Cliff back in the days. 0:13:19.640 --> 0:13:21.800 It was fun. I think Cliff's greatd a lot of 0:13:21.800 --> 0:13:25.160 different things, but one was he hired well. He was 0:13:25.200 --> 0:13:28.520 able to attract really talented people and then he just 0:13:28.600 --> 0:13:31.240 let them do what they do. So he's not a micromanager. 0:13:31.320 --> 0:13:33.959 He just lets them run with it. And so that 0:13:34.080 --> 0:13:36.040 was a very fortunate thing for me right place, right 0:13:36.040 --> 0:13:37.360 time in terms of being able to get a lot 0:13:37.360 --> 0:13:41.400 of responsibility early on, and that's how I was able 0:13:41.440 --> 0:13:43.480 to not just be a researcher building models and creating 0:13:43.520 --> 0:13:46.360 new strategies that I'd run by Cliff and he would say, Okay, 0:13:46.360 --> 0:13:47.760 you're doing this dumb or doing that dumb, and you 0:13:47.840 --> 0:13:51.720 got to improve this, but also doing all the trading 0:13:51.960 --> 0:13:55.000 by myself for the firm for the first several years, 0:13:55.200 --> 0:13:56.600 and then eventually saying, hey, Cliff, you know I need 0:13:56.720 --> 0:13:58.520 some help here. We need to hire, you know, someone 0:13:58.559 --> 0:14:01.720 to run technology other than me. We need to hire 0:14:01.800 --> 0:14:03.840 more traders than just me so that I can actually sleep. 0:14:04.440 --> 0:14:06.520 So that's how he ran it. And it was a 0:14:06.520 --> 0:14:08.040 lot of fun. I mean you mentioned it earlier on. 0:14:08.080 --> 0:14:10.240 I mean Cliff hilarious and he's. 0:14:10.040 --> 0:14:12.920 A funny guy. And it's rare to find someone who 0:14:13.000 --> 0:14:17.320 is a quant who can communicate as eloquently as he 0:14:17.440 --> 0:14:20.240 can and at the same time has such a devilish 0:14:20.320 --> 0:14:24.360 sense of humor. Like that's an unusual trifecta right there. 0:14:24.200 --> 0:14:27.760 And it's part of what makes him fantastic as an individual, 0:14:27.760 --> 0:14:31.320 but also fantastic to work with and work for. It 0:14:31.640 --> 0:14:35.480 made the place fun even in the tough times. And 0:14:35.520 --> 0:14:37.440 so that's a big reason why I think a lot 0:14:37.440 --> 0:14:39.840 of people stuck through lots of the ups and downs 0:14:39.840 --> 0:14:40.960 that any organization has. 0:14:41.200 --> 0:14:44.240 Let's talk a little bit about the AQR experience. The 0:14:44.400 --> 0:14:49.600 firm seems very I almost want to say academic. They 0:14:49.640 --> 0:14:51.960 publish a lot of white papers, they do a lot 0:14:52.040 --> 0:14:57.800 of research, They have very specific opinions on different topics 0:14:57.840 --> 0:15:01.000 that seem to come up in the world of finance. 0:15:01.120 --> 0:15:06.440 How much of this intellectual firepower is part think tank 0:15:06.480 --> 0:15:08.240 and how much of it is just Hey, if you're 0:15:08.240 --> 0:15:11.040 going to have an investment perspective, you need to have 0:15:11.080 --> 0:15:13.280 the intellectual underpinnings to justify it. 0:15:14.360 --> 0:15:16.280 So I think one thing that makes acar a very 0:15:16.280 --> 0:15:20.640 powerful is its ability to attract top talent, specifically on 0:15:20.680 --> 0:15:24.680 the academic side. The smart people want to hang out 0:15:24.680 --> 0:15:27.920 with other smart people. That there is definitely a network 0:15:27.920 --> 0:15:30.800 effect that happens there. And I would say part of 0:15:30.800 --> 0:15:34.400 the compensation you're getting indirectly by being in an organization 0:15:34.560 --> 0:15:38.200 like that is getting exposure to all these great minds 0:15:38.200 --> 0:15:40.520 that you can learn from, you can bounce ideas off of. 0:15:41.040 --> 0:15:43.120 So is it a think tank? Yeah, I think it 0:15:43.160 --> 0:15:45.040 is a think tank from that perspective, But at the 0:15:45.120 --> 0:15:47.000 end of the day, it's a business and they're there 0:15:47.040 --> 0:15:49.840 to make money, make money for their investors, so I 0:15:49.880 --> 0:15:52.360 think there is a lot of focus on that as well. 0:15:52.400 --> 0:15:56.640 So the publications, you see a lot of white papers, 0:15:57.200 --> 0:15:59.600 and sure, I would say it rhymes with a lot 0:15:59.600 --> 0:16:01.640 of things they do. But they obviously keep a lot 0:16:01.680 --> 0:16:05.440 of the special sauce unpublished and use that within their funds. 0:16:05.600 --> 0:16:08.680 But they're still writing about broad strokes. So let's talk 0:16:08.680 --> 0:16:11.640 about a white paper that you wrote titled the Evolution 0:16:11.760 --> 0:16:16.040 of Alpha. Tell us how has alpha evolved over the 0:16:16.040 --> 0:16:17.360 past few decades. 0:16:17.560 --> 0:16:20.280 Sure, this is a white paper I wrote from my 0:16:20.400 --> 0:16:25.640 clear Apha Cio CEO hat and it really talks about 0:16:25.680 --> 0:16:29.160 the history of the hedge fund industry, why different models 0:16:29.160 --> 0:16:33.200 of delivering alpha, starting with let's say single strategy hedge funds, 0:16:34.280 --> 0:16:40.080 fund of funds, multi strategy funds, and now multi strategy 0:16:40.160 --> 0:16:44.560 multi manager are multipm funds and that's the latest evolution. 0:16:44.640 --> 0:16:46.280 And then we talk about what we think might be 0:16:46.320 --> 0:16:50.000 the next step, part of which we think we will drive. 0:16:51.040 --> 0:16:54.600 So that's the point of the paper. And there's reasons 0:16:54.680 --> 0:16:57.280 why you went from different models from one to the next, 0:16:57.600 --> 0:16:59.600 and it has to do with a variety of things. 0:16:59.600 --> 0:17:00.920 I can Curg. You to read the paper, it's on 0:17:00.920 --> 0:17:01.640 our website. 0:17:02.000 --> 0:17:05.959 But so let's follow that up. What were the drivers 0:17:06.680 --> 0:17:10.960 of the shift from a single manager to multiple managers 0:17:11.000 --> 0:17:13.959 to multi strategy to multi manager multi strategy. 0:17:14.359 --> 0:17:15.719 What was the key driver of that? 0:17:16.240 --> 0:17:19.200 Starting back this is around two thousand, let's say. Obviously 0:17:19.240 --> 0:17:22.359 hedge funds existed before that, but that's really the point 0:17:22.359 --> 0:17:25.400 at which at least a meaningful amount of institution investors 0:17:25.400 --> 0:17:28.480 actually started having investments in hedge funds as like a 0:17:28.560 --> 0:17:31.639 normal course of business. That was the year obviously that 0:17:31.840 --> 0:17:33.760 the market sold off a lot. That was the Enron 0:17:34.280 --> 0:17:38.840 fiasco and whatnot. A lot of Wall Street was let go, 0:17:38.960 --> 0:17:41.000 so a lot of talent was being let go, and 0:17:41.119 --> 0:17:44.119 much of that talent was investment analysts, research chants. The 0:17:44.160 --> 0:17:46.720 covered stocks new stocks, deeply knew the management of those 0:17:46.720 --> 0:17:50.280 companies deeply. So if you're an investment analyst at a 0:17:50.280 --> 0:17:54.320 Wall Street bank, you go off and hang up a shingle, 0:17:54.359 --> 0:17:56.600 start a single strategy hedge fund where you're picking stocks. 0:17:56.960 --> 0:17:59.080 You had an argument why you'd have an edge because 0:17:59.119 --> 0:18:01.920 you knew these managers these stocks deeply. And that's really 0:18:02.560 --> 0:18:04.800 was like a Cambrian explosion of hedge funds at that 0:18:04.840 --> 0:18:07.080 moment in time, and even to this day, I think 0:18:07.160 --> 0:18:10.159 in terms of like sheer number count, the vast majority 0:18:10.200 --> 0:18:12.040 of hedge funds are really stock picking hedge funds. 0:18:12.040 --> 0:18:14.720 Long short eleven thousand hedge funds out there too. 0:18:14.720 --> 0:18:19.680 Yeah, yeah, long short discretionary equity stockpicking hedge funds. That 0:18:20.680 --> 0:18:23.440 models survived for a little while, but as investors were 0:18:23.440 --> 0:18:26.959 investing in these individual kind of single strategy, single style 0:18:27.040 --> 0:18:30.520 hedge funds, what they realize is that anyone single approach 0:18:31.040 --> 0:18:32.639 is not very consistent. You know, it's going to go 0:18:32.640 --> 0:18:34.800 through it's good periods and it's bad periods, and it's 0:18:34.800 --> 0:18:38.240 hard to hang on to what I would call be 0:18:38.280 --> 0:18:40.879 exposed to what the line item risk is. When you 0:18:40.920 --> 0:18:44.120 have these quarterly reviews of what's going on the portfolio, 0:18:44.359 --> 0:18:47.240 invariably the discussion is, let's talk about the things that 0:18:47.280 --> 0:18:51.040 are down the most, and that leads to, you know, 0:18:51.520 --> 0:18:55.320 firing managers when they're down, usually just after a environment 0:18:55.320 --> 0:18:58.240 that was just bad for their approach, before it rebounds 0:18:58.280 --> 0:19:00.320 and does well, you know, in the next year. So 0:19:00.560 --> 0:19:04.640 that model, well it still exists today, is tough from 0:19:04.680 --> 0:19:07.800 an investment to stick with. Then you switch to fund 0:19:07.840 --> 0:19:10.480 of funds and soucial investors. You know, one stop shop, 0:19:10.520 --> 0:19:12.160 buy into a fund of funds. You can get exposure 0:19:12.200 --> 0:19:16.600 to many different strategies and styles in one vehicle. That's 0:19:16.760 --> 0:19:19.639 what came out of that and was to address this inconsistency. 0:19:19.680 --> 0:19:22.240 So fund of funds were more consistent than a single 0:19:22.240 --> 0:19:27.520 strategy fund. But I would say the consequence and its 0:19:28.359 --> 0:19:31.600 or the issue really is both for fund of funds 0:19:31.640 --> 0:19:34.840