WEBVTT - Re-run: Gappy Paleologo 0:00:02.720 --> 0:00:12.640 Bloomberg Audio Studios, podcasts, radio news, Happy Thanksgiving. 0:00:13.520 --> 0:00:16.280 I hope you're having a great holiday. We are obviously 0:00:16.360 --> 0:00:18.880 not recording on this Thursday, so we're. 0:00:18.680 --> 0:00:23.239 Gonna rerun a favorite old episode. It's going to be great. 0:00:23.320 --> 0:00:26.400 You're going to enjoy it even more the second time. Bye. 0:00:30.520 --> 0:00:34.199 Wait gay palio logo or. 0:00:36.320 --> 0:00:38.519 I'm so excited for you to tackle that and not me. 0:00:38.880 --> 0:00:39.360 Good luck. 0:00:39.520 --> 0:00:41.040 I thought I had it down, but then I heard 0:00:41.080 --> 0:00:43.519 you say it, and I feel like. 0:00:43.479 --> 0:00:45.720 When I first met you, I think I asked you 0:00:46.479 --> 0:00:53.040 if you go by gappie because of your famous track 0:00:53.040 --> 0:00:56.960 record of taking gardening leave, like having gaps in your 0:00:57.040 --> 0:00:57.920 career as well. 0:00:58.640 --> 0:01:02.600 Okay I didn't remember. Yeah, that's a great excuse for 0:01:02.600 --> 0:01:06.720 for a nickname. No, But the reason is when I 0:01:06.760 --> 0:01:09.840 came to the States for grad school, and this was 0:01:09.880 --> 0:01:12.720 a long time ago, in ninety five. So the first 0:01:12.720 --> 0:01:15.759 thing that you did was set up an email account. 0:01:17.200 --> 0:01:19.160 You still had the freedom to choose an Emil account. 0:01:19.160 --> 0:01:21.440 Now they just give you your initials with the number, 0:01:21.640 --> 0:01:27.559 and so my initials are gap Gapo, and of course 0:01:27.640 --> 0:01:32.040 it was taken. So I said, okay, well Gappy, and 0:01:32.080 --> 0:01:36.480 then everybody in grad school and then my wife was Italian, 0:01:36.760 --> 0:01:39.600 everybody started to call me Gappy and that's stuck. 0:01:40.000 --> 0:01:41.040 And now at. 0:01:40.880 --> 0:01:44.200 Work they just have dispensed with my real name, like 0:01:44.280 --> 0:01:46.640 on all systems, I'm just Gappy Paliologo. 0:01:46.720 --> 0:01:48.920 So I expect that that will be, you know. 0:01:49.240 --> 0:01:53.360 Prosecuted for tax evasion because on my tax forms there 0:01:53.400 --> 0:01:55.120 is Gappy Paliologo or something like that. 0:01:55.440 --> 0:01:58.800 Well, hello, and welcome to the Stuff podcast. 0:01:58.920 --> 0:02:01.800 I'm at Livian and I'm Katie Greifeld. 0:02:01.440 --> 0:02:06.120 And we have a guest today, Gabby Paleo Logo, who 0:02:06.200 --> 0:02:10.560 is now at pali Asney has been at most of 0:02:10.600 --> 0:02:13.760 the other pig Catch funs and Hudsond River Trading. I 0:02:13.800 --> 0:02:16.200 do want to start by talking about. 0:02:15.919 --> 0:02:19.040 Gardening there, Okay, Natural Purse. 0:02:19.320 --> 0:02:23.320 I think that we counted from your link. Your LinkedIn 0:02:23.440 --> 0:02:27.400 is like famous for discussing your gardening leave in some detail, 0:02:27.960 --> 0:02:30.519 and I think we counted three years of gardening leave. 0:02:30.919 --> 0:02:33.840 No, I think it's a bit like Okay, it's not precise. 0:02:33.960 --> 0:02:37.720 Fifteen months from Citadel, one year Hudson River Trading, and 0:02:38.040 --> 0:02:42.200 four months from Millennium. Okay, so pretty close, not terrible, 0:02:42.200 --> 0:02:44.480 though a bit less than two years. 0:02:44.880 --> 0:02:49.080 From my perspective, it seems very fun. Did you enjoy 0:02:49.080 --> 0:02:50.440 your three years of gardening? 0:02:50.680 --> 0:02:51.800 I do so. 0:02:52.200 --> 0:02:57.840 I try to keep myself busy, so I teach, typically 0:02:57.880 --> 0:03:01.239 at some university. So the first time during my Seitaadel 0:03:01.240 --> 0:03:05.400 two millennium, Guardian Leve I was teaching at Cornell and 0:03:05.520 --> 0:03:09.239 in the HRT to Bam Guardian Leve was at NYU. 0:03:09.440 --> 0:03:12.480 And I love teaching. And then what I do is 0:03:13.320 --> 0:03:17.800 it helps me focus on stuff. Usually what I do 0:03:18.320 --> 0:03:22.359 in you know, whenever I read a book or read 0:03:22.400 --> 0:03:25.560 a paper that I like, I take notes, take notes 0:03:25.600 --> 0:03:29.720 in lattech, and then I read, arrive or think about things, 0:03:29.919 --> 0:03:34.079 and so that typically is the basis for my course material, 0:03:34.600 --> 0:03:37.760 and then it becomes the basis for my books. I've 0:03:37.760 --> 0:03:39.680 written a couple of books during my non competes. 0:03:39.880 --> 0:03:43.160 Interesting because thinking about gardening leave. Matt and I talk 0:03:43.160 --> 0:03:46.040 about it all the time, because it's very alluring to me. 0:03:46.280 --> 0:03:49.520 Gardening leave doesn't really exist in journalism. I love to 0:03:49.560 --> 0:03:51.720 imagine what I would do. But one of the questions 0:03:51.760 --> 0:03:53.560 I had for you was, you know, do you ever 0:03:53.640 --> 0:03:57.160 have anxiety about losing your edge or falling behind? But 0:03:57.640 --> 0:03:59.840 it sounds like teaching is one of the ways that. 0:04:00.600 --> 0:04:02.960 Yeah, I'm not particularly worried with that. 0:04:03.200 --> 0:04:05.800 I think that there is only a very specific subset 0:04:05.960 --> 0:04:10.080 of quantitative researchers who are afraid of losing their edges. 0:04:10.880 --> 0:04:13.800 And yeah, that's not been my case. I keep reading. 0:04:14.040 --> 0:04:15.440 I try to stay up to date. 0:04:15.680 --> 0:04:18.800 To the feedback into the work. Like do you get 0:04:18.880 --> 0:04:21.520 ideas or like deep in your understanding of techniques by 0:04:21.839 --> 0:04:24.160 teaching and writing the books? Or are they just sort 0:04:24.200 --> 0:04:24.680 of like. 0:04:26.080 --> 0:04:29.680 Extracurricular No, no, no, it's definitely I learn a lot 0:04:29.720 --> 0:04:30.680 from writing the books. 0:04:31.000 --> 0:04:32.440 How long do you I get to hear your next job? 0:04:32.480 --> 0:04:35.600 And yeah, generate more profits by of. 0:04:35.560 --> 0:04:38.400 Course, plenty more profits. Sell that to my employers. 0:04:38.520 --> 0:04:42.000 No, but I definitely I learn a lot from writing 0:04:42.279 --> 0:04:46.440 from the first drafts, and then I rewrite and rewrite, 0:04:46.520 --> 0:04:49.640 and I learn a lot from discarding material too. It's 0:04:49.760 --> 0:04:52.520 very useful to discard material. It makes you really focus 0:04:52.560 --> 0:04:56.159 on what matters and what doesn't. So I try to 0:04:56.160 --> 0:05:00.600 give a narrative, like a logical connection between various topics, 0:05:00.760 --> 0:05:04.039 and that is something that is possible only when you 0:05:04.080 --> 0:05:08.000 write a book. I really do not like writing that. 0:05:08.160 --> 0:05:10.760 Nobody I think likes writing, maybe except for you. 0:05:11.120 --> 0:05:15.760 I I think I understand that it's weird even among writers, but. 0:05:15.720 --> 0:05:18.799 It is very I find it very painful. I find 0:05:18.839 --> 0:05:23.400 painful letting go of material, Yes, but I also like it. 0:05:23.560 --> 0:05:27.800 You know, it's some kind of strange delayed gratification. 0:05:27.960 --> 0:05:30.600 I guess one theory that I have written is that 0:05:31.839 --> 0:05:37.600 hedge funded quantitative research gardening leave is like a source 0:05:37.640 --> 0:05:40.359 of like human flourishing, because you have all these like 0:05:40.440 --> 0:05:43.719 highly trained people who haven't enforced the year of And 0:05:43.760 --> 0:05:46.159 I've written that all the Hedge fund researchers should go 0:05:46.160 --> 0:05:51.800 work at LM companies or like analytics departments of sports teams. 0:05:52.680 --> 0:05:55.960 And I'm like, partially kidding and partially not. How true 0:05:56.640 --> 0:05:59.760 is it for you? Like how much of like your 0:06:00.720 --> 0:06:06.839 quantitative skills at this point are really just for investing in? 0:06:06.880 --> 0:06:09.680 How much of it is like if you spent three months, 0:06:10.440 --> 0:06:12.839 you know, consulting for a soccer team, you would be 0:06:12.839 --> 0:06:14.520 able to tell them how to find better players. 0:06:17.080 --> 0:06:19.920 I'm not sure, so I'll say this right. I was 0:06:19.960 --> 0:06:22.320 thinking a few days ago if there was a kind 0:06:22.320 --> 0:06:26.000 of a common thread in my professional life because it 0:06:26.040 --> 0:06:30.200 seems kind of random, And actually I think that there is, 0:06:30.640 --> 0:06:34.880 because I think that I was about fourteen when I 0:06:34.920 --> 0:06:38.480 realized that I had an aptitude for applied math. I 0:06:38.520 --> 0:06:43.200 discovered physics, and I liked math, and I also liked 0:06:43.200 --> 0:06:47.720 literature very much, so I loved reading. I read a lot. 0:06:48.360 --> 0:06:52.000 I was not a very social animal. And then basically 0:06:52.080 --> 0:06:56.280 since then, I've been doing the same thing in various forms. Right, 0:06:56.320 --> 0:06:59.279 I did physics, I did applied math. I didn't do 0:06:59.360 --> 0:07:02.680 applied math in finance. They did applied math in weird 0:07:02.760 --> 0:07:06.800 things like optimization and logistics. So I have been doing 0:07:06.880 --> 0:07:08.760 kind of the same thing over and over, which has 0:07:08.800 --> 0:07:12.760 been writing and applying math to something. So I think 0:07:12.800 --> 0:07:14.960 that I could do it. I would like to do it, 0:07:15.320 --> 0:07:21.040 but I also think that it's not that simple to 0:07:21.080 --> 0:07:23.480 go to a new field and say, oh, after three months, 0:07:23.480 --> 0:07:26.600 I know soccer. No, there is a lot of specificity, 0:07:26.720 --> 0:07:30.840 And the beauty of I think being a good applied 0:07:31.040 --> 0:07:35.000 mathematician is that they start with the problems and with 0:07:35.080 --> 0:07:39.040 the domain first, and that they're sufficiently mature from a 0:07:39.080 --> 0:07:43.040 mathematical standpoint that they are not making too much of 0:07:43.080 --> 0:07:46.640 an effort in using math. So I think the good 0:07:46.800 --> 0:07:51.560 art of being an applied mathematician is to study persistently 0:07:51.720 --> 0:07:54.680 the application. So no, I don't think that after three 0:07:54.680 --> 0:07:57.440 months it would be good enough. But after a year, 0:07:58.120 --> 0:08:01.040 you know, about a year of being fully in an application, 0:08:01.560 --> 0:08:04.280 then you start getting a little bit better and then 0:08:05.080 --> 0:08:07.640 the mass is not the problem, and then you start 0:08:07.640 --> 0:08:08.640 doing some good work. 0:08:09.040 --> 0:08:12.040 You have a famous essay on like advice for quant 0:08:12.080 --> 0:08:15.480 careers and you say that, like, the things that matter 0:08:15.560 --> 0:08:20.480 the most are creativity and genuine interest in the problems 0:08:21.360 --> 0:08:25.720 more than you know, math course power. Yeah, this is 0:08:25.760 --> 0:08:28.160 a dumb question, but how does one develop? How does 0:08:28.160 --> 0:08:33.480 one identify you know, creativity and interest in financial topics? 0:08:33.480 --> 0:08:36.120 And is the obvious answer those are where the money is, 0:08:36.240 --> 0:08:38.920 or like like why why did you fall in love 0:08:38.960 --> 0:08:40.960 with finance as a topic? And is the answer because 0:08:41.720 --> 0:08:42.480 that's what the money is. 0:08:42.559 --> 0:08:45.160 So first of all, I think that creativity is either 0:08:45.240 --> 0:08:49.240 personality trait doesn't belong to You're not creative in finance, 0:08:49.800 --> 0:08:52.400 you know, you're you're creative in in cooking, you're creative 0:08:52.400 --> 0:08:56.080 in whatever. And it's a mix I guess of extraversion 0:08:56.240 --> 0:09:00.480 open and as to experience, and I don't what else. 0:09:00.480 --> 0:09:03.079 I'm not a psychologist, but I do believe that people 0:09:03.120 --> 0:09:06.319 are genuinely creative, and in fact, you see it right 0:09:06.360 --> 0:09:11.880 that sometimes you ask someone and you find out that, yes, 0:09:11.920 --> 0:09:16.600 they like writing, they play some instrument, if badly, and 0:09:16.880 --> 0:09:19.640 you know, and they paint and they do whatever. And 0:09:19.720 --> 0:09:22.240 so I would say, if you go to finance because 0:09:22.240 --> 0:09:24.360 that's where the money is, there's nothing wrong with that. 0:09:24.520 --> 0:09:27.840 And in a way, that's my story. You know, I 0:09:27.559 --> 0:09:29.760 was I was a researcher, and I wanted to have 0:09:29.800 --> 0:09:34.760 more money and whatnot. But eventually you stay in finance, 0:09:34.840 --> 0:09:37.520 or at least in my you know, little domain, because 0:09:37.679 --> 0:09:42.079 you're genuinely curious about finding out stuff, right. 0:09:41.960 --> 0:09:46.000 So, like why are the problems like why do they 0:09:46.040 --> 0:09:48.600 arisk curiosity? Like why are the problems of finance intrigue 0:09:48.600 --> 0:09:52.319 you after years of doing it right? Like what's interesting 0:09:52.320 --> 0:09:54.199 about those problems as opposed to other domains. 0:09:54.360 --> 0:09:56.480 It's really hard for me to say, Like I think 0:09:56.520 --> 0:10:00.320 that I read once that a young songwriter asked Bob 0:10:00.400 --> 0:10:03.400 Dylan how to become a good songwriter, and bub Bylan 0:10:03.559 --> 0:10:06.880 just answered, well, what's going on? What do you mean, 0:10:06.920 --> 0:10:08.880 what's going on? Yeah, what's going on? What's going on 0:10:08.920 --> 0:10:12.760 in your life? Just you know, look around. So sometimes 0:10:12.800 --> 0:10:15.280 I get these questions from investors or but you know, 0:10:15.520 --> 0:10:18.200 how do you keep yourself interested. How do you find problems? 0:10:18.840 --> 0:10:22.800 It's not a problem like the problems jump at you 0:10:22.880 --> 0:10:24.800 like there are too many problems. There are too many 0:10:24.800 --> 0:10:29.480 interesting problems. So if anything, the skill is in sorting 0:10:29.520 --> 0:10:32.400 the problems in the right order. Right, That is where 0:10:32.559 --> 0:10:36.440 maybe having some maturity in doing research kicks in. But 0:10:36.800 --> 0:10:40.960 there are lots of problems, infinite problems, weird problems. 0:10:41.040 --> 0:10:42.320 What's your favorite problem right now? 0:10:43.559 --> 0:10:45.400 I don't like right now, what are we working on? 0:10:45.440 --> 0:10:49.000 I mean, we are trying to understand how earnings are monetized? Right, 0:10:49.000 --> 0:10:51.640 how do you make money in earnings? It's such a 0:10:51.720 --> 0:10:54.079 basic thing in fundamental equities. 0:10:54.840 --> 0:10:57.960 And you mean, if you're like correct about predicting earnings? 0:10:58.040 --> 0:11:01.360 Yes, what are I mean? Without get into much into details, 0:11:01.440 --> 0:11:05.640 but you know there what are the relevant variables? Imagine 0:11:05.640 --> 0:11:07.880 that you had an oracle who told you what the 0:11:07.960 --> 0:11:10.240 variables are? What would you do with that? What would 0:11:10.240 --> 0:11:13.800 you do if you'd had all the information in the world, right, 0:11:13.880 --> 0:11:16.320 and everything in your world here in existence? Would be 0:11:16.400 --> 0:11:17.920 like an approximation problem. 0:11:18.040 --> 0:11:21.880 There's there's an incredible styled story of like the guys 0:11:22.120 --> 0:11:25.920 hacked into I think like one of the newswire services 0:11:25.920 --> 0:11:29.679 and got earnings releases early, like for hundreds of companies, 0:11:29.880 --> 0:11:32.160 and they traded on this and they had like a 0:11:32.200 --> 0:11:35.320 seventy percent success rate, which is great, but also like 0:11:35.520 --> 0:11:37.720 it means that had a thirty percent, Like they traded 0:11:37.720 --> 0:11:40.320 the wrong way, knowing earnings perfectly in advance. It's like 0:11:40.360 --> 0:11:40.880 a good. 0:11:41.000 --> 0:11:43.520 Yeah, yes, so they had the racle on it. You know, 0:11:43.600 --> 0:11:46.319 it's still hard, Yes, it's still very hard. Actually, shout 0:11:46.320 --> 0:11:48.839 out to Victor Hagan, who wrote the paper about ten 0:11:48.880 --> 0:11:51.720 years ago on this. He made a organize a simple 0:11:51.760 --> 0:11:56.080 controlled experiment where he gave basically a biased coin where 0:11:56.120 --> 0:11:58.160 you I think had a success rate of sixty percent 0:11:58.280 --> 0:12:01.200 forty percent failure, and you some capital and you could 0:12:01.200 --> 0:12:05.480 invest it over time on these informed predictions, and a 0:12:05.520 --> 0:12:09.800 lot of subjects went bankrupt. Okay, now I think we 0:12:09.840 --> 0:12:12.560 are better than that, but still there are lots of 0:12:12.800 --> 0:12:17.120 problems related to trading around an event. For example, before we. 0:12:17.080 --> 0:12:21.199 Get too far away, you mentioned Bob Dylan. It actually 0:12:21.280 --> 0:12:23.959 reminded me of another Bob Dylan quote which I'm going 0:12:24.040 --> 0:12:27.040 to paraphrase poorly, but he basically said, when asked about 0:12:27.520 --> 0:12:30.200 writing songs, do you think that you could write whatever 0:12:30.240 --> 0:12:32.240 the work that was being referenced now, and he said, 0:12:33.000 --> 0:12:35.760 I don't think so. It's like the words were in 0:12:35.840 --> 0:12:38.080 the air and I just plucked them out. They were 0:12:38.120 --> 0:12:40.440 just sort of hanging in the air and they came 0:12:40.440 --> 0:12:42.760 to me. And it kind of also rang true with 0:12:42.800 --> 0:12:45.080 what you were saying about you didn't go looking for problems. 0:12:45.080 --> 0:12:48.800 They're just there necessarily. I actually want to go back 0:12:48.800 --> 0:12:51.280 to applied math if it doesn't interrupt the course of 0:12:51.320 --> 0:12:54.920 conversation too much. You tweeted on June twenty fourth that 0:12:55.000 --> 0:12:58.120 there's no child prodigies when it comes to poetry, when 0:12:58.160 --> 0:13:01.560 it comes to applied mathematics. And I'm not saying that. 0:13:01.600 --> 0:13:03.360 You said that you were a prodigy, but you were 0:13:03.400 --> 0:13:07.640 a child at fourteen. I mean, how how fourteen do 0:13:07.679 --> 0:13:10.480 you realize that you have an aptitude for something like 0:13:10.520 --> 0:13:12.240 applied mathematics. 0:13:13.000 --> 0:13:15.280 I don't want to flex about this stuff, No you should. 0:13:17.000 --> 0:13:19.240 I think I'm honestly a little weird. I'm just a 0:13:19.240 --> 0:13:20.839 little weird, I think, honestly. 0:13:20.559 --> 0:13:23.720 But I like prodigy weird or I did. 0:13:23.640 --> 0:13:26.760 Have my share of yeah, adults telling me that I 0:13:26.880 --> 0:13:29.880 was good at this or that or you know, but yeah, 0:13:30.080 --> 0:13:31.319 I mean, okay. 0:13:31.720 --> 0:13:33.520 I'm just a little bit atypical. 0:13:33.559 --> 0:13:36.880 Also, when I talk to investors, I think investors enjoying 0:13:36.920 --> 0:13:42.360 my presence because I think I'm incredibly unfiltered for somebody 0:13:42.400 --> 0:13:43.120 who's talking to. 0:13:43.120 --> 0:13:45.720 Them, so it's like fun for them. 0:13:45.840 --> 0:13:48.280 And I was very unfiltered when I talked to my 0:13:48.440 --> 0:13:54.280 professors in school. Sometimes I corrected them stuff like this. Yeah, 0:13:54.280 --> 0:13:56.560 I don't know, Honestly, I don't know. 0:13:56.720 --> 0:13:59.840 When you talk to like fundamental equity portfolio managers, like 0:14:01.440 --> 0:14:05.720 how much like matrix algebras they're in your conversations like 0:14:05.760 --> 0:14:09.280 how quantity are the fundamental pms or whatever. 0:14:09.800 --> 0:14:11.600 I don't think they're quantity, but I think that they're 0:14:11.679 --> 0:14:15.400 very analytical. So I don't think that they would make 0:14:16.040 --> 0:14:20.240 great mathematicians, but I think they would make very very 0:14:20.280 --> 0:14:24.040 decent applied mathematicians. Actually, they tend to be very analytical. 0:14:24.320 --> 0:14:27.240 They tend to be very process oriented. And they have 0:14:27.280 --> 0:14:31.240 also additional qualities that actually mentioned in that essay, like 0:14:31.480 --> 0:14:35.880 they have very little disposition effect, so that's part of 0:14:35.960 --> 0:14:39.920 being analytical. They have no sound cost fallacy in them. 0:14:40.280 --> 0:14:42.200 So even though they don't do a lot of math, 0:14:42.360 --> 0:14:44.240 but they do some math. Okay, So first of all, 0:14:44.240 --> 0:14:47.840 they're fluent in a sense in basic literacy, but I 0:14:47.840 --> 0:14:51.200 think it's more their process that is closer to if 0:14:51.240 --> 0:14:55.000 not a mathematical one, but more of a scientific one. 0:14:55.240 --> 0:14:58.520 And when it comes to being a quant does it 0:14:58.560 --> 0:15:01.040 basically boil down to being good at math and being 0:15:01.080 --> 0:15:04.480 interested in math? Are things such as statistics and physics? 0:15:04.800 --> 0:15:08.720 I mean, do you need to have any finance or 0:15:08.800 --> 0:15:10.440 economics background at all? 0:15:11.600 --> 0:15:16.160 So I think that having an economics background is not 0:15:16.600 --> 0:15:20.920 necessarily a benefit, might even be a disadvantage actually, But 0:15:21.400 --> 0:15:23.840 just based on very few samples that I have a 0:15:23.880 --> 0:15:28.000 lot of very good, outstanding quantitative researchers actually come from 0:15:28.000 --> 0:15:32.360 physics and specifically from astrophysics. That's the experience that I've 0:15:32.360 --> 0:15:34.240 had in a couple of places. 0:15:34.000 --> 0:15:38.320 In broad brushstrokes, could you talk about why economics in 0:15:38.360 --> 0:15:41.640 the small sample size you have, how could that possibly 0:15:41.760 --> 0:15:44.000 be a detriment good? 0:15:45.200 --> 0:15:47.680 So I can answer the second question more easily. I 0:15:47.760 --> 0:15:52.920 think that astrophysicists deal with large amounts of data, and 0:15:53.400 --> 0:15:56.640 they deal with observational data, so they don't get to 0:15:56.760 --> 0:16:00.640 do a lot of experiments, and that's good for finance. Right, 0:16:00.720 --> 0:16:02.520 you deal with a lot of data, you need to 0:16:02.560 --> 0:16:05.880 know how to have good agen for observational data, and 0:16:05.880 --> 0:16:07.880 you need to have very good theory, like you need 0:16:07.920 --> 0:16:11.360 to have very good instruments without being falling in love 0:16:11.480 --> 0:16:17.000 with those instruments. Whereas I think economists, Okay, first of all, 0:16:17.160 --> 0:16:21.400 my statement is purely empirical. Okay, so I'm just really 0:16:21.440 --> 0:16:24.600 guessing on economists, and I'm going to be hated by 0:16:24.680 --> 0:16:30.040 all economists or economists in finance, but I do have 0:16:30.120 --> 0:16:32.560 my issues with their methods. 0:16:32.680 --> 0:16:32.840 Right. 0:16:32.880 --> 0:16:34.800 So, first of all, I think that there is an 0:16:34.840 --> 0:16:38.520 original scene in economics, which is I think a lot 0:16:38.520 --> 0:16:43.520 of economics is informed by a desire to be as 0:16:43.600 --> 0:16:48.120 rigorous as mathematics, right, and so a lot of theoreticians 0:16:48.120 --> 0:16:51.520 in economics are very deductive in their approach. If you 0:16:51.600 --> 0:16:55.360 think of you know, the unrealistic assumptions behind the welfare 0:16:55.400 --> 0:17:00.760 theorems or Rows impossibility theorem or whatnot, or just pick 0:17:00.880 --> 0:17:04.720 up you know Samuelson textbooks, and I think this is 0:17:05.000 --> 0:17:07.719 just rather very acxiomatic. 0:17:07.240 --> 0:17:07.960 Very deductive. 0:17:08.359 --> 0:17:13.720 Whereas physicists are very happy to think in terms of small, 0:17:14.280 --> 0:17:18.520 idealized models that apply to a specific domain, and if 0:17:18.520 --> 0:17:20.880 the model doesn't work out, they will discard and make 0:17:20.920 --> 0:17:25.960 another one. The grand theory behind physical theories exists, like, 0:17:26.080 --> 0:17:28.680 there are people who do this for a living, but many, 0:17:28.760 --> 0:17:33.440 many good theoretical economists physicists starting the small and then 0:17:33.480 --> 0:17:37.960 they expand the domain of their models. So economists tend 0:17:38.000 --> 0:17:40.800 to maybe in a sense, fall in love with methods 0:17:40.840 --> 0:17:42.399 too much, with techniques too much. 0:17:55.119 --> 0:17:57.480 We had clip Asness on the podcast a little while ago, 0:17:58.080 --> 0:18:01.240 and my father, not a finance listened to the episode 0:18:01.240 --> 0:18:03.679 and said, I still don't know what a quant is. 0:18:04.240 --> 0:18:08.920 I just read skimmed your new book which is called 0:18:08.920 --> 0:18:13.080 The Elements of Quantitative Investing, and as lays out the elements, 0:18:13.480 --> 0:18:15.159 what is a quant like? What are the elements? Like? 0:18:15.200 --> 0:18:17.600 What's the thing that makes someone a quant investor that, 0:18:17.680 --> 0:18:20.960 like someone reading a slim book about the Elements of 0:18:21.040 --> 0:18:22.359 quant investing needs to learn? 0:18:23.359 --> 0:18:26.800 Well, if I am being consistent with my book, investing 0:18:26.880 --> 0:18:30.439 is really about problems and not about specific techniques or 0:18:30.440 --> 0:18:33.240 anything like this. Right, So it's basically a way to 0:18:33.560 --> 0:18:36.960 go through the whole investment process from let's say preparing 0:18:37.000 --> 0:18:43.000 the ingredients to cooking to eating that is very processed driven. Ultimately, 0:18:43.680 --> 0:18:47.119 you would imagine that one thing that you know quantu 0:18:47.160 --> 0:18:50.800 investing has in common across multiple domains you know, if 0:18:50.800 --> 0:18:56.040 you do futures, stocks, event based and whatnot. Is I 0:18:56.080 --> 0:18:58.800 think the number of bets tends to be high in 0:18:58.880 --> 0:19:04.600 systematic right, so you can be a very successful microeconomic 0:19:04.760 --> 0:19:08.440 investor portfolio manager. And you you know, according to even 0:19:08.640 --> 0:19:12.440 several statements by Buffett, you know, he made like ten 0:19:12.560 --> 0:19:16.720 twelve very good bets. Okay, so that's great, and that's 0:19:16.760 --> 0:19:20.080 not quantu investing. You know, you could put enough pms 0:19:20.240 --> 0:19:22.399 making you know, twenty bets in their lives and you 0:19:22.680 --> 0:19:26.040 will get a few that have let's say twelve thirteen right, 0:19:26.160 --> 0:19:29.800 and they will be rich. We do not have that luxury, right. 0:19:29.840 --> 0:19:31.960 We have to make millions of bets. You know, we 0:19:32.040 --> 0:19:35.560 trade a portfolio with three thousand stocks sometimes in waves 0:19:35.640 --> 0:19:39.959 of half an hour. You can't make a judgment on 0:19:40.000 --> 0:19:42.440 all of these bets. So you need a method that 0:19:42.520 --> 0:19:46.240 reduces the dimension of your problem to something that can 0:19:46.280 --> 0:19:50.600 be treated in a systematic manner. I don't know if 0:19:50.640 --> 0:19:53.600 that answers for you. You know that, but you know, basically, 0:19:53.600 --> 0:19:55.879 basically the idea is, think about if you make a 0:19:55.880 --> 0:19:58.919 lot of bets, you cannot bet individually. You have to 0:19:58.960 --> 0:20:00.680 have some kind of view res take or some kind 0:20:00.680 --> 0:20:01.800 of method around that. 0:20:01.960 --> 0:20:03.800 Right, and like to me, like the book sort of 0:20:03.920 --> 0:20:06.680 you know the standard method I guess and quant investing 0:20:06.760 --> 0:20:10.480 is you built a factor model of what drives your 0:20:10.560 --> 0:20:13.280 universal investments. You're shaking your head. 0:20:13.400 --> 0:20:16.640 Yeah, I yes, and no. I think yes because the book, 0:20:16.760 --> 0:20:18.679 you know, has maybe one hundred and fifty pages on 0:20:18.720 --> 0:20:19.480 factor models. 0:20:19.840 --> 0:20:23.000 But also no, because maybe. 0:20:22.840 --> 0:20:25.360 In one hundred years from now, I suspect there will 0:20:25.359 --> 0:20:28.320 be still something left. But you know, we might have 0:20:28.560 --> 0:20:32.000 better techniques and not necessary factor models any longer. I 0:20:32.000 --> 0:20:32.880 don't know, we. 0:20:32.840 --> 0:20:34.879 Don't want to go. Two attractions of that one is like, 0:20:35.000 --> 0:20:39.800 are the better techniques something more neural netty unstructured? 0:20:40.040 --> 0:20:42.639 Who knows? Yeah, something like that. I mean there is, 0:20:42.880 --> 0:20:44.480 there is a revolution every five years. 0:20:44.600 --> 0:20:52.080 So my other question is like I've never fully understood 0:20:52.920 --> 0:20:56.160 like a factor model is like, here are some factors 0:20:56.200 --> 0:20:59.919 that drive the returns of stocks, and then there's like 0:21:00.080 --> 0:21:04.320 some residual idios and credit return There are clearly people 0:21:04.720 --> 0:21:09.320 whose business is to identify factors and then invest in factors. 0:21:10.160 --> 0:21:13.200 My impression is that at like the places that you work, 0:21:13.560 --> 0:21:16.680 the business is the opposite of that is to pedge 0:21:16.680 --> 0:21:19.280 out your factory risk as much as possible and to 0:21:19.320 --> 0:21:22.800 get as much idiotsyncratic risk as possible. Is that right? 0:21:22.920 --> 0:21:26.080 And like, like, how do you discriminate between like a 0:21:26.119 --> 0:21:28.679 factory return and idiosyncratic return, Like what makes the thing 0:21:28.720 --> 0:21:30.720 a factor as opposed to another thing. 0:21:30.880 --> 0:21:32.159 So that's a good question. 0:21:32.240 --> 0:21:36.320 So first, a lot of systematic investing is still about factors, 0:21:36.400 --> 0:21:39.000 just not the factors that get published in the literature, 0:21:39.080 --> 0:21:42.760 you know, not the factors that Cliff maybe was talking about. 0:21:43.280 --> 0:21:46.480 And yet a lot of successful systematic investing is really 0:21:46.520 --> 0:21:48.800 factor driven, see in. 0:21:48.720 --> 0:21:50.399 The sense that you have a model that has like 0:21:50.560 --> 0:21:54.520 twenty factors and like ten are like value, and you 0:21:54.680 --> 0:21:56.560 neutralize those and you try the other time kind. 0:21:56.440 --> 0:21:58.159 Of you do, and you do the rest. You have 0:21:58.240 --> 0:22:02.080 other terms that matter. So that's one thing, but there 0:22:02.080 --> 0:22:07.080 are two other things. There are sometimes sources of returns 0:22:07.080 --> 0:22:11.320 that are factor like but not quite like factors. So 0:22:12.440 --> 0:22:14.879 you may have a theme. For example, you may identify 0:22:14.920 --> 0:22:19.280 a theme in the market that is not pervasive enough 0:22:19.600 --> 0:22:22.240 or is alive only for a few months, but it 0:22:22.320 --> 0:22:25.920 is there and it's not only affecting let's say two stocks, right, 0:22:26.000 --> 0:22:29.960 So these brought themes can be invested on, but cannot 0:22:30.119 --> 0:22:34.320 really model in the traditional way as a traditional factor model. Also, 0:22:34.359 --> 0:22:37.840 there is a lot of good modeling in factors as 0:22:37.880 --> 0:22:40.680 opposed to bad modeling. So it seems easy, but it's 0:22:40.680 --> 0:22:42.560 not that easy. So there is a little bit of 0:22:42.560 --> 0:22:46.680 craftsmanship in making these models. Okay, And then the third 0:22:46.720 --> 0:22:49.720 thing is that there are also returns that have nothing 0:22:49.760 --> 0:22:52.600