WEBVTT - Harin de Silva on Portfolio Management (Podcast) 0:00:00.080 --> 0:00:06.080 M This is Masters in Business with Very Renaults on 0:00:06.240 --> 0:00:10.880 Bluebird Radio. My special guest this week is Hornda Silva. 0:00:11.080 --> 0:00:15.480 He is a fascinating quant a pioneer in low vall 0:00:15.760 --> 0:00:20.440 and factor based investing. He runs the Analytic Investors Group 0:00:20.520 --> 0:00:24.840 at Wells Fargo Asset Management. His team runs over twenty 0:00:24.880 --> 0:00:30.200 billion dollars in an assortment of quantitative strategies and really 0:00:30.480 --> 0:00:34.639 just a fascinating guy. UM who has spent a lot 0:00:34.680 --> 0:00:40.520 of time studying factors, studying quantitative investing, thinking about what 0:00:40.720 --> 0:00:45.640 does and doesn't work and when and why. I find 0:00:45.640 --> 0:00:49.840 a lot of quants tend to be UM a little 0:00:49.880 --> 0:00:54.800 more singularly focused, and he's a pretty broad based, holistic 0:00:54.880 --> 0:00:58.880 sort of guy. He He's quite a fascinating background and 0:00:59.160 --> 0:01:03.080 really interesting set of hobbies. UM. So, with no further 0:01:03.120 --> 0:01:10.440 ado my conversation with Wells Fargoes horind Da Silva. This 0:01:10.880 --> 0:01:15.319 is Mesters in Business with Very Reholts on Bloomberg Radio. 0:01:17.560 --> 0:01:21.000 My special guest this week is Horirenda Silva. He is 0:01:21.160 --> 0:01:25.720 a leader and portfolio manager at the Analytic Investors Group 0:01:25.800 --> 0:01:30.039 of Wells Fargo Asset Management. His team runs a variety 0:01:30.080 --> 0:01:35.119 of quantitative strategies with assets of over twenty billion dollars. 0:01:35.120 --> 0:01:39.360 Harin is known as a pioneer in both low volatility 0:01:39.720 --> 0:01:44.400 and factor based investing. He has won numerous awards, including 0:01:45.040 --> 0:01:48.800 multiple CFA Institute, Graham and Dot Awards, as well as 0:01:49.560 --> 0:01:55.360 multiple Bernstein Fabosi Awards from institutional investor Harendra da Silva. 0:01:55.760 --> 0:02:00.080 Welcome to Bloomberg. Thanks to having me on, Barry. I 0:02:00.160 --> 0:02:02.400 had to chat with you. Yep. I've been looking forward 0:02:02.400 --> 0:02:05.280 to talking to you because you have such an interesting 0:02:05.400 --> 0:02:09.680 background and your career has taken so many interesting paths. 0:02:10.320 --> 0:02:13.760 Tell us about your life a bit. How did you 0:02:13.880 --> 0:02:16.960 get into the financial services business? How do you go 0:02:17.120 --> 0:02:24.400 from Sri Lanka to UC Irvine. Well, apart from watching 0:02:24.400 --> 0:02:26.400 that episode of The Graduate as a kid, we had 0:02:26.440 --> 0:02:28.519 the advice to the guy who was go West young 0:02:28.560 --> 0:02:33.000 man um that was kind of the original inspiration. But 0:02:33.400 --> 0:02:36.480 I really you know, growing up in Sri Lanka, it 0:02:36.560 --> 0:02:39.080 was traditional for people to go to school or the 0:02:39.160 --> 0:02:43.680 university in the UK. And so I studied as an 0:02:43.760 --> 0:02:51.400 engineer undergrad and had the misfortune to graduate which was 0:02:51.440 --> 0:02:55.800 the height of a recession. And uh, you know, at 0:02:55.840 --> 0:02:58.200 the time, I had two choices. I could go onto 0:02:58.200 --> 0:03:01.680 graduate school. Why could go back to Sri Lanka, and 0:03:02.360 --> 0:03:03.880 you know, Sri Lanka was in the middle of a 0:03:03.960 --> 0:03:07.240 civil war at the time, so the choice was not difficult, 0:03:09.080 --> 0:03:13.000 and I made the decision to go to graduate school 0:03:13.000 --> 0:03:16.600 at the University of Rochester to study finance. And I 0:03:16.680 --> 0:03:19.120 was interested in finance because I saw a lot of 0:03:19.520 --> 0:03:24.800 similarities between finance and engineering, which was, you know, the 0:03:24.840 --> 0:03:30.160 ability to kind of design products, design strategies, and the 0:03:30.200 --> 0:03:33.320 idea that you could build something and actually put it 0:03:33.360 --> 0:03:36.680 to the test really appealed to me. So that's why 0:03:36.760 --> 0:03:39.000 I initially went to the University of Rochester to study 0:03:39.040 --> 0:03:44.840 finance and study finance for several years and then started 0:03:44.840 --> 0:03:50.119 working for a consulting firm called Analysis Group, and I 0:03:50.160 --> 0:03:53.920 was had by another stroke of good fortune and got 0:03:54.680 --> 0:03:58.839 assigned to a project for Merrill Lynch in the mid 0:03:58.880 --> 0:04:01.720 eighties where we were taking managers to go into the 0:04:01.800 --> 0:04:05.840 Marylands Consults program and if you remember remember that program, 0:04:05.920 --> 0:04:09.080 but it was one of the first rap programs. And 0:04:09.120 --> 0:04:11.160 so I was twenty five years old and I got 0:04:11.200 --> 0:04:15.840 to visit something like money managers in person. So you 0:04:15.920 --> 0:04:18.599 go to the money manager, you'd listen to their story 0:04:18.920 --> 0:04:22.320 and you try to capture in a quantitative way what 0:04:22.360 --> 0:04:26.320 they were doing. And that's when I first got really 0:04:26.400 --> 0:04:30.000 kind of interested in factor investing because I realized that, 0:04:30.160 --> 0:04:32.000 you know, you go and talk to, for example, a 0:04:32.000 --> 0:04:36.120 bunch of growth managers, and talking to them, you realized 0:04:36.120 --> 0:04:39.440 that all the ones that were doing well at that 0:04:39.480 --> 0:04:44.080 particular time well focused on a particular factors, and not 0:04:44.200 --> 0:04:47.320 only were the growth focused then maybe for example, focused 0:04:47.360 --> 0:04:50.520 on earning the acceleration, and those were the guys who 0:04:50.560 --> 0:04:52.680 are doing well at that time. And then you'd go 0:04:52.800 --> 0:04:56.520 talk to the value managers, for example, and you realize, well, 0:04:56.680 --> 0:04:59.040 the only ones that are doing really well are the 0:04:59.080 --> 0:05:02.440 ones who are f for example, divident deals. And that's 0:05:02.440 --> 0:05:05.279 when I realized, wow, you know, the factors actually explained 0:05:05.360 --> 0:05:08.200 a lot, and I kind of asked myself the question, 0:05:09.080 --> 0:05:12.360 which obviously wasn't related to the project I was working on. 0:05:12.560 --> 0:05:15.080 Is it the manager or is it the factor. I'm 0:05:15.120 --> 0:05:19.920 hearing a parallel between what you described in your background 0:05:20.000 --> 0:05:24.080 with mechanical engineering and the ability to test that in 0:05:24.120 --> 0:05:28.320 the real world with factor investing and being able to 0:05:28.440 --> 0:05:33.040 quantify what's driving returns. Am I reading too much into that? 0:05:33.279 --> 0:05:36.720 Or is there some parallel there? No? I think there 0:05:36.760 --> 0:05:38.760 is a parallel. I think it's the same idea of 0:05:38.839 --> 0:05:41.279 kind of what makes this work. And you know it 0:05:41.400 --> 0:05:43.919 maybe even a biased view because in an engineer, you 0:05:44.000 --> 0:05:47.520 think there's always there's a way to there's a formula, 0:05:47.680 --> 0:05:51.080 or there's a way to quantify something. So obviously if 0:05:51.080 --> 0:05:53.200 I had a history background, that would not think are 0:05:53.240 --> 0:05:57.400 you thinking was a manager or the process as opposed 0:05:57.440 --> 0:06:00.480 to something they were doing that was focusing on the factor. 0:06:00.760 --> 0:06:04.360 So I think the engineering aspect really kind of affected 0:06:04.440 --> 0:06:07.839 the way I looked at the problem. Very very interesting. 0:06:07.880 --> 0:06:12.920 And some of the factors that you cover include not 0:06:13.080 --> 0:06:16.520 just the traditional factors um, but you spend a lot 0:06:16.560 --> 0:06:19.760 of time focusing on low volatility. Tell us a little 0:06:19.760 --> 0:06:23.560 bit why that factor is significant, what what are the 0:06:23.600 --> 0:06:27.320 common elements in the factors that that you find intriguing. Well, 0:06:27.360 --> 0:06:30.719 that factor, to me was probably the one that was 0:06:30.800 --> 0:06:34.520 I call it the most neglected factor because I was 0:06:34.600 --> 0:06:40.640 working on my PhD thesis in the early nineties when 0:06:41.160 --> 0:06:46.000 Farmer and French came out with this paper that basically said, 0:06:46.839 --> 0:06:50.240 if you want to describe what they what academics kind 0:06:50.240 --> 0:06:54.120 of called the cross section of returns, In other words, 0:06:54.160 --> 0:06:57.080 which stocks go up and which stocks to go. That 0:06:57.839 --> 0:07:01.680 value book to market and far Camp were very good 0:07:01.680 --> 0:07:05.960 at explaining it, and that data did a really poor job, 0:07:06.200 --> 0:07:10.880 and that high data stocks had the same return as 0:07:10.920 --> 0:07:14.760 low beata stocks. To me, everybody when they read the 0:07:14.800 --> 0:07:17.920 paper in nine two focused on, oh yeah, the value 0:07:17.960 --> 0:07:21.080 premium and a small cap premium. And what I found 0:07:21.160 --> 0:07:24.640 really curious was, Wow, you can build a portfolio of 0:07:24.720 --> 0:07:28.160 Lottle better stocks that's going to have a way better 0:07:28.280 --> 0:07:32.800 returned risk profile than a portfolio of high data stocks 0:07:32.880 --> 0:07:36.360 or beta one portfolio. And I was really fascinated by 0:07:36.480 --> 0:07:38.960 why a no one focused on it, and most people 0:07:39.000 --> 0:07:43.040 didn't think it was really that interesting. So what I call, 0:07:43.400 --> 0:07:46.040 you know, what's now referred to in our team as 0:07:46.080 --> 0:07:49.040 a low all anomaly is this idea that if you 0:07:49.120 --> 0:07:51.720 build a portfolio a little beata stocks, you get a 0:07:51.800 --> 0:07:55.240 much better shop ratio, a much better return risk ratio 0:07:55.360 --> 0:07:59.760 than the market portfolio. Translate that for the lady listener, 0:08:00.640 --> 0:08:04.120 what are loval what are low beta stocks? And how 0:08:04.160 --> 0:08:08.200 do what is the significance of the sharp ratio? Typically 0:08:08.480 --> 0:08:11.520 a little bit of stock is what we mean by 0:08:11.520 --> 0:08:14.000 a little bit of stock is a stock that doesn't 0:08:14.080 --> 0:08:18.640 move a lot with the market moves in the mark, 0:08:18.680 --> 0:08:20.200 it will go up less in the market. It will 0:08:20.240 --> 0:08:22.040 go down less in the morning, go down less in 0:08:22.080 --> 0:08:26.240 the market exactly. And what if you put them in 0:08:26.280 --> 0:08:29.440 a portfolio. The portfolio obviously, if you buy a portfolio 0:08:29.560 --> 0:08:31.080 of a little bit of stocks and be it as 0:08:31.120 --> 0:08:35.840 a point eight, they'll actually move less than the market. 0:08:36.120 --> 0:08:38.959 So portfolio will go up less in the market and 0:08:39.000 --> 0:08:42.160 go down lest in the market. But what it also 0:08:42.240 --> 0:08:49.560 means is that the because you're invested in equities, you 0:08:49.679 --> 0:08:52.600 get the equity of risk premium. So the long run 0:08:52.640 --> 0:08:55.880 return of equities with a lot less volatility so on 0:08:55.920 --> 0:09:01.400 a risk of the dropacious, it's better than traditional portfolios, 0:09:02.360 --> 0:09:05.120 right right. And what the Farmer, all the work the 0:09:05.200 --> 0:09:09.480 Farmer and French did showed was that low beta stocks 0:09:09.520 --> 0:09:12.760 have actually the same return over the very long run 0:09:13.000 --> 0:09:16.920 as HIGHBERDA stocks or better one stocks. And what's really 0:09:16.920 --> 0:09:19.160 fascinating is if you look at a little bit of stocks. 0:09:19.160 --> 0:09:22.360 You know, when you first tell people, they tell you, oh, yeah, 0:09:22.400 --> 0:09:26.840 a little bit of stock. Oh yeah, that's just that's Amazon. Sorry, 0:09:26.840 --> 0:09:30.199 that's that's electric utility, And you go no, no, no, no, 0:09:30.280 --> 0:09:33.120 that's not electric utilities. A little bit of stock is 0:09:33.120 --> 0:09:35.960 the stock that doesn't move with the market. So early 0:09:36.080 --> 0:09:40.520 on in its cycle, Amazon was indeed a little bit 0:09:40.559 --> 0:09:44.040 of stock because what was driving it was this idiot 0:09:44.040 --> 0:09:47.640 think credit returned related to doing business in a very 0:09:47.720 --> 0:09:53.080 unusual way. As the company evolved, it became increasingly a 0:09:53.120 --> 0:09:55.800 Beta one stock, and now it's a bet at one 0:09:55.840 --> 0:09:58.320 point to one point three stock because it's a very, 0:09:58.480 --> 0:10:01.240 very large cap company. It's the very large component of 0:10:01.280 --> 0:10:06.240 the economy, and it's no longer very geosyncratic Richard. So 0:10:06.280 --> 0:10:08.920 if you look at our portfolios very you find that 0:10:09.000 --> 0:10:12.520 companies like that are now very high data. For example, 0:10:12.720 --> 0:10:16.040 even Tesler was actually in a little bit of portfolio 0:10:16.559 --> 0:10:19.600 four years ago. It's no longer in a little bit 0:10:19.600 --> 0:10:23.160 of portfolio because it's megacap and it moves so much 0:10:23.200 --> 0:10:25.640 with the market. But when people think of a little 0:10:25.640 --> 0:10:27.680 bit of portfolios, you know, the other thing you see 0:10:27.679 --> 0:10:29.480 often in a little bit of portfolios that you've got 0:10:29.480 --> 0:10:33.600 to be very careful with is biotech companies, right, because 0:10:33.600 --> 0:10:37.720 the biotech company will often have two or three patterns, 0:10:38.800 --> 0:10:44.240 and it's going through a process for regulatory approval after 0:10:44.280 --> 0:10:47.120 the drug, so it's not really moving. The moving in 0:10:47.160 --> 0:10:50.960 the market at all, So stuff like that very often 0:10:51.000 --> 0:10:53.440 you see those in a little bit of portfolios. So 0:10:53.559 --> 0:10:56.120 it really is kind of it's kind of fascinating to 0:10:56.440 --> 0:10:59.880 to watch this and if you look at sectors, for example, 0:11:00.400 --> 0:11:03.520 spent more of my life studying this anomaly and anything else. 0:11:03.559 --> 0:11:07.640 But if you look in the sixties, energy was low BEATA. 0:11:08.080 --> 0:11:11.560 Nobody really cared about it. It was almost utility. Went 0:11:11.600 --> 0:11:16.000 through the oil crisis in the seventies, it became very 0:11:16.080 --> 0:11:19.959 high data because it was the fact it sort of 0:11:20.280 --> 0:11:23.600 started moving the market. Through the seventies and eighties, oil 0:11:23.640 --> 0:11:26.680 companies were very HIGHBATA, you know, when the market was 0:11:26.720 --> 0:11:30.760 dominated by the Seven Sisters. Then it became LOWBATA, and 0:11:30.800 --> 0:11:34.720 as we went through this last crisis with energy consumption falling, 0:11:34.800 --> 0:11:38.560 they became high BEATA once again. So it really is 0:11:39.040 --> 0:11:42.960 sounding a little bit geek like, but it's fascinating to 0:11:43.080 --> 0:11:46.719 watch the evolution of companies and industries because it's not 0:11:46.800 --> 0:11:48.760 as simple as oh yeah, a little bit of stocks 0:11:48.800 --> 0:11:51.600 are different paying utilities. So let's talk a little bit 0:11:51.720 --> 0:11:57.600 about factor investing, and in general, we've seen many factors 0:11:58.200 --> 0:12:03.480 significantly underperformed over the past decade. Why is that? What 0:12:03.520 --> 0:12:08.000 are your thoughts here, Well, when you say factors under perform, 0:12:08.040 --> 0:12:10.720 you know you're saying the return to the factor was 0:12:10.760 --> 0:12:16.840 not the expected. Sign is that the well, you know, 0:12:16.960 --> 0:12:21.360 the granddaddy of underperformance. The past decade has been value 0:12:21.520 --> 0:12:27.319 versus growth, but there has been some other factor surprises 0:12:27.360 --> 0:12:30.920 to the downside. I guess um when when we had 0:12:30.960 --> 0:12:34.080 the big blow up in in volatility a couple of 0:12:34.120 --> 0:12:39.080 years ago, that seemed to affect some factor performance and 0:12:40.160 --> 0:12:44.040 small cap has dramatically lagged for for quite a while. 0:12:44.080 --> 0:12:46.720 It's starting to catch up over the past year, but 0:12:46.920 --> 0:12:50.360 the past decade was not kind two small caps. When 0:12:50.400 --> 0:12:52.720 you look at the world of factors, and I know 0:12:53.400 --> 0:12:56.840 there are many, many more factors than just you know, 0:12:57.000 --> 0:13:00.600 the three or six that most people are familiar with, 0:13:01.040 --> 0:13:04.679 how do you look at what's doing well, what's doing poorly? 0:13:04.760 --> 0:13:08.960 And how do you contextualize that? Yes, so I really 0:13:09.000 --> 0:13:12.400 look at it from two dimensions. One is the does 0:13:12.440 --> 0:13:17.959 the factor matter? Right? So does the factor describe what's 0:13:17.960 --> 0:13:20.120 going on in the market? And when I mean by describe, 0:13:20.160 --> 0:13:22.880 if you look at the factor, can I tell you 0:13:22.960 --> 0:13:26.800 whether a group of stocks either out performing on the performing? 0:13:26.880 --> 0:13:29.800 So that to me the sign doesn't really matter when 0:13:30.040 --> 0:13:33.160 in the first dimension is is this factor meaningful? So 0:13:33.360 --> 0:13:36.720 just to pick up, you know, a random factor. You 0:13:36.720 --> 0:13:41.240 could pick a factor as where the name of the 0:13:41.360 --> 0:13:46.840 company is in the alphabet, right, that's a factor. You'll 0:13:46.880 --> 0:13:50.079 find that that study is actually completely useless in explaining 0:13:50.080 --> 0:13:52.800 whether a group of stocks went up or down, right, 0:13:52.920 --> 0:13:56.679 because it's just random. On the other hand, small camp 0:13:56.720 --> 0:13:59.800 as you mentioned, is actually really useful in terms of 0:14:00.280 --> 0:14:04.600 people are running away from risk. Usually small cap companies 0:14:04.640 --> 0:14:07.960 do really poorly if they're running towards risk, as they've 0:14:07.960 --> 0:14:10.040 done a little bit in the last three to six months. 0:14:10.480 --> 0:14:14.720 Small cap companies really generally do well. The correlation isn't one, 0:14:15.559 --> 0:14:20.360 but generally, regardless of the environment, there is a difference 0:14:20.360 --> 0:14:23.800 in performance in large cap companies with the small cap companies, 0:14:24.160 --> 0:14:27.840 and the same versus value the same in sort of 0:14:27.920 --> 0:14:32.400 quality related factors. Now, the expectation that people form on 0:14:32.480 --> 0:14:35.160 these factors is they look at the long run return, 0:14:35.480 --> 0:14:38.160 you know, whether it's from a Farmer French study or elsewhere, 0:14:38.440 --> 0:14:40.880 and then they say, wow, you know, this factor on 0:14:41.000 --> 0:14:44.120 average has been positive, so I expected to be positive 0:14:44.360 --> 0:14:48.040 going forward, And that I think is one of the 0:14:48.080 --> 0:14:52.400 misunderstandings with factor investing because you know when you when 0:14:52.400 --> 0:14:55.480 you pace the quantitative back, the first thing that goes 0:14:55.520 --> 0:15:00.200 through my head is what's the hit rate? Right? Because 0:15:00.200 --> 0:15:02.120 when I when I tell you something is going to outperform, 0:15:02.200 --> 0:15:04.480 the first thing you need to be doing, is an investor, 0:15:04.720 --> 0:15:07.160 is to say, Okay, how often is that going to happen. 0:15:07.560 --> 0:15:12.080 My conjecture is that even the best factors will outperform 0:15:12.320 --> 0:15:16.040 six or seven out of out of ten times. So 0:15:16.080 --> 0:15:17.800 you can think of that in meaning it's going to 0:15:17.880 --> 0:15:21.560 miss three or four out of ten times. Yeah, so 0:15:21.600 --> 0:15:25.360 the underperformed three or four at ten times. So you 0:15:25.400 --> 0:15:27.240 think of a coin, if you have a sixty percent 0:15:27.320 --> 0:15:30.720 chance of winning, you can get a bunch of classes 0:15:30.760 --> 0:15:33.240 in a row even with a sixty percent chance of winning. 0:15:34.600 --> 0:15:37.080 So so the degree under performance and the length of 0:15:37.160 --> 0:15:40.560 periods and the performance can be really, really long. And 0:15:40.720 --> 0:15:44.560 that I think has not been adequately communicated to people 0:15:44.560 --> 0:15:47.160 who are investing in these strategies because the other things 0:15:47.280 --> 0:15:51.120 is factors of momentum, and this is only recently coming 0:15:51.120 --> 0:15:53.520 to the four where people are talking about it, and 0:15:53.720 --> 0:15:55.920 this is something so you're not let me interrupt you 0:15:55.960 --> 0:15:58.640 a second or and you're you're not talking about momentum 0:15:58.680 --> 0:16:03.160 itself as a factor. You're talking about the momentum of 0:16:03.280 --> 0:16:08.920 other factors impacting that factor exactly. And I think that 0:16:09.120 --> 0:16:12.160 is probably probably one of the most least appreciated things 0:16:12.160 --> 0:16:15.160 in investing, and it's something to be really really aware of. 0:16:15.640 --> 0:16:18.520 And I noticed this when I first got into investing, 0:16:18.640 --> 0:16:22.000 because I look at these investment firms and you know, 0:16:22.080 --> 0:16:25.640 they'd look growing like gangbasters because their performance was great. 0:16:25.880 --> 0:16:27.880 You know, the head of the firm was viewed as 0:16:27.880 --> 0:16:31.320 a genius. And I look at it really closely as 0:16:31.360 --> 0:16:35.480 a you know, ex engineer, and go, it's not what's 0:16:35.520 --> 0:16:39.760 blading up on this one and this factor with its 0:16:39.800 --> 0:16:44.800 earnings acceleration or undeliveraged companies, whatever. The fact is that's 0:16:44.840 --> 0:16:48.240 been in favor for the last five years, and as 0:16:48.240 --> 0:16:50.560 long as it's in favor, they're going to do really, 0:16:50.640 --> 0:16:53.800 really well. And then suddenly the factor starts under performing 0:16:54.200 --> 0:16:56.720 and the managers say, as well, you know, my style 0:16:56.840 --> 0:16:58.520 is out of favor, but it's going to come back. 0:16:59.720 --> 0:17:01.920 So cynically, you know, if you're an investor, you know 0:17:02.040 --> 0:17:05.560 this right, because if you're doing well, you're a genius. 0:17:05.640 --> 0:17:08.399 But if you're doing coolly your styles out of favor. Um, 0:17:09.960 --> 0:17:15.359 it's an asymmetrical bet. Yeah, it's an asymmetrical bet. So 0:17:15.480 --> 0:17:22.640 beyond momentum, factors have persistence that tends to continue to exist. 0:17:23.160 --> 0:17:25.800 Are some factors more persistent than others that we can 0:17:25.800 --> 0:17:30.240 to really get into wonky geek territory here, But how 0:17:30.320 --> 0:17:37.080 consistent does persistence apply to different factors? Is it similar 0:17:37.240 --> 0:17:41.359 or or some factors do they tend to enjoy that 0:17:41.480 --> 0:17:47.280 momentum for longer periods than other factors. It's remarkably consistent. 0:17:47.800 --> 0:17:51.200 I mean I in all the work I've done, the work, 0:17:51.320 --> 0:17:53.840 the time and effort I put into modeling each factor 0:17:53.840 --> 0:17:59.520 individually has not been fruitful. What I see very consistently 0:18:00.080 --> 0:18:03.840 is that factors tend to the factors that I worked 0:18:03.880 --> 0:18:06.960 in the last year tend to continue to work. The 0:18:07.000 --> 0:18:11.280 ones that have worked in the last two to three years, 0:18:11.480 --> 0:18:14.160 they tend to work well, but a little less. So. 0:18:14.200 --> 0:18:17.399 The persistence is very strong over one year, less strong 0:18:17.440 --> 0:18:20.879 over two to three years. And then after three years 0:18:20.920 --> 0:18:23.480 you actually start to see some mini version. When you 0:18:23.480 --> 0:18:26.639 look at manager cycles, you will really really stop saying that, 0:18:26.840 --> 0:18:29.000 but I mean they managed cycles. Is the tendency for 0:18:29.080 --> 0:18:32.560 certain types of managers to perform. And so I think 0:18:32.600 --> 0:18:36.080 when you're when you're thinking about factor investing, it's really 0:18:36.240 --> 0:18:40.520 important to actually weigh the factors that have been working well, 0:18:42.000 --> 0:18:45.800 not only recently, but also think about the mean reversion factor. Right, 0:18:46.000 --> 0:18:49.760 So if you think about, you know, value factors right now, 0:18:50.080 --> 0:18:52.160 right now, it's kind of a nice time for value 0:18:52.320 --> 0:18:54.879 right because the last six months have been very strong. 0:18:55.640 --> 0:18:59.240 So the fact that has momentum not great momentum because 0:18:59.280 --> 0:19:01.560 it's only been strong for three to four months, maybe 0:19:01.600 --> 0:19:04.480 six months, but the mean reversion aspect of it is 0:19:04.480 --> 0:19:09.000 actually quite strong. So what's really fascinating about this? When 0:19:09.000 --> 0:19:12.840 I first started running money using this tract of momentum approach, 0:19:13.920 --> 0:19:17.520 I was doing it for a uh the US client 0:19:17.720 --> 0:19:22.880 using US stocks, and it was a client was based 0:19:22.880 --> 0:19:24.680 out of Japan, and they came to me and said, hey, 0:19:24.720 --> 0:19:27.600 what this work in Japan? And you know, being the 0:19:27.640 --> 0:19:30.240 typical quant, I said, yeah, well, let me check, right, 0:19:30.240 --> 0:19:33.480 So I collected all this data in Japan and I 0:19:33.560 --> 0:19:39.320 found that the same fact exists for Japanese stocks that 0:19:39.440 --> 0:19:42.280 you see this same factor momentum and then you know, 0:19:42.320 --> 0:19:46.800 subsequently repested it in in emerging markets and in Europe 0:19:46.960 --> 0:19:50.480 and you see the same. So I think what you're 0:19:50.520 --> 0:19:54.200 seeing is really and you can depending on which camp 0:19:54.240 --> 0:19:57.280 you fall into. I dated the economic cycle. Oh, it's 0:19:57.320 --> 0:20:00.000 just human behavior, right. If you think about the way 0:20:00.080 --> 0:20:02.680 our decision making process sense to work, is we tend 0:20:02.720 --> 0:20:04.840 to like things, so we tend to focus on things 0:20:04.840 --> 0:20:08.040 that are work recently. So that recentcly bias, I think, 0:20:08.160 --> 0:20:10.760 is there in the way we buy stocks and the 0:20:10.800 --> 0:20:14.200 way we think of fads coming in and out of favor, 0:20:15.040 --> 0:20:18.119 and that's what's driving That's what something you need to 0:20:18.119 --> 0:20:21.359 take into account when you're tractor investing, because I think 0:20:21.880 --> 0:20:25.879 the idea that yeah, value work, small cap works, quality works. 0:20:25.920 --> 0:20:28.560 So you take these you know, five words, six factor tilts, 0:20:28.560 --> 0:20:31.240 and you're going to beat the market regardless of what happens. Well, 0:20:31.280 --> 0:20:33.080 that's going to work if you have a very long 0:20:33.200 --> 0:20:36.000 or a reason. But if those factors out of favor 0:20:36.080 --> 0:20:39.320 for the last three years, you're in for a little 0:20:39.320 --> 0:20:41.600 bit of pain for the next two or three years. 0:20:41.640 --> 0:20:44.840 So Horne, let's talk a little bit about the idea 0:20:45.040 --> 0:20:51.159 of managers expressing their philosophy in their portfolio. I I 0:20:51.240 --> 0:20:55.680 can't help but think that you're a part lo val, 0:20:56.080 --> 0:21:02.879 part value sort of quant. Is that a fair just ryption? Yeah, 0:21:02.920 --> 0:21:07.360 I would say it's it's part global active quant active 0:21:07.440 --> 0:21:10.600 quant because I really think, I mean, love all is 0:21:10.640 --> 0:21:14.760 an anomaly. But as a manager, you can express a 0:21:14.800 --> 0:21:17.520 lot more views than just having a low Boll view 0:21:17.560 --> 0:21:20.280 in the portfolio. I want to talk to you about 0:21:20.320 --> 0:21:23.600 some of the funds you guys specifically manage, but before 0:21:24.359 --> 0:21:27.320 I do, I have to ask you a question. What 0:21:27.520 --> 0:21:32.840 is the fundamental law of active management? Well, that is 0:21:32.880 --> 0:21:38.960 actually a formula, and the idea behind the formula is 0:21:39.000 --> 0:21:44.760 that you can relate your investing success to really three things. 0:21:46.400 --> 0:21:49.880 So if you think about investing in US lodge cap stocks, 0:21:49.960 --> 0:21:52.119 the first thing that's going to matter for you in 0:21:52.240 --> 0:21:55.840 terms of your relative success of investing is how big 0:21:55.880 --> 0:21:59.320 your universe is, so what we call brand. The second 0:21:59.480 --> 0:22:02.600 is your bill lead forecast, which is as a quant, 0:22:02.680 --> 0:22:07.360 measured by the correlation between your predictions and what actually happens. 0:22:07.400 --> 0:22:10.800 The quants called that your information coefficient, how much information 0:22:10.880 --> 0:22:14.000 you have. And then the third thing is how effectively 0:22:14.119 --> 0:22:19.240 you transfer your information into your portfolio, So you overweight 0:22:19.320 --> 0:22:21.800 the stocks you like, and are you underweight the stocks 0:22:21.920 --> 0:22:24.760 don't like. And that's what quants referred to as the 0:22:24.800 --> 0:22:29.920 transfer coefficient. So the three decisions that are the three 0:22:30.000 --> 0:22:33.080 inputs to determining your success is one is how big 0:22:33.119 --> 0:22:36.159 the universe? You know, what the breadth of your investment decisions. 0:22:36.640 --> 0:22:39.560 The second is how well are you forecasting? And the 0:22:39.640 --> 0:22:43.399 third is how effectively are you transferring all your information 0:22:43.720 --> 0:22:47.200 into the portfolio? The transfer coefficient, and that's a formula 0:22:47.320 --> 0:22:50.359 that was very useful when you think about how much 0:22:51.280 --> 0:22:55.040 our performance you can get from a portfolio. And it's 0:22:55.080 --> 0:22:58.720 a formula that my colleagues Steve Sali and Roger Clark 0:22:58.760 --> 0:23:03.760 and I developed um in the nineties and then published 0:23:03.760 --> 0:23:08.359 a paper in the two thousand timeframe. That's where that 0:23:08.440 --> 0:23:11.919 question came from. So now let's talk about some of 0:23:11.920 --> 0:23:16.840 the specific funds that that you manage over at Wells Fargo, 0:23:17.440 --> 0:23:22.240 starting with the Global Dividends Opportunity Funds. From the name, 0:23:23.040 --> 0:23:26.840 I'm going to guess that it is both global and 0:23:26.960 --> 0:23:30.879 dividend focused. Um, what do we make of the trend 0:23:31.040 --> 0:23:35.639 of falling dividends at least here in the US over 0:23:35.680 --> 0:23:40.600 the past call it a few decades, Yeah, I mean 0:23:40.600 --> 0:23:43.520 that's been kind of a corporate trend right because of 0:23:43.560 --> 0:23:49.480 the tendency to have buy back as a methodology forgive 0:23:49.880 --> 0:23:53.399 beturning money to to shareholders. So I mean it's a 0:23:53.520 --> 0:23:57.199 challenge from a form divid and focused strategy in that 0:23:57.320 --> 0:24:01.639 particular portfolio. The other thing we do is use covered calls. 0:24:02.119 --> 0:24:07.520 So Analytic got it start as a firm in doing 0:24:07.600 --> 0:24:11.760 covered call strategies. So we actually use a vault of 0:24:11.800 --> 0:24:16.360 the forecasting model to identify overvalue call options and then 0:24:16.520 --> 0:24:21.480 use that to generate additional income for the portfolio. Interesting, 0:24:21.560 --> 0:24:24.320 it's a little bit unusual, but this is typical quant 0:24:24.960 --> 0:24:28.919 approach in that you're not just using one way to 0:24:29.040 --> 0:24:32.680 generate income. You're using dividends as well as covered calls 0:24:32.720 --> 0:24:36.760 as a way to generate income for the portfolio. So historically, 0:24:36.960 --> 0:24:43.480 covered call writing was always a challenge because you're balancing, um, 0:24:43.560 --> 0:24:46.879 the risk of a stock that's working out getting cold 0:24:46.920 --> 0:24:54.080 away versus the versus the income you get from selling 0:24:54.119 --> 0:24:57.119 the calls. I'm going to assume giving your background and 0:24:57.280 --> 0:25:03.280 low vall that um you managed to offset that because 0:25:03.840 --> 0:25:07.520 you're going to have a lower beta group of names. 0:25:07.560 --> 0:25:10.000 They're they're less likely to get called away when the 0:25:10.000 --> 0:25:12.920 stock starts to run up or I should say less 0:25:12.960 --> 0:25:18.480 likely to run up and therefore have the stock called away. Yeah, 0:25:18.600 --> 0:25:21.680 so that I mean that portfolio is team managed, so 0:25:21.720 --> 0:25:25.119 it's actually uses some of the other skills within Wells 0:25:25.119 --> 0:25:27.679 frougu as well, So we're not the only manager. So 0:25:27.720 --> 0:25:31.919 we just manage the option portflio. And the reason the 0:25:31.960 --> 0:25:36.720 way we avoid the stop getting called away is by 0:25:36.840 --> 0:25:41.040 using index calls. Because if you use the index calls, 0:25:41.160 --> 0:25:44.119 all you're susceptible to the market run up, not the 0:25:44.160 --> 0:25:47.880 individual stocks themselves going up, right, right, you still run 0:25:47.920 --> 0:25:52.080 the risk of having to buy in to replace the 0:25:52.080 --> 0:25:55.880 the the underlying right well, the underlying wouldn't get called 0:25:55.920 --> 0:25:59.719 away because you're selling the calls on the SMPI index 0:25:59.800 --> 0:26:03.040 very example, so you would have to be you'd be 0:26:03.119 --> 0:26:05.199 on the hook for the payment. But the key with 0:26:05.359 --> 0:26:09.399 call writing that most people don't think about is you 0:26:09.480 --> 0:26:12.280 have to have a way to value the call. Right, 0:26:12.920 --> 0:26:16.360 So if volatility is over priced, you know, as it 0:26:16.440 --> 0:26:19.320 was at the start of this year, for example, that's 0:26:19.320 --> 0:26:22.600 a great time to be selling calls. Then you're getting 0:26:22.600 --> 0:26:27.920 paid for exactly getting paid for the risk. But having 0:26:27.920 --> 0:26:30.760 a call writing strategy where you're always selling the same 0:26:30.800 --> 0:26:34.879 call that is usually not going to be as successful 0:26:34.920 --> 0:26:39.040 as something that is actually constantly looking at you know, 0:26:39.160 --> 0:26:42.280 one month, two month, three month horizon and different strikes 0:26:42.359 --> 0:26:45.119 and trying to figure out where's the most amount of 0:26:45.160 --> 0:26:50.360 miss pricing coming in the marketplace. Now, for example, as 0:26:50.400 --> 0:26:53.200 we are in sitting here in you know, in the 0:26:53.760 --> 0:26:57.280 and the may longer dated calls actually more miss priced 0:26:57.280 --> 0:26:59.679 than shot it calls. So you really need to be 0:26:59.680 --> 0:27:02.760 thinking about increasing the tenor of your call if you're 0:27:02.760 --> 0:27:07.280 in a call writing strategy. Very very interesting. What about 0:27:07.280 --> 0:27:11.119 the Low Volatility US Equity Fund? What what's the philosophy 0:27:11.160 --> 0:27:17.040 behind that? So that's a fairly vanilla fund um from 0:27:17.119 --> 0:27:19.400 if you think about everything that we do, because it's 0:27:19.600 --> 0:27:24.119 long US stock. The idea is to have a bottlatility 0:27:24.240 --> 0:27:27.480 of about seventy percent of the equity market and and 0:27:27.560 --> 0:27:32.120 a similar return. The fund itself is new, but we've 0:27:32.200 --> 0:27:35.520 run that strategy now since the early two thousands. So 0:27:35.600 --> 0:27:38.359 it's you know, I'm going to show my age because 0:27:38.359 --> 0:27:41.200 it's I've been involved with that type of for sixteen 0:27:41.240 --> 0:27:46.360 years and we're building a portfolio that has that has 0:27:46.400 --> 0:27:50.080 a low beta, so the average beata for all the 0:27:50.119 --> 0:27:53.240 stocks in the portfolio is around point six point seven. 0:27:53.760 --> 0:27:57.000 But at the same time, we're tilting towards the characteristics 0:27:57.080 --> 0:27:59.359 that are in favor. So if you look at the 0:27:59.400 --> 0:28:03.440 portfolio right now, you'll see that it has a very 0:28:03.520 --> 0:28:07.720 big loading on price to sales as a characteristic. That's 0:28:07.720 --> 0:28:11.159 a factor that has really really been rewarded in the marketplace. 0:28:11.720 --> 0:28:15.360 Investors are really focusing on that right now. Trading earnings 0:28:15.480 --> 0:28:21.040 is not useful as because any trailings earnings number contains 0:28:21.080 --> 0:28:25.399 the pandemic. So using forward looking numbers like forward pe 0:28:25.720 --> 0:28:29.960 price to sales are really really important. Asset turnover is 0:28:30.000 --> 0:28:32.959 a factor that is really important right now as well, 0:28:33.119 --> 0:28:36.320 so you'll see a lot of stocks with high asset 0:28:36.359 --> 0:28:40.560 turnover um in that portfolio. So we tend to look 0:28:40.560 --> 0:28:43.400 at a very broad range of factors, not just sort 0:28:43.400 --> 0:28:47.760 of you know, value, growth, quality, small cap, but really 0:28:47.800 --> 0:28:51.040 kind of try to capture the pross section of factors 0:28:51.120 --> 0:28:54.760 that fundamental investors look at. Let's talk a little bit 0:28:54.840 --> 0:28:58.800 about where we are in this market cycle today. Do 0:28:58.920 --> 0:29:02.760 you look at us as sort of late cycle or 0:29:03.000 --> 0:29:06.720 was last year a reset and this is a relatively 0:29:06.800 --> 0:29:10.400 young market, or do you not care about any of 0:29:10.440 --> 0:29:19.040 those things I do care um from the perspective of 0:29:19.160 --> 0:29:23.360 looking at things in a historical context, because that's often 0:29:23.440 --> 0:29:25.360 a kind of a useful guide as you're trying to 0:29:25.360 --> 0:29:28.960 figure out which factors too blobal weight and underweight, and 0:29:29.080 --> 0:29:31.680 you know, does it make sense? And I would say, 0:29:31.840 --> 0:29:36.680 given the way factors are behaving right now, it's much 0:29:36.800 --> 0:29:41.800 more of a really early cycle. There's a huge focus 0:29:41.960 --> 0:29:46.440 on in the US and globally on estimate revisions. So 0:29:46.600 --> 0:29:50.920 stocks with high being revised upwards are doing incredibly well, 0:29:51.000 --> 0:29:53.560 so people are really focused on that as a factor. 0:29:54.640 --> 0:29:58.080 Small cap is doing well, Low price to sales stocks 0:29:58.080 --> 0:30:01.640 are doing well. Those are all that associated early in 0:30:01.680 --> 0:30:05.600 the fact in the cycle. If you look at interest 0:30:05.680 --> 0:30:09.160 rate sensitivity as a factor, you know that is something 0:30:09.240 --> 0:30:12.440 really people are really focused on because there's concerned that 0:30:12.760 --> 0:30:15.480 there's going to be a rise in rates. And you 0:30:15.520 --> 0:30:19.240 should think about equities having duration. Most people don't, but 0:30:19.360 --> 0:30:22.760 equities do have duration, and different equities have different types 0:30:22.800 --> 0:30:26.640 of different levels of duration. So that's a measure managing 0:30:26.680 --> 0:30:30.680 newport fill. So when you say duration, harand let me 0:30:30.720 --> 0:30:34.080 interrupt yourself. When you say duration, most people think in 0:30:34.240 --> 0:30:38.760 terms of fixed income and bonds is having a duration. Hey, 0:30:38.760 --> 0:30:40.760 this is a ten year bond, of twenty year bond 0:30:40.800 --> 0:30:44.000 and nine bond, what have you. What does duration mean 0:30:44.080 --> 0:30:48.480 when it comes to equity. I'm assuming there's some sensitivity 0:30:48.560 --> 0:30:52.160 to changes in interest rate policy. What do you mean 0:30:52.160 --> 0:30:55.240 by duration, he said to me. The duration of a 0:30:55.280 --> 0:31:00.360 stock is how sensitive a stock is in the tenure yield. 0:31:00.720 --> 0:31:06.800 So if it's insitive, then you'll see that it's it's insensitive. 0:31:07.080 --> 0:31:09.880 You'll see that it's not affected by changes in rates. 0:31:11.520 --> 0:31:16.240 And you know, when you look at individual companies, it's 0:31:16.280 --> 0:31:18.840 really fascinating. You stop. When you look at them carefully 0:31:18.840 --> 0:31:21.800 from that perspective, you'll see that some companies, for example, 0:31:22.520 --> 0:31:27.400 have a lot of floating rate debt, so as rates 0:31:27.560 --> 0:31:31.720 rise there interest payments are going to rise. So those 0:31:31.720 --> 0:31:35.520 companies tend to be more interest rate sensitive than others. Huh, 0:31:35.800 --> 0:31:39.960 that's really that's really interesting. So much has happened since 0:31:40.000 --> 0:31:44.360 you started in the industry today. What do you think 0:31:44.400 --> 0:31:51.280 are the biggest differences in asset management relative to years 0:31:51.280 --> 0:31:53.600 ago or so? Well, there's a lot been a lot 0:31:53.680 --> 0:31:57.240 of good developments, I think, you know, on the positive side, 0:31:57.800 --> 0:32:03.040 um fees have come down, the trading costs have come down, 0:32:03.640 --> 0:32:09.160 so your ability to trade a portfolio mo uh, you know, 0:32:09.240 --> 0:32:13.200 to have higher turnover to capture factor rotation. That's become 0:32:13.240 --> 0:32:19.920 a lot easier. The costs of data um have come down, 0:32:20.000 --> 0:32:24.600 but at the same time, the amount of data available 0:32:24.640 --> 0:32:28.239 for purchase has gone up. So if you look at 0:32:28.320 --> 0:32:31.320 us as a group as a team, you know our 0:32:31.440 --> 0:32:36.320 data costs is millions, but it seems to always go up, 0:32:36.400 --> 0:32:38.840 not come down. What are your thoughts on some of 0:32:38.880 --> 0:32:43.959 these alternative data sources. I know people are buying satellite 0:32:44.040 --> 0:32:49.840 data where you can see movement of tankers and ships 0:32:49.880 --> 0:32:52.840 that are I've even seen some people say we could 0:32:52.880 --> 0:32:56.520 tell how loaded the ship is by how low it 0:32:56.560 --> 0:32:59.320 sits in the water relative to its waterline. Do you 0:32:59.400 --> 0:33:04.680 do you have anything it's on these alternative data sources? Yeah, 0:33:05.280 --> 0:33:08.120 I think those that type of data is really useful 0:33:08.760 --> 0:33:13.040 in terms of updating your earnings estimate forecasts, because that's 0:33:13.120 --> 0:33:16.600 ultimately what it comes down to. The challenge with that 0:33:16.720 --> 0:33:21.080 data is that it's really really time sensitive. So when 0:33:21.120 --> 0:33:23.880 I think of data quality, I'm always trying to think 0:33:23.920 --> 0:33:28.600 about what horizon do I need to invest with to 0:33:28.680 --> 0:33:31.800 actually use that. Now that's really useful for me in 0:33:31.800 --> 0:33:34.520 a short run trading model. But that's not the sweet 0:33:34.560 --> 0:33:37.240 spot for from our size because we can't turn those 0:33:37.240 --> 0:33:42.600 portfolios over enough to capture that. So I I prefer data, 0:33:42.680 --> 0:33:46.400 for example that looks at you know, um. Just to 0:33:46.520 --> 0:33:49.200 pick up example of something I'm working on now, is 0:33:50.040 --> 0:33:53.000 what's the carbon footprint of a company and how can 0:33:53.040 --> 0:33:57.000 it be measured? Right? Because we know the cost of 0:33:57.000 --> 0:33:59.240 emitting carbon is going to go up in the future. 0:34:00.280 --> 0:34:02.800 That's going to be a big factor in the profitability 0:34:02.800 --> 0:34:06.160 of companies and their behavior, and they need to invest 0:34:07.160 --> 0:34:10.520 in terms of new plants, encuipment. So what data can 0:34:10.600 --> 0:34:13.560 be used to capture that. That's kind of a moment intermediate, 0:34:13.600 --> 0:34:17.120 long horizon factor. And the more data I can collect 0:34:17.120 --> 0:34:19.319 on that dimension, the better if I am. But it 0:34:19.360 --> 0:34:22.600 doesn't rely on me getting to some information quicker than 0:34:23.440 --> 0:34:26.960 somebody else and the information kind of dying at the 0:34:26.960 --> 0:34:31.040 next learnings announcement that you know that makes a lot 0:34:31.080 --> 0:34:33.960 of sense. In fact, since you mentioned low carbon I'm 0:34:33.960 --> 0:34:36.600 going to jump ahead to another question. What are your 0:34:36.600 --> 0:34:40.920 thoughts on E s G. On environmental, social and corporate 0:34:40.960 --> 0:34:45.640 governance as potential factors. I've I've heard people describe them 0:34:45.680 --> 0:34:48.600 as risk screens. What do you think of E s G. 0:34:50.400 --> 0:34:53.640 I think they're really important as risk screens. I think 0:34:53.680 --> 0:34:56.799 if you what we've found is that if you use 0:34:57.280 --> 0:35:03.080 E s G related factors actually incredibly important in describing 0:35:03.160 --> 0:35:05.640 the future return volatil the of a start. The thing 0:35:05.719 --> 0:35:11.000 that's most important is governance, and you'll find that companies 0:35:11.040 --> 0:35:14.880 with poor governance the returns are very very fat tailed 0:35:15.880 --> 0:35:18.279 and as a portfolio manager, you need to account for 0:35:18.320 --> 0:35:23.000 that because most risk models missed that. Right, a poorly 0:35:23.040 --> 0:35:28.400 government company has a significant chance of a really negative return, 0:35:29.600 --> 0:35:32.320 but it doesn't happen very often. It will happen once 0:35:32.360 --> 0:35:36.799 every fifteen years, once every thirty years. So in a 0:35:36.840 --> 0:35:40.359 typical risk model it actually doesn't show up, but it 0:35:40.400 --> 0:35:43.280 does show up if you look at you know, long 0:35:45.080 --> 0:35:48.600 time series of data and beef. I find these E 0:35:48.760 --> 0:35:53.920 s G factors are really really important in risk forecasting. 0:35:54.080 --> 0:35:58.880 They're not useful in return forecasting because I think you 0:35:58.920 --> 0:36:03.520 can make the case that people like these stocks or 0:36:03.640 --> 0:36:05.799 the like these stocks for other reasons, you know, just 0:36:05.880 --> 0:36:08.960 like you have people like since some people like sin stocks, right, 0:36:09.000 --> 0:36:12.920 that's where there's a sin stock etf um So I 0:36:12.920 --> 0:36:16.359 think the return aspect for me, is less important than 0:36:16.400 --> 0:36:21.040 the volatility aspect. Huh. That's really interesting. It's it's sort 0:36:21.080 --> 0:36:26.560 of the Charlie Manger approach, which is, don't be more smart, 0:36:26.760 --> 0:36:31.000 be less stupid. In other words, and I love phrases it, 0:36:31.040 --> 0:36:35.560 but you're you're looking to screen out potential disasters with 0:36:35.640 --> 0:36:41.319 E s G rather than screen in additional alpha. Right. 0:36:41.400 --> 0:36:43.600 That's to me, that's exactly the way to think about 0:36:43.640 --> 0:36:47.760 because these companies have something in their behavior where there's 0:36:47.800 --> 0:36:51.920 going to be a chance that they have a bad 0:36:51.960 --> 0:36:56.279 outcome in the next twenty years. Right. But if you 0:36:56.320 --> 0:36:59.160 have a portfolio of poorly government companies and suppose you 0:36:59.200 --> 0:37:03.000 have a hundred stocks in them, there's a significant chance 0:37:03.080 --> 0:37:04.879 that one of them is going to have a bad 0:37:04.920 --> 0:37:08.520 outcome next year. So that they is a really key 0:37:08.560 --> 0:37:14.560 dimension in using E s G in a portfolio because 0:37:15.040 --> 0:37:17.520 most people think don't think about it that way. But 0:37:17.920 --> 0:37:21.440 I found that with D s G factors, and increasingly 0:37:21.440 --> 0:37:25.680 with environmental factors like carbon or water pollution, or you know, 0:37:26.040 --> 0:37:30.360 even something is like plastics, the company's plastic emissions, is 0:37:30.360 --> 0:37:33.279 there a way to measure that and quantify and incorporate 0:37:33.280 --> 0:37:36.200 in the portfolio Because that's increasingly going to be something 0:37:36.239 --> 0:37:40.080 that investors care about and something that the company will 0:37:40.120 --> 0:37:43.239 have to care about in the way people assess their 0:37:43.239 --> 0:37:50.080 future profitability. That's really that's really kind of kind of intriguing. 0:37:50.239 --> 0:37:54.480 So so here we are, the economy is just starting 0:37:54.520 --> 0:37:58.719 to reopen. People are more concerned with inflation than they 0:37:58.719 --> 0:38:03.200 are with unemployment. It's means, what factors do you see 0:38:03.760 --> 0:38:09.040 really taking advantage of the post COVID reopening, anything stand 0:38:09.080 --> 0:38:13.280 out in particular, and what do you think is um 0:38:13.360 --> 0:38:18.239 the wrong factor for this phase of the recovery. Well, 0:38:18.360 --> 0:38:24.360 I would stay away from anything that uses recent accounting data. 0:38:24.600 --> 0:38:27.319 So just to just to give you something tangible, you know, 0:38:28.000 --> 0:38:30.400 people focus on things like r o E and r 0:38:30.440 --> 0:38:33.560 o A right return on equity return and affect those 0:38:33.640 --> 0:38:38.840 numbers are really have been affected by the company's performance 0:38:38.880 --> 0:38:42.839 in COVID. So that's those are factors I would focus on. 0:38:43.600 --> 0:38:46.560 I mentioned trailing learning zeal as a fact that you 0:38:46.600 --> 0:38:50.200 should not look at, so that anything that uses trailing 0:38:50.200 --> 0:38:53.160 accounting data you've got to stay away from. But if 0:38:53.160 --> 0:38:55.359 you want to look at the valuation, which I think 0:38:55.600 --> 0:38:59.680 there's a lot of evaluation factors that are you should 0:38:59.680 --> 0:39:02.680 be looking at looking at the ratio of price to 0:39:02.800 --> 0:39:06.520 sales is a really excellent factor right now given where 0:39:06.520 --> 0:39:10.839 we are in the cycle. Staying away from companies with 0:39:10.960 --> 0:39:15.359 a lot of debt, especially debt that is floating rate 0:39:15.400 --> 0:39:19.000 as opposed to fix rate, is something that's that you 0:39:19.080 --> 0:39:23.480 should be looking at doing. Going towards companies that have 0:39:23.719 --> 0:39:27.399 high operating margins in terms of their business model. That's 0:39:27.440 --> 0:39:29.719 a little bit difficult to do because of the accounting 0:39:29.760 --> 0:39:33.680 data problem for the last year. Uh, that's something that 0:39:33.760 --> 0:39:37.839 you should be incorporating into your portfolio. And the other 0:39:37.920 --> 0:39:40.600 thing that I would really emphasize in the current cycle 0:39:41.440 --> 0:39:45.280 because of the change we're seeing in the way companies 0:39:45.320 --> 0:39:49.680 do business, is staying away from companies where there's a 0:39:49.680 --> 0:39:54.440 lot of disagreements about their future earnings. So one thing 0:39:54.480 --> 0:39:59.640 people don't have attention to is looking at analyst dispersion. 0:40:00.320 --> 0:40:03.200 So if you look at an earnings forecast, everybody looks 0:40:03.239 --> 0:40:05.759 at the mean, but you should also look at is 0:40:05.840 --> 0:40:08.000 look at the difference between the high and the lower 0:40:08.080 --> 0:40:11.680 or the spread between analysts, because whenever they has a 0:40:11.719 --> 0:40:15.919 big spread, that means there's a lot of disagreement as 0:40:15.920 --> 0:40:18.760 to the future profitability of the company, and that factor 0:40:18.960 --> 0:40:21.839 is something that's going to be really important in this 0:40:21.960 --> 0:40:25.800 stage of the cycle. Really interesting. I have one curveball 0:40:26.400 --> 0:40:31.120 question to h to throw at you. Um, what sort 0:40:31.120 --> 0:40:35.080 of motorcycle do you like to ride? Oh? My goodness, 0:40:35.080 --> 0:40:38.759 how much time do you have? Well I did read 0:40:38.840 --> 0:40:42.920 that you have bite pretty much all over the world. 0:40:43.360 --> 0:40:47.239 How much of an exaggeration is that? Uh? No, that 0:40:47.360 --> 0:40:51.120 that that is true. I mean motorcycle is reatively speaking, 0:40:51.120 --> 0:40:55.200 are cheap. Um. And one of my hobbies is exploring 0:40:55.239 --> 0:40:57.879 the world on a motorcycle. So I like to keep 0:40:57.920 --> 0:41:01.440 bikes at different out of the world. I can you know, 0:41:01.520 --> 0:41:03.640 I can show up, I leave my clothes on the 0:41:03.680 --> 0:41:06.759 bike and can hop on and ride. But my my 0:41:06.960 --> 0:41:12.520 daily rider, because I ride to work, is an electric 0:41:12.600 --> 0:41:15.600 Hollie Davidson, which is actually a wonderful bike. It's a 0:41:16.719 --> 0:41:24.160 called Hallie Davidson Live Wire. Um. It's quiet, it's fast, um. 0:41:24.200 --> 0:41:26.200 And when I leave early morning for work, I don't 0:41:26.239 --> 0:41:31.240 disturb my neighbors. Um. And we have so solar panels 0:41:31.280 --> 0:41:36.480 at home so it doesn't cost me anything to run. Um. 0:41:36.520 --> 0:41:40.920 My favorite bike to ride on the weekends is to 0:41:40.960 --> 0:41:44.560 have an obscure Italian bike called the bi motor, the Due, 0:41:45.600 --> 0:41:50.279 which is a two stroke, very light sport bike. And 0:41:50.320 --> 0:41:54.640 then my favorite bike for touring is you know BMWs 0:41:54.680 --> 0:41:57.200 because you can get them service anywhere in the world, 0:41:57.320 --> 0:42:01.000 and there it's almost like a train. They almost never takedown, right, 0:42:01.120 --> 0:42:03.759 They're big, they're solid, they're comfortable, and they could go 0:42:04.640 --> 0:42:07.800 on and on and on. Do you find I asked 0:42:07.800 --> 0:42:09.720 this question as a kid who used to write dirt 0:42:09.719 --> 0:42:14.560 bikes and and some of the smaller one fifties do 0:42:14.640 --> 0:42:18.520 you find like traffic is so heavy these days and 0:42:18.680 --> 0:42:22.280 people are just not paying attention. It's a little more 0:42:22.520 --> 0:42:29.600 challenging to to be on a motorcycle. There is considerably 0:42:29.640 --> 0:42:35.279 more distracted driving um in southern California. Actually, in California, 0:42:35.360 --> 0:42:39.080 it's legal to filter or split lanes, So when you're 0:42:39.160 --> 0:42:42.040 driving down the middle of lanes, what you'll often see 0:42:42.320 --> 0:42:44.480 is the you know, the person next to you and 0:42:44.560 --> 0:42:47.920 driving a car has their phone in their lap. And 0:42:47.960 --> 0:42:49.799 I don't know why, there's a tendency if you're look 0:42:49.840 --> 0:42:51.759 if you're texting, you always put the phone in your 0:42:51.840 --> 0:42:53.719 lap and then you look down away from where you're 0:42:53.800 --> 0:42:56.840 driving and you text, and I see that probably you 0:42:56.880 --> 0:42:59.520 know the time in the in the morning, so that 0:43:00.239 --> 0:43:02.440 it is a hazard that one has to deal with, 0:43:03.360 --> 0:43:07.640 and it does make it um so that usually when 0:43:07.680 --> 0:43:10.160 I get to work in the morning, I'm really awake 0:43:10.880 --> 0:43:14.960 because my adrenaline is flowing to see, to say the 0:43:15.040 --> 0:43:19.720 very least, And you have a trip planned later for 0:43:20.800 --> 0:43:25.480 parts of Asia. Where are you heading to this year? Well, 0:43:25.520 --> 0:43:28.480 this is actually a continuation of a trip that was 0:43:28.600 --> 0:43:33.399 got canceled last year because of COVID. So last year 0:43:33.640 --> 0:43:38.200 I left the motorcycle. I was writing in Riga in Latviere, 0:43:38.480 --> 0:43:41.120 and I'm writing this year. The plan is to write 0:43:41.160 --> 0:43:45.680 from Riga to Saint Petersburg to Moscow and then next 0:43:45.800 --> 0:43:49.960 year to ride from Moscow all the way to the 0:43:50.000 --> 0:43:53.399 east coast of Russia to Ladivostok, which is right next 0:43:53.440 --> 0:43:56.879 to Tokyo. Right, I've never been to Moscow, but St. 0:43:56.880 --> 0:44:01.440 Petersburg is an amazing city and you can spend weeks there. 0:44:01.680 --> 0:44:06.919 It's just an unbelievable amount of things to see and do. Yeah, 0:44:06.960 --> 0:44:09.480 I'm really looking forward to that. I've put lots of 0:44:09.560 --> 0:44:12.719 wonderful things about that city. All right, So I know 0:44:12.800 --> 0:44:15.160 I only have you for a couple more minutes. Let's 0:44:15.280 --> 0:44:18.680 jump to our favorite questions that we ask all of 0:44:18.719 --> 0:44:21.720 our guests, starting with what are you streaming these days? 0:44:21.800 --> 0:44:27.200 Give us some of your favorite Netflix, Amazon Prime podcast entertainment. 0:44:27.880 --> 0:44:30.319 So I'm I'm going to be a disappointment on that 0:44:30.440 --> 0:44:35.040 dimension because I don't think I watched Netflix in over 0:44:35.080 --> 0:44:38.120 a year, so I'm not. I didn't grow up with 0:44:38.160 --> 0:44:42.200 televisions in Sri Lanka or Scream, so I'm I'm almost 0:44:42.239 --> 0:44:45.920 never watched them. Well, all right, listen, I would be 0:44:45.960 --> 0:44:49.839 more productive if I wasn't if I wasn't watching. I'm 0:44:49.840 --> 0:44:52.640 a big reader. I mean I read more, I more 0:44:52.680 --> 0:44:54.960 than anybody else I know, so I'm probably got the 0:44:54.960 --> 0:44:59.520 world's biggest Amazon books built. So so let me let 0:44:59.520 --> 0:45:01.960 me jump to that question. Then tell us about some 0:45:02.040 --> 0:45:04.120 of your favorite books. What if some are your all 0:45:04.200 --> 0:45:08.920 time favorites, and what are you reading now? Well, what 0:45:09.040 --> 0:45:12.360 I'm reading now? There's two books that I'm really enjoying. 0:45:12.760 --> 0:45:18.960 One is called The Well Gardened Mind, m Um. It's 0:45:19.000 --> 0:45:22.960 a book on how gardening and nature affects the way 0:45:23.040 --> 0:45:26.520 we think. And this book, I think, to an investor 0:45:26.719 --> 0:45:30.799 is really fascinating because it talks about how you exposure 0:45:30.840 --> 0:45:35.120 to nature affects your decision making. So if we take 0:45:35.160 --> 0:45:38.840 two people, for example, or two groups of students and 0:45:38.880 --> 0:45:41.280 they're about to take the exam, one of them books 0:45:41.280 --> 0:45:45.319 through an urban environment, are the group box to an arboretum, 0:45:45.640 --> 0:45:48.319 so they exposed to nature. The one that boxer an 0:45:48.360 --> 0:45:52.440 arboretum will have higher test case. And that's because of 0:45:52.560 --> 0:45:57.480 something that's called attention restoration. Because we are also focused 0:45:57.640 --> 0:46:00.959 in such short time periods now that after a while 0:46:01.080 --> 0:46:03.319 we get attention fatigue, so you have to figure out 0:46:03.400 --> 0:46:05.840 where to restore that. And if you're involved in trading 0:46:05.960 --> 0:46:09.480 or building portfolios, this is something that that's really really critical. 0:46:09.600 --> 0:46:13.120 So this book is a really fascinating book from st 0:46:13.400 --> 0:46:16.920 from that standpoint, because I think, especially in the COVID environment, 0:46:16.960 --> 0:46:19.560 we're all working longer hours and you have to figure 0:46:19.600 --> 0:46:22.920 out a way to restore your attention during the day. 0:46:23.200 --> 0:46:25.239 And that's kind of one of the big things that 0:46:25.360 --> 0:46:28.439 got out of this book. Um. But the other book 0:46:28.440 --> 0:46:32.840 I'm reading is I'm a I'm a total Formula one fanatic. Um. 0:46:32.880 --> 0:46:35.320 I'm reading this book by one of my favorite designers, 0:46:35.400 --> 0:46:39.200 Adrian Newey, and he wrote a book last year called 0:46:39.239 --> 0:46:43.040 How How to Build a Car and Adrian Nui, I 0:46:43.120 --> 0:46:45.000 think is one of the b he's the design of 0:46:45.000 --> 0:46:47.120 a red bull. If we didn't know, but he's one 0:46:47.120 --> 0:46:50.719 of the best card designers ever to go through Formula one. 0:46:51.040 --> 0:46:57.600 And the book goes through his designed philosophy and how 0:46:58.560 --> 0:47:01.840 his philosophy evolved over time and all the different cars 0:47:01.840 --> 0:47:05.360 that he designed, but it also decided describes his career. 0:47:05.920 --> 0:47:10.200 And you know, if most people don't realize it, but 0:47:10.280 --> 0:47:13.640 Adrian was, you know, one of the key partners that Williams, 0:47:13.640 --> 0:47:15.760 which is now one of the worst Formula one teams, 0:47:16.200 --> 0:47:19.279 and it was a disagreement with the owners of the 0:47:19.320 --> 0:47:23.080 company that left him. They do him leaving, So if 0:47:23.080 --> 0:47:26.680 not for that disagreement, Williams would probably be continue to 0:47:26.680 --> 0:47:29.600 be the number one team in UH in Formula one. 0:47:29.680 --> 0:47:31.719 So it kind of highlights to me one of the 0:47:31.760 --> 0:47:35.800 importance of realizing that teams are really important to a 0:47:35.840 --> 0:47:40.719 business and if you let key team members go UH, 0:47:40.920 --> 0:47:43.280 that's going to have a big impact on your business. 0:47:43.320 --> 0:47:45.440 So there is a really strong tide of how to 0:47:45.520 --> 0:47:49.640 build an effective team in a very high performance environment 0:47:49.719 --> 0:47:53.480 in this book Give us Another the last one m 0:47:54.320 --> 0:47:57.000 The most other book I read more recently, which is 0:47:57.000 --> 0:48:03.000 a little more academic, is annoyed. Sure, yeah, and I 0:48:03.040 --> 0:48:05.080 think you've talked about that. I think I've seen that 0:48:05.120 --> 0:48:09.920 in your podcast. Um. The other one that I really 0:48:09.960 --> 0:48:12.799 liked that I read recently was actually by one of 0:48:12.800 --> 0:48:17.120 the people who was one of the founders of Analytic, 0:48:17.800 --> 0:48:21.080 were involved in its founding, which is a book called 0:48:21.120 --> 0:48:25.560 A Man for All Markets. Sure, and I think it's 0:48:25.560 --> 0:48:29.239 a book that anybody going into quantity financial really by 0:48:29.360 --> 0:48:32.080 at Top was definitely one of the smart st guys 0:48:32.160 --> 0:48:38.080 I've ever met, UM, and so that I really really 0:48:38.160 --> 0:48:44.640 enjoyed reading. UM. So, I you know, pretty pretty wide array, 0:48:44.719 --> 0:48:49.560 but I'm really fascinated by this interaction between the how, 0:48:51.000 --> 0:48:55.040 what what we have faced with effects our decision making. 0:48:55.440 --> 0:48:59.520 And another book I read recently that I really liked 0:49:00.120 --> 0:49:05.520 is called The Nature of Fear about Survival Lessons in 0:49:05.600 --> 0:49:09.120 the while that's how we what happens to us when 0:49:09.160 --> 0:49:13.359 we are fearful, because if we think about investors, you know, 0:49:14.480 --> 0:49:17.680 one of the issues that's happened is with for one case, 0:49:17.800 --> 0:49:21.200 and people having to manage their own portfolios. I don't 0:49:21.200 --> 0:49:27.760 think people realize how they're environment affects their decision making, 0:49:27.920 --> 0:49:30.279 and that's why it's really important to show kind of 0:49:30.280 --> 0:49:34.759 average investor investing, you know, having exposure in for one case, 0:49:35.200 --> 0:49:40.279 not to make decisions very often. You know, generally they 0:49:40.320 --> 0:49:43.239 say look at it once a year. But also realize 0:49:43.440 --> 0:49:46.919 what type of mood you're in when you're making that decisions. 0:49:46.960 --> 0:49:50.799 And I think that's really underappreciated. To make sure that 0:49:50.840 --> 0:49:54.320 you're not in a fearful state or what can cause 0:49:54.360 --> 0:49:56.759 you to be in a fearful state when you look 0:49:56.800 --> 0:50:00.680 at that. So you know, do some all things like 0:50:00.800 --> 0:50:04.000 download your statement, look at it, you know, wait a month, 0:50:04.080 --> 0:50:06.920 then make the decision, but don't be in a hurry 0:50:07.040 --> 0:50:10.319 and allow yourself time to think about the decision you're 0:50:10.320 --> 0:50:13.480 going to make getting put on the decision. But you know, 0:50:13.880 --> 0:50:16.120 if I can think about this team, it's this broader 0:50:16.200 --> 0:50:20.120 team of thinking about how your state of mind affects 0:50:20.120 --> 0:50:22.640 your decision and how can you manage your state of mind? 0:50:22.840 --> 0:50:26.319 Really interesting. Tell us about any mentors you might have had, 0:50:27.000 --> 0:50:32.680 who who helps guide your career. I was pretty lucky, 0:50:32.760 --> 0:50:35.120 I think when I went to the University of Rochester. 0:50:35.280 --> 0:50:38.680 So there was a gentleman by the name of Paul 0:50:38.800 --> 0:50:44.760 McAvoy who was the dean of the Business school, and 0:50:45.600 --> 0:50:48.200 I was making a living at the time, you know, 0:50:48.640 --> 0:50:51.000 in addition to going to school programming, and he hired 0:50:51.040 --> 0:50:54.320 me as a programmer for some research projects. And Paul 0:50:54.440 --> 0:50:57.440 was a very well known economist. He was on the 0:50:57.520 --> 0:51:01.040 President's Council of Economic Advisors. So working with them, I 0:51:01.160 --> 0:51:05.200 really learned that kind of think about how to sell problems, 0:51:05.239 --> 0:51:10.120 but also think about applying economics mhm, you know, much 0:51:10.160 --> 0:51:13.719 broader context than major policy or interest rate policy, and 0:51:13.760 --> 0:51:20.760 thinking about you know, the whole Kansian world of animal 0:51:20.840 --> 0:51:23.600 spirits and how they affect markets. So that was he 0:51:23.680 --> 0:51:26.760 was probably I think one of the most instrumental people 0:51:27.040 --> 0:51:32.640 to me. Uh. And then also Shin Kasu, who was 0:51:32.680 --> 0:51:35.080 the founder of Analytic. He was the head of the 0:51:35.200 --> 0:51:39.000 con department at the University of California at Irvine. It 0:51:39.120 --> 0:51:41.720 was very fortunate to work with him. And then also 0:51:43.080 --> 0:51:45.680 I would say the gentleman who was my PhD advisor 0:51:46.080 --> 0:51:50.120 and also kind of a well known figure in in finance, 0:51:50.360 --> 0:51:55.840 professor Robert Howgen, who wrote a book called The Inefficient 0:51:55.920 --> 0:51:59.680 Market Hypothesis and the Incredible January Effects. A very very 0:51:59.760 --> 0:52:03.520 color a full character, but somebody was always willing to 0:52:03.640 --> 0:52:10.080 question markets and do unusual things to build portfolios in 0:52:10.200 --> 0:52:14.279 terms of using at the time large scale optimizers and 0:52:14.520 --> 0:52:18.160 building large scale factor models in the world where everybody 0:52:18.239 --> 0:52:22.000 in the eighties we were convinced that markets were perfectly etician, 0:52:22.160 --> 0:52:24.919 and now we know that's not the case. To say 0:52:24.920 --> 0:52:27.919 the very least, what sort of advice would you give 0:52:27.960 --> 0:52:30.920 to a recent college grad who was interested in a 0:52:31.040 --> 0:52:37.839 career in either factor investing or quantitative finance. I think 0:52:37.880 --> 0:52:42.360 the hardest thing in starting in the business right now 0:52:43.000 --> 0:52:49.600 is figuring out whether you're invest actually invests interested in 0:52:49.680 --> 0:52:54.120 investing all your interested in what you think is investing, 0:52:54.400 --> 0:53:03.120 because investing is really about doing research to figure out 0:53:03.200 --> 0:53:06.439 what's going on in the market and then figuring out 0:53:06.480 --> 0:53:11.359 way to exploit that for the benefit of your clients. 0:53:11.480 --> 0:53:18.200 Right it's not about frequent trading or moving faster than 0:53:18.280 --> 0:53:21.640 somebody else. And what I find when I talk to 0:53:21.719 --> 0:53:25.399 younger people is they're really focused on trying to get 0:53:25.400 --> 0:53:32.719 an edge by getting this short run informational advantage, and 0:53:32.840 --> 0:53:36.439 that's not that's not sustainable. And you also can't use 0:53:36.560 --> 0:53:41.480 that to invest institutional money because people tend to have 0:53:41.719 --> 0:53:46.040 longer horizons. So my piece of advice to them is 0:53:46.239 --> 0:53:51.479 understand what type of investing you're interested in, and whether 0:53:51.560 --> 0:53:54.240 you like doing that type of research, because the hardest 0:53:54.239 --> 0:53:57.879 thing about doing research is eight percent at the time, 0:53:58.560 --> 0:54:03.120 it's a dead end. So if you don't enjoy the journey, 0:54:04.920 --> 0:54:07.400 it can be really frustrating, right, I mean, think about it. 0:54:07.440 --> 0:54:09.840 Think about it this way. You're souted like being a chef, 0:54:09.960 --> 0:54:14.560 but of the dishes you make taste absolutely horrible, for 0:54:14.840 --> 0:54:16.880 four out of five get sent back to the kitchen. 0:54:17.560 --> 0:54:22.360 Really really interesting, and in our final question, what do 0:54:22.400 --> 0:54:25.920 you know about the world of research and portfolio management 0:54:25.960 --> 0:54:30.760 today that you wish you knew back in the nineties 0:54:30.800 --> 0:54:36.440 when you were really first getting started. Without a doubt Bory. 0:54:36.640 --> 0:54:41.200 For me, it would be the impact of human eimations 0:54:41.280 --> 0:54:46.920 and sentiments on markets. I think by the time I 0:54:46.960 --> 0:54:52.200 did not appreciate how much that mattered, and now I 0:54:52.239 --> 0:54:56.759 see that it matters a great degree. And I think 0:54:57.480 --> 0:55:00.440 something I worked very hard at is trying away to 0:55:00.520 --> 0:55:05.160 build a way to quantify that. But I didn't have 0:55:05.200 --> 0:55:10.120 an appreciation for how much emotion and people's attitude and 0:55:10.160 --> 0:55:14.239 sentiment matters in the way assets are price and I 0:55:14.280 --> 0:55:21.440 think that is not taught enough in schools. Huh. Really 0:55:21.520 --> 0:55:25.000 quite quite interesting. Thank you her In for being so 0:55:25.080 --> 0:55:28.000 generous with your time. We have been speaking with horendraw 0:55:28.160 --> 0:55:32.480 to Silver. He is the leader of Wells Fargoes quantitative 0:55:32.480 --> 0:55:36.280 strategy group known as Analytic Investors. They manage over twenty 0:55:36.280 --> 0:55:41.040 billion dollars and assets. If you enjoy this conversation, well, 0:55:41.160 --> 0:55:44.640 be sure and check out all of our previous UH interviews. 0:55:44.719 --> 0:55:47.680 There are nearly four hundred of them, and you can 0:55:47.719 --> 0:55:51.279 find them at iTunes or Spotify or any of your 0:55:51.320 --> 0:55:56.400 favorite podcast sites. We love your comments, feedback and suggestions 0:55:56.960 --> 0:56:00.200 right to us at m IB podcast at bloom Berg 0:56:00.280 --> 0:56:03.320 dot net. You can sign up from my daily reads 0:56:03.440 --> 0:56:06.880 at Reholts dot com. Check out my weekly column on 0:56:07.040 --> 0:56:10.520 Bloomberg dot com slash Opinion. Follow me on Twitter at 0:56:10.600 --> 0:56:13.440 rit Holts. I would be remiss if I did not 0:56:13.560 --> 0:56:17.680 thank the crack staff that helps put these conversations together 0:56:17.800 --> 0:56:21.680 each week. UH Tico val Bron is our project manager. 0:56:22.040 --> 0:56:26.680 Tim Harrow is my audio engineer. Michael Boyle is my producer. 0:56:27.040 --> 0:56:31.120 Michael Batnick is my head of research. I'm Barry Ridholts. 0:56:31.120 --> 0:56:34.680 You're listening to Master's Business on Bloomberg Radio.