1 00:00:00,440 --> 00:00:04,440 Speaker 1: Look ahead, imagine more. Gain insight for your industry with 2 00:00:04,480 --> 00:00:08,480 Speaker 1: forward thinking advice from the professionals at Cone Resnick. Is 3 00:00:08,480 --> 00:00:11,559 Speaker 1: your business ready to break through? Find out more at 4 00:00:11,640 --> 00:00:19,319 Speaker 1: Cone Resnick dot com Slash Breakthrough. This is Master's in 5 00:00:19,400 --> 00:00:23,840 Speaker 1: Business with Barry Ridholts on Bloomberg Radio. This week on 6 00:00:24,040 --> 00:00:26,960 Speaker 1: Masters in Business, we have a very special guest. His 7 00:00:27,080 --> 00:00:30,480 Speaker 1: name is Jeff de Graff and he is known as 8 00:00:30,520 --> 00:00:37,360 Speaker 1: a technicians technician. He has a storied career, most notably 9 00:00:37,560 --> 00:00:42,680 Speaker 1: his time as the chief technician at Lehman Brothers, where 10 00:00:42,720 --> 00:00:46,840 Speaker 1: he famously resigned pretty much the day of Lehman's all 11 00:00:46,880 --> 00:00:50,800 Speaker 1: time high. Jeff is now the founder and presidents and 12 00:00:50,920 --> 00:00:56,200 Speaker 1: chief technical strategist of Renaissance Macro, better known as ren Mack, 13 00:00:57,280 --> 00:01:01,200 Speaker 1: which is really an interesting shop that come binds both 14 00:01:02,000 --> 00:01:06,399 Speaker 1: macro analysis and technical analysis. In fact, one of the 15 00:01:06,440 --> 00:01:09,880 Speaker 1: things that makes Jeff so unique is the fact that 16 00:01:09,920 --> 00:01:14,640 Speaker 1: he has both a c f A and a CMT, 17 00:01:15,520 --> 00:01:20,800 Speaker 1: which means that he is very schooled in both fundamental 18 00:01:21,080 --> 00:01:24,960 Speaker 1: and technical analysis of of equities, and I think you'll 19 00:01:25,000 --> 00:01:29,160 Speaker 1: find his approach to be somewhat unique. The way ren 20 00:01:29,280 --> 00:01:33,400 Speaker 1: Mack was built to create its own unique database is 21 00:01:33,480 --> 00:01:36,600 Speaker 1: something that not a lot of companies can can lay 22 00:01:36,640 --> 00:01:39,200 Speaker 1: claim to UH, and it's part of the reason that 23 00:01:39,319 --> 00:01:43,360 Speaker 1: for the past decade or so he's been named one 24 00:01:43,400 --> 00:01:45,319 Speaker 1: of the top and and in fact has been ranked 25 00:01:45,400 --> 00:01:49,600 Speaker 1: number one by Institutional Investor for the space he covers. So, 26 00:01:50,320 --> 00:01:55,520 Speaker 1: without any further ado, here is my conversation with Jeff 27 00:01:55,560 --> 00:02:02,720 Speaker 1: de Graff this Masters in Business with Barry Ridholts on 28 00:02:02,840 --> 00:02:07,160 Speaker 1: Bloomberg Radio. My special guest this week is Jeff Degraff. 29 00:02:07,520 --> 00:02:11,960 Speaker 1: He is the chairman and head technical analyst at Renaissance Macro. 30 00:02:12,480 --> 00:02:16,480 Speaker 1: He has quite the storied background. Started out at Merrill Lynch, 31 00:02:16,800 --> 00:02:19,080 Speaker 1: was at Lehman Brothers for a number of years, where 32 00:02:19,080 --> 00:02:22,440 Speaker 1: he was not only chief technician but also on the 33 00:02:22,440 --> 00:02:27,040 Speaker 1: firm's investment policy committee as a managing director. Moved to 34 00:02:27,120 --> 00:02:29,880 Speaker 1: I s I in two thousand and seven before launching 35 00:02:29,960 --> 00:02:34,080 Speaker 1: his own firm in two thousand and eleven. UH. He 36 00:02:34,240 --> 00:02:37,480 Speaker 1: is both a c f A and a CMT charterholder, 37 00:02:37,520 --> 00:02:41,000 Speaker 1: a member of the New York Society of Securities Analysts 38 00:02:41,280 --> 00:02:44,239 Speaker 1: and the m T A UH. He has been number 39 00:02:44,280 --> 00:02:48,680 Speaker 1: one ranked in Institutional Investor magazine for the last twelve years. 40 00:02:49,040 --> 00:02:52,640 Speaker 1: Ranked his number one technol analysts for the last eleven years. 41 00:02:52,639 --> 00:02:55,320 Speaker 1: And we know he's a great technician because he resigned 42 00:02:55,400 --> 00:02:59,120 Speaker 1: Lehman Brothers literally the day of the stocks all time high. 43 00:02:59,520 --> 00:03:02,200 Speaker 1: Jeff de Ra, Welcome to Bloomberg. Thank you for having me. 44 00:03:02,520 --> 00:03:05,440 Speaker 1: So I've been following your work for a number of years. 45 00:03:05,520 --> 00:03:08,760 Speaker 1: I have a lot of friends who are technicians, who 46 00:03:08,800 --> 00:03:12,840 Speaker 1: who have nothing but good things to say about you. 47 00:03:12,960 --> 00:03:16,919 Speaker 1: So let's jump right in to your background and talk 48 00:03:16,960 --> 00:03:19,960 Speaker 1: a little bit about what makes what you do a 49 00:03:19,960 --> 00:03:24,560 Speaker 1: little different than the average technicians. You describe yourself as 50 00:03:24,600 --> 00:03:29,840 Speaker 1: a macro analyst. What does that mean? Well, we um, 51 00:03:29,880 --> 00:03:32,160 Speaker 1: you know, we we really pride ourselves on looking at 52 00:03:32,240 --> 00:03:34,920 Speaker 1: the big picture and within that what I mean is 53 00:03:35,000 --> 00:03:39,360 Speaker 1: currencies and and bond markets and commodity markets and then 54 00:03:39,600 --> 00:03:41,440 Speaker 1: trying to put all the pieces together. I mean, I 55 00:03:41,480 --> 00:03:44,400 Speaker 1: think the world's always appolosible. That's why I love this business. 56 00:03:44,400 --> 00:03:46,600 Speaker 1: It's a it's a chess match, you know, and it's 57 00:03:46,600 --> 00:03:49,000 Speaker 1: never different. It's never the same thing the same right, 58 00:03:49,040 --> 00:03:52,440 Speaker 1: and so it's really it's it's you know, it's it's 59 00:03:52,480 --> 00:03:56,520 Speaker 1: upon us. Um. You know. This weekend, great example, I 60 00:03:56,560 --> 00:03:58,800 Speaker 1: go through about a thousand charts on the weekend, right, 61 00:03:58,880 --> 00:04:01,880 Speaker 1: and I put a pile of charts, UM in the 62 00:04:02,320 --> 00:04:04,440 Speaker 1: I need to figure this out pile, right, And there's 63 00:04:04,520 --> 00:04:08,200 Speaker 1: usually you know, five to ten Why do Chinese steel 64 00:04:08,240 --> 00:04:11,200 Speaker 1: stocks look good while the rest of the world doesn't, right, 65 00:04:11,280 --> 00:04:13,760 Speaker 1: And so you know, and then we we then start 66 00:04:13,800 --> 00:04:16,760 Speaker 1: to backtrack and figure out what's going on. So I think, 67 00:04:17,120 --> 00:04:19,640 Speaker 1: you know what what we do that's different is we 68 00:04:19,680 --> 00:04:22,240 Speaker 1: believe in fundamentals, but we start with the charts, and 69 00:04:22,279 --> 00:04:24,640 Speaker 1: I think that's the that's the difference. So that raises 70 00:04:24,680 --> 00:04:28,039 Speaker 1: an interesting question. You're both a c f A, which 71 00:04:28,040 --> 00:04:32,760 Speaker 1: stands for Chartered Financial Analysts, essentially the key to looking 72 00:04:32,760 --> 00:04:35,360 Speaker 1: at stocks on a fundamental basis, officially a c f 73 00:04:35,480 --> 00:04:38,760 Speaker 1: A charter holder which means you've gone per distance right 74 00:04:38,839 --> 00:04:44,239 Speaker 1: three tests, and a CMT Chartered Market technician. So that's 75 00:04:44,560 --> 00:04:50,320 Speaker 1: relatively unusual, having both fundamental abilities and technicals. What what 76 00:04:50,360 --> 00:04:55,000 Speaker 1: motivated you to go for both accreditation? Well, my my 77 00:04:55,000 --> 00:04:59,760 Speaker 1: my background is formal education is in finance, so obviously 78 00:04:59,760 --> 00:05:02,920 Speaker 1: that's more fundamental than technical. And and like everybody who 79 00:05:02,960 --> 00:05:07,880 Speaker 1: comes through any business school, it was you know, relatively 80 00:05:08,240 --> 00:05:11,880 Speaker 1: pooh pooed, uh, the art of technical analysis, UM, and 81 00:05:11,920 --> 00:05:13,960 Speaker 1: so I bought into that as I you know, was 82 00:05:14,240 --> 00:05:17,520 Speaker 1: searching for grades more than anything else. And UM, you know, 83 00:05:17,640 --> 00:05:21,520 Speaker 1: once I um got into the business, uh, it just 84 00:05:21,720 --> 00:05:26,599 Speaker 1: found um that the technicians who I appreciated, Bob Farrell, 85 00:05:26,640 --> 00:05:29,039 Speaker 1: who I grew up under, Steve Schaubin, who was my 86 00:05:29,120 --> 00:05:32,039 Speaker 1: mentor at at Lehman Brothers, and just a fantastic individual 87 00:05:32,080 --> 00:05:36,360 Speaker 1: and great technician. Um, I just I found that there 88 00:05:36,440 --> 00:05:38,520 Speaker 1: was something to what they were saying. In fact, it 89 00:05:38,600 --> 00:05:41,839 Speaker 1: was usually more prescient than what you're seeing out of 90 00:05:41,880 --> 00:05:44,760 Speaker 1: the out of the fundamental side. So I picked up 91 00:05:44,839 --> 00:05:48,040 Speaker 1: the Edwards and McGee book. I read it. Um, it 92 00:05:48,080 --> 00:05:50,440 Speaker 1: was interesting. I didn't you know, I didn't buy into 93 00:05:50,480 --> 00:05:53,080 Speaker 1: it wholeheartedly, but certainly there were you know, parts of 94 00:05:53,080 --> 00:05:56,640 Speaker 1: it that I appreciated and could see the light with. UM. 95 00:05:56,680 --> 00:06:01,520 Speaker 1: I thought the the books, the Wiser books UM or 96 00:06:01,560 --> 00:06:05,799 Speaker 1: the I think Schweizer, Swigger, UM, the Right Market Wizard books. 97 00:06:05,800 --> 00:06:08,240 Speaker 1: So I thought those were fantastic. And what that did 98 00:06:08,279 --> 00:06:11,920 Speaker 1: for me really solidified it was UM and I've always 99 00:06:11,920 --> 00:06:16,360 Speaker 1: been this type of person. It was about probability, right, 100 00:06:16,480 --> 00:06:19,960 Speaker 1: and the best way for me to manage risk and 101 00:06:20,080 --> 00:06:22,080 Speaker 1: thinking about it, whether it's at the poker table, the 102 00:06:22,120 --> 00:06:25,480 Speaker 1: blackjack table, or in the markets was through technical analysis, 103 00:06:25,520 --> 00:06:27,720 Speaker 1: and that just really hit me over the head. As 104 00:06:27,880 --> 00:06:32,000 Speaker 1: as to the type of discipline essentially counting cards in 105 00:06:32,040 --> 00:06:34,880 Speaker 1: the market, um is the last You start with the 106 00:06:34,920 --> 00:06:37,400 Speaker 1: evidence in the data, you lay out what's most likely, 107 00:06:37,520 --> 00:06:40,320 Speaker 1: least likely in everything in between, and that colors how 108 00:06:40,400 --> 00:06:43,040 Speaker 1: you see the markets. Yeah. Look, I I described a 109 00:06:43,080 --> 00:06:46,200 Speaker 1: little differently the difference between the pot odds and the 110 00:06:46,200 --> 00:06:48,880 Speaker 1: odds in my hand. Right, there's a certain probability of 111 00:06:49,360 --> 00:06:52,600 Speaker 1: pulling a card to complete an inside flush or an 112 00:06:52,600 --> 00:06:56,920 Speaker 1: inside straight. Pardon me, Um, if the opportunity to stay 113 00:06:57,040 --> 00:07:01,560 Speaker 1: in the pot is low enough and the the reward 114 00:07:01,600 --> 00:07:04,320 Speaker 1: is high enough. Absolutely those even though it might be 115 00:07:04,360 --> 00:07:07,440 Speaker 1: a very slim chance of pulling that straight, the chance 116 00:07:07,480 --> 00:07:09,480 Speaker 1: to stay in makes an awful lot of sense. And 117 00:07:09,560 --> 00:07:11,480 Speaker 1: that's how we think about You know, I took the 118 00:07:11,960 --> 00:07:14,800 Speaker 1: m T A course with Ralph Acampora, and one of 119 00:07:14,800 --> 00:07:18,080 Speaker 1: the lines that have stayed with me all these years 120 00:07:18,080 --> 00:07:22,360 Speaker 1: has been fundamentals tell you what to buy, Technicals tell 121 00:07:22,400 --> 00:07:25,800 Speaker 1: you when to buy. There's there's some truth to that. 122 00:07:25,920 --> 00:07:28,840 Speaker 1: I would I would add to that though, too. Um. 123 00:07:28,880 --> 00:07:31,120 Speaker 1: In fact, you know, it's just talking to somebody about this. 124 00:07:31,160 --> 00:07:35,480 Speaker 1: With gold, UM, oftentimes the technicals will tell you, um 125 00:07:35,600 --> 00:07:39,280 Speaker 1: what to buy, and maybe you don't know the fundamental story, right. 126 00:07:39,320 --> 00:07:41,480 Speaker 1: I mean, if you think about when Apple first broke 127 00:07:41,520 --> 00:07:44,600 Speaker 1: out of this huge base formation, nobody had a clue 128 00:07:44,600 --> 00:07:47,240 Speaker 1: about the iPhone, and I mean it just was unbelievable, 129 00:07:47,400 --> 00:07:50,920 Speaker 1: you know, sort of the the the the the ramp 130 00:07:50,960 --> 00:07:53,240 Speaker 1: and the product and changing the world. Same thing with 131 00:07:53,280 --> 00:07:56,760 Speaker 1: gold today. You know, the gold trends have changed, UM, 132 00:07:56,920 --> 00:07:59,160 Speaker 1: and they changed in the first quarter for US. But 133 00:07:59,600 --> 00:08:02,320 Speaker 1: you know, some me asked me, well, is it uh? Currencies? 134 00:08:02,440 --> 00:08:05,080 Speaker 1: Is it uh? You know, negative interest rates. I don't 135 00:08:05,080 --> 00:08:07,880 Speaker 1: know officially what the answer is, but the charts are 136 00:08:07,920 --> 00:08:11,240 Speaker 1: telling you that something is out there that has a 137 00:08:11,320 --> 00:08:14,640 Speaker 1: high probability of continuing. Let me ask you a simple question. 138 00:08:14,920 --> 00:08:19,680 Speaker 1: What do most people misunderstand about technical analysis? I think, 139 00:08:19,680 --> 00:08:22,880 Speaker 1: and this will you know, This will uh send shivers 140 00:08:22,920 --> 00:08:25,960 Speaker 1: down to some people's spines. I think people believe that 141 00:08:26,040 --> 00:08:29,680 Speaker 1: technical analysis can predict the future, and I really don't 142 00:08:29,680 --> 00:08:33,360 Speaker 1: see it as that. I see technical analysis as identifying trends, 143 00:08:33,920 --> 00:08:38,079 Speaker 1: identifying opportunities within those trends, and taking advantage of them. 144 00:08:38,280 --> 00:08:40,400 Speaker 1: So to say it's predicting the future. I think is 145 00:08:40,400 --> 00:08:43,720 Speaker 1: is a little a little misguided. I'm very Rihults. You're 146 00:08:43,760 --> 00:08:47,360 Speaker 1: listening to Masters in Business on Bloomberg Radio. My special 147 00:08:47,360 --> 00:08:51,480 Speaker 1: guest today is Jeff Degraff. He is the chairman and 148 00:08:51,800 --> 00:08:55,680 Speaker 1: head technical analyst. Is that your your property title? CEO 149 00:08:55,840 --> 00:09:01,760 Speaker 1: and chairman? And yeah. Renaissance macro a uh, pretty much 150 00:09:01,760 --> 00:09:07,400 Speaker 1: a global research shop that supports institutions, edge funds, commutual funds, 151 00:09:07,440 --> 00:09:11,360 Speaker 1: et cetera. Let's jump right in. Let's jump right in 152 00:09:11,440 --> 00:09:15,320 Speaker 1: why technicals work. And I think it's it's pretty interesting 153 00:09:15,559 --> 00:09:17,960 Speaker 1: for the lay person, for the average investor who might 154 00:09:18,000 --> 00:09:20,720 Speaker 1: be listening to this or some student in an NBA 155 00:09:20,840 --> 00:09:24,120 Speaker 1: course where they tell you this stuff doesn't work, Explain 156 00:09:24,440 --> 00:09:27,880 Speaker 1: what is technical analysis and why does it work? Well? 157 00:09:27,920 --> 00:09:31,880 Speaker 1: That there are definitely elements within technical analysis that I 158 00:09:31,920 --> 00:09:34,040 Speaker 1: would even say probably don't work, and I want to 159 00:09:34,040 --> 00:09:36,439 Speaker 1: be careful with some of those, and and and Elliott 160 00:09:36,440 --> 00:09:39,440 Speaker 1: wave Fibonacci, some of the more fringe stuff, or just 161 00:09:39,760 --> 00:09:44,200 Speaker 1: generally the patterns that some people there there are oscillations 162 00:09:44,240 --> 00:09:46,960 Speaker 1: that people sort of believe must mean revert. And that's 163 00:09:47,000 --> 00:09:48,880 Speaker 1: really you know, we've done a lot of work on that, 164 00:09:48,960 --> 00:09:50,760 Speaker 1: and that doesn't prove to be true. There there are 165 00:09:50,840 --> 00:09:55,000 Speaker 1: certain conditions that you can overlay to help create better 166 00:09:55,280 --> 00:09:58,320 Speaker 1: probabilities or opportunities. But really when it comes down to 167 00:09:58,480 --> 00:10:02,000 Speaker 1: for us is is technical analysis works because it's about 168 00:10:02,040 --> 00:10:05,640 Speaker 1: trend analysis. And if you think about just the world 169 00:10:05,720 --> 00:10:08,959 Speaker 1: in which we live, um, you know there are trends 170 00:10:08,960 --> 00:10:12,400 Speaker 1: in place everywhere, right, I mean earnings are generally trending, 171 00:10:12,720 --> 00:10:15,160 Speaker 1: um Uh, And so you know to expect that there's 172 00:10:15,160 --> 00:10:18,040 Speaker 1: sort of this randomness and earnings there there isn't right, 173 00:10:18,040 --> 00:10:20,040 Speaker 1: there generally is a trend. Now, there might be missed 174 00:10:20,040 --> 00:10:23,000 Speaker 1: opportunities in those earnings trends here and there, but for 175 00:10:23,040 --> 00:10:26,240 Speaker 1: the most part, uh, you know, a company's fundamental trajectory 176 00:10:26,280 --> 00:10:28,800 Speaker 1: will be a trend, and we're capturing that through price. 177 00:10:28,840 --> 00:10:31,560 Speaker 1: And the idea is that the markets are efficient and 178 00:10:31,600 --> 00:10:33,880 Speaker 1: so what you know, what I know from a fundamental 179 00:10:33,960 --> 00:10:36,679 Speaker 1: sense is probably already embedded in that price. And what 180 00:10:36,720 --> 00:10:39,880 Speaker 1: we're doing is we're just simply measuring that price, taking 181 00:10:39,920 --> 00:10:43,439 Speaker 1: that temperature and understanding or trying to understand whether or 182 00:10:43,480 --> 00:10:46,360 Speaker 1: not the probabilities are for good continuation in that price 183 00:10:46,720 --> 00:10:48,800 Speaker 1: or for a reversal in that price. So so the 184 00:10:48,840 --> 00:10:52,400 Speaker 1: baseline assumption is that a trend in place, that momentum 185 00:10:52,440 --> 00:10:55,920 Speaker 1: is going to continue until such time as something acts 186 00:10:55,960 --> 00:10:59,959 Speaker 1: to stop it. The probabilities, overwhelmingly, whether it's academic research 187 00:11:00,080 --> 00:11:02,760 Speaker 1: our own research, are that there's a persistence and trends 188 00:11:02,760 --> 00:11:05,000 Speaker 1: in the market. It's called momentum in a lot of 189 00:11:05,320 --> 00:11:08,240 Speaker 1: in a lot of academic studies. Um. And it drives 190 00:11:08,280 --> 00:11:11,760 Speaker 1: people nuts because quote unquote shouldn't work, right, But the 191 00:11:11,800 --> 00:11:14,559 Speaker 1: reality is is that it does and um, and that's 192 00:11:14,559 --> 00:11:17,040 Speaker 1: what we exploit. Well, why shouldn't it work. Let's let's 193 00:11:17,080 --> 00:11:19,440 Speaker 1: step back, because you're a big macro guy and you 194 00:11:19,440 --> 00:11:22,680 Speaker 1: look at things from both the fundamental technical quant an 195 00:11:22,679 --> 00:11:26,880 Speaker 1: economic perspective. Hey, every day people are earning money. That 196 00:11:26,960 --> 00:11:31,760 Speaker 1: money gets shoveled into their four oh one case and elsewhere. Ultimately, 197 00:11:31,880 --> 00:11:34,600 Speaker 1: there's only so many stocks in the universe that a 198 00:11:34,640 --> 00:11:40,079 Speaker 1: fund manager with a given uh sector or topic or 199 00:11:40,960 --> 00:11:43,560 Speaker 1: charge is going to buy. And so he's gonna go 200 00:11:43,640 --> 00:11:46,160 Speaker 1: back and keep buying his favorite names over and over. 201 00:11:46,520 --> 00:11:48,920 Speaker 1: I mean, that's it's a great point that the academics 202 00:11:48,920 --> 00:11:52,559 Speaker 1: would say. Um, there's the efficient market hypothesis, which says 203 00:11:52,679 --> 00:11:55,760 Speaker 1: that the um. You know, the the weak form, the 204 00:11:55,800 --> 00:11:59,000 Speaker 1: strong form, that that information should already be discounted in 205 00:11:59,040 --> 00:12:01,280 Speaker 1: the market price. The reality is, is it just it 206 00:12:01,360 --> 00:12:05,120 Speaker 1: just isn't right. It's sort of kind of eventually more 207 00:12:05,200 --> 00:12:08,240 Speaker 1: or less efficient, but it's not instantly efficient. You have 208 00:12:08,679 --> 00:12:11,480 Speaker 1: there are too many people who have been consistently beating 209 00:12:11,520 --> 00:12:14,280 Speaker 1: the markets. I know the academics like to just shrug 210 00:12:14,320 --> 00:12:17,000 Speaker 1: it off and say outlawyers run off, but there are 211 00:12:17,040 --> 00:12:20,200 Speaker 1: just too many Howard marks and too many Warren buffets, 212 00:12:20,240 --> 00:12:23,800 Speaker 1: even though we're talking, you know, a few dozen, but 213 00:12:23,920 --> 00:12:26,680 Speaker 1: they shouldn't exist, and they do, and and that that 214 00:12:27,400 --> 00:12:31,760 Speaker 1: sort of begets that perfectly efficient thing. So what do 215 00:12:31,800 --> 00:12:35,320 Speaker 1: you think is more important? Trends or mean reversion without 216 00:12:35,360 --> 00:12:38,480 Speaker 1: question trend um If you look at mean reversion without 217 00:12:38,520 --> 00:12:41,160 Speaker 1: the presence of trend in other words, trying to identify 218 00:12:41,240 --> 00:12:43,839 Speaker 1: mean reversion without looking at first what the underlying trend 219 00:12:43,920 --> 00:12:49,000 Speaker 1: is um, it is quickly a recipe and a system 220 00:12:49,120 --> 00:12:53,959 Speaker 1: for losses um. The trends are historically um and this 221 00:12:54,000 --> 00:12:56,680 Speaker 1: is a crossed assets it's not just equities, but the 222 00:12:56,679 --> 00:13:01,840 Speaker 1: trends are historically prescient in giving you some foresight into 223 00:13:02,000 --> 00:13:05,120 Speaker 1: the next move higher and that's that can be anything 224 00:13:05,160 --> 00:13:08,120 Speaker 1: from intra day to to you know, long term, multi 225 00:13:08,200 --> 00:13:11,880 Speaker 1: multi year. You know what we find the sweet spot um, 226 00:13:11,960 --> 00:13:14,120 Speaker 1: And this isn't you know, I'm not I'm not breaking 227 00:13:14,120 --> 00:13:16,960 Speaker 1: any rules here or breaking any new ground. But we 228 00:13:17,040 --> 00:13:21,120 Speaker 1: find that from three months, uh, three months in other words, 229 00:13:21,160 --> 00:13:24,760 Speaker 1: one month, two months, three months, uh, the returns of 230 00:13:24,760 --> 00:13:28,160 Speaker 1: of equities over that period um tend to me mean reverting. 231 00:13:28,160 --> 00:13:30,760 Speaker 1: In other words, if I have strong one month performance, 232 00:13:30,800 --> 00:13:34,160 Speaker 1: the probability of me having another outperformance the next month 233 00:13:34,240 --> 00:13:36,920 Speaker 1: is actually pretty low. UM. If I start getting into 234 00:13:36,960 --> 00:13:39,719 Speaker 1: six month twelve month time frames and look out for 235 00:13:39,760 --> 00:13:42,480 Speaker 1: the next six to twelve months, that probability actually shifts 236 00:13:42,520 --> 00:13:45,640 Speaker 1: to being more momentum oriented. Right, So you want to 237 00:13:45,640 --> 00:13:47,559 Speaker 1: be careful when people talk about, well, I'm not a 238 00:13:47,559 --> 00:13:49,680 Speaker 1: trend foller, I'm not a momentum player. You know, you 239 00:13:49,760 --> 00:13:52,960 Speaker 1: really have to define what your time frame is because 240 00:13:53,000 --> 00:13:55,520 Speaker 1: if you're a swing trader, if you're a short term player, 241 00:13:55,600 --> 00:13:58,640 Speaker 1: then you can be anti momentum. But I wouldn't suggest that, 242 00:13:58,880 --> 00:14:01,559 Speaker 1: you know, you use twelve month or nine month momentum 243 00:14:02,000 --> 00:14:04,200 Speaker 1: and try to fade that. Historically that doesn't work out 244 00:14:04,200 --> 00:14:08,679 Speaker 1: for so long. How does valuation fit into into your analysis? Well, 245 00:14:08,720 --> 00:14:13,280 Speaker 1: let's let's take valuation and lump it with fundamental analysis. 246 00:14:13,400 --> 00:14:17,640 Speaker 1: And and we would look at UM fundamental analysis as 247 00:14:18,160 --> 00:14:22,280 Speaker 1: UM one silo in what we call conditional factors. These 248 00:14:22,280 --> 00:14:25,160 Speaker 1: are things that tend to support a bull phase or 249 00:14:25,200 --> 00:14:27,480 Speaker 1: tend to support a bear phase. So you have these conditions, 250 00:14:27,560 --> 00:14:30,960 Speaker 1: valuation being one, UM that certainly would be more supportive 251 00:14:31,040 --> 00:14:34,280 Speaker 1: of a bull phase, presuming there's uh, there's good valuation. 252 00:14:34,520 --> 00:14:38,360 Speaker 1: I would put things like credit, sentiment, seasonality. All these 253 00:14:38,400 --> 00:14:42,040 Speaker 1: would be conditions that that support a bull or bear phase. UM. 254 00:14:42,120 --> 00:14:44,360 Speaker 1: Think about it. If you will like the amount of 255 00:14:44,400 --> 00:14:47,600 Speaker 1: gas in the tank, it sort of tells you how 256 00:14:47,640 --> 00:14:50,760 Speaker 1: far you can go. UM. The other side of that 257 00:14:51,040 --> 00:14:54,000 Speaker 1: is momentum and trend, and we think about that is 258 00:14:54,040 --> 00:14:56,640 Speaker 1: how hot the spark is in the engine. Each one 259 00:14:56,640 --> 00:15:00,640 Speaker 1: of these independently is useless, right, But it's the combination 260 00:15:00,760 --> 00:15:03,640 Speaker 1: of both that's important. So if I've got strong conditions, 261 00:15:03,640 --> 00:15:05,880 Speaker 1: if I've got a lot of barishness, I've got good valuation, 262 00:15:06,200 --> 00:15:09,560 Speaker 1: I've got seasonality, credit conditions are good, and I've got 263 00:15:09,560 --> 00:15:12,640 Speaker 1: that hot spark, I've got momentum, I've got trend. That's 264 00:15:12,640 --> 00:15:16,120 Speaker 1: a great combination. So for us, that's about position sizing, right, 265 00:15:16,160 --> 00:15:18,560 Speaker 1: that's a bigger call. That's something that we're more comfortable in, 266 00:15:18,640 --> 00:15:21,320 Speaker 1: will make a bigger bet with. If I've got the 267 00:15:21,680 --> 00:15:24,320 Speaker 1: market today, if I've got a hot spark, in other words, 268 00:15:24,320 --> 00:15:26,960 Speaker 1: we've got good trend, we've got good momentum, but the 269 00:15:27,440 --> 00:15:29,200 Speaker 1: way that we see the fuel in the tank is 270 00:15:29,200 --> 00:15:32,040 Speaker 1: being maybe a quarter full. I'll still play, but I 271 00:15:32,080 --> 00:15:35,000 Speaker 1: have to understand that the probabilities of this being an 272 00:15:35,000 --> 00:15:37,680 Speaker 1: O nine type of trend change or an OH three 273 00:15:37,680 --> 00:15:41,080 Speaker 1: type of trend change really are are are low. How 274 00:15:41,080 --> 00:15:44,600 Speaker 1: does sector work figure into your macro approach? Do you 275 00:15:44,640 --> 00:15:49,320 Speaker 1: look at specific market sectors technology, healthcare, energy? Absolutely? We 276 00:15:49,360 --> 00:15:51,840 Speaker 1: think you know, we're known for market calls. I mean, 277 00:15:51,840 --> 00:15:53,800 Speaker 1: that's sort of what people want to hear. But the 278 00:15:53,840 --> 00:15:55,840 Speaker 1: reality is the way that we really make money air 279 00:15:55,920 --> 00:15:59,720 Speaker 1: through sectors. And uh. We we look at sector relative performance, 280 00:15:59,720 --> 00:16:02,640 Speaker 1: we global relative performance. So we bring it all together 281 00:16:02,680 --> 00:16:07,240 Speaker 1: and find that there's a huge uh correlation between between 282 00:16:07,360 --> 00:16:10,880 Speaker 1: regional markets and the sectors um and so we'll we'll 283 00:16:11,000 --> 00:16:13,600 Speaker 1: use all that to identify where the best and where 284 00:16:13,640 --> 00:16:16,040 Speaker 1: the worst sectors are, and we quantify the process. We 285 00:16:16,080 --> 00:16:18,720 Speaker 1: have ways in which we've quantified, so it's not Jeff 286 00:16:18,760 --> 00:16:20,400 Speaker 1: de graph We can got, you know, in a bad 287 00:16:20,440 --> 00:16:23,600 Speaker 1: mood someday and saying everything looks terrible. Um, we haven't quantified, 288 00:16:23,640 --> 00:16:25,320 Speaker 1: so we can back test it, and we can give 289 00:16:25,360 --> 00:16:28,440 Speaker 1: people the confidence and assuredness that hey, if you follow 290 00:16:28,480 --> 00:16:31,720 Speaker 1: this system, here's what you're looking at in terms of probabilities. 291 00:16:31,880 --> 00:16:34,920 Speaker 1: I'm Barry Rihults. You're listening to Masters in Business on 292 00:16:35,000 --> 00:16:39,080 Speaker 1: Bloomberg Radio. My special guests this week is Jeff DeGraf. 293 00:16:39,600 --> 00:16:44,360 Speaker 1: He is a technician extraordinaire and and I jokingly started 294 00:16:44,400 --> 00:16:47,960 Speaker 1: the show by saying he resigned Lehman Brothers pretty much 295 00:16:48,000 --> 00:16:50,760 Speaker 1: to the day of it's all time high. That's how 296 00:16:50,760 --> 00:16:53,800 Speaker 1: we know he's a really good technician. But that actually 297 00:16:53,880 --> 00:16:57,120 Speaker 1: is a true anecdote. You did move to I s 298 00:16:57,120 --> 00:17:00,800 Speaker 1: I pretty much early two oh seven thousand seven, when 299 00:17:01,120 --> 00:17:03,960 Speaker 1: February oh seven was my resignation, and that's pretty much 300 00:17:04,000 --> 00:17:06,000 Speaker 1: the top sick and it was the it was my 301 00:17:06,040 --> 00:17:08,439 Speaker 1: origination letter was the day after the high in the 302 00:17:08,440 --> 00:17:11,280 Speaker 1: stock price. So that's lucky, not good, But that is 303 00:17:11,280 --> 00:17:14,000 Speaker 1: a true story. I love that story that I've said 304 00:17:14,000 --> 00:17:15,960 Speaker 1: that to people and They're like, no, that can't be him, 305 00:17:15,960 --> 00:17:18,480 Speaker 1: Like no, no, he's a really good technician. He saw 306 00:17:18,560 --> 00:17:20,440 Speaker 1: that that trend break and he said that sad, I'm 307 00:17:20,440 --> 00:17:24,359 Speaker 1: out of here. Um. But it's kind of interesting because 308 00:17:24,400 --> 00:17:26,560 Speaker 1: you left for I s A. You were there for 309 00:17:26,600 --> 00:17:29,200 Speaker 1: a couple of years. Ed him and another guy who 310 00:17:29,320 --> 00:17:32,399 Speaker 1: thirty plush years number one ranked. We found him on 311 00:17:32,440 --> 00:17:35,720 Speaker 1: the show. He's great. But at a time when when 312 00:17:36,000 --> 00:17:40,959 Speaker 1: commission dollars are plumbering, when research budgets are really being constrained, 313 00:17:41,400 --> 00:17:44,840 Speaker 1: you decide to launch a new research farm, right, what 314 00:17:44,880 --> 00:17:49,080 Speaker 1: was the thinking like making that leap? Well, you know, look, 315 00:17:49,160 --> 00:17:53,720 Speaker 1: the research budgets are contracting, but when you're when you're 316 00:17:53,760 --> 00:17:57,439 Speaker 1: bloated and have you know, too much capacity, that's a 317 00:17:57,440 --> 00:18:00,119 Speaker 1: bigger problem. When you're starting with eight people, which we 318 00:18:00,200 --> 00:18:03,199 Speaker 1: did uh and are now up to um. You know, 319 00:18:03,280 --> 00:18:05,879 Speaker 1: that's a that's a different that's a different game. And 320 00:18:05,960 --> 00:18:09,760 Speaker 1: so you know, focusing on one of the keys to 321 00:18:09,880 --> 00:18:13,000 Speaker 1: starting ren MAC was, uh, we wanted to build a 322 00:18:13,000 --> 00:18:15,879 Speaker 1: world class database and you know, you just have to 323 00:18:15,880 --> 00:18:18,760 Speaker 1: do that yourself. You can't do it under another another 324 00:18:18,880 --> 00:18:21,280 Speaker 1: entity or you're basically building it for somebody else. And 325 00:18:21,320 --> 00:18:25,160 Speaker 1: so the idea was build a world class database, quantify 326 00:18:25,280 --> 00:18:28,800 Speaker 1: approach this in a much different way to work into 327 00:18:28,840 --> 00:18:32,920 Speaker 1: people's process so that they have another overlay look of 328 00:18:33,000 --> 00:18:35,960 Speaker 1: the street, spend its time and I don't falls them 329 00:18:35,960 --> 00:18:38,800 Speaker 1: for this on fundamental research and the nitty gritty the 330 00:18:38,840 --> 00:18:41,480 Speaker 1: quote unquote knowing the company is better than anybody else. 331 00:18:41,960 --> 00:18:43,960 Speaker 1: But the reality is is not enough time is spent 332 00:18:44,560 --> 00:18:47,960 Speaker 1: in the process of just understanding what the macro environment is, 333 00:18:48,000 --> 00:18:50,520 Speaker 1: what the trends are. And so from our standpoint, we 334 00:18:50,520 --> 00:18:52,280 Speaker 1: want to be able to quantify that for people so 335 00:18:52,280 --> 00:18:54,720 Speaker 1: that they didn't have to become technicians, but they could 336 00:18:54,720 --> 00:18:56,720 Speaker 1: look at it and say, okay, I understand that the 337 00:18:56,800 --> 00:18:59,159 Speaker 1: risks are high in technology, that the opportunity set is 338 00:18:59,160 --> 00:19:02,520 Speaker 1: actually high and in adustrials and have some quantification around that. 339 00:19:02,760 --> 00:19:05,679 Speaker 1: And that's really what we provide. So n MAC is 340 00:19:05,840 --> 00:19:10,480 Speaker 1: creating a dimensional analysis that simply isn't available to from 341 00:19:10,480 --> 00:19:13,320 Speaker 1: other researches. Is that what sets you guys apart from 342 00:19:13,359 --> 00:19:15,800 Speaker 1: everyone else. Absolutely, I think that's that's that's a huge 343 00:19:15,800 --> 00:19:19,639 Speaker 1: part of it. And and how does one combine economics, 344 00:19:19,760 --> 00:19:24,040 Speaker 1: quant fundamentals and technicals in one package. Well, we we 345 00:19:24,080 --> 00:19:26,720 Speaker 1: don't do the fundamental side per se UM. We have 346 00:19:26,840 --> 00:19:29,400 Speaker 1: Neil Datta who does our our economic side, and that's Look, 347 00:19:29,440 --> 00:19:32,760 Speaker 1: there's a lot of high frequency data in economics and 348 00:19:32,760 --> 00:19:34,840 Speaker 1: and even more so when you think about the globe 349 00:19:35,280 --> 00:19:37,679 Speaker 1: UH and those are important data points. So what we 350 00:19:37,760 --> 00:19:40,600 Speaker 1: do is we use those data points UM, we test 351 00:19:40,640 --> 00:19:43,760 Speaker 1: those data points. We look at them within the context 352 00:19:43,800 --> 00:19:47,080 Speaker 1: of what's happening to trends to see if they're useful. Again, 353 00:19:47,200 --> 00:19:49,280 Speaker 1: some of those conditional factors that I spoke about in 354 00:19:49,280 --> 00:19:51,879 Speaker 1: the earlier segment UM and that's how we we we 355 00:19:52,000 --> 00:19:55,720 Speaker 1: marry it together in terms of this UM conditional elements. 356 00:19:55,880 --> 00:19:59,160 Speaker 1: One of the things that you're known for is changing 357 00:19:59,200 --> 00:20:02,080 Speaker 1: the weight of certain indicators depending on whether or not 358 00:20:02,119 --> 00:20:05,919 Speaker 1: we're in a bullish or bearish market. Few people managed 359 00:20:05,960 --> 00:20:09,120 Speaker 1: to do this. Well, how do you go about approaching that? 360 00:20:09,320 --> 00:20:11,239 Speaker 1: You have to quantify it. You can't do it by 361 00:20:11,240 --> 00:20:13,879 Speaker 1: the seat of your pants. You have to have UM, 362 00:20:13,880 --> 00:20:17,160 Speaker 1: a quantification of the discipline, and you have to test 363 00:20:17,200 --> 00:20:19,800 Speaker 1: that over time. And we've done that. And so a 364 00:20:19,840 --> 00:20:22,359 Speaker 1: big one for us is our trend model UM, where 365 00:20:22,440 --> 00:20:26,719 Speaker 1: we have basically a bullish bearish trend UM. It can 366 00:20:26,720 --> 00:20:28,520 Speaker 1: go neutral, but we don't really have a neutral state. 367 00:20:28,520 --> 00:20:30,520 Speaker 1: We'd like to have either black or white. And what 368 00:20:30,560 --> 00:20:32,480 Speaker 1: we find is that other indicators that if you looked 369 00:20:32,520 --> 00:20:35,440 Speaker 1: at over the entire spectrum of bullish and bearish might 370 00:20:35,480 --> 00:20:37,639 Speaker 1: not be worth a damn. But when you break it 371 00:20:37,680 --> 00:20:41,159 Speaker 1: down between bearish and bullish, UM, some indicators work very 372 00:20:41,240 --> 00:20:44,280 Speaker 1: very well in a bear state. Other indicators work very 373 00:20:44,359 --> 00:20:46,560 Speaker 1: very well in a bull state, but they don't work 374 00:20:46,600 --> 00:20:50,280 Speaker 1: well across those different states. So for us, the quantification 375 00:20:50,600 --> 00:20:52,960 Speaker 1: trend is a big one. The quantification of trend and 376 00:20:53,000 --> 00:20:56,879 Speaker 1: then understanding what conditions work within that trend are a 377 00:20:56,960 --> 00:20:58,720 Speaker 1: huge part of what we do. So what do you 378 00:20:58,760 --> 00:21:01,040 Speaker 1: do in a crisis? We saw the oh eight o 379 00:21:01,160 --> 00:21:04,840 Speaker 1: nine crisis ramping up. Essentially all the correlations went to 380 00:21:04,920 --> 00:21:08,399 Speaker 1: one and it seemed like you were either in bonds 381 00:21:08,560 --> 00:21:10,960 Speaker 1: or equity like products and there was nothing in between. 382 00:21:11,280 --> 00:21:13,960 Speaker 1: How do you analyze as those sort of circumstances. Well, 383 00:21:13,960 --> 00:21:17,280 Speaker 1: we we have ways to measure sentiment, which obviously was 384 00:21:17,800 --> 00:21:20,119 Speaker 1: a disaster. I mean people were apocalyptic as we like 385 00:21:20,200 --> 00:21:22,600 Speaker 1: to call it at the time. UM, we have ways 386 00:21:22,640 --> 00:21:26,159 Speaker 1: to measure the UM, the severity of the downtrend, the 387 00:21:26,280 --> 00:21:29,080 Speaker 1: risk adjusted returns UM, and we look at those and 388 00:21:29,080 --> 00:21:31,879 Speaker 1: when they're they're so bad, um believe it or not, 389 00:21:31,960 --> 00:21:34,119 Speaker 1: our system flags it. So we have an understanding that 390 00:21:34,119 --> 00:21:37,400 Speaker 1: there's probably some capitulation taking place. And then we look 391 00:21:37,400 --> 00:21:39,920 Speaker 1: at the credit markets. Credit markets are a huge part 392 00:21:39,960 --> 00:21:41,480 Speaker 1: of our input that I don't think a lot of 393 00:21:41,480 --> 00:21:44,080 Speaker 1: people pay as much attention to as they should. And look, 394 00:21:44,119 --> 00:21:48,000 Speaker 1: the credit markets made their low UH in November two 395 00:21:48,000 --> 00:21:51,080 Speaker 1: thousand and eight, and we're healing for a good three 396 00:21:51,119 --> 00:21:54,040 Speaker 1: months prior to the equity low. Right, So when we 397 00:21:54,080 --> 00:21:56,600 Speaker 1: looked at that that combination of things going on, saying, boy, 398 00:21:56,640 --> 00:21:58,879 Speaker 1: credits getting better, but the equity markets are turning in 399 00:21:58,920 --> 00:22:02,560 Speaker 1: a new low. There some opportunity here. And while we 400 00:22:02,560 --> 00:22:05,040 Speaker 1: were warming up to equities again, we needed that spark. 401 00:22:05,080 --> 00:22:08,520 Speaker 1: We needed to see that that engine spark. And that's 402 00:22:08,560 --> 00:22:11,199 Speaker 1: what we saw in the early part of March of 403 00:22:11,240 --> 00:22:14,199 Speaker 1: that year with these big breath days in this thrust. 404 00:22:14,320 --> 00:22:16,600 Speaker 1: That's the that's the spark that we needed to say, Hey, 405 00:22:16,840 --> 00:22:19,880 Speaker 1: these conditions are in place for what should be um 406 00:22:19,920 --> 00:22:23,480 Speaker 1: a pretty impressive rally. I'm Barry Ridholtz. You're listening to 407 00:22:23,600 --> 00:22:27,240 Speaker 1: Masters in Business on Bloomberg Radio. My special guest today 408 00:22:27,480 --> 00:22:31,560 Speaker 1: is Jeff DeGraf. He is the founder and CEO of 409 00:22:31,840 --> 00:22:36,439 Speaker 1: and head to technician at Renaissance Macro Analysis. Am I 410 00:22:36,480 --> 00:22:41,240 Speaker 1: pronouncing that right? We'll make it easy rend mac. Jeff 411 00:22:41,280 --> 00:22:44,560 Speaker 1: has been number one ranked by Institutional Investor magazine for 412 00:22:44,560 --> 00:22:49,240 Speaker 1: the past twelve years as both a technical and macro analyst, 413 00:22:49,600 --> 00:22:52,960 Speaker 1: probably best known for his years as the chief technician 414 00:22:53,080 --> 00:22:56,399 Speaker 1: at Lehman Brothers. Let's talk a little bit about the macro, 415 00:22:56,600 --> 00:22:59,560 Speaker 1: which is something that has been fascinating. It drives a 416 00:22:59,560 --> 00:23:03,000 Speaker 1: lot of new stories. It makes a great narrative. You know, 417 00:23:03,040 --> 00:23:06,480 Speaker 1: in my office we call certain people macro tourists. The 418 00:23:06,520 --> 00:23:10,040 Speaker 1: folks who dabble in macro. They have gotten killed over 419 00:23:10,040 --> 00:23:13,840 Speaker 1: the past few years. What what is that about? Well, 420 00:23:13,840 --> 00:23:16,639 Speaker 1: it's about opportunity and thinking that you know, you can 421 00:23:16,720 --> 00:23:20,160 Speaker 1: you can use the news environment to make money, which 422 00:23:20,200 --> 00:23:23,639 Speaker 1: is usually pretty difficult to the party. Yeah, getting back 423 00:23:23,680 --> 00:23:26,240 Speaker 1: to the discounting mechanism, right, so, um, you know, I 424 00:23:26,240 --> 00:23:30,439 Speaker 1: think that's one that's one area of of of trouble 425 00:23:30,560 --> 00:23:33,600 Speaker 1: or or this problematic Uh, you know, look, the macro. 426 00:23:34,080 --> 00:23:38,720 Speaker 1: The reason that we specialize in macro is because of 427 00:23:38,720 --> 00:23:41,800 Speaker 1: the street pays attention to their industry. They pay attention 428 00:23:41,840 --> 00:23:44,760 Speaker 1: to their individual stocks, and they pay attention to their models. 429 00:23:45,040 --> 00:23:48,280 Speaker 1: They don't really incorporate what's going on in the globe 430 00:23:48,320 --> 00:23:52,080 Speaker 1: and whether or not the central bank assets are expanding 431 00:23:52,200 --> 00:23:55,200 Speaker 1: or contracting, or you know, negative rates and the potential 432 00:23:55,200 --> 00:23:57,520 Speaker 1: impact of that. So what we're trying to do is 433 00:23:58,200 --> 00:24:01,119 Speaker 1: really cut out that niche and give the opportunity to 434 00:24:01,600 --> 00:24:03,920 Speaker 1: look for somebody who's got expertise and that who does 435 00:24:03,960 --> 00:24:06,199 Speaker 1: this on a daily basis, so that they can incorporate 436 00:24:06,240 --> 00:24:10,680 Speaker 1: that into their small little world which is really industry focused. 437 00:24:11,200 --> 00:24:14,000 Speaker 1: So we've seen a number of hedge fund players the 438 00:24:14,040 --> 00:24:17,760 Speaker 1: past few years really struggle. Warren Buffett just came out 439 00:24:18,160 --> 00:24:23,439 Speaker 1: at the annual seen Berkshire shareholder meeting in response to 440 00:24:23,480 --> 00:24:26,679 Speaker 1: a question said to people, Hey, it's a lot of 441 00:24:26,760 --> 00:24:30,280 Speaker 1: underperformance and it's a lot of excess fees. Uh, he's 442 00:24:30,320 --> 00:24:33,640 Speaker 1: not a fan. Why have hedge funds been having so 443 00:24:33,720 --> 00:24:37,400 Speaker 1: much difficulty in the present environment. Well, I think it's 444 00:24:37,440 --> 00:24:41,040 Speaker 1: been policy related. And if you look at the excess 445 00:24:41,040 --> 00:24:44,920 Speaker 1: returns on a volatility adjusted basis for for the S 446 00:24:45,000 --> 00:24:48,880 Speaker 1: and P right the pure index um, they've been one 447 00:24:48,880 --> 00:24:51,639 Speaker 1: of the five best periods that we've had since the 448 00:24:51,800 --> 00:24:55,600 Speaker 1: nineteen twenties. It's a generational rally. People afford it the 449 00:24:55,600 --> 00:24:59,160 Speaker 1: whole way up two hundred plus percent over six years. 450 00:24:58,920 --> 00:25:03,000 Speaker 1: That's a monster. You're also putting people into these index 451 00:25:03,080 --> 00:25:06,639 Speaker 1: products where they're looking at these returns, right, and they're saying, again, 452 00:25:06,720 --> 00:25:09,560 Speaker 1: why should I pay active management forget hedge funds, but 453 00:25:09,600 --> 00:25:11,919 Speaker 1: just active management when I can buy an index product 454 00:25:12,000 --> 00:25:14,719 Speaker 1: for fifteen basis points and called today and I'm actually 455 00:25:14,720 --> 00:25:18,439 Speaker 1: outperforming most people. And that's fine, that happens, But that 456 00:25:18,560 --> 00:25:21,920 Speaker 1: also happened at the end of right. That also happened 457 00:25:22,160 --> 00:25:24,520 Speaker 1: at the end of two thousand and seven. And so 458 00:25:24,680 --> 00:25:27,680 Speaker 1: when we look at our metrics of how much fuels 459 00:25:27,680 --> 00:25:30,159 Speaker 1: in the tank, this actually isn't the point where you 460 00:25:30,200 --> 00:25:33,080 Speaker 1: want to start endorsing indexes. This is the point where 461 00:25:33,080 --> 00:25:36,800 Speaker 1: you want to start endorsing active management hedge funds to 462 00:25:36,920 --> 00:25:40,280 Speaker 1: look for an opportunity set um that will produce something 463 00:25:40,320 --> 00:25:42,719 Speaker 1: that's better than what we think is is the the 464 00:25:42,760 --> 00:25:46,400 Speaker 1: excess returns on a volatility adjusted basis going forward. So, 465 00:25:46,400 --> 00:25:49,200 Speaker 1: so you mentioned some of the signals that were coming 466 00:25:49,200 --> 00:25:52,080 Speaker 1: from the credit market and elsewhere in oh eight oh nine, 467 00:25:52,760 --> 00:25:56,600 Speaker 1: you know what did how did you analyze the financial crisis. 468 00:25:56,640 --> 00:26:00,480 Speaker 1: What really stood out from that period that you're unique 469 00:26:00,560 --> 00:26:05,360 Speaker 1: way of looking at markets UH was insightful. I think 470 00:26:05,359 --> 00:26:07,560 Speaker 1: there are two things. The first was, if you remember 471 00:26:07,640 --> 00:26:11,560 Speaker 1: the UH, the internal hedge fund of bear Sterns blew up, 472 00:26:11,640 --> 00:26:14,720 Speaker 1: and we were seeing that summer of oh seventh exactly, 473 00:26:14,720 --> 00:26:16,800 Speaker 1: we're seeing that stress in the credit markets and the 474 00:26:16,800 --> 00:26:20,320 Speaker 1: swap markets, particularly ahead of time, and UM, you know, 475 00:26:20,320 --> 00:26:22,200 Speaker 1: it just worked its way down from tens to five 476 00:26:22,200 --> 00:26:25,400 Speaker 1: statoos and and then sort of went away and said, well, 477 00:26:25,400 --> 00:26:27,800 Speaker 1: what that's weird, Like there's always some you know, something 478 00:26:27,800 --> 00:26:29,960 Speaker 1: goes kaboom here and then two weeks later we you know, 479 00:26:29,960 --> 00:26:33,399 Speaker 1: we yeah, right right, and then boom, you know, it 480 00:26:33,480 --> 00:26:37,720 Speaker 1: happens UM. And then you have the continued deterioration UM 481 00:26:37,760 --> 00:26:40,760 Speaker 1: in these in these financials on the way down. So 482 00:26:41,000 --> 00:26:43,879 Speaker 1: you know, talking about big top formations and the things 483 00:26:43,960 --> 00:26:46,800 Speaker 1: that you know, sort of traditional technical analysis looks at 484 00:26:47,080 --> 00:26:51,040 Speaker 1: those were in place in a lot of these financials. UH. 485 00:26:51,080 --> 00:26:53,080 Speaker 1: In the in the mid part of two thousand and 486 00:26:53,080 --> 00:26:55,960 Speaker 1: seven and obviously extending into two thousand and eight, UM, 487 00:26:56,000 --> 00:26:57,919 Speaker 1: you had what was considered at the time the whale 488 00:26:58,119 --> 00:27:01,760 Speaker 1: of of bear Stern we rallied off of that into 489 00:27:01,760 --> 00:27:03,760 Speaker 1: the summer of oh eight, and then just you know, 490 00:27:03,960 --> 00:27:06,639 Speaker 1: with this lethargy started to roll over again, which was 491 00:27:06,720 --> 00:27:09,359 Speaker 1: the moment that you know, not all is well and 492 00:27:09,400 --> 00:27:11,280 Speaker 1: then there may be some other fish to come up 493 00:27:11,520 --> 00:27:14,560 Speaker 1: to the surface here as well. I recall August oh eight, 494 00:27:14,640 --> 00:27:17,440 Speaker 1: and you could just smell something was coming. It was. 495 00:27:17,560 --> 00:27:20,119 Speaker 1: It was one of those things where, gee, this just 496 00:27:20,560 --> 00:27:23,760 Speaker 1: I know that you're an evidence based guy. I like 497 00:27:23,880 --> 00:27:25,720 Speaker 1: to think I'm an evidence based guy. But it was 498 00:27:25,760 --> 00:27:28,480 Speaker 1: one of those moments over the past twenty years where 499 00:27:28,520 --> 00:27:31,280 Speaker 1: you could say, see something wicked this way comes. You 500 00:27:31,320 --> 00:27:33,199 Speaker 1: couldn't put a finger on it, but you knew it 501 00:27:33,240 --> 00:27:36,560 Speaker 1: was comment. And remember intra bank lending rates were spiking, 502 00:27:36,680 --> 00:27:40,480 Speaker 1: the library ois spread was spiking, the euro basis swaps, 503 00:27:40,640 --> 00:27:42,600 Speaker 1: so there were a lot of things that just said 504 00:27:42,600 --> 00:27:45,960 Speaker 1: the mechanism was having trouble, that there was there was 505 00:27:46,080 --> 00:27:50,320 Speaker 1: distrust amongst counterparties. Uh. And that's actually a much different 506 00:27:50,359 --> 00:27:53,000 Speaker 1: scenario than we have today. While the European banks don't 507 00:27:53,040 --> 00:27:56,240 Speaker 1: look good to us, the internal mechanism of that that 508 00:27:56,320 --> 00:27:59,280 Speaker 1: counterparty risk is actually in pretty good shape. You don't 509 00:27:59,280 --> 00:28:01,400 Speaker 1: have the same and in the gears that you had 510 00:28:01,440 --> 00:28:03,359 Speaker 1: in O eight oh nine. Now this just seems to 511 00:28:03,359 --> 00:28:06,040 Speaker 1: be almost more I don't want to use the word systemic, 512 00:28:06,080 --> 00:28:09,520 Speaker 1: but more sort of generational in terms of what's happening 513 00:28:09,520 --> 00:28:12,320 Speaker 1: to banks that the you know, the banking business has 514 00:28:12,359 --> 00:28:15,000 Speaker 1: just become a bad business. It's a secular change that 515 00:28:15,200 --> 00:28:18,359 Speaker 1: some of its technology, some of it's the new generation 516 00:28:18,440 --> 00:28:21,439 Speaker 1: coming up that is distrustful. But it doesn't seem to 517 00:28:21,520 --> 00:28:25,600 Speaker 1: be the same set sector that it was ten years ago, right, right, 518 00:28:25,600 --> 00:28:27,440 Speaker 1: And we actually think that that's one of the reasons 519 00:28:27,440 --> 00:28:30,120 Speaker 1: why we we looked at the starting Rendmack. We think 520 00:28:30,119 --> 00:28:33,359 Speaker 1: that there's still opportunity for good research. Um, you know, 521 00:28:33,400 --> 00:28:35,400 Speaker 1: particularly if you're willing to invest in it. The big 522 00:28:35,440 --> 00:28:37,399 Speaker 1: banks just don't have that much interest in doing that here, 523 00:28:37,560 --> 00:28:41,120 Speaker 1: not willing to put money and effort into into the research. 524 00:28:41,160 --> 00:28:44,600 Speaker 1: You would think that that's a potential cash cow for them, 525 00:28:44,800 --> 00:28:47,480 Speaker 1: or has the industry changed so much that it no 526 00:28:47,600 --> 00:28:51,640 Speaker 1: longer is well you know, Look, research was forever a 527 00:28:51,720 --> 00:28:54,960 Speaker 1: byproduct of banking, right, and the settlement in early two 528 00:28:54,960 --> 00:28:58,040 Speaker 1: thousand sort of drove a wedge between the official link 529 00:28:58,120 --> 00:29:01,120 Speaker 1: between those two. So Ever, since then, research has always 530 00:29:01,200 --> 00:29:03,920 Speaker 1: been considered a cost center. Right, So there's been this 531 00:29:04,040 --> 00:29:07,840 Speaker 1: juniorization of research taking place where people are swapping out 532 00:29:07,880 --> 00:29:10,480 Speaker 1: senior analysts for junior analysts just to have the coverage 533 00:29:10,720 --> 00:29:12,600 Speaker 1: helps the bank, but they don't have to pay for it. 534 00:29:13,120 --> 00:29:14,840 Speaker 1: You know, look, we we we still believe in good 535 00:29:14,880 --> 00:29:17,640 Speaker 1: old fashioned research and think that there's a premium to 536 00:29:17,640 --> 00:29:19,320 Speaker 1: be had for that. And you know, our business is 537 00:29:19,320 --> 00:29:22,040 Speaker 1: proving that that's true. Had a conversation with someone who 538 00:29:22,080 --> 00:29:26,360 Speaker 1: talked about how middle market and merchant banking has been 539 00:29:26,360 --> 00:29:29,920 Speaker 1: abandoned by the large banks if they've moved upstream, and 540 00:29:29,960 --> 00:29:33,800 Speaker 1: these guys are screaming for any sort of coverage uh, 541 00:29:34,400 --> 00:29:37,520 Speaker 1: transactional bankers and and there's a dearth there. I wonder 542 00:29:37,520 --> 00:29:41,320 Speaker 1: how much of an opportunity exists for either boutique or 543 00:29:41,920 --> 00:29:45,560 Speaker 1: purpose specific research shops like your own that can help 544 00:29:45,640 --> 00:29:48,040 Speaker 1: fill in the void. But we certainly hope. So so 545 00:29:48,120 --> 00:29:50,440 Speaker 1: let's talk a little bit about I. I where you've 546 00:29:50,480 --> 00:29:53,280 Speaker 1: been ranked twelve years running? Is that right? I think 547 00:29:53,320 --> 00:29:59,520 Speaker 1: that's right. That's an incredible track record tool mass to 548 00:29:59,720 --> 00:30:02,080 Speaker 1: what do you And for people who may not be 549 00:30:02,120 --> 00:30:07,680 Speaker 1: familiar with institutional investor, people, UH vote and they actually 550 00:30:07,760 --> 00:30:11,680 Speaker 1: vote based to some degree on their assets under management 551 00:30:11,760 --> 00:30:16,440 Speaker 1: and the commissions they spend. And they specifically say this 552 00:30:16,480 --> 00:30:19,200 Speaker 1: is our favorite economists. That what's been ed Hyman for 553 00:30:19,240 --> 00:30:22,200 Speaker 1: thirty five years running, the joke being he's actually not 554 00:30:22,200 --> 00:30:25,920 Speaker 1: an economist. Um, just play one on TV and you've 555 00:30:25,920 --> 00:30:30,320 Speaker 1: been numbered one for twelve years running as a macro 556 00:30:30,360 --> 00:30:33,640 Speaker 1: analysts and eleven years as a technolonalyst. Is that right? 557 00:30:33,200 --> 00:30:36,040 Speaker 1: That that's quite a track record to what do you 558 00:30:37,040 --> 00:30:41,240 Speaker 1: to blame or credit that? Yeah? I guess what we 559 00:30:41,320 --> 00:30:43,560 Speaker 1: try to do is we try to be as intellectually 560 00:30:43,600 --> 00:30:47,040 Speaker 1: honest as we possibly can. Um. We are very very 561 00:30:47,040 --> 00:30:50,360 Speaker 1: committed to making people money. UM. That is I mean 562 00:30:50,400 --> 00:30:54,000 Speaker 1: that is job one as we see it, UM. And uh, 563 00:30:54,080 --> 00:30:55,959 Speaker 1: I think you know the other important part of it 564 00:30:56,040 --> 00:30:58,320 Speaker 1: is we we try to quantify the process. We try 565 00:30:58,320 --> 00:31:02,000 Speaker 1: to demystify the technical process. And so you know, if 566 00:31:02,080 --> 00:31:05,240 Speaker 1: you don't have a lot of technical experience, UM, we 567 00:31:05,280 --> 00:31:07,920 Speaker 1: don't try to use the jargon e words. We try 568 00:31:07,920 --> 00:31:11,040 Speaker 1: to say, hey, here's you know, here are the probabilities 569 00:31:11,120 --> 00:31:14,160 Speaker 1: of this taking place based on these these certain factors 570 00:31:14,240 --> 00:31:16,080 Speaker 1: of which they are technical. And so I think a 571 00:31:16,080 --> 00:31:19,160 Speaker 1: lot of that has to do with the quantification, the 572 00:31:19,200 --> 00:31:22,400 Speaker 1: demystification of the of the process. So I went out 573 00:31:22,400 --> 00:31:24,680 Speaker 1: on Twitter over the weekend and said, hey, I'm interviewing 574 00:31:24,760 --> 00:31:27,920 Speaker 1: Jeff degraph. Any questions and a few interesting things popped 575 00:31:28,000 --> 00:31:32,040 Speaker 1: up from from some technicians on Twitter. One of the 576 00:31:32,080 --> 00:31:35,560 Speaker 1: ones I liked was, how do you, as an analyst 577 00:31:35,720 --> 00:31:39,280 Speaker 1: put a new and intriguing lens on the macro review 578 00:31:39,400 --> 00:31:43,160 Speaker 1: when so much of it is is will trod uh Land, 579 00:31:43,280 --> 00:31:46,120 Speaker 1: So many people have have our covering macro. How do 580 00:31:46,160 --> 00:31:48,760 Speaker 1: you keep it fresh and interesting and valuable. Yeah, well, 581 00:31:48,840 --> 00:31:51,040 Speaker 1: we we rely on our database, and we rely on 582 00:31:51,600 --> 00:31:55,680 Speaker 1: our computer programmers, and um, we rely on the uh 583 00:31:55,840 --> 00:31:59,000 Speaker 1: quantification of the data. Um. I mean, I'll give you 584 00:31:59,040 --> 00:32:02,120 Speaker 1: a great example. We you know, our single stock database 585 00:32:02,240 --> 00:32:04,240 Speaker 1: goes back to the existence of the SMP, back to 586 00:32:04,280 --> 00:32:06,959 Speaker 1: the early nineteen sixties. So when we go through and 587 00:32:07,000 --> 00:32:09,800 Speaker 1: look out, hey, do do breakouts work? Do breakdowns work? 588 00:32:09,840 --> 00:32:11,880 Speaker 1: How does this, you know, play itself out? We're not 589 00:32:11,920 --> 00:32:14,360 Speaker 1: talking about the next or last ten years or fifteen years. 590 00:32:14,400 --> 00:32:17,000 Speaker 1: We're really talking about, you know, over longer than my 591 00:32:17,080 --> 00:32:20,320 Speaker 1: lifespan so far. Um, you know, the the beginning of 592 00:32:20,360 --> 00:32:23,800 Speaker 1: the SMP some fifty five plus years and so, Um, 593 00:32:23,840 --> 00:32:25,680 Speaker 1: you know, I think that's one of the things that 594 00:32:25,680 --> 00:32:28,560 Speaker 1: that differentiates us and puts a different spin on things, 595 00:32:28,640 --> 00:32:31,320 Speaker 1: is that when you get the work from us, you've 596 00:32:31,360 --> 00:32:34,080 Speaker 1: got the totality of work, and you know, we'll lay 597 00:32:34,080 --> 00:32:36,200 Speaker 1: it out and say, hey, this works or this doesn't work, 598 00:32:36,320 --> 00:32:39,960 Speaker 1: or this works, but only in these conditions, and um, 599 00:32:40,000 --> 00:32:42,560 Speaker 1: you know, not many people are doing that. We've been 600 00:32:42,600 --> 00:32:46,400 Speaker 1: speaking with Jeff DeGraf of ren Mack. Uh. Jeff, where 601 00:32:46,440 --> 00:32:48,200 Speaker 1: can people find your work if they want to read 602 00:32:48,240 --> 00:32:51,760 Speaker 1: more about what you guys do? Our website ww dot 603 00:32:51,760 --> 00:32:55,280 Speaker 1: ren mac dot com. If you enjoy this conversation, be 604 00:32:55,320 --> 00:32:58,360 Speaker 1: sure and check out our podcast extras, where we keep 605 00:32:58,400 --> 00:33:03,240 Speaker 1: the tape rolling and continue chatting about all things market related. Uh, 606 00:33:03,360 --> 00:33:06,360 Speaker 1: be sure and check out all of our previous conversations. 607 00:33:06,400 --> 00:33:10,959 Speaker 1: You can find them on Apple iTunes, SoundCloud and on 608 00:33:11,000 --> 00:33:14,720 Speaker 1: Bloomberg dot com. Check out my daily column on Bloomberg 609 00:33:14,800 --> 00:33:18,440 Speaker 1: View dot com or follow me on Twitter at rit Halts. 610 00:33:18,560 --> 00:33:21,880 Speaker 1: I'm Barry Hults. You've been listening to Masters and Business 611 00:33:21,880 --> 00:33:25,480 Speaker 1: on Bloomberg Radio. Are you looking to take your business 612 00:33:25,480 --> 00:33:29,000 Speaker 1: to the next level? The accounting, tax and advisory professionals 613 00:33:29,000 --> 00:33:32,800 Speaker 1: from Cone Resnick can guide you. Cone Resnick delivers industry 614 00:33:32,800 --> 00:33:36,880 Speaker 1: expertise and forward thinking perspective that can help turn business 615 00:33:36,920 --> 00:33:43,160 Speaker 1: possibilities into business opportunities. Look ahead, gain insight, imagine more. 616 00:33:43,760 --> 00:33:46,440 Speaker 1: Is your business ready to break through? Learn more at 617 00:33:46,480 --> 00:33:53,280 Speaker 1: cone resnick dot com Slash Breakthrough cone Resnick Accounting, Tax Advisory. 618 00:33:53,440 --> 00:33:57,240 Speaker 1: Welcome to the podcast portion of our conversation, Jeff, thank 619 00:33:57,240 --> 00:33:58,920 Speaker 1: you so much for doing this. Now I get to 620 00:33:59,440 --> 00:34:03,440 Speaker 1: take off my headphones. I normally have these little headphones 621 00:34:03,480 --> 00:34:07,040 Speaker 1: that are very unobtrusive, but um, I wasn't in the 622 00:34:07,080 --> 00:34:10,520 Speaker 1: office Friday. I forgot to bring them in, so I'm 623 00:34:10,560 --> 00:34:13,080 Speaker 1: a little bit of a mess today. Um, really, thank 624 00:34:13,120 --> 00:34:15,160 Speaker 1: you so much for doing this. I have a few 625 00:34:15,160 --> 00:34:19,480 Speaker 1: people who are serious uh technicians. I think J. C. 626 00:34:19,680 --> 00:34:22,640 Speaker 1: Perett's how do you speak at an m T A 627 00:34:22,960 --> 00:34:25,720 Speaker 1: event might have been been here. He was like, dude, 628 00:34:25,840 --> 00:34:27,839 Speaker 1: so exciting to listen to Jeff. I'm like, all right, 629 00:34:27,840 --> 00:34:29,960 Speaker 1: give me a couple of questions. So some of those 630 00:34:30,040 --> 00:34:35,040 Speaker 1: questions were his, Um, you studied finance in college. Did 631 00:34:35,120 --> 00:34:37,680 Speaker 1: you know from day one you wanted to go right 632 00:34:37,719 --> 00:34:40,880 Speaker 1: into uh, right onto Wall Street? Yeah? Yeah, it was. 633 00:34:41,560 --> 00:34:45,480 Speaker 1: It was pretty easy. I like the I mean look, 634 00:34:45,480 --> 00:34:48,359 Speaker 1: I was trying to get out of Michigan so at 635 00:34:48,360 --> 00:34:53,560 Speaker 1: a kalamazoo kalamazoo. Um. But you know, I liked the 636 00:34:54,120 --> 00:34:57,920 Speaker 1: intellectual challenge. I like the lifestyle. I remember the first interview. 637 00:34:57,960 --> 00:35:00,759 Speaker 1: I was in Chicago looking at an opportunity and the 638 00:35:00,760 --> 00:35:04,879 Speaker 1: first interview, Um, the guy said, Uh, you'll never meet 639 00:35:05,120 --> 00:35:09,680 Speaker 1: an industry where there's the funniest and smartest people at 640 00:35:09,680 --> 00:35:13,120 Speaker 1: the same time. That's interesting. I said, sign me up. 641 00:35:13,560 --> 00:35:16,680 Speaker 1: You're right. So I enjoyed that. That that's really interesting. 642 00:35:16,719 --> 00:35:19,600 Speaker 1: There are a number of hilarious people in this industry. 643 00:35:19,760 --> 00:35:23,239 Speaker 1: Most people are not familiar with them. Um, but they're 644 00:35:23,239 --> 00:35:26,040 Speaker 1: out there and they definitely have a uh, there's some 645 00:35:26,040 --> 00:35:30,360 Speaker 1: sense of games. My my partner, uh, Josh Brown. People 646 00:35:30,360 --> 00:35:34,400 Speaker 1: don't realize this guy is hilarious, and people simply have 647 00:35:34,480 --> 00:35:37,000 Speaker 1: no idea how funny is although I think on Twitter 648 00:35:37,040 --> 00:35:40,279 Speaker 1: people have finally, uh finally figured that out. So you 649 00:35:40,320 --> 00:35:42,600 Speaker 1: go straight to Wall Street. You were Merrill Lynch in 650 00:35:42,600 --> 00:35:45,120 Speaker 1: the early days, is that right? Yea early days, and 651 00:35:45,160 --> 00:35:50,320 Speaker 1: then I moved over to Lehman Brothers under Steve Schaubin, 652 00:35:50,560 --> 00:35:53,000 Speaker 1: who had been at Meryl. So I knew Steve from 653 00:35:53,160 --> 00:35:57,480 Speaker 1: my Merril days. Uh started out doing international work at 654 00:35:57,560 --> 00:36:00,600 Speaker 1: Lehman Brothers and then moved into the hot seat in 655 00:36:00,600 --> 00:36:04,880 Speaker 1: in two thousand there as chief chief technician at Lehman. 656 00:36:04,960 --> 00:36:08,319 Speaker 1: So what were the golden days of Lehman Brothers? Like, Oh, 657 00:36:08,360 --> 00:36:13,120 Speaker 1: it was you know, I was too young to know better. Um, yeah, 658 00:36:13,360 --> 00:36:18,560 Speaker 1: I mean the eight to two thousand was just unbelievable. 659 00:36:19,280 --> 00:36:21,759 Speaker 1: It was it was. It was so much fun. It 660 00:36:21,840 --> 00:36:24,040 Speaker 1: was so fun to come into the to the office. 661 00:36:24,400 --> 00:36:29,879 Speaker 1: Lehman Brothers had a great culture. Um. So that was yeah, yeah, yeah, 662 00:36:29,920 --> 00:36:31,759 Speaker 1: I mean it was just it was and it was 663 00:36:31,880 --> 00:36:34,560 Speaker 1: the little train who thought they could right and so 664 00:36:34,760 --> 00:36:37,440 Speaker 1: just people were you know, hungry, and uh, it was 665 00:36:37,520 --> 00:36:39,640 Speaker 1: it was just it was fun. We were all climbing 666 00:36:39,640 --> 00:36:42,319 Speaker 1: in the right direction. Um, little train. There were the 667 00:36:42,360 --> 00:36:47,279 Speaker 1: fourth fourth largest investment bank. They dominated mortgage underwriting. They 668 00:36:47,320 --> 00:36:50,200 Speaker 1: were a substantial force for a long time. But remember 669 00:36:50,200 --> 00:36:53,080 Speaker 1: that wasn't a big deal until the mid offs, right, 670 00:36:53,120 --> 00:36:56,040 Speaker 1: so nobody realized until a little there were there were 671 00:36:56,040 --> 00:36:58,319 Speaker 1: early signs that there were issues there. Oh two oh 672 00:36:58,360 --> 00:37:02,480 Speaker 1: three things just got talk about looking at at data. 673 00:37:02,719 --> 00:37:06,440 Speaker 1: One of my favorite charts has always been UM meeting 674 00:37:06,480 --> 00:37:09,719 Speaker 1: income to Meetian home price. And I was looking at 675 00:37:09,719 --> 00:37:12,040 Speaker 1: this long before the collapse, and you could see you 676 00:37:12,080 --> 00:37:15,359 Speaker 1: were three standard deviations away from the norm. So either 677 00:37:15,440 --> 00:37:17,600 Speaker 1: everybody's going to get a raise or something bad is 678 00:37:17,640 --> 00:37:21,840 Speaker 1: going to happen. It was pretty much one or the other. Um. 679 00:37:22,440 --> 00:37:26,120 Speaker 1: Did you ever spend much time under Dick fold And 680 00:37:26,120 --> 00:37:27,960 Speaker 1: and meet meet him, work with him or was he 681 00:37:28,080 --> 00:37:29,719 Speaker 1: off in the corner office? I mean I meant him 682 00:37:29,719 --> 00:37:32,359 Speaker 1: a few times and it wasn't the big place. There wasn't. Yeah, 683 00:37:32,360 --> 00:37:37,279 Speaker 1: there wasn't daily interaction. Tell us about the research process there? 684 00:37:37,400 --> 00:37:40,520 Speaker 1: How How was that was pretty much traditional Wall Street 685 00:37:40,640 --> 00:37:44,160 Speaker 1: research at at Lehman, Yeah it was, but it was 686 00:37:44,360 --> 00:37:48,640 Speaker 1: you know, they were good, hungry young analysts. Um my 687 00:37:48,760 --> 00:37:54,000 Speaker 1: president now Steve hash who's president of of Ren mack Um, 688 00:37:54,160 --> 00:37:58,239 Speaker 1: actually ran the research department there. Um, we invested in 689 00:37:58,360 --> 00:38:00,680 Speaker 1: up in commerce. I mean we just believe in you know, 690 00:38:00,840 --> 00:38:05,440 Speaker 1: good smart young thinkers. And uh is another one was 691 00:38:05,440 --> 00:38:09,080 Speaker 1: was that Meryl Lordly and you brought him along as well? Absolutely, 692 00:38:09,120 --> 00:38:10,919 Speaker 1: So that's you know, that's how we think about the world. 693 00:38:10,960 --> 00:38:13,839 Speaker 1: Where where's the rest of your team from? Oh, it's 694 00:38:13,880 --> 00:38:16,000 Speaker 1: all over the map. Uh Some I s I sales 695 00:38:16,040 --> 00:38:18,040 Speaker 1: people a lot of people that have been just from 696 00:38:18,040 --> 00:38:21,600 Speaker 1: different parts of the of the business. Um, yeah, all 697 00:38:21,640 --> 00:38:25,640 Speaker 1: all different walks of life. So what's the plan for 698 00:38:26,440 --> 00:38:30,280 Speaker 1: a relatively you know, you're five years old just about 699 00:38:30,400 --> 00:38:34,680 Speaker 1: is that right? Relatively young, fast growing company. How do 700 00:38:34,719 --> 00:38:37,440 Speaker 1: you see this playing at for someone who's not yet fifty? 701 00:38:38,160 --> 00:38:41,160 Speaker 1: What do you want to do with this company? Uh? Look, 702 00:38:41,200 --> 00:38:44,839 Speaker 1: I'm I'm a big believer in the research process and 703 00:38:44,920 --> 00:38:47,520 Speaker 1: while others are sort of moving away from it, you know, 704 00:38:47,640 --> 00:38:50,320 Speaker 1: call it straw hats in January. I think that there's 705 00:38:50,440 --> 00:38:53,560 Speaker 1: opportunity there for the right people. It's not just plug 706 00:38:53,600 --> 00:38:55,080 Speaker 1: and play and you know, hope for the best. I 707 00:38:55,120 --> 00:38:56,480 Speaker 1: think you have to get the right people in there. 708 00:38:56,719 --> 00:38:58,560 Speaker 1: But there's still I mean, we see it in the business. 709 00:38:58,600 --> 00:39:04,160 Speaker 1: There's still a demand and for good, um, thoughtful analysts, right, 710 00:39:04,239 --> 00:39:07,680 Speaker 1: not just people that do stock research, but people that 711 00:39:08,200 --> 00:39:11,440 Speaker 1: think differently, do the hard work, roll up their sleeves, 712 00:39:11,480 --> 00:39:15,000 Speaker 1: you know, understand the company. There's there's there's interest there. Now, 713 00:39:15,280 --> 00:39:17,080 Speaker 1: what we're what we want to do and make sure 714 00:39:17,080 --> 00:39:19,480 Speaker 1: that we do with this is that it ties into 715 00:39:19,520 --> 00:39:23,360 Speaker 1: the macro play, right, So it's not just covering semiconductors, 716 00:39:23,400 --> 00:39:27,000 Speaker 1: but the semiconductors from a broader standpoint, and how and 717 00:39:27,080 --> 00:39:30,160 Speaker 1: what that means for the macro world. You know, there's 718 00:39:30,280 --> 00:39:33,640 Speaker 1: there's a thesis kicking around that following the early two 719 00:39:33,680 --> 00:39:37,280 Speaker 1: thousand analysts settlement with the New York State Attorney General. 720 00:39:37,880 --> 00:39:41,440 Speaker 1: Part of the settlement was a mandate that large banks 721 00:39:41,520 --> 00:39:45,680 Speaker 1: funds independent third party research, and you and that that 722 00:39:45,719 --> 00:39:48,680 Speaker 1: mandate has now ended. So you had this huge boom 723 00:39:48,719 --> 00:39:53,440 Speaker 1: throughout the aughts of independent research, some of which was 724 00:39:53,480 --> 00:39:56,680 Speaker 1: pretty good, some of which was of dubious value, but hey, 725 00:39:56,719 --> 00:39:58,520 Speaker 1: there was a mandate and we had money to spend, 726 00:39:59,000 --> 00:40:01,920 Speaker 1: go spend it. That has run its course, and that 727 00:40:02,000 --> 00:40:05,640 Speaker 1: seems to be at least in part behind some of 728 00:40:05,680 --> 00:40:10,680 Speaker 1: the shakeout that's happened in the research space. But what's 729 00:40:10,800 --> 00:40:14,520 Speaker 1: left are the companies that people are sending research dollars to, 730 00:40:15,040 --> 00:40:17,920 Speaker 1: whether they have to or not. They're the companies they 731 00:40:18,160 --> 00:40:20,960 Speaker 1: find value at and want to buy purchase their research 732 00:40:21,480 --> 00:40:23,560 Speaker 1: U I s I. There's a run of them that 733 00:40:24,080 --> 00:40:26,160 Speaker 1: have have been around for a while and are likely 734 00:40:26,200 --> 00:40:30,080 Speaker 1: to continue being around. Which is a long winded way 735 00:40:30,200 --> 00:40:32,560 Speaker 1: to get to the question of how do you see 736 00:40:32,600 --> 00:40:36,920 Speaker 1: the rest of the shakeout in research playing out. I mean, 737 00:40:36,920 --> 00:40:39,040 Speaker 1: it's a it's a great question. I think you're gonna 738 00:40:39,160 --> 00:40:46,359 Speaker 1: end up with um with the traditional banks again moving 739 00:40:46,400 --> 00:40:50,200 Speaker 1: towards that juniorization and meaning they'll they'll swap out a 740 00:40:50,280 --> 00:40:53,680 Speaker 1: high paid senior analyst with a junior guy without a 741 00:40:53,680 --> 00:40:56,680 Speaker 1: lot of experience but doesn't demand a big check, and 742 00:40:56,760 --> 00:40:59,880 Speaker 1: so they still have coverage. But you know, it's not 743 00:41:00,640 --> 00:41:04,440 Speaker 1: it's not. Uh. I'm trying to think of a classic 744 00:41:04,560 --> 00:41:08,040 Speaker 1: example of an analyst who who was the axe on 745 00:41:08,040 --> 00:41:11,040 Speaker 1: a particular stock or in a particular sector. But Rick 746 00:41:11,120 --> 00:41:14,960 Speaker 1: Sherlan's on on Microsoft or Charlie Wolf on Apple. They're 747 00:41:15,000 --> 00:41:18,480 Speaker 1: handful of guys who knew it better than anybody. That 748 00:41:18,560 --> 00:41:20,520 Speaker 1: era seems to be coming to an end. Yeah, I 749 00:41:20,880 --> 00:41:23,080 Speaker 1: think so for the big banks, but there's still that 750 00:41:23,120 --> 00:41:26,360 Speaker 1: opportunity set for the independence right now, a number of 751 00:41:26,400 --> 00:41:29,960 Speaker 1: firms forget the macro space that that that we focus on. 752 00:41:30,080 --> 00:41:32,239 Speaker 1: But um, you've got it for media, You've got it 753 00:41:32,239 --> 00:41:35,360 Speaker 1: for industrials, you you've had it for financials. So you know, 754 00:41:35,400 --> 00:41:39,000 Speaker 1: even these silos, Um, Dana Telsey came out of Bear Sterns. 755 00:41:39,120 --> 00:41:45,480 Speaker 1: She's tag right on housing, Dana is on retail. So 756 00:41:45,640 --> 00:41:48,520 Speaker 1: people who have an expertise in the space that becomes 757 00:41:48,560 --> 00:41:51,480 Speaker 1: their area. That's right, That's right, that's that's kind of 758 00:41:51,800 --> 00:41:55,279 Speaker 1: that's kind of fascinating that that's we didn't really see 759 00:41:55,280 --> 00:41:58,560 Speaker 1: that twenty or so years ago, or did we UM 760 00:41:59,760 --> 00:42:02,040 Speaker 1: my letter writers and things. But I think there's there's 761 00:42:02,040 --> 00:42:06,399 Speaker 1: a few things there. One is that the the execution business, right, 762 00:42:06,440 --> 00:42:09,000 Speaker 1: having a broker dealing the execution business through technology has 763 00:42:09,000 --> 00:42:12,799 Speaker 1: gotten much simpler. Right, So this whole best execution I 764 00:42:12,800 --> 00:42:16,200 Speaker 1: mean Ren Mack, little old Renmac can provide UM the 765 00:42:16,239 --> 00:42:20,520 Speaker 1: best execution because we we basically use UM. The other 766 00:42:20,560 --> 00:42:22,920 Speaker 1: big banks al goes, right, so we we come in 767 00:42:23,000 --> 00:42:26,560 Speaker 1: and and and and uh sort of you know, from 768 00:42:26,600 --> 00:42:30,320 Speaker 1: a from a from a darker perspective from the outside, 769 00:42:30,320 --> 00:42:32,600 Speaker 1: people don't know exactly who's trading what, but you know, 770 00:42:32,680 --> 00:42:36,759 Speaker 1: we know from our desk, the you know. The The 771 00:42:36,800 --> 00:42:40,880 Speaker 1: other part of that is the the technology has allowed 772 00:42:40,920 --> 00:42:45,440 Speaker 1: distribution UM to be a lot cheaper than it was. 773 00:42:46,360 --> 00:42:48,959 Speaker 1: I mean, I remember when I started UM. We would 774 00:42:48,960 --> 00:42:52,440 Speaker 1: send faxes, you know, and it was priced per sheet, 775 00:42:52,840 --> 00:42:56,200 Speaker 1: per per recipient, right, So I mean there was a 776 00:42:56,239 --> 00:42:58,040 Speaker 1: there was a half a million dollars. I'm serious, there 777 00:42:58,080 --> 00:43:01,040 Speaker 1: was a half a million dollar cost and distributing our 778 00:43:01,120 --> 00:43:04,280 Speaker 1: research because we had to pay the long distance fee 779 00:43:04,560 --> 00:43:09,160 Speaker 1: and the facts fees. And you know, once the proliferation 780 00:43:09,160 --> 00:43:12,840 Speaker 1: of email came about, writing a program to just convert 781 00:43:12,880 --> 00:43:16,040 Speaker 1: that to a PDF and sending it out was simple, 782 00:43:16,160 --> 00:43:19,160 Speaker 1: so facts as you're really talking late eighties, early nineties. 783 00:43:19,200 --> 00:43:22,040 Speaker 1: By the mid nineties email was starting to pick up 784 00:43:22,040 --> 00:43:25,000 Speaker 1: a bit. It was but to have research done, you 785 00:43:25,000 --> 00:43:27,880 Speaker 1: know in a way that um, you know we're sending 786 00:43:27,920 --> 00:43:31,319 Speaker 1: big PDFs over That's exactly right, that's exactly right. That 787 00:43:31,400 --> 00:43:34,920 Speaker 1: was a bandwidth issue which wasn't solved bill after global 788 00:43:34,960 --> 00:43:38,800 Speaker 1: crossing in Metromedia, fiber collapsed and left all this dark 789 00:43:38,840 --> 00:43:41,719 Speaker 1: fibers that are so expensive to build free and or 790 00:43:41,760 --> 00:43:44,520 Speaker 1: at least cheap for everybody else to pick up on 791 00:43:44,520 --> 00:43:48,439 Speaker 1: on their bones. Except supply will create demand. And well 792 00:43:48,480 --> 00:43:52,360 Speaker 1: that's the story of every major technology boom is after 793 00:43:52,400 --> 00:43:55,440 Speaker 1: the bus, you have all this in expensive infrastructure. So 794 00:43:55,560 --> 00:43:58,960 Speaker 1: that leads to the obvious question, which you alluded to previously, 795 00:43:59,160 --> 00:44:05,760 Speaker 1: how has tech anology change the way you do business? Well? Uh, 796 00:44:06,000 --> 00:44:09,000 Speaker 1: doing business or doing analysis? I think there are two 797 00:44:09,040 --> 00:44:12,040 Speaker 1: different things, right, Um, you know, look, business has done 798 00:44:12,320 --> 00:44:14,239 Speaker 1: you know, in the same in the same way. I mean, 799 00:44:14,280 --> 00:44:17,239 Speaker 1: obviously it's relationships and you're you know, you understand what 800 00:44:17,239 --> 00:44:19,719 Speaker 1: the clients are looking for. And UM, I mean I 801 00:44:19,760 --> 00:44:22,600 Speaker 1: don't think that that will ever go aware certainly shouldn't UM. 802 00:44:22,640 --> 00:44:25,839 Speaker 1: In terms of the analysis, UM. You know, I think 803 00:44:25,920 --> 00:44:29,960 Speaker 1: one of the problems that you end up with is UM. 804 00:44:30,000 --> 00:44:33,120 Speaker 1: You know, you give people the opportunity to sort of 805 00:44:33,160 --> 00:44:35,759 Speaker 1: do things, and they think they can do it right, 806 00:44:35,840 --> 00:44:39,160 Speaker 1: and they don't have the background or the understanding, UM 807 00:44:39,200 --> 00:44:42,319 Speaker 1: to fully take advantage of what some of the technology 808 00:44:42,360 --> 00:44:45,400 Speaker 1: can do. UM. And so for instance, let me interrupt 809 00:44:45,440 --> 00:44:49,120 Speaker 1: you there. So in the mid to late nineties and 810 00:44:49,120 --> 00:44:52,080 Speaker 1: early two thousands, you could get all manner of charts 811 00:44:52,160 --> 00:44:57,759 Speaker 1: for free everywhere online, right, and everyone fancied themselves a technician. 812 00:44:58,400 --> 00:45:05,680 Speaker 1: Most were not. Right. So is that democratization by technology? UM? 813 00:45:05,800 --> 00:45:08,839 Speaker 1: Is that a problem that people actually think they could 814 00:45:08,840 --> 00:45:11,920 Speaker 1: do things when there's a handful of technicians who came 815 00:45:11,960 --> 00:45:14,160 Speaker 1: out of that era who are really good and a 816 00:45:14,280 --> 00:45:17,440 Speaker 1: number of people who you know, they they think they're technicians, 817 00:45:17,520 --> 00:45:22,000 Speaker 1: but they're just you know, exhibiting confirmation biased I have this. 818 00:45:22,080 --> 00:45:24,120 Speaker 1: Let me go find a chart that I own this, 819 00:45:24,400 --> 00:45:27,160 Speaker 1: let me find something that that confirms my prior position. 820 00:45:27,360 --> 00:45:28,640 Speaker 1: I think, I think, but I think that happens with 821 00:45:28,680 --> 00:45:30,839 Speaker 1: almost anything that's out there, right, I mean, I think 822 00:45:30,880 --> 00:45:33,960 Speaker 1: I can retile my bathroom. I can't retie my bathroom, right, 823 00:45:34,000 --> 00:45:35,879 Speaker 1: I mean that's there are YouTube videos that will show 824 00:45:35,920 --> 00:45:37,040 Speaker 1: you how to do it, but it's still not going 825 00:45:37,080 --> 00:45:38,359 Speaker 1: to look as good as if I pay the guy 826 00:45:38,400 --> 00:45:40,560 Speaker 1: to do it, right, And that's why you hire a problem, 827 00:45:40,680 --> 00:45:42,680 Speaker 1: right exactly. So it's the you know, it's really the 828 00:45:42,719 --> 00:45:46,160 Speaker 1: same thing in any in any business, and uh um, 829 00:45:46,200 --> 00:45:48,680 Speaker 1: you know, we we find we find similar you know, 830 00:45:48,719 --> 00:45:52,680 Speaker 1: similar situations. But you know what we're doing which is 831 00:45:52,719 --> 00:45:55,880 Speaker 1: so unique is again we're quantifying that process. So instead 832 00:45:55,880 --> 00:45:58,319 Speaker 1: of drawing a trend line or um, you know, saying 833 00:45:58,360 --> 00:46:02,920 Speaker 1: it's overbater over sold, we contextualize that and we show 834 00:46:03,440 --> 00:46:05,800 Speaker 1: you know, what that really means in terms of the 835 00:46:06,200 --> 00:46:08,480 Speaker 1: history and whether or not it's valuable. And that's what 836 00:46:09,120 --> 00:46:10,960 Speaker 1: you know, that's what the amateurs and frankly a lot 837 00:46:10,960 --> 00:46:13,160 Speaker 1: of the pros don't even do. And so um, that's 838 00:46:13,200 --> 00:46:17,200 Speaker 1: one thing that really sets us apart. So you're using technology, 839 00:46:18,120 --> 00:46:22,040 Speaker 1: um in a very significant way. You've built this database. 840 00:46:22,560 --> 00:46:24,920 Speaker 1: What did you use for sources to put that together? 841 00:46:24,960 --> 00:46:27,560 Speaker 1: How long did it take to clean up that database 842 00:46:27,600 --> 00:46:29,359 Speaker 1: to get it to do what you want? How many 843 00:46:29,360 --> 00:46:32,480 Speaker 1: different components are you tracking in that? Tell us a 844 00:46:32,520 --> 00:46:35,560 Speaker 1: little bit about the secret sauce um as much as 845 00:46:35,600 --> 00:46:38,640 Speaker 1: you're willing to write keeping it secret um. Look, it's 846 00:46:38,719 --> 00:46:41,640 Speaker 1: you know, we use great we use we use CRISP data, 847 00:46:41,760 --> 00:46:46,319 Speaker 1: CRISP price data um. And we've got that again going back, 848 00:46:46,960 --> 00:46:49,040 Speaker 1: you know, s and P ninety going back to the 849 00:46:49,080 --> 00:46:52,160 Speaker 1: mid the mid nineteen twenties and for people don't understand 850 00:46:52,239 --> 00:46:54,399 Speaker 1: Chris but comes out of the University of Chicago, if 851 00:46:54,640 --> 00:46:59,840 Speaker 1: memory serves, and really a deep and fairly clean database, 852 00:47:00,239 --> 00:47:04,160 Speaker 1: uh of of market information. I think it goes all 853 00:47:04,160 --> 00:47:07,000 Speaker 1: the way back to the twenties. Something thinking of the 854 00:47:07,120 --> 00:47:09,880 Speaker 1: SMP ninety back to the twenties, which is, whenever you 855 00:47:09,920 --> 00:47:15,080 Speaker 1: see the SMP five hundred quoted beyond it's it's the predecessor, 856 00:47:15,520 --> 00:47:18,600 Speaker 1: which was in the SNP five. Even the SMP five 857 00:47:18,680 --> 00:47:22,200 Speaker 1: hundred was in the SMP fire two. Sometime in the latent, 858 00:47:22,360 --> 00:47:26,840 Speaker 1: I'm trying to remember when they changed the waiting sector 859 00:47:27,680 --> 00:47:30,200 Speaker 1: that all went away in the eighties. Sometimes ye so 860 00:47:30,440 --> 00:47:32,880 Speaker 1: changes and and has certainly look at that, and we 861 00:47:32,880 --> 00:47:36,080 Speaker 1: look at the various waitings over time. UM. We use 862 00:47:36,080 --> 00:47:39,919 Speaker 1: option data UM for a big part of our sentiment work. UM. 863 00:47:39,960 --> 00:47:44,960 Speaker 1: We incorporate fundamental data UM from various various sources UM. 864 00:47:45,040 --> 00:47:48,279 Speaker 1: And then UM we also, which I think uniquely, we 865 00:47:48,320 --> 00:47:52,560 Speaker 1: bring in economic data so that we can see what 866 00:47:52,800 --> 00:47:56,080 Speaker 1: that looks like in relation to these other things that 867 00:47:56,120 --> 00:47:59,360 Speaker 1: we're looking at. Technically four stocks, Right, So does p 868 00:47:59,560 --> 00:48:03,160 Speaker 1: M I work cure does the UM you know, do 869 00:48:03,239 --> 00:48:07,239 Speaker 1: the UH the H four data from the FED? Does 870 00:48:07,360 --> 00:48:11,200 Speaker 1: that have any influence? And so UM always looking, always adding, 871 00:48:11,239 --> 00:48:14,799 Speaker 1: always building, and uh CFTC data we use that as well. So, 872 00:48:14,800 --> 00:48:18,840 Speaker 1: so let's talk about economic data. UM. What is actually 873 00:48:18,880 --> 00:48:22,360 Speaker 1: going on in terms of I'm not looking for a 874 00:48:22,400 --> 00:48:27,040 Speaker 1: forecast to the future historically, what is the correlation between 875 00:48:27,239 --> 00:48:29,840 Speaker 1: changes in the overall economy, either for the better or 876 00:48:29,920 --> 00:48:35,640 Speaker 1: wars and markets. I've always looked at markets leading economic data, 877 00:48:35,719 --> 00:48:39,839 Speaker 1: although not by as much as some people imagine. Well 878 00:48:39,880 --> 00:48:43,200 Speaker 1: that's true. I mean, look, economic data is certainly UM 879 00:48:43,640 --> 00:48:47,040 Speaker 1: less noisy believe it or not, UM, but it also lags. 880 00:48:47,080 --> 00:48:49,400 Speaker 1: I mean, there's a reason they are leading indicators coincidental 881 00:48:49,440 --> 00:48:53,560 Speaker 1: indicators and lagging indicators right and meaning leading the cycle 882 00:48:53,800 --> 00:48:56,720 Speaker 1: or lagging the cycle. And look, the reason that business 883 00:48:56,719 --> 00:48:58,360 Speaker 1: is so hard. If you can just look at economic 884 00:48:58,440 --> 00:49:01,840 Speaker 1: data and forecast the US in p correctly, it'd be easy. 885 00:49:02,520 --> 00:49:04,799 Speaker 1: It just it doesn't happen. Everybody's going to be rich, 886 00:49:04,960 --> 00:49:08,000 Speaker 1: right exactly. So you know what we look at is 887 00:49:08,440 --> 00:49:11,479 Speaker 1: historically the market has sniffed things out. Now, it's gotten 888 00:49:11,480 --> 00:49:13,719 Speaker 1: it wrong before. But as I like to say that, 889 00:49:13,800 --> 00:49:15,839 Speaker 1: you know, the market will fib but it won't be 890 00:49:16,480 --> 00:49:19,040 Speaker 1: a chronic liar, right, And so you know, it's a 891 00:49:19,120 --> 00:49:21,040 Speaker 1: great line. You have to be careful of that. But 892 00:49:21,280 --> 00:49:23,719 Speaker 1: the reality is that the market gets it right, and 893 00:49:23,760 --> 00:49:26,200 Speaker 1: the market gets it right better than the p m 894 00:49:26,239 --> 00:49:28,200 Speaker 1: I gets it right. It gets it right better than 895 00:49:28,239 --> 00:49:30,759 Speaker 1: the employment data gets it right, etcetera. So that's why 896 00:49:30,800 --> 00:49:33,759 Speaker 1: it's really important from our standpoint to you know, put 897 00:49:33,760 --> 00:49:36,480 Speaker 1: your ear on the track, understand or try to understand 898 00:49:36,560 --> 00:49:39,719 Speaker 1: you know what's coming down then the pipe. Um. But 899 00:49:40,080 --> 00:49:42,520 Speaker 1: you know, from our advantage point, it's a very difficult 900 00:49:42,800 --> 00:49:45,359 Speaker 1: and challenging environment trying to do that with just economic data. 901 00:49:46,040 --> 00:49:51,000 Speaker 1: And that's probably why so many people, uh always go 902 00:49:51,080 --> 00:49:54,600 Speaker 1: to the quote by Samuelson, which is, marketing indices have 903 00:49:54,760 --> 00:49:59,800 Speaker 1: forecast nine of the past four recessions markets will swing wildly. 904 00:50:00,000 --> 00:50:02,360 Speaker 1: They're noisy, but they're going to do a better job 905 00:50:02,520 --> 00:50:06,760 Speaker 1: than the average person scratching their chin and saying, here's 906 00:50:06,800 --> 00:50:09,640 Speaker 1: here's what this this month's non farm payer all means. Yeah. 907 00:50:09,680 --> 00:50:11,600 Speaker 1: But and let's you know, let's take it to the 908 00:50:11,600 --> 00:50:14,440 Speaker 1: next step to what do I really care about the 909 00:50:14,520 --> 00:50:19,120 Speaker 1: GDP number? If I'm invested in the SMP, I'm not right, 910 00:50:19,120 --> 00:50:21,600 Speaker 1: I'm not I'm not invested in I don't have a 911 00:50:21,680 --> 00:50:24,680 Speaker 1: GDP swap, right. In other words, GDP up over three 912 00:50:24,719 --> 00:50:26,560 Speaker 1: percent and I make money that has nothing to do 913 00:50:26,600 --> 00:50:28,160 Speaker 1: with that. I want to know what's going to happen 914 00:50:28,200 --> 00:50:30,799 Speaker 1: to the SMP, right, And so you know, maybe we're 915 00:50:30,840 --> 00:50:33,640 Speaker 1: not in recession, but you still have a correction or 916 00:50:33,680 --> 00:50:36,759 Speaker 1: bear market in the STP. That's important, right, And so 917 00:50:37,040 --> 00:50:41,360 Speaker 1: from our standpoint, you know, the work on uh, getting 918 00:50:41,400 --> 00:50:45,400 Speaker 1: the economy right. I get it from the perspective of 919 00:50:45,600 --> 00:50:48,399 Speaker 1: the nation, and certainly I appreciate that. But from the 920 00:50:48,440 --> 00:50:51,799 Speaker 1: perspective of the investor, what I'm really trying to do 921 00:50:51,920 --> 00:50:54,279 Speaker 1: is get the SNP right. You know, and the what 922 00:50:54,400 --> 00:50:57,439 Speaker 1: I can tell you is getting the economy right has 923 00:50:57,680 --> 00:51:01,040 Speaker 1: very little to do with getting the S P right historically. 924 00:51:01,160 --> 00:51:04,400 Speaker 1: That that is a theme that I've heard from guests 925 00:51:04,440 --> 00:51:07,399 Speaker 1: on the show for the past couple of years is well, 926 00:51:07,440 --> 00:51:10,239 Speaker 1: the economy is interesting and the market is interesting, and 927 00:51:10,280 --> 00:51:12,799 Speaker 1: on occasion they seem to be insane, but most of 928 00:51:12,800 --> 00:51:15,480 Speaker 1: the time one goes one way and the other is 929 00:51:15,520 --> 00:51:18,960 Speaker 1: just off uh in its own path, and and trying 930 00:51:18,960 --> 00:51:21,279 Speaker 1: to use the economy to forecast the market is just 931 00:51:21,320 --> 00:51:23,960 Speaker 1: a fool's Errand it certainly seems that way. We want 932 00:51:23,960 --> 00:51:25,560 Speaker 1: to know what's going on, there's no doubt about it, 933 00:51:25,600 --> 00:51:28,840 Speaker 1: but to to draw the link between the economy and 934 00:51:28,920 --> 00:51:31,920 Speaker 1: saying that that that's gonna mandate the S and P 935 00:51:32,120 --> 00:51:36,000 Speaker 1: does X good luck. So before I go to my 936 00:51:36,080 --> 00:51:39,320 Speaker 1: favorite questions, I asked all my guests one last Twitter question. 937 00:51:39,400 --> 00:51:43,040 Speaker 1: Someone had asked, so, why not manage a fund? Why 938 00:51:43,040 --> 00:51:45,960 Speaker 1: not run money or put together e t F Y 939 00:51:46,040 --> 00:51:48,200 Speaker 1: be an analyst? So I do this question all the time. 940 00:51:48,200 --> 00:51:49,600 Speaker 1: That's one of the reasons why we started run Back, 941 00:51:49,600 --> 00:51:51,200 Speaker 1: to be honest with you. So we we have a 942 00:51:51,480 --> 00:51:56,560 Speaker 1: small albeit small um. We have a rend Mack Capital Um, 943 00:51:56,560 --> 00:51:59,640 Speaker 1: where we haven't actively raised money, we have a ongoing 944 00:51:59,680 --> 00:52:02,760 Speaker 1: stress of you that's in that mostly partner money right now. Um, 945 00:52:02,800 --> 00:52:07,359 Speaker 1: but that's that's definitely uh, you know stage Renmack two 946 00:52:07,440 --> 00:52:10,640 Speaker 1: point oh, that's in that. In that zone, there are 947 00:52:10,719 --> 00:52:13,839 Speaker 1: people who left big firms to launch their own research shop. 948 00:52:14,360 --> 00:52:17,640 Speaker 1: Rich Bernstein probably most notable, who's now running you know, 949 00:52:17,719 --> 00:52:21,560 Speaker 1: three or four billion dollars. There's there's definitely a path 950 00:52:21,640 --> 00:52:25,480 Speaker 1: to that. And I love the idea of having that 951 00:52:25,560 --> 00:52:28,279 Speaker 1: pile of money which generates revenue which then can be 952 00:52:28,280 --> 00:52:32,799 Speaker 1: plowed right back into making the research faster, sexy, or 953 00:52:32,840 --> 00:52:34,680 Speaker 1: more interesting. There's a lot of stuff you can do 954 00:52:34,760 --> 00:52:37,600 Speaker 1: when you have that much a u M with a 955 00:52:37,640 --> 00:52:39,600 Speaker 1: fee on it. It just lets you plout right back 956 00:52:39,600 --> 00:52:41,359 Speaker 1: into the business. And we want to be careful. I mean, 957 00:52:41,400 --> 00:52:43,719 Speaker 1: obviously we don't want to have conflicts there. But what 958 00:52:43,800 --> 00:52:46,400 Speaker 1: we do is, you know, we eat our own cooking. 959 00:52:46,680 --> 00:52:49,960 Speaker 1: And um, it's a quantitative process. We think about it 960 00:52:50,040 --> 00:52:52,840 Speaker 1: very quantitatively. It's not you know, hey, I like that 961 00:52:52,880 --> 00:52:55,560 Speaker 1: idea or that, it's it's what is the system spit out? 962 00:52:55,800 --> 00:52:58,320 Speaker 1: How does that overlay with these things? And then here's 963 00:52:58,440 --> 00:53:02,040 Speaker 1: how we're managing that portfolio. So the question that always 964 00:53:02,120 --> 00:53:05,960 Speaker 1: used to come up on the old UM research desks 965 00:53:06,120 --> 00:53:09,640 Speaker 1: was idea generation. Hey, what's what's the idea of generation? 966 00:53:09,719 --> 00:53:12,719 Speaker 1: Machine looked like, you guys don't really do that. It's 967 00:53:12,800 --> 00:53:16,440 Speaker 1: it's pretty much spitting out from that database. Well, it's 968 00:53:16,480 --> 00:53:19,080 Speaker 1: idea generation is just not you know, it's just not 969 00:53:19,400 --> 00:53:21,799 Speaker 1: a noodling over it every single day and saying, hey, 970 00:53:21,840 --> 00:53:23,440 Speaker 1: you know, what are the what are this? What's this? 971 00:53:23,480 --> 00:53:26,960 Speaker 1: And that um it's looking at it now. It's important though, 972 00:53:27,000 --> 00:53:30,240 Speaker 1: is that you know, we we understand through our research 973 00:53:30,320 --> 00:53:34,680 Speaker 1: that there are points where UM, certain things will perform 974 00:53:34,840 --> 00:53:39,840 Speaker 1: better UM in certain environments. Right, So a great example, UM, 975 00:53:39,880 --> 00:53:42,440 Speaker 1: you know, shorts right here in this environment are not 976 00:53:42,560 --> 00:53:44,960 Speaker 1: performing well, and we actually track that on a daily 977 00:53:44,960 --> 00:53:46,920 Speaker 1: basis to see, hey, if you were to to be 978 00:53:46,960 --> 00:53:49,160 Speaker 1: a seller of a breakdown, what's the performance. I mean, 979 00:53:49,160 --> 00:53:52,279 Speaker 1: they're just they're just getting steamrolled. And that's actually an 980 00:53:52,280 --> 00:53:55,640 Speaker 1: important becomes an important market indicator. But it also gives 981 00:53:55,719 --> 00:53:58,680 Speaker 1: us some idea that the breakdowns in this environment have 982 00:53:58,760 --> 00:54:02,320 Speaker 1: actually been a source of alpha UM, that breakouts are working, 983 00:54:02,400 --> 00:54:05,879 Speaker 1: that overbought conditions aren't a place to be selling UM, 984 00:54:05,920 --> 00:54:08,960 Speaker 1: they're actually a reflection of the momentum. So our idea 985 00:54:09,040 --> 00:54:14,480 Speaker 1: generation is a combination of using some traditional and nontraditional 986 00:54:14,520 --> 00:54:18,640 Speaker 1: techniques frankly, but then overlaying those and understanding how those 987 00:54:18,719 --> 00:54:21,279 Speaker 1: work throughout history and where we should be at any 988 00:54:21,280 --> 00:54:23,719 Speaker 1: given point in time. So, I know, I say, the 989 00:54:23,800 --> 00:54:28,239 Speaker 1: show's UH tagline is no forecast, no stock picks. So 990 00:54:28,280 --> 00:54:32,400 Speaker 1: I'm gonna ask this question slightly differently. I've been hearing 991 00:54:32,480 --> 00:54:36,520 Speaker 1: for I don't know, five six years, this rally is overboard, 992 00:54:36,640 --> 00:54:40,200 Speaker 1: it's artificial, it's fed induced. It's gonna end any day now, 993 00:54:40,480 --> 00:54:44,359 Speaker 1: or so I've heard every day for the past five years. 994 00:54:44,400 --> 00:54:47,600 Speaker 1: So where do you see us within the overall market cycle? 995 00:54:47,920 --> 00:54:52,440 Speaker 1: And where does this end? Or can this just continue 996 00:54:52,440 --> 00:54:56,319 Speaker 1: into such point as something comes along to stop it? Well, look, 997 00:54:56,360 --> 00:55:00,520 Speaker 1: I I view the world as this ever expanding UH 998 00:55:00,719 --> 00:55:04,680 Speaker 1: sample of the population, right, So you know the reality 999 00:55:04,760 --> 00:55:06,520 Speaker 1: is as well, we have really good data as good 1000 00:55:06,560 --> 00:55:08,560 Speaker 1: or data is as good as anyone else is. You know, 1001 00:55:08,800 --> 00:55:11,279 Speaker 1: the markets and rough rice back in the you know, 1002 00:55:11,440 --> 00:55:14,919 Speaker 1: the Chinese in the fifteenth century. I don't have that data. 1003 00:55:15,000 --> 00:55:17,640 Speaker 1: So maybe something happened that was completely different that you know, 1004 00:55:17,680 --> 00:55:20,040 Speaker 1: would skew other things. But what I can tell you 1005 00:55:20,080 --> 00:55:22,839 Speaker 1: is if you look over the last nine years UH, 1006 00:55:22,880 --> 00:55:25,000 Speaker 1: and you look at risk adjusted returns for the SMP 1007 00:55:25,400 --> 00:55:28,480 Speaker 1: versus the risk free rate, and you measure those, we 1008 00:55:28,560 --> 00:55:32,080 Speaker 1: are in UM, you know, the ninety percentile of what 1009 00:55:32,120 --> 00:55:34,960 Speaker 1: you'd expect for excess returns. If you look at those 1010 00:55:35,000 --> 00:55:38,160 Speaker 1: other periods of time, the forward returns are not something 1011 00:55:38,200 --> 00:55:39,960 Speaker 1: that you want to write home about. In fact, you'd 1012 00:55:39,960 --> 00:55:42,799 Speaker 1: want to steer yourself towards that that active management, not 1013 00:55:43,320 --> 00:55:47,400 Speaker 1: towards passive management. So I, you know, I view this 1014 00:55:47,560 --> 00:55:52,359 Speaker 1: as the fuel in the tank is relatively slight UM. 1015 00:55:52,560 --> 00:55:56,759 Speaker 1: But within that context, it's important to recognize that momentum 1016 00:55:56,800 --> 00:56:00,640 Speaker 1: has been good. The trends for equities are positive UM. 1017 00:56:00,719 --> 00:56:02,760 Speaker 1: And so while I think the path at least resistance 1018 00:56:02,760 --> 00:56:04,759 Speaker 1: in the near term is higher by near term I 1019 00:56:04,760 --> 00:56:08,240 Speaker 1: mean three to six, maybe twelve months UM, the amount 1020 00:56:08,239 --> 00:56:10,799 Speaker 1: of fuel we have to really propel it at this 1021 00:56:10,880 --> 00:56:14,400 Speaker 1: stage still seems to be relatively lacking. So this is 1022 00:56:14,440 --> 00:56:17,920 Speaker 1: not in our view. This turn was not some historic 1023 00:56:18,040 --> 00:56:21,480 Speaker 1: low that's going to provide UM, you know, very good 1024 00:56:21,760 --> 00:56:24,960 Speaker 1: UH risk adjusted returns going forward. I think it's enough 1025 00:56:25,000 --> 00:56:28,239 Speaker 1: to probably catch people off sides get people to reposition 1026 00:56:28,719 --> 00:56:31,560 Speaker 1: and then you know, come back and uh and give 1027 00:56:31,600 --> 00:56:34,640 Speaker 1: us a tougher environment. In two thousand and seventeen, what 1028 00:56:34,840 --> 00:56:40,080 Speaker 1: is additional fuel that could keep the momentum going because 1029 00:56:40,120 --> 00:56:44,520 Speaker 1: because it's we've seen profits sort of top out and 1030 00:56:44,560 --> 00:56:48,440 Speaker 1: start to roll over a bit. Um. Energy prices never 1031 00:56:48,640 --> 00:56:52,640 Speaker 1: low energy prices never really provided the too consumers that 1032 00:56:52,719 --> 00:56:55,520 Speaker 1: they normally do. In theory, it help them pay down 1033 00:56:55,560 --> 00:56:58,080 Speaker 1: some debt, a little cash in their pocket. But we 1034 00:56:58,080 --> 00:57:01,440 Speaker 1: didn't see a surgeon retail spending UM. And we have 1035 00:57:01,480 --> 00:57:04,960 Speaker 1: an election coming up in November. What could change the 1036 00:57:05,080 --> 00:57:08,120 Speaker 1: dynamic that says, hey, this could go on for years, 1037 00:57:08,200 --> 00:57:10,840 Speaker 1: not quarters, no great question. It's usually something in the 1038 00:57:10,880 --> 00:57:14,320 Speaker 1: credit cycle, right so it could be QUEI four. I 1039 00:57:14,360 --> 00:57:16,640 Speaker 1: don't think that's likely, but that's you know, let's let's 1040 00:57:16,680 --> 00:57:20,520 Speaker 1: keep our our minds open. It could be fiscal stimulus UM, 1041 00:57:20,720 --> 00:57:24,840 Speaker 1: which both sides have been talking about fairly uh consistently. 1042 00:57:25,400 --> 00:57:27,640 Speaker 1: Right now, we have the credit cycle is flat that 1043 00:57:27,760 --> 00:57:31,800 Speaker 1: you know if you look at global central bank balance sheets, UM. 1044 00:57:32,040 --> 00:57:34,560 Speaker 1: So we don't concern ourselves as much with the rates 1045 00:57:34,680 --> 00:57:36,800 Speaker 1: as we do. What's happening to the composition of the 1046 00:57:36,800 --> 00:57:39,600 Speaker 1: balance sheet, right, So an expanding balance sheet is obviously 1047 00:57:39,640 --> 00:57:44,600 Speaker 1: credit creation. A contracting balance sheet is credit deterioration or destruction. UM. 1048 00:57:44,760 --> 00:57:48,000 Speaker 1: Global balance sheets as we measure them are about flat 1049 00:57:48,080 --> 00:57:50,120 Speaker 1: year over year, and that's actually one of the lowest 1050 00:57:50,200 --> 00:57:53,200 Speaker 1: levels that we've seen in the last fifteen years. So 1051 00:57:53,360 --> 00:57:57,480 Speaker 1: you know, changing that dynamic would be important. The Chinese 1052 00:57:57,560 --> 00:58:01,200 Speaker 1: with the FX reserves stabilizing would be one part. UM. 1053 00:58:01,440 --> 00:58:05,840 Speaker 1: Sovereign wealth funds not pulling UH their their wealth out 1054 00:58:05,880 --> 00:58:09,160 Speaker 1: of of the U S asset markets UM, that would 1055 00:58:09,160 --> 00:58:11,480 Speaker 1: be another point. UM. So you know, there's a lot 1056 00:58:11,520 --> 00:58:13,560 Speaker 1: of different dynamics that take place with this, but credit 1057 00:58:13,680 --> 00:58:15,919 Speaker 1: is usually at the forefront of it, and i'd say 1058 00:58:15,920 --> 00:58:17,960 Speaker 1: non financial leverage that we as we look at it, 1059 00:58:18,000 --> 00:58:20,320 Speaker 1: which is flattened here. If we can start to see 1060 00:58:20,320 --> 00:58:23,040 Speaker 1: that uptick would be would be helpful as well. Last 1061 00:58:23,320 --> 00:58:27,959 Speaker 1: politically related question, UM, we keep hearing and again both 1062 00:58:27,960 --> 00:58:32,520 Speaker 1: sides talking about a tax holiday to repatriate some of 1063 00:58:32,600 --> 00:58:36,040 Speaker 1: the tens of trillions of corporate dollars that are overseas. 1064 00:58:36,600 --> 00:58:39,400 Speaker 1: UM does at least two trillion just out of the 1065 00:58:39,480 --> 00:58:43,560 Speaker 1: SNP five and I've seen estimates as high as ten trillion. 1066 00:58:44,320 --> 00:58:47,959 Speaker 1: If whoever gets elected in November passes something like that. 1067 00:58:48,400 --> 00:58:50,720 Speaker 1: Is that a temporary blip. Does that have the potential 1068 00:58:50,840 --> 00:58:54,360 Speaker 1: to stimulate the economy here? Does that hurt Europe and 1069 00:58:54,440 --> 00:58:57,360 Speaker 1: Asia where the money might be sitting. What's the impact 1070 00:58:57,400 --> 00:59:02,240 Speaker 1: of that big repatriation assuming it actually happens. Yeah, I mean, look, 1071 00:59:02,280 --> 00:59:06,360 Speaker 1: when you when you withdraw UM money from one system 1072 00:59:06,480 --> 00:59:09,280 Speaker 1: to another, there usually as a transfer there, right, And 1073 00:59:09,320 --> 00:59:12,800 Speaker 1: so you're talking about tighter credit conditions and looser credit conditions. 1074 00:59:13,240 --> 00:59:15,600 Speaker 1: And by the way, the thinking behind this just to 1075 00:59:15,880 --> 00:59:19,360 Speaker 1: you mentioned infrastructure before the deal is the Democrats want 1076 00:59:19,360 --> 00:59:23,840 Speaker 1: to big infrastructure bill, bridges, roads, electrical grid, etcetera. The 1077 00:59:23,840 --> 00:59:28,080 Speaker 1: Republicans want to change the corporate tax rate and or 1078 00:59:28,200 --> 00:59:31,240 Speaker 1: repatriate the overseas dollar, but temporary tax holiday, maybe you 1079 00:59:31,280 --> 00:59:33,880 Speaker 1: take tax at at six percent, five percent, something like that. 1080 00:59:34,120 --> 00:59:36,960 Speaker 1: So if there's a deal struck that that's where I 1081 00:59:37,040 --> 00:59:39,200 Speaker 1: was leading from with that. I mean, that's you know, 1082 00:59:39,280 --> 00:59:41,000 Speaker 1: is that a positive? Is that a negative? Is it 1083 00:59:41,120 --> 00:59:44,400 Speaker 1: globally neutral viewed as a positive for the US? I 1084 00:59:44,400 --> 00:59:46,360 Speaker 1: mean this is not my area of expertise, but any means, 1085 00:59:46,360 --> 00:59:47,760 Speaker 1: but I would I would it as a positive for 1086 00:59:47,800 --> 00:59:50,800 Speaker 1: the US. UM and then the question is is how 1087 00:59:50,880 --> 00:59:53,560 Speaker 1: is that capital utilized? Right? Is it? You know, is 1088 00:59:53,560 --> 00:59:58,880 Speaker 1: it really going into property, plant, equipment, R and D spending? Look, 1089 00:59:58,920 --> 01:00:01,520 Speaker 1: I think the reality is the trajectory is the trajectory. 1090 01:00:01,520 --> 01:00:05,280 Speaker 1: I don't think of a boon. Uh if if companies 1091 01:00:05,320 --> 01:00:09,040 Speaker 1: thought that they could earn positive returns on projects, they 1092 01:00:09,080 --> 01:00:10,840 Speaker 1: do it. I mean, for God's sakes, interest rates are 1093 01:00:10,920 --> 01:00:12,800 Speaker 1: you know, next to nothing, So it's not it's not 1094 01:00:12,840 --> 01:00:14,480 Speaker 1: a huge hurdle here. You don't see a lot of 1095 01:00:14,480 --> 01:00:18,320 Speaker 1: CAPEX spending, although some people have have said that's misleading 1096 01:00:18,320 --> 01:00:20,760 Speaker 1: when you look at it as a percentage of GDP 1097 01:00:20,960 --> 01:00:24,400 Speaker 1: or as a percentage of other activity, it's actually at 1098 01:00:24,400 --> 01:00:26,320 Speaker 1: a fairly high rate. I think you'd probably go to 1099 01:00:26,400 --> 01:00:31,200 Speaker 1: corporate bybex really more so than than Capex. Really that 1100 01:00:31,320 --> 01:00:33,840 Speaker 1: that would be interesting. Let's in the last fifteen minutes 1101 01:00:33,920 --> 01:00:36,880 Speaker 1: or so, we have get to our standard questions. We 1102 01:00:36,880 --> 01:00:40,840 Speaker 1: we talked about what you did before UH Wall Street, 1103 01:00:40,880 --> 01:00:45,880 Speaker 1: which was college. Who are your early mentors Bob Ferrell, 1104 01:00:46,400 --> 01:00:49,400 Speaker 1: uh Steve Shoubin. Let's talk about Bob Farrell a little 1105 01:00:49,400 --> 01:00:52,520 Speaker 1: bit because Dave Rosenberg is a friend another guy who 1106 01:00:52,520 --> 01:00:54,960 Speaker 1: has him as a mentor. I've had heard his name 1107 01:00:55,000 --> 01:00:58,960 Speaker 1: come up from Ralph Akimpora has mentioned him. A number 1108 01:00:58,960 --> 01:01:01,720 Speaker 1: of people have mentioned, well he was the first. Remember 1109 01:01:01,720 --> 01:01:06,600 Speaker 1: he was the first one to actually um had a 1110 01:01:06,640 --> 01:01:12,080 Speaker 1: technical analysis department and Marylands right back in the fifties 1111 01:01:12,080 --> 01:01:15,920 Speaker 1: and sixties. Yeah. Um. And just a sweetheart of a 1112 01:01:15,920 --> 01:01:21,480 Speaker 1: guy and very intuitive, a great amount of experience and 1113 01:01:21,520 --> 01:01:24,480 Speaker 1: just understanding of the business. And what I really appreciated 1114 01:01:25,120 --> 01:01:28,360 Speaker 1: about Bob's perspective is he lived and you know, didn't 1115 01:01:28,360 --> 01:01:31,400 Speaker 1: grow up in but lived through um, you know, the 1116 01:01:31,440 --> 01:01:35,040 Speaker 1: tumultuous times of the late sixties, the seventies and the 1117 01:01:35,120 --> 01:01:39,560 Speaker 1: you know, I mean horrendous markets almost as bad as 1118 01:01:39,560 --> 01:01:43,360 Speaker 1: though I don't know people risk adjusted. Absolutely it was right, um, 1119 01:01:43,520 --> 01:01:47,080 Speaker 1: no doubt about it. So when you know, when you 1120 01:01:47,160 --> 01:01:49,960 Speaker 1: have somebody who's gone through that, there's a perspective that 1121 01:01:50,000 --> 01:01:52,040 Speaker 1: they bring. You know, I can read about it all 1122 01:01:52,080 --> 01:01:55,040 Speaker 1: I want, but when you're living it, it's completely different. Right. 1123 01:01:55,080 --> 01:01:58,640 Speaker 1: So this just a very unique perspective that um, you 1124 01:01:58,640 --> 01:02:01,800 Speaker 1: know that I really appreciated and and found found useful. 1125 01:02:02,080 --> 01:02:05,200 Speaker 1: Steve Schobin, who was started in the in the Mary 1126 01:02:05,280 --> 01:02:08,200 Speaker 1: Lynch Technical Analysis Department, then left for Lehman brothers in 1127 01:02:08,200 --> 01:02:10,800 Speaker 1: the mid nineties, who I eventually joined in the late 1128 01:02:10,880 --> 01:02:17,040 Speaker 1: nineties at Lehman. UM was equally as um as intuitive 1129 01:02:17,360 --> 01:02:20,200 Speaker 1: and Uh well he started a little later. I think 1130 01:02:20,200 --> 01:02:23,800 Speaker 1: he started in sixty eight. UM had a very very 1131 01:02:23,840 --> 01:02:27,720 Speaker 1: good perspective, and I worked more closely with Steve Um. 1132 01:02:28,120 --> 01:02:36,120 Speaker 1: His ability to um understand and really synthesized things qualitatively 1133 01:02:36,600 --> 01:02:40,960 Speaker 1: was unmatched from anybody I've worked with since. UM. He 1134 01:02:41,080 --> 01:02:44,280 Speaker 1: just had a very good intuition about the market. And 1135 01:02:44,640 --> 01:02:48,160 Speaker 1: I was far more quantitative than Steve, but his intuition. 1136 01:02:48,200 --> 01:02:51,280 Speaker 1: I certainly learned a lot from uh in Uh in 1137 01:02:51,360 --> 01:02:53,640 Speaker 1: my years working with him, and a great guy. So 1138 01:02:53,880 --> 01:02:58,240 Speaker 1: beyond Steve, if you're out there beyond beyond mentors, what 1139 01:02:58,320 --> 01:03:02,520 Speaker 1: other investors influenced your approach to the markets? Well, you know, 1140 01:03:02,560 --> 01:03:06,400 Speaker 1: without being specific about people, I think, what's what's interesting 1141 01:03:06,440 --> 01:03:10,000 Speaker 1: about the business, and you know, at whether it was 1142 01:03:10,080 --> 01:03:13,400 Speaker 1: at Meryl or Lehman or even at Rehnmac now UM, 1143 01:03:13,680 --> 01:03:17,520 Speaker 1: what I find is and very refreshing is it's the 1144 01:03:17,720 --> 01:03:23,800 Speaker 1: people that UM are very very successful, who are interested 1145 01:03:23,920 --> 01:03:26,720 Speaker 1: in our work. Right. In other words, it's not the 1146 01:03:26,760 --> 01:03:29,919 Speaker 1: hotshot m b A who you know learned the same 1147 01:03:29,960 --> 01:03:32,600 Speaker 1: thing that everybody does, that technical analysis is just a 1148 01:03:32,640 --> 01:03:35,160 Speaker 1: bunch of bunk. You know, their quote unquote smarter than 1149 01:03:35,160 --> 01:03:37,280 Speaker 1: the market, and they'll get it all figured out. It's 1150 01:03:37,320 --> 01:03:40,880 Speaker 1: the season professional with the scars and the battle wounds 1151 01:03:41,120 --> 01:03:44,800 Speaker 1: who are always interested in our perspective because they've seen 1152 01:03:44,840 --> 01:03:47,480 Speaker 1: it before, right, they understand that there's something more to 1153 01:03:47,560 --> 01:03:49,680 Speaker 1: the business. And you know, you can get into this 1154 01:03:49,720 --> 01:03:52,040 Speaker 1: debate between art and science, and I get it, and 1155 01:03:52,200 --> 01:03:55,040 Speaker 1: I do think that technical analysis probably relies too much 1156 01:03:55,080 --> 01:03:59,160 Speaker 1: on art, fundamental analysis relies probably too much on science. Um. 1157 01:03:59,680 --> 01:04:02,400 Speaker 1: We try to blend the two, right, taking the I 1158 01:04:02,480 --> 01:04:05,400 Speaker 1: understand there's something here, let's try to quantify it and 1159 01:04:05,600 --> 01:04:08,240 Speaker 1: do something around that. So um and look, even in 1160 01:04:08,280 --> 01:04:11,200 Speaker 1: fundamental analysis, there's an art to understanding where the kink 1161 01:04:11,280 --> 01:04:13,360 Speaker 1: in the hockey stick of growth is right, or what 1162 01:04:13,440 --> 01:04:15,760 Speaker 1: the difference between K and G in terms of the 1163 01:04:15,760 --> 01:04:18,160 Speaker 1: cost of capital and and the growth rate is. You know, 1164 01:04:18,240 --> 01:04:20,560 Speaker 1: so there's there's an art to everything that that's done. 1165 01:04:20,800 --> 01:04:22,680 Speaker 1: We just try to quantify it to the extent that 1166 01:04:22,720 --> 01:04:25,120 Speaker 1: we can. Um And so you know, when I look 1167 01:04:25,160 --> 01:04:28,520 Speaker 1: at the people that read our research and and that 1168 01:04:28,760 --> 01:04:31,280 Speaker 1: I'm good friends with in the business. Um, you know, 1169 01:04:31,320 --> 01:04:33,080 Speaker 1: there are people that I'm proud to have his clients. 1170 01:04:33,080 --> 01:04:35,640 Speaker 1: I mean, they're they're they're successful people. And I think 1171 01:04:35,880 --> 01:04:39,440 Speaker 1: you go back to the you know, to the Wizards 1172 01:04:39,440 --> 01:04:41,760 Speaker 1: of Wall Street books, and you know, I learned a 1173 01:04:41,800 --> 01:04:44,920 Speaker 1: lot from Richard Dennis and his Turtle system and just 1174 01:04:45,040 --> 01:04:47,520 Speaker 1: the way that they think about things right and stand 1175 01:04:48,160 --> 01:04:50,760 Speaker 1: people on it. It means it's quantitative and it's not 1176 01:04:50,880 --> 01:04:53,160 Speaker 1: purely in art. There has to be rules you can 1177 01:04:53,200 --> 01:04:55,160 Speaker 1: teach me. Yeah, And I think look, as as much 1178 01:04:55,160 --> 01:04:57,400 Speaker 1: as anything, what we try to do is we try 1179 01:04:57,440 --> 01:05:01,600 Speaker 1: to remain disciplined, right, And I think discipline is and 1180 01:05:02,040 --> 01:05:05,640 Speaker 1: people in the business understand that, but it's underrated amongst 1181 01:05:05,680 --> 01:05:08,320 Speaker 1: the investing public. I think, without question it's I think 1182 01:05:08,360 --> 01:05:11,440 Speaker 1: that I think it's underrated amongst the entire street. Is 1183 01:05:11,480 --> 01:05:15,440 Speaker 1: how how important and underutilized discipline is, right, And the 1184 01:05:15,800 --> 01:05:18,520 Speaker 1: problem being is that when you quantify it, you also 1185 01:05:18,600 --> 01:05:21,240 Speaker 1: quantify what your loss is going to be right, and 1186 01:05:21,320 --> 01:05:23,479 Speaker 1: so you know that you're not always going to be right, 1187 01:05:23,720 --> 01:05:25,480 Speaker 1: but you have to be willing to be wrong by 1188 01:05:25,520 --> 01:05:27,480 Speaker 1: this much. And most people say, I don't want to 1189 01:05:27,480 --> 01:05:29,520 Speaker 1: be wrong by this much right, And so instead of 1190 01:05:29,600 --> 01:05:31,240 Speaker 1: quantifying it. They'll just do it by the seat of 1191 01:05:31,280 --> 01:05:33,400 Speaker 1: their pants. So I can do it successfully, some can't. 1192 01:05:33,600 --> 01:05:36,480 Speaker 1: I'd rather quantify it and say, hey, here's where I am, 1193 01:05:36,560 --> 01:05:39,520 Speaker 1: here's my risk profile. Now what can I do to 1194 01:05:39,760 --> 01:05:42,560 Speaker 1: maybe further mitigate that, or how do you know, how 1195 01:05:42,600 --> 01:05:45,240 Speaker 1: can I position it so that I'm I'm willing to 1196 01:05:45,280 --> 01:05:48,200 Speaker 1: accept that and move on knowing that what I call 1197 01:05:48,360 --> 01:05:50,360 Speaker 1: terminal wealth is going to be far better than if 1198 01:05:50,400 --> 01:05:52,480 Speaker 1: I were to just index or something along those lines. 1199 01:05:52,760 --> 01:05:54,720 Speaker 1: The quote I read this week, and I don't remember where, 1200 01:05:54,760 --> 01:05:57,800 Speaker 1: what book or what publication I read this was we 1201 01:05:57,920 --> 01:06:01,880 Speaker 1: learned nothing from our winners. It's our losers that teach us. 1202 01:06:02,080 --> 01:06:05,880 Speaker 1: And there's those battle scars. You don't get those. The 1203 01:06:05,920 --> 01:06:08,320 Speaker 1: worst thing that can happen to a nubie investor is 1204 01:06:08,640 --> 01:06:10,920 Speaker 1: a winning streak. They learned nothing from it, and they 1205 01:06:10,920 --> 01:06:14,960 Speaker 1: start to think they're they're brilliant. You mentioned Turtle Traders 1206 01:06:15,120 --> 01:06:18,520 Speaker 1: and and market Wizards. That's the perfect transition to the 1207 01:06:18,560 --> 01:06:22,000 Speaker 1: next question. By the way, we've had Schwager on he's fantastic, 1208 01:06:22,320 --> 01:06:24,160 Speaker 1: and I don't know if you know Mike Koval's book 1209 01:06:24,560 --> 01:06:29,560 Speaker 1: Total Traders. He was really interesting. He's been entranced by 1210 01:06:29,720 --> 01:06:33,600 Speaker 1: Dennis's concept of let's raise them the way they raise 1211 01:06:34,360 --> 01:06:38,120 Speaker 1: turtles in these farms in Singapore which are used as 1212 01:06:38,160 --> 01:06:40,560 Speaker 1: a as a food source. If we can raise turtles, 1213 01:06:40,600 --> 01:06:42,960 Speaker 1: we can raise traders. And and let's so let's talk 1214 01:06:42,960 --> 01:06:45,880 Speaker 1: about some of your favorite books. The first book I 1215 01:06:45,920 --> 01:06:49,400 Speaker 1: read in when I got into the business was Market Wizards, 1216 01:06:49,440 --> 01:06:53,240 Speaker 1: and it was absolutely fascinating. You imply, um, you enjoyed 1217 01:06:53,280 --> 01:06:55,760 Speaker 1: the book as well. Yeah, at least two of them. 1218 01:06:55,760 --> 01:06:58,680 Speaker 1: I think there's three in order read to Market Wizards, 1219 01:06:58,680 --> 01:07:02,280 Speaker 1: New Market Wizards, and head Fun Wizards. Think yet, but 1220 01:07:02,680 --> 01:07:05,320 Speaker 1: so be it? Um, you know that that to me, 1221 01:07:05,360 --> 01:07:09,680 Speaker 1: I thought was sort of bringing theoretical to reality. Right, 1222 01:07:09,720 --> 01:07:12,440 Speaker 1: there's always the difference of you know, up on the chalkboard, 1223 01:07:12,480 --> 01:07:14,840 Speaker 1: it looks nice, but you know, in the trenches, how 1224 01:07:14,840 --> 01:07:16,720 Speaker 1: does this really play out? And that was you know, 1225 01:07:16,840 --> 01:07:19,200 Speaker 1: using both you had fundamental traders there, you had technical 1226 01:07:19,240 --> 01:07:22,240 Speaker 1: traders there get some that did a combination. Uh, and 1227 01:07:22,280 --> 01:07:24,720 Speaker 1: obviously all did it disciplined. By the way, what you 1228 01:07:24,760 --> 01:07:27,200 Speaker 1: mentioned is a theme that runs throughout the whids to 1229 01:07:27,560 --> 01:07:32,360 Speaker 1: every you absolutely have to have it without question. What 1230 01:07:32,360 --> 01:07:36,440 Speaker 1: what other books are standouts to you that either were influential, 1231 01:07:36,880 --> 01:07:40,720 Speaker 1: or just that you really enjoyed a great deal. I mean, 1232 01:07:40,760 --> 01:07:43,040 Speaker 1: this is probably a little bit more controversial, but I 1233 01:07:43,080 --> 01:07:48,520 Speaker 1: will say that i've i've certainly um internalized the thought 1234 01:07:48,560 --> 01:07:53,920 Speaker 1: process of the Austrian cycle of economics. UM. Not that 1235 01:07:53,960 --> 01:07:56,520 Speaker 1: it's always right, I wouldn't, I wouldn't think about it 1236 01:07:56,560 --> 01:07:59,720 Speaker 1: that way, but in terms of sort of grounding yourself 1237 01:07:59,760 --> 01:08:02,520 Speaker 1: and understanding that trees don't grow to the sky. You 1238 01:08:02,560 --> 01:08:04,439 Speaker 1: can't dig your way to China no matter how hard 1239 01:08:04,440 --> 01:08:08,080 Speaker 1: you try. I think it's just a good understanding not 1240 01:08:08,160 --> 01:08:11,560 Speaker 1: only of credit of money UH and the influence on 1241 01:08:11,600 --> 01:08:14,840 Speaker 1: the economy over time and the business cycle. No, no 1242 01:08:14,880 --> 01:08:17,960 Speaker 1: doubt about that. UM any other books before we move 1243 01:08:18,000 --> 01:08:21,439 Speaker 1: on to our two favorite questions, I think any book 1244 01:08:21,439 --> 01:08:26,480 Speaker 1: on market history is fantastic, just to again try to internalize, 1245 01:08:26,640 --> 01:08:29,720 Speaker 1: you know, and understand what Bob Ferrell knew from living it. 1246 01:08:30,560 --> 01:08:33,280 Speaker 1: The more you can understand the history of the markets, 1247 01:08:33,320 --> 01:08:36,200 Speaker 1: the more you'll find that things aren't aren't changing, they're 1248 01:08:36,200 --> 01:08:38,040 Speaker 1: staying the same. Give me a few I have a 1249 01:08:38,080 --> 01:08:40,040 Speaker 1: few favorites of my own, and the reminiscence of a 1250 01:08:40,080 --> 01:08:45,080 Speaker 1: stock operators classic the same around the same period that 1251 01:08:45,160 --> 01:08:47,760 Speaker 1: came out. You would appreciate this if you haven't read this. 1252 01:08:48,439 --> 01:08:51,479 Speaker 1: I'm fond of talking about Richard Wykoff's How I Trade 1253 01:08:51,479 --> 01:08:56,759 Speaker 1: Stocks and Bonds. If you swap out telephone wire for Internet, 1254 01:08:56,920 --> 01:09:00,000 Speaker 1: It's like it was written yesterday. Absolutely, it's amazing more 1255 01:09:00,000 --> 01:09:05,160 Speaker 1: and changed the question. I've recently started, um actually fondly 1256 01:09:05,720 --> 01:09:10,840 Speaker 1: reading the minutes from Federal Reserve meetings, really because the 1257 01:09:10,880 --> 01:09:15,320 Speaker 1: same thing right back, way back, way back to the thirties, right, 1258 01:09:15,479 --> 01:09:18,320 Speaker 1: no kidding, because you'll find that they're you know, we 1259 01:09:18,400 --> 01:09:20,640 Speaker 1: like to think that they're they're driving silly cars and 1260 01:09:20,680 --> 01:09:22,640 Speaker 1: wearing wool suits in the summer, and they don't have 1261 01:09:22,640 --> 01:09:25,800 Speaker 1: a clue. I mean, they're very thoughtful there as as 1262 01:09:25,840 --> 01:09:28,160 Speaker 1: of course they are, right. The Lords of Banking really 1263 01:09:28,160 --> 01:09:32,800 Speaker 1: makes that clear that book. Really, if you thought these 1264 01:09:32,840 --> 01:09:35,559 Speaker 1: are just a bunch of idiots flailing about, that will 1265 01:09:35,600 --> 01:09:38,280 Speaker 1: disabuse you of those notes. And and remember at the time, 1266 01:09:38,360 --> 01:09:41,559 Speaker 1: their technology that they had was superior to anything that 1267 01:09:41,600 --> 01:09:44,760 Speaker 1: they had thirty years prior. Right, So it's not like 1268 01:09:45,040 --> 01:09:47,559 Speaker 1: we're suddenly so much smarter because of all this stuff. 1269 01:09:47,680 --> 01:09:49,880 Speaker 1: It's just, you know, there are certain things that are 1270 01:09:49,920 --> 01:09:52,719 Speaker 1: just unknowable and and you find that in the business, 1271 01:09:52,800 --> 01:09:56,519 Speaker 1: So I think that's interesting. Um there's a good book 1272 01:09:56,600 --> 01:10:02,320 Speaker 1: called UMU, A Nation of Deadbeats, which which is a 1273 01:10:03,280 --> 01:10:05,640 Speaker 1: just a very good history. I'm not a fan of 1274 01:10:05,680 --> 01:10:08,840 Speaker 1: the title, but it's a very good history of the 1275 01:10:09,000 --> 01:10:14,720 Speaker 1: US economic cycles boom busts, and takes us through with 1276 01:10:14,760 --> 01:10:17,599 Speaker 1: a lot of interesting anecdotes about the you know, how 1277 01:10:17,640 --> 01:10:20,040 Speaker 1: the green bag became the green back, and and just 1278 01:10:20,160 --> 01:10:24,160 Speaker 1: you know, some interesting anecdotes about the US specifically. That 1279 01:10:24,240 --> 01:10:26,439 Speaker 1: title reminded me of a book I used for research 1280 01:10:26,520 --> 01:10:30,200 Speaker 1: some years ago about the nineteenth century banking in the 1281 01:10:30,240 --> 01:10:33,960 Speaker 1: United States called a Nation of counterfeiters, and all these 1282 01:10:33,960 --> 01:10:37,960 Speaker 1: banks would issue these notes wildcatting and eventually walk away 1283 01:10:38,000 --> 01:10:41,000 Speaker 1: from him. Eventually, that's why we ended up with a 1284 01:10:41,000 --> 01:10:44,120 Speaker 1: federal reserve. So our last two questions my favorite two 1285 01:10:44,200 --> 01:10:47,720 Speaker 1: questions I asked all of my guests. So a millennial 1286 01:10:47,920 --> 01:10:51,240 Speaker 1: or a recent college graduate comes to you and says, hey, Jeff, 1287 01:10:51,280 --> 01:10:55,200 Speaker 1: I'm thinking about going into finance. What sort of advice 1288 01:10:55,240 --> 01:10:58,040 Speaker 1: would you give them? Just get experience, get your feet wet, 1289 01:10:58,120 --> 01:11:00,759 Speaker 1: get your feet wet, get your feet wet. The second, 1290 01:11:00,920 --> 01:11:05,080 Speaker 1: and from from my perspective, UM I really don't hire 1291 01:11:05,080 --> 01:11:07,840 Speaker 1: people unless you're programmers. You have to have just a 1292 01:11:07,880 --> 01:11:11,160 Speaker 1: solid understanding of programming because that's really where the power is, 1293 01:11:11,320 --> 01:11:14,280 Speaker 1: you know. Um. So you know, if you're coming out 1294 01:11:14,360 --> 01:11:16,920 Speaker 1: and you're you're committed to the business and you want 1295 01:11:16,920 --> 01:11:19,040 Speaker 1: to show the commitment to the business as a you know, 1296 01:11:19,080 --> 01:11:22,640 Speaker 1: as a young fresh graduate, I'd say getting rolled in 1297 01:11:22,680 --> 01:11:24,959 Speaker 1: the c f A program as soon as you possibly 1298 01:11:24,960 --> 01:11:27,000 Speaker 1: can show that this is where you want to be. 1299 01:11:27,560 --> 01:11:31,240 Speaker 1: Obviously it's more specific than than an NBA program. Um. 1300 01:11:31,320 --> 01:11:35,679 Speaker 1: In fact of my my alma mater I um uh, 1301 01:11:35,720 --> 01:11:38,400 Speaker 1: you know, I really encouraged the students to to get 1302 01:11:38,439 --> 01:11:40,679 Speaker 1: their feet wet with the cf A program while they're 1303 01:11:40,680 --> 01:11:43,600 Speaker 1: in college and then you know, just gives them a 1304 01:11:43,720 --> 01:11:47,000 Speaker 1: leg up as they get out. Um to understand, um, 1305 01:11:47,040 --> 01:11:49,400 Speaker 1: you know to prospective employers that hey, I'm serious about 1306 01:11:49,400 --> 01:11:52,360 Speaker 1: this business and I've invested my resources and time to 1307 01:11:52,680 --> 01:11:57,040 Speaker 1: do this. Um. But programming history and just you know, commitment, 1308 01:11:57,200 --> 01:12:00,720 Speaker 1: get involved. And our final question, what is it that 1309 01:12:00,800 --> 01:12:03,880 Speaker 1: you know about investing today? You wish you knew twenty 1310 01:12:03,920 --> 01:12:06,639 Speaker 1: something years ago when you began. That's a great question, 1311 01:12:06,720 --> 01:12:10,600 Speaker 1: I think, um, instead of I knew about this, but 1312 01:12:10,640 --> 01:12:12,680 Speaker 1: how about the appreciation of this. I think it is 1313 01:12:12,720 --> 01:12:15,000 Speaker 1: probably a better word way to think about it is 1314 01:12:15,040 --> 01:12:20,479 Speaker 1: the absolute power of compound interest, right. I mean, you know, 1315 01:12:20,640 --> 01:12:22,360 Speaker 1: you can look at the tables, you can do all 1316 01:12:22,400 --> 01:12:25,519 Speaker 1: the forward valuation calculations you want and see how you 1317 01:12:25,520 --> 01:12:28,719 Speaker 1: can tune a thousand dollars into something you know, extraordinary. 1318 01:12:28,760 --> 01:12:33,000 Speaker 1: But the power of living for twenty years and seeing 1319 01:12:33,040 --> 01:12:37,680 Speaker 1: that work is astounding, and I think it's underappreciated by 1320 01:12:37,800 --> 01:12:42,639 Speaker 1: the masses. Humans have a hard time conceptualizing long periods 1321 01:12:42,640 --> 01:12:45,000 Speaker 1: of time. And I'm not talking eons and billions of 1322 01:12:45,080 --> 01:12:48,800 Speaker 1: years on an astronomical level, just your own lifetime. Hey, 1323 01:12:48,840 --> 01:12:51,200 Speaker 1: if I do this for thirty years, here's the net. 1324 01:12:51,840 --> 01:12:54,120 Speaker 1: My father in law was in town this weekend. He 1325 01:12:54,200 --> 01:12:58,000 Speaker 1: showed me a picture of his his Mustang that was 1326 01:12:58,040 --> 01:13:00,880 Speaker 1: brand new when he bought it in ninety five, and 1327 01:13:00,960 --> 01:13:02,519 Speaker 1: he said, I just saw it an eBay for a 1328 01:13:02,520 --> 01:13:05,840 Speaker 1: little under a hundred thousand dollars and so, I you know, 1329 01:13:05,920 --> 01:13:08,680 Speaker 1: I did the quick math on it, and uh, it 1330 01:13:08,760 --> 01:13:11,600 Speaker 1: worked out to about a seven and a half annualized 1331 01:13:11,680 --> 01:13:14,000 Speaker 1: rate of return. It would have done better in the market, 1332 01:13:14,040 --> 01:13:16,760 Speaker 1: just right. But you know, but now that it seem 1333 01:13:16,840 --> 01:13:19,479 Speaker 1: like a little better, but it seems like a big number, 1334 01:13:19,520 --> 01:13:21,640 Speaker 1: and you know that's the beauty of compounding. You just 1335 01:13:21,680 --> 01:13:25,919 Speaker 1: don't realize what, Hey, sixty five mustang, you're talking almost 1336 01:13:25,960 --> 01:13:29,080 Speaker 1: fifty years ago, more than fifty years ago. That that's 1337 01:13:29,400 --> 01:13:32,080 Speaker 1: a fascinating thing. Well, Jeff, thank you so much for 1338 01:13:32,080 --> 01:13:35,200 Speaker 1: doing this experisode. Generous with your time. I'm sure people, 1339 01:13:35,439 --> 01:13:38,880 Speaker 1: especially the technicians out there, are going to be fascinated 1340 01:13:38,920 --> 01:13:42,000 Speaker 1: by this. Uh. If you've enjoyed this conversation, be sure 1341 01:13:42,040 --> 01:13:43,640 Speaker 1: and look up an Inch or down an Inch on 1342 01:13:43,680 --> 01:13:46,840 Speaker 1: Apple iTunes and you can see the other ninety or 1343 01:13:46,960 --> 01:13:51,640 Speaker 1: so um conversations we've had with various notables in the 1344 01:13:51,680 --> 01:13:54,880 Speaker 1: financial industry. I would be remiss if I did not 1345 01:13:55,320 --> 01:14:00,759 Speaker 1: thank my booker and audio engineer, Taylor Riggs for helping 1346 01:14:00,800 --> 01:14:04,080 Speaker 1: to organize this. Uh. My head of research is Michael 1347 01:14:04,120 --> 01:14:07,280 Speaker 1: bat Nick, and Charlie Vollmer is our producer. You've been 1348 01:14:07,320 --> 01:14:11,719 Speaker 1: listening to Masters in Business on Bloomberg Radio look Ahead, 1349 01:14:12,080 --> 01:14:15,759 Speaker 1: imagine more, gain insight for your industry with forward thinking 1350 01:14:15,800 --> 01:14:19,759 Speaker 1: advice from the professionals at Cone Resnick. Is your business 1351 01:14:19,760 --> 01:14:22,960 Speaker 1: ready to break through? Find out more at Cone Resnick 1352 01:14:23,040 --> 01:14:24,840 Speaker 1: dot com. Slash breakthrough