1 00:00:03,240 --> 00:00:10,440 Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio. Today. 2 00:00:10,480 --> 00:00:13,640 Speaker 1: I have a very special guest, and I really mean it. 3 00:00:13,800 --> 00:00:17,080 Speaker 1: We have a very special guest, Ed Hyman. He is 4 00:00:17,120 --> 00:00:20,560 Speaker 1: the founder of I s I, Chairman of evercres I 5 00:00:20,800 --> 00:00:27,600 Speaker 1: s I UM, a super highly regarded economic research firm. 6 00:00:27,720 --> 00:00:30,080 Speaker 1: Let me let me share a statistic with you which 7 00:00:30,120 --> 00:00:34,880 Speaker 1: is impossible. This is an impossible data point. So every 8 00:00:34,960 --> 00:00:40,920 Speaker 1: year the UH, the institutional investor, puts out their survey 9 00:00:40,960 --> 00:00:46,400 Speaker 1: of top strategists, analysts, economists. It's a run that that 10 00:00:47,040 --> 00:00:50,280 Speaker 1: literally is voted on by people who are putting money 11 00:00:51,040 --> 00:00:54,320 Speaker 1: UH to work, big big pension funds, big institutions, big 12 00:00:54,360 --> 00:00:57,720 Speaker 1: neustrel funds. And these are the people they say are 13 00:00:58,040 --> 00:01:03,600 Speaker 1: the most helpful, the the top ranked folks UH in 14 00:01:03,680 --> 00:01:07,199 Speaker 1: the world of Wall Street research. And it's a great 15 00:01:07,240 --> 00:01:10,680 Speaker 1: honor to be I I ranked number one in any 16 00:01:10,720 --> 00:01:14,840 Speaker 1: given year. Our our guest today, Ed Hyman, has been 17 00:01:15,000 --> 00:01:20,560 Speaker 1: I I ranked number one for thirty five consecutive years. 18 00:01:22,160 --> 00:01:26,080 Speaker 1: That that's just a number that that is impossible. You know. 19 00:01:26,120 --> 00:01:28,360 Speaker 1: I'm a big New York Knicks fan and and during 20 00:01:28,400 --> 00:01:33,840 Speaker 1: the UM Patrick Ewing, Charles Oakley, UH, Anthony Mason John 21 00:01:33,880 --> 00:01:37,880 Speaker 1: Starks era. It was always Michael Jordan's in the way, 22 00:01:37,959 --> 00:01:40,920 Speaker 1: and and for six of let's call it ten years, 23 00:01:41,600 --> 00:01:44,480 Speaker 1: Jordan's bulls, along with Scottie Pippen and the rest of 24 00:01:44,520 --> 00:01:49,560 Speaker 1: the cast, prevented the New York Knicks from getting either 25 00:01:49,640 --> 00:01:54,160 Speaker 1: to the finals or or winning the finals. And they 26 00:01:54,200 --> 00:01:57,520 Speaker 1: came close to a couple of times. Uh Charles Smith 27 00:01:57,560 --> 00:02:02,000 Speaker 1: fingerroll once um uh did a season for them, a 28 00:02:02,040 --> 00:02:07,360 Speaker 1: bad finger role. But Michael Jordan's the greatest basketball player 29 00:02:07,360 --> 00:02:11,200 Speaker 1: of all times, you know, won six championships and and 30 00:02:11,200 --> 00:02:16,040 Speaker 1: and I think it was uh six championship um m 31 00:02:16,120 --> 00:02:20,560 Speaker 1: v p s and maybe eight total uh nbah m 32 00:02:20,600 --> 00:02:25,800 Speaker 1: v p s. Ed Himan for thirty five consecutive years 33 00:02:25,840 --> 00:02:32,040 Speaker 1: has been I I ranked as the institutional world's top economists. 34 00:02:32,320 --> 00:02:37,360 Speaker 1: That's just a streak that is unimaginable. I can't not 35 00:02:37,400 --> 00:02:40,919 Speaker 1: only can I not conceptualize it. I can't ever imagine 36 00:02:40,960 --> 00:02:44,840 Speaker 1: anyone finding themselves in a position to to top this 37 00:02:44,840 --> 00:02:47,320 Speaker 1: this streak. And and think about how frustrating it must 38 00:02:47,360 --> 00:02:50,880 Speaker 1: have been for all of the Looking around Wall Street, 39 00:02:50,880 --> 00:02:54,239 Speaker 1: there are some really really good economists, some really savvy 40 00:02:54,360 --> 00:03:00,960 Speaker 1: people who have a fantastic um handle uh on on 41 00:03:01,000 --> 00:03:04,160 Speaker 1: the world of of economics and what's actually happening in 42 00:03:04,200 --> 00:03:08,320 Speaker 1: the economy. They have perennially been you know, number two 43 00:03:08,440 --> 00:03:13,160 Speaker 1: or worse to to Ed Hyman's UH top rank. It's 44 00:03:13,200 --> 00:03:18,760 Speaker 1: an astonishing um feet you'll find this conversation really quite 45 00:03:18,960 --> 00:03:22,680 Speaker 1: quite fascinating, quite interesting. Ed's a guy who doesn't do 46 00:03:22,760 --> 00:03:24,639 Speaker 1: a lot of media, he said, he you know, went 47 00:03:24,680 --> 00:03:29,280 Speaker 1: for about fifteen years where he did no media whatsoever. Um. 48 00:03:29,320 --> 00:03:33,280 Speaker 1: This is something I'm I'm nothing if not tenacious and relentless, 49 00:03:33,320 --> 00:03:36,920 Speaker 1: And eventually he succumbed to my charms and agreed to 50 00:03:36,960 --> 00:03:42,000 Speaker 1: do our podcast. And I think you'll find his approach 51 00:03:42,080 --> 00:03:46,160 Speaker 1: to looking at the world uh fascinating, not just from 52 00:03:46,160 --> 00:03:50,680 Speaker 1: an economic perspective, not just how he views the world 53 00:03:50,760 --> 00:03:54,720 Speaker 1: of of economics, but how he built a business which 54 00:03:54,800 --> 00:03:58,120 Speaker 1: eventually was sold for north of four million dollars to 55 00:03:58,200 --> 00:04:00,960 Speaker 1: have a corps with with the upside potential it's worth 56 00:04:01,000 --> 00:04:04,880 Speaker 1: even more than that. But there's so much insight and 57 00:04:04,960 --> 00:04:09,160 Speaker 1: so much wisdom uh in his experience and his perspective. 58 00:04:09,640 --> 00:04:12,800 Speaker 1: I found it to be an absolutely fascinating conversation and 59 00:04:12,880 --> 00:04:15,360 Speaker 1: I think you will also so. With no further Ado. 60 00:04:15,800 --> 00:04:19,800 Speaker 1: Here's my conversation with ever Cores I ses Ed Hyman. 61 00:04:24,200 --> 00:04:28,520 Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio. 62 00:04:29,120 --> 00:04:33,240 Speaker 1: My special guest today is Ed Hyman. He is the 63 00:04:33,279 --> 00:04:36,240 Speaker 1: founder of I s I now the chairman of I 64 00:04:36,520 --> 00:04:40,360 Speaker 1: s I ever Core. Mr Hyman has the unique distinction 65 00:04:40,440 --> 00:04:45,159 Speaker 1: of being the number one rated economist on Wall Street 66 00:04:45,240 --> 00:04:50,040 Speaker 1: by Institutional Investor. It's their poll of of big investors 67 00:04:50,080 --> 00:04:54,360 Speaker 1: for the past thirty five consecutive years running, an absolutely 68 00:04:55,000 --> 00:04:57,640 Speaker 1: astonishing feat. You may not have heard of him. Most 69 00:04:57,640 --> 00:05:01,520 Speaker 1: of his clients are big institutions, hedge funds, pension funds, etcetera. 70 00:05:02,520 --> 00:05:06,520 Speaker 1: But Ed is really well known on Wall Street, very influential. 71 00:05:06,560 --> 00:05:09,640 Speaker 1: Let me just give a short version of your curriculum, Vita. 72 00:05:10,279 --> 00:05:13,200 Speaker 1: You graduate with a bachelors and engineering from the University 73 00:05:13,200 --> 00:05:16,320 Speaker 1: of Texas in nineteen sixty seven. Then you go on 74 00:05:16,400 --> 00:05:20,240 Speaker 1: to get your m b a from uh the Massachusetts 75 00:05:20,240 --> 00:05:24,479 Speaker 1: Institute of Technology in nineteen sixty nine, and finally you 76 00:05:24,600 --> 00:05:27,880 Speaker 1: ended up forming I s I. In is that more 77 00:05:27,920 --> 00:05:30,320 Speaker 1: or less correct? Left left the middle part out, but 78 00:05:30,360 --> 00:05:31,960 Speaker 1: it's perfect. A couple of years in the middle, we'll 79 00:05:32,000 --> 00:05:35,400 Speaker 1: get to well, welcome to Bloomberg. Thank you. So Ed 80 00:05:35,440 --> 00:05:37,400 Speaker 1: and I have been talking about him doing the show 81 00:05:37,440 --> 00:05:40,600 Speaker 1: for some time, and I'm really thrilled to have him here. 82 00:05:40,720 --> 00:05:43,280 Speaker 1: Most people don't know who you are because you're not 83 00:05:43,320 --> 00:05:46,719 Speaker 1: really all that public facing you. You you and your 84 00:05:46,720 --> 00:05:52,680 Speaker 1: office face the institutional universe, right, So I don't. Our 85 00:05:52,720 --> 00:05:57,159 Speaker 1: clients are all institutional investors, and so we don't really 86 00:05:57,200 --> 00:06:00,280 Speaker 1: have a retail face, and so we have a very 87 00:06:00,320 --> 00:06:03,520 Speaker 1: low profile. I also noticed that most of our clients 88 00:06:03,720 --> 00:06:07,960 Speaker 1: have a low profile as well. So any event, uh, 89 00:06:08,120 --> 00:06:11,520 Speaker 1: maybe I'm just not famous either, But well, you're famous. 90 00:06:11,560 --> 00:06:15,000 Speaker 1: You're famous amongst people who manage billions and billions of dollars, 91 00:06:15,000 --> 00:06:18,360 Speaker 1: So that's a very influential sort of fame. Let's let's 92 00:06:18,360 --> 00:06:20,320 Speaker 1: talk a little bit about how you ended up on 93 00:06:20,400 --> 00:06:23,719 Speaker 1: Wall Street. So you get an engineering degree. You didn't 94 00:06:23,720 --> 00:06:27,320 Speaker 1: go the usual route. Most people in your role end 95 00:06:27,400 --> 00:06:30,640 Speaker 1: up having a bachelor's in economics and neither get a 96 00:06:30,720 --> 00:06:34,880 Speaker 1: PhD in economics or something comparable. You took a very 97 00:06:34,960 --> 00:06:37,760 Speaker 1: different route. How do you go from a bachelors and 98 00:06:37,839 --> 00:06:41,880 Speaker 1: engineering and an m b a To essentially creating the 99 00:06:41,920 --> 00:06:46,880 Speaker 1: world of econometric modeling. So because I was an engineer. 100 00:06:47,160 --> 00:06:51,440 Speaker 1: I knew I was mathematical, and M I t s 101 00:06:51,480 --> 00:06:55,839 Speaker 1: Business School is one of two or three of the 102 00:06:55,960 --> 00:06:59,320 Speaker 1: business schools that have a quantitative vent. So that's what 103 00:06:59,400 --> 00:07:03,880 Speaker 1: I wanted to And when I got there, Uh, I 104 00:07:04,000 --> 00:07:10,360 Speaker 1: had a research assistance job working with Ed Ku, who 105 00:07:10,400 --> 00:07:14,960 Speaker 1: was a fairly well known economist and working on econometric 106 00:07:15,040 --> 00:07:18,720 Speaker 1: models just by chance, and at M I T. They 107 00:07:18,760 --> 00:07:23,880 Speaker 1: had developed the first time sharing computer where the data 108 00:07:24,120 --> 00:07:27,400 Speaker 1: is often in one central place and you could access 109 00:07:27,440 --> 00:07:31,800 Speaker 1: that data from off site spaces with a with a 110 00:07:31,840 --> 00:07:36,480 Speaker 1: time shared computer. And so I spent uh really those 111 00:07:36,520 --> 00:07:41,000 Speaker 1: two years at M I T immersed in doing econometric modeling, 112 00:07:41,960 --> 00:07:47,720 Speaker 1: and then I did my master's thesis for a guy 113 00:07:47,800 --> 00:07:51,880 Speaker 1: named Paul Kutner who's a fairly well known Both of 114 00:07:52,720 --> 00:07:56,840 Speaker 1: Ku and Kutner have passed away working on forecasting commodity 115 00:07:56,880 --> 00:08:02,360 Speaker 1: prices with with econometric models, and then later on I 116 00:08:02,440 --> 00:08:08,360 Speaker 1: ran a commodity fund using econometric models to forecast pork prices. Basically. So, 117 00:08:08,360 --> 00:08:10,760 Speaker 1: so these issues that you approach, do you look at 118 00:08:10,800 --> 00:08:14,160 Speaker 1: these as engineering problems to be solved or are they 119 00:08:14,200 --> 00:08:19,520 Speaker 1: really pure economics? Uh? I think they're they're economics. But 120 00:08:19,720 --> 00:08:25,440 Speaker 1: in this case there market economics and and business cycle economics, 121 00:08:26,240 --> 00:08:29,480 Speaker 1: and that's really what I think I do. At M 122 00:08:29,480 --> 00:08:32,960 Speaker 1: I T. They had this first time sharing computer, and 123 00:08:33,000 --> 00:08:37,280 Speaker 1: then uh Otto Eckstein, who was a professor at Harvard 124 00:08:37,559 --> 00:08:42,640 Speaker 1: started a company called Data Resources, which did econometric modeling 125 00:08:43,000 --> 00:08:46,240 Speaker 1: with time sharing computer, and I was lucky enough to 126 00:08:46,520 --> 00:08:48,920 Speaker 1: go to work there, and that's really how I got 127 00:08:48,960 --> 00:08:51,640 Speaker 1: into this. So that sequence of events is how I 128 00:08:51,679 --> 00:08:54,520 Speaker 1: got where I am today. So your training, and we're 129 00:08:54,559 --> 00:08:57,680 Speaker 1: talking M I T was sixty nine University of Texas 130 00:08:57,760 --> 00:09:01,080 Speaker 1: Engineering with sixty seven. These were really the early days 131 00:09:01,160 --> 00:09:04,240 Speaker 1: of this quantitative analysis, wasn't it. Well, this was this 132 00:09:04,320 --> 00:09:08,400 Speaker 1: time sharing computer, was the first use of time sharing computer. 133 00:09:08,920 --> 00:09:14,800 Speaker 1: They also had developed the Saber of airline ticketing system, 134 00:09:15,080 --> 00:09:17,920 Speaker 1: which still exists, and that was still exists. It's a 135 00:09:17,960 --> 00:09:22,240 Speaker 1: company down in Texas and that is still the sort 136 00:09:22,280 --> 00:09:25,679 Speaker 1: of birthplace of time sharing computing, which is now every everywhere. 137 00:09:26,360 --> 00:09:31,160 Speaker 1: That's where I got started doing uh time series analysis 138 00:09:31,200 --> 00:09:34,320 Speaker 1: studying economic data. So it was fairly natural for you 139 00:09:34,360 --> 00:09:36,520 Speaker 1: to then take because you were really one of the 140 00:09:36,520 --> 00:09:40,280 Speaker 1: first people on Wall Street to say, hey, let's take 141 00:09:40,280 --> 00:09:43,880 Speaker 1: this massive computing power that we're developing and apply it 142 00:09:44,000 --> 00:09:49,120 Speaker 1: to modeling business cycles, modeling economics, modeling forecasting. This was 143 00:09:49,400 --> 00:09:53,280 Speaker 1: not any great aha moment. It was just obvious, Hey, 144 00:09:53,320 --> 00:09:55,679 Speaker 1: this is what these tools are here for, right And 145 00:09:55,720 --> 00:10:00,679 Speaker 1: so I, Um, I was at Data Resources and Cyrus J. 146 00:10:00,840 --> 00:10:04,120 Speaker 1: Lawrence was a client, and so I went to work 147 00:10:04,240 --> 00:10:09,240 Speaker 1: for Cyrus J. Lawrence doing the economic forecasting but also 148 00:10:09,360 --> 00:10:14,440 Speaker 1: building models the forecast industries like kept goods, autos, retail. 149 00:10:15,000 --> 00:10:17,600 Speaker 1: And that's really how I got launched in the direction 150 00:10:17,720 --> 00:10:21,360 Speaker 1: that I'm launched in now. So in the last minute, UM, 151 00:10:21,440 --> 00:10:24,520 Speaker 1: we have one of the things you're sort of infamous 152 00:10:24,559 --> 00:10:28,760 Speaker 1: for on Wall Street is despite all this computing power 153 00:10:28,800 --> 00:10:31,640 Speaker 1: and despite the use of technology, you have a tendency 154 00:10:31,679 --> 00:10:34,360 Speaker 1: to take a bunch of charts, mark them up with 155 00:10:34,400 --> 00:10:37,280 Speaker 1: a sharpie, mark him up by hands, and then fax 156 00:10:37,320 --> 00:10:40,040 Speaker 1: that out or today scan it and send it out 157 00:10:40,120 --> 00:10:44,640 Speaker 1: as a PDF. Where did the idea for hand marking 158 00:10:44,720 --> 00:10:47,920 Speaker 1: up charts and tables ever come from? So we had 159 00:10:48,040 --> 00:10:50,560 Speaker 1: a morning meeting at Cyrus J. Lawrence and I would 160 00:10:50,559 --> 00:10:52,720 Speaker 1: come in and mark us some charts and pass out 161 00:10:52,720 --> 00:10:55,400 Speaker 1: to the sales guys, and they started singing out to 162 00:10:55,440 --> 00:10:58,480 Speaker 1: the clients and the clients liked it, so we all 163 00:10:58,520 --> 00:11:01,920 Speaker 1: have a thinked when you see something, if it's been 164 00:11:02,000 --> 00:11:05,839 Speaker 1: marked on by hand, your eye goes right to it absolutely, 165 00:11:06,120 --> 00:11:08,240 Speaker 1: and so that's where it came from, and it's still 166 00:11:08,320 --> 00:11:11,920 Speaker 1: a good technique. I'm very ridult. You're listening to Masters 167 00:11:11,920 --> 00:11:15,040 Speaker 1: in Business on Bloomberg Radio. My special guest today is 168 00:11:15,240 --> 00:11:18,040 Speaker 1: Ed Hyman. He is the chairman of Evercres. I s 169 00:11:18,040 --> 00:11:21,640 Speaker 1: I UM, and I just wanna I love this quote 170 00:11:21,679 --> 00:11:26,240 Speaker 1: from Peter Lynch, he's the fame manager of Fidelities Magellan Funds, 171 00:11:26,480 --> 00:11:30,640 Speaker 1: and he described you as much more practical than most economists, 172 00:11:30,640 --> 00:11:35,280 Speaker 1: more interested in examining railroad card deliveries than Laugher curves. 173 00:11:35,360 --> 00:11:37,400 Speaker 1: That was in his book One Up on Wall Street. 174 00:11:37,679 --> 00:11:41,479 Speaker 1: So really the question is do you consider yourself an economist? 175 00:11:41,559 --> 00:11:45,160 Speaker 1: Are you a strategist? How do you describe yourself? Well, first, 176 00:11:45,559 --> 00:11:48,400 Speaker 1: I'm a practitioner, but you know, from my early days 177 00:11:49,200 --> 00:11:52,640 Speaker 1: I was really going off in the economics area at 178 00:11:52,760 --> 00:11:55,439 Speaker 1: M I T Than Data Resources and then at C 179 00:11:55,720 --> 00:11:59,240 Speaker 1: at C. J. Lawrence. But I view myself really as 180 00:11:59,240 --> 00:12:04,560 Speaker 1: a business side goal expert and a market cycle effects sinado. 181 00:12:04,800 --> 00:12:08,640 Speaker 1: So that's really what I'm trying to apply the logics 182 00:12:08,720 --> 00:12:12,280 Speaker 1: of economics too. Makes makes perfect sense to me. So 183 00:12:12,679 --> 00:12:15,000 Speaker 1: let's let's get into that in a little detail, because 184 00:12:15,520 --> 00:12:19,160 Speaker 1: over the past couple of years, especially during the financial crisis, 185 00:12:19,520 --> 00:12:24,400 Speaker 1: the economics profession has come in for some some criticism. Um, 186 00:12:24,480 --> 00:12:27,080 Speaker 1: so let's talk a little bit about the data you 187 00:12:27,120 --> 00:12:32,360 Speaker 1: look at. You early in your career created a survey 188 00:12:32,400 --> 00:12:37,239 Speaker 1: that went out to four hundred different companies in trucking, retailing, 189 00:12:37,320 --> 00:12:41,760 Speaker 1: home building, manufacturing. How how did that come about? How 190 00:12:41,760 --> 00:12:45,560 Speaker 1: did the idea for this regular survey of people in 191 00:12:45,600 --> 00:12:50,800 Speaker 1: the real economy come about? So probably probably thirty years 192 00:12:50,800 --> 00:12:54,520 Speaker 1: ago or more. Uh, there was a survey of retailers 193 00:12:55,480 --> 00:13:00,000 Speaker 1: that came out once a week and very widely followed. 194 00:13:00,240 --> 00:13:02,080 Speaker 1: And I saw that, and I thought, why don't we 195 00:13:02,120 --> 00:13:05,120 Speaker 1: do that for many industries, not just retailing. So we 196 00:13:05,120 --> 00:13:08,360 Speaker 1: started a retail survey, which we still have, and then 197 00:13:08,440 --> 00:13:11,880 Speaker 1: we branched out and now we survey about thirty different 198 00:13:11,920 --> 00:13:17,520 Speaker 1: areas and have really gone very wide feel. So, for example, 199 00:13:17,559 --> 00:13:21,120 Speaker 1: as you mentioned, we survey trucking companies and asked them, 200 00:13:21,160 --> 00:13:23,760 Speaker 1: how are your sales this week compared to what you expected? 201 00:13:24,760 --> 00:13:27,839 Speaker 1: Same question every week to the same person. If the 202 00:13:27,880 --> 00:13:31,240 Speaker 1: person is not there, Typically the the CFO. If they're 203 00:13:31,280 --> 00:13:34,440 Speaker 1: not there, we used last week's reading, so there's no 204 00:13:35,000 --> 00:13:38,600 Speaker 1: change in the survey due to somebody changing the answer. 205 00:13:39,160 --> 00:13:41,600 Speaker 1: And so we've been doing that UH for a long time, 206 00:13:41,600 --> 00:13:44,520 Speaker 1: and now we cover almost every single nook and cranny 207 00:13:44,559 --> 00:13:47,280 Speaker 1: of the US economy. We also survey companies that do 208 00:13:47,320 --> 00:13:50,079 Speaker 1: business in China and ask them how their sales are. 209 00:13:50,240 --> 00:13:53,280 Speaker 1: So what do all these surveys ultimately end up informing 210 00:13:53,320 --> 00:13:56,760 Speaker 1: you about? So I have UH, if you follow the surveys, 211 00:13:57,120 --> 00:14:01,160 Speaker 1: you have an almost perfect knowledge of the US economy today. 212 00:14:01,640 --> 00:14:03,720 Speaker 1: They're not the least bit predicted. We're not asking what 213 00:14:03,760 --> 00:14:06,079 Speaker 1: do you think sales will be next week, next quarter? 214 00:14:06,240 --> 00:14:09,520 Speaker 1: But you know what's happening right now in real time, 215 00:14:09,600 --> 00:14:14,800 Speaker 1: in real time. The surveys are for revenue. So like 216 00:14:14,920 --> 00:14:18,480 Speaker 1: our trucking survey got very strong, and part of that 217 00:14:18,520 --> 00:14:22,120 Speaker 1: with price increases, they were getting rate increases. UH. So 218 00:14:22,200 --> 00:14:25,200 Speaker 1: we catch capture both the miles driven and the and 219 00:14:25,240 --> 00:14:29,440 Speaker 1: the rates. Our airline survey was very strong, UH, and 220 00:14:29,480 --> 00:14:31,680 Speaker 1: now it's come off in part because fares have been 221 00:14:31,760 --> 00:14:34,680 Speaker 1: under pressure. So it's a it's a it's a nominal measure. 222 00:14:35,360 --> 00:14:38,600 Speaker 1: Each each of the surveys. So one of the issues 223 00:14:38,640 --> 00:14:41,520 Speaker 1: that we always run into, at least with investor surveys, 224 00:14:42,000 --> 00:14:44,880 Speaker 1: is whether or not people are actually telling the truth. 225 00:14:45,200 --> 00:14:47,560 Speaker 1: You have an issue with that. Are CFOs pretty honest 226 00:14:47,600 --> 00:14:49,920 Speaker 1: with you about what they're doing or do you run 227 00:14:49,960 --> 00:14:53,600 Speaker 1: into a little wishful thinking here and again the I 228 00:14:53,640 --> 00:14:58,080 Speaker 1: think we're getting the straight shot of the companies that 229 00:14:58,120 --> 00:15:01,520 Speaker 1: do it, that participate with this UH do it for 230 00:15:01,560 --> 00:15:04,400 Speaker 1: two reasons. One, they get to see the survey result. 231 00:15:04,720 --> 00:15:08,760 Speaker 1: So if you're running a trucking company and somebody will 232 00:15:08,760 --> 00:15:12,400 Speaker 1: tell you every week how twelve other truckers put together 233 00:15:13,520 --> 00:15:17,080 Speaker 1: a consensus, you can tell if you're gaining or losing 234 00:15:17,880 --> 00:15:20,680 Speaker 1: UH market share. Here's how you're doing relative to the 235 00:15:20,720 --> 00:15:22,600 Speaker 1: rest of your You know what your answer was, you 236 00:15:22,640 --> 00:15:24,480 Speaker 1: don't know, and you know what the overall is. You 237 00:15:24,520 --> 00:15:26,720 Speaker 1: can you can get a feel for it. The second 238 00:15:26,800 --> 00:15:30,280 Speaker 1: is we give them our economic research and so there 239 00:15:30,320 --> 00:15:32,960 Speaker 1: we've gotten about three companies to work with us on 240 00:15:33,000 --> 00:15:36,640 Speaker 1: a on a weekly basis. That that's really fascinating and 241 00:15:36,800 --> 00:15:38,760 Speaker 1: that answers the question how did you get people to 242 00:15:38,880 --> 00:15:41,680 Speaker 1: agree to do these You've you've given them an insensive 243 00:15:41,960 --> 00:15:45,040 Speaker 1: and so because of that. Uh. I really don't think 244 00:15:45,320 --> 00:15:48,440 Speaker 1: there's any incentive for them to game the system. We 245 00:15:48,520 --> 00:15:53,360 Speaker 1: also do a survey, for example, of hedge funds, and 246 00:15:53,440 --> 00:15:59,040 Speaker 1: we're trying to determine whether they're really extended or are defensive. 247 00:16:00,640 --> 00:16:03,880 Speaker 1: Occasionally I worried that one of the participants might put 248 00:16:03,920 --> 00:16:08,240 Speaker 1: in of a real fake number, fake number to try 249 00:16:08,240 --> 00:16:11,360 Speaker 1: and make it look like people are really enthusiastic, are 250 00:16:11,400 --> 00:16:14,280 Speaker 1: really pessimistic, and then trade against that. So he wants 251 00:16:14,280 --> 00:16:16,760 Speaker 1: to influence the survey and then take the other side 252 00:16:16,800 --> 00:16:19,720 Speaker 1: of the trade. I think about that occasionally. But so 253 00:16:20,240 --> 00:16:23,480 Speaker 1: this really is in how traditional economics has been done 254 00:16:23,480 --> 00:16:26,760 Speaker 1: in the past. Usually there's official government data and people 255 00:16:26,800 --> 00:16:30,440 Speaker 1: take that and crunch numbers. You're really looking at the 256 00:16:30,600 --> 00:16:34,600 Speaker 1: economy with the rubber meets the road, so to speak. Yes, 257 00:16:34,720 --> 00:16:37,720 Speaker 1: but as as a constant job to look at what 258 00:16:37,760 --> 00:16:40,560 Speaker 1: our surveys are saying and then compare it to what 259 00:16:40,600 --> 00:16:42,840 Speaker 1: the government stats are saying, whether it's retail sales or 260 00:16:42,840 --> 00:16:45,600 Speaker 1: GDP or housing starts. So you're always going back and 261 00:16:45,640 --> 00:16:49,880 Speaker 1: forth to try and triangulate the best picture is their lead. 262 00:16:49,960 --> 00:16:52,960 Speaker 1: Is there a lag? Do they often coincide? Uh? The 263 00:16:53,000 --> 00:16:57,840 Speaker 1: surveys are definitely coincident. Sometimes the government data can be lagging, 264 00:16:57,960 --> 00:17:00,920 Speaker 1: and it's and it's always lagging just because it comes 265 00:17:00,920 --> 00:17:04,520 Speaker 1: out a month late or two weeks late. Uh So 266 00:17:04,920 --> 00:17:10,560 Speaker 1: we're always working real time, and the gunment data is 267 00:17:10,600 --> 00:17:12,600 Speaker 1: always with some sort of lag, could be a week 268 00:17:12,640 --> 00:17:15,800 Speaker 1: for employment or two or three weeks for retail sales. 269 00:17:15,840 --> 00:17:18,200 Speaker 1: That that has to be tremendously valuable to your clients. 270 00:17:18,640 --> 00:17:21,399 Speaker 1: It's it's valuable to our clients. It's very valuable to me. 271 00:17:21,560 --> 00:17:24,320 Speaker 1: It's I think it forms my sort of whole vision 272 00:17:24,400 --> 00:17:26,840 Speaker 1: of what is happening on a current basis. So that 273 00:17:26,920 --> 00:17:29,600 Speaker 1: leads me to my next question, how do you assemble 274 00:17:29,840 --> 00:17:33,200 Speaker 1: your economic perspectives. One of the things that you did 275 00:17:33,240 --> 00:17:37,600 Speaker 1: earlier in your career, when most of Wall Street was 276 00:17:37,680 --> 00:17:41,000 Speaker 1: making monthly forecasts, you said, we get data weekly, let's 277 00:17:41,000 --> 00:17:44,080 Speaker 1: do this on a weekly basis. What goes into into 278 00:17:44,119 --> 00:17:48,520 Speaker 1: that process, So it's a little bit has followed the 279 00:17:48,560 --> 00:17:52,119 Speaker 1: Internet the frequency you had first you had mailed, then 280 00:17:52,119 --> 00:17:57,680 Speaker 1: you had facts, then you had email, and as that happened, 281 00:17:57,920 --> 00:18:00,159 Speaker 1: you could go faster and faster. And also data is 282 00:18:00,160 --> 00:18:04,040 Speaker 1: coming out faster, and so it's changed dramatically in the 283 00:18:04,119 --> 00:18:07,160 Speaker 1: forty years I've been doing this, and so we went 284 00:18:07,680 --> 00:18:11,600 Speaker 1: uh too, weekly, and then we went to daily, and 285 00:18:11,680 --> 00:18:16,520 Speaker 1: so now every day is a complete immersion and you 286 00:18:16,520 --> 00:18:19,359 Speaker 1: know what's happened, what the markets are doing, and we 287 00:18:19,440 --> 00:18:23,199 Speaker 1: put out a piece every every morning. Uh and I 288 00:18:23,240 --> 00:18:26,240 Speaker 1: can feel it. It's gonna go it's gonna go virtual 289 00:18:26,560 --> 00:18:30,520 Speaker 1: or they'll be constantly continuous, not that far off in 290 00:18:30,560 --> 00:18:33,320 Speaker 1: the distance, not that far from distance, and it almost 291 00:18:33,400 --> 00:18:37,960 Speaker 1: is now. But it is more or less a daily phenomenon. 292 00:18:38,040 --> 00:18:40,639 Speaker 1: I'm Barry Ridhalt. You're listening to Masters in Business on 293 00:18:40,640 --> 00:18:43,960 Speaker 1: Bloomberg Radio. My special guest today is Ed Hyman. He 294 00:18:44,080 --> 00:18:46,480 Speaker 1: is the founder of I s I and the chairman 295 00:18:46,920 --> 00:18:49,080 Speaker 1: of ever Corps r s I, which is a very 296 00:18:49,160 --> 00:18:53,880 Speaker 1: large research and asset management firm located here in Manhattan 297 00:18:53,920 --> 00:18:57,800 Speaker 1: and offices pretty much all over. Let's talk a little 298 00:18:57,800 --> 00:19:01,920 Speaker 1: bit about the institutional investor rankings. What what you've accomplished 299 00:19:02,000 --> 00:19:07,120 Speaker 1: with that is is really unprecedented. Thirty five consecutive years 300 00:19:07,119 --> 00:19:11,439 Speaker 1: from one to two thousand and fifteen and counting, you 301 00:19:11,480 --> 00:19:15,280 Speaker 1: were the number one rated economist according to a poll 302 00:19:15,320 --> 00:19:20,719 Speaker 1: of institutional investors. That that's Michael Jordan's plus Tiger Woods 303 00:19:20,720 --> 00:19:24,520 Speaker 1: plus Derek Jeter rolled into one nobody has ever had 304 00:19:24,520 --> 00:19:28,400 Speaker 1: at Look. Bill Miller's streak was what fifteen years, that's 305 00:19:28,480 --> 00:19:33,720 Speaker 1: kids stuff. This is thirty five years. It's unprecedented. How 306 00:19:33,760 --> 00:19:37,159 Speaker 1: on earth do you explain this? They? Well, first, I 307 00:19:37,200 --> 00:19:41,720 Speaker 1: think Barry, I've been really lucky. Never it never hurts. 308 00:19:42,080 --> 00:19:46,359 Speaker 1: So the space that I got into has been a 309 00:19:46,400 --> 00:19:50,040 Speaker 1: space that has not been that competitive in terms of 310 00:19:50,080 --> 00:19:54,439 Speaker 1: other people, you know, other economists in the in the space. 311 00:19:54,920 --> 00:19:57,400 Speaker 1: So I've been I've been a little bit lucky. I've 312 00:19:57,440 --> 00:20:02,680 Speaker 1: been very lucky in the places I've worked, uh, like C. J. Lawrences, 313 00:20:02,720 --> 00:20:06,720 Speaker 1: which is really where it happened for me. Uh. And 314 00:20:06,920 --> 00:20:10,680 Speaker 1: my mission always and our mission at ever Chorus I 315 00:20:10,920 --> 00:20:16,399 Speaker 1: s I is to help our clients. That's that's what 316 00:20:16,680 --> 00:20:20,439 Speaker 1: I want us to do. And that comes across clearly 317 00:20:21,280 --> 00:20:23,199 Speaker 1: in the work that you get. And so everything I 318 00:20:23,280 --> 00:20:27,399 Speaker 1: do is aimed at trying to help our clients, and 319 00:20:27,440 --> 00:20:30,240 Speaker 1: that's what they respond to. So for example, if you 320 00:20:30,320 --> 00:20:34,320 Speaker 1: have an idea, it doesn't help if they don't understand it. 321 00:20:35,040 --> 00:20:37,840 Speaker 1: And so I spend a lot of time thinking about 322 00:20:39,160 --> 00:20:43,679 Speaker 1: communicating the idea as well as conceiving the idea, and 323 00:20:43,800 --> 00:20:48,600 Speaker 1: then we have forty salespeople, uh that or my megaphone 324 00:20:48,720 --> 00:20:52,200 Speaker 1: and megaphone for our other analyst, and so that combination 325 00:20:52,560 --> 00:20:56,560 Speaker 1: gives us a very loud signal in the in the community. 326 00:20:56,640 --> 00:20:59,040 Speaker 1: Do you spend a lot of time making sure those 327 00:20:59,080 --> 00:21:03,320 Speaker 1: salespeople really understand your thoughts, your thought process, and and 328 00:21:03,520 --> 00:21:06,560 Speaker 1: what you're trying to communicate to the clients. So we 329 00:21:06,680 --> 00:21:10,159 Speaker 1: have a terrific group of salespeople and they are my 330 00:21:10,800 --> 00:21:15,919 Speaker 1: forty biggest accounts, each one of them. And so every 331 00:21:16,119 --> 00:21:21,040 Speaker 1: morning at seven o'clock, seven fifteen, I start meeting with 332 00:21:21,119 --> 00:21:25,639 Speaker 1: them and our other forty research teams to try and 333 00:21:25,880 --> 00:21:28,760 Speaker 1: tell them what I'm thinking. And other analysts do as well, 334 00:21:29,200 --> 00:21:31,440 Speaker 1: And so that's what you have. If you cannot get 335 00:21:31,720 --> 00:21:34,719 Speaker 1: your salesman to understand what you're saying, what you're thinking, 336 00:21:34,800 --> 00:21:37,960 Speaker 1: what you're trying to get at, then the clients aren't either. 337 00:21:38,440 --> 00:21:41,040 Speaker 1: And so that's that's your first line. And we do 338 00:21:41,119 --> 00:21:45,720 Speaker 1: that every single morning, every day. Seven How long does 339 00:21:45,760 --> 00:21:48,800 Speaker 1: that that morning conference last at last till till eight? 340 00:21:49,160 --> 00:21:51,720 Speaker 1: So you're you're I'm up on goodly early. You have 341 00:21:51,840 --> 00:21:54,920 Speaker 1: to also be up at a ridiculous a right, right, 342 00:21:55,119 --> 00:21:58,399 Speaker 1: So we start, uh my team comes in at around 343 00:21:58,480 --> 00:22:05,840 Speaker 1: six fifteen and I start really at around five, um, 344 00:22:05,840 --> 00:22:10,760 Speaker 1: watching Bloomberg and getting up on the news and what's happening. 345 00:22:12,000 --> 00:22:16,120 Speaker 1: Then I read a dozen newspapers and by I meet 346 00:22:16,160 --> 00:22:20,960 Speaker 1: with our team to launch. We have very similar schedules. UM, 347 00:22:21,119 --> 00:22:23,440 Speaker 1: only I'm not doing the meeting at seven fifteen. That 348 00:22:23,440 --> 00:22:28,159 Speaker 1: that's uh, that's really significant. So beside yourself, who are 349 00:22:28,200 --> 00:22:30,439 Speaker 1: some of your favorite economists? Who who do you like 350 00:22:30,560 --> 00:22:36,840 Speaker 1: to look at their economic work? So they Um, the 351 00:22:36,880 --> 00:22:39,600 Speaker 1: person that probably had the most influence on me was 352 00:22:39,840 --> 00:22:43,400 Speaker 1: Milton Freeman. And he's not putting out economic work now, 353 00:22:43,920 --> 00:22:50,600 Speaker 1: but he I I was at a presentation he gave 354 00:22:50,640 --> 00:22:53,840 Speaker 1: an M I T. When I was twenty three, and 355 00:22:53,880 --> 00:22:57,439 Speaker 1: he had a debate with Paul Samuelson and I just 356 00:22:57,480 --> 00:23:02,000 Speaker 1: fell in love with Freeman two Giants to Giants and uh. 357 00:23:02,160 --> 00:23:05,880 Speaker 1: So he had a big influence on me. Uh. And 358 00:23:05,920 --> 00:23:10,000 Speaker 1: then Otto Eckstein, who I mentioned of, hired me right 359 00:23:10,000 --> 00:23:12,240 Speaker 1: out of M I T. And he had a huge 360 00:23:12,320 --> 00:23:16,760 Speaker 1: influence on me. He was very clear thinker, very hard working, 361 00:23:17,520 --> 00:23:21,840 Speaker 1: very good communicator. Uh and and he really influenced a 362 00:23:21,880 --> 00:23:24,479 Speaker 1: lot of what I think now. So those are two 363 00:23:24,560 --> 00:23:27,320 Speaker 1: of the legends of economics, and what about the next 364 00:23:27,359 --> 00:23:31,080 Speaker 1: generation of strategists and economists coming up? Anybody you look 365 00:23:31,119 --> 00:23:33,280 Speaker 1: at in the let's call it the under forty set. 366 00:23:33,840 --> 00:23:37,480 Speaker 1: They so this sort of a drought right there. So 367 00:23:37,640 --> 00:23:42,200 Speaker 1: there was a time when there were all these fabulous strategists, uh, 368 00:23:42,280 --> 00:23:47,119 Speaker 1: like Byron Ween and Barton Biggs, Steve Galberth, Henry McVeigh 369 00:23:47,240 --> 00:23:51,280 Speaker 1: and Uh, now there's some great strategists France Wat Trahan. 370 00:23:52,119 --> 00:23:58,800 Speaker 1: Uh is you worked with us and now has another firm. Uh. 371 00:23:58,920 --> 00:24:01,679 Speaker 1: And we're we have in our shop Dennis de Buscher, 372 00:24:02,359 --> 00:24:04,880 Speaker 1: who I have great hopes for. He's He's my up 373 00:24:04,880 --> 00:24:09,800 Speaker 1: and comer strategist. I'm Barry Ritults. You're listening to Masters 374 00:24:09,800 --> 00:24:12,520 Speaker 1: in Business on Bloomberg Radio. My special guest today is 375 00:24:12,720 --> 00:24:16,040 Speaker 1: Ed Hyman. He is the number one ranked economist in 376 00:24:16,080 --> 00:24:21,480 Speaker 1: the Institutional Investor Survey of Large Institutions and currently the 377 00:24:21,560 --> 00:24:24,160 Speaker 1: chairman of ever Corps. I s I. Let's talk about 378 00:24:24,200 --> 00:24:27,080 Speaker 1: what it was like building I S I. But before 379 00:24:27,119 --> 00:24:30,080 Speaker 1: we start, I have to read a quote here and 380 00:24:30,119 --> 00:24:33,360 Speaker 1: it reflects directly to what you said in the earlier segment. 381 00:24:33,640 --> 00:24:35,240 Speaker 1: So while we were looking up a lot of the 382 00:24:35,280 --> 00:24:39,000 Speaker 1: details on your background. There was a blog post by 383 00:24:39,000 --> 00:24:41,600 Speaker 1: a client of yours and this is a couple of 384 00:24:41,640 --> 00:24:44,320 Speaker 1: years old, and this person writes they are a long 385 00:24:44,440 --> 00:24:47,199 Speaker 1: term research client of Ed Himan. I s I and 386 00:24:47,320 --> 00:24:51,200 Speaker 1: here's why he is consistently the number one ranked economic 387 00:24:51,359 --> 00:24:54,520 Speaker 1: researcher on Wall Street. He sticks to his core mission 388 00:24:54,520 --> 00:24:59,719 Speaker 1: of providing high quality and independent research. He helps portfolio 389 00:24:59,760 --> 00:25:02,680 Speaker 1: man ers makes sense of the world. He sorts through 390 00:25:02,720 --> 00:25:07,480 Speaker 1: the reams of economic data and government surveys to provide 391 00:25:07,560 --> 00:25:11,520 Speaker 1: a real time analysis of what's happening. He provides a 392 00:25:11,680 --> 00:25:16,240 Speaker 1: very high level of client service. He is independent and unconflicted. 393 00:25:16,640 --> 00:25:21,600 Speaker 1: He never pushes a product discuss. So, as I mentioned, 394 00:25:21,920 --> 00:25:25,440 Speaker 1: I view my career as being a continuum, starting with 395 00:25:25,560 --> 00:25:28,159 Speaker 1: my work at M I T. Then I had the 396 00:25:28,160 --> 00:25:31,240 Speaker 1: good fortune working with Data Resources c J. Lawrence, and 397 00:25:31,280 --> 00:25:35,600 Speaker 1: all these were really high quality experiences for me. And 398 00:25:35,640 --> 00:25:38,880 Speaker 1: then CJ. Lawrence was brought by Dorge Bank, and that 399 00:25:38,960 --> 00:25:41,800 Speaker 1: was a discontinuity and what I was trying to do, 400 00:25:42,160 --> 00:25:44,760 Speaker 1: And so a group of us left and started ies I. 401 00:25:45,320 --> 00:25:48,320 Speaker 1: But it was really a continuation of what I had 402 00:25:48,320 --> 00:25:51,720 Speaker 1: been doing. Same core team, same core team, except at 403 00:25:51,760 --> 00:25:56,679 Speaker 1: that point we were just Macro just economics. At CJ. Lawrence, 404 00:25:56,720 --> 00:25:59,560 Speaker 1: we did everything we did, you know, stock research in 405 00:25:59,840 --> 00:26:02,560 Speaker 1: the street work as well as economic and strategy work. 406 00:26:02,760 --> 00:26:05,400 Speaker 1: So we developed the idea that we wanted to be 407 00:26:05,760 --> 00:26:09,240 Speaker 1: the best at whatever we were doing. And at that point, 408 00:26:09,480 --> 00:26:13,040 Speaker 1: it was not really possible to be the best at 409 00:26:13,080 --> 00:26:15,680 Speaker 1: stock research because that was being done in the Moulst 410 00:26:15,720 --> 00:26:18,120 Speaker 1: bracket firms with banking, and you couldn't afford to hire 411 00:26:18,119 --> 00:26:19,600 Speaker 1: the analysts, and they were doing it at a very 412 00:26:19,680 --> 00:26:25,760 Speaker 1: high level. And so when UH they separated banking and research, UH, 413 00:26:25,800 --> 00:26:29,240 Speaker 1: that gave us at an ability to hire the best analysts. 414 00:26:29,520 --> 00:26:32,600 Speaker 1: The economics worked then, and then you had the financial 415 00:26:32,640 --> 00:26:35,360 Speaker 1: crisis and the banks have been under siege, and so 416 00:26:35,400 --> 00:26:41,160 Speaker 1: now we definitely have UH thirty of the best fundamental 417 00:26:41,680 --> 00:26:45,560 Speaker 1: of fundamental analysts on the street. So that's that's really 418 00:26:45,600 --> 00:26:49,320 Speaker 1: allowed you to stay focused and every segment you go into, 419 00:26:50,119 --> 00:26:53,880 Speaker 1: there's no dilly delling. It's all in or not at all, right. 420 00:26:54,240 --> 00:26:59,040 Speaker 1: And so I grew up in an environment where I 421 00:26:59,080 --> 00:27:02,159 Speaker 1: was working with analyst, and I thought that gave me 422 00:27:02,200 --> 00:27:05,720 Speaker 1: a bottoms up advantage, and that's where I am now. 423 00:27:06,240 --> 00:27:08,480 Speaker 1: So we have this group of analysts I meet with 424 00:27:08,720 --> 00:27:13,920 Speaker 1: every morning, whether it's industrials or banks or retail China. 425 00:27:14,040 --> 00:27:18,000 Speaker 1: And so I feel that that collaborative approach gives me 426 00:27:18,080 --> 00:27:21,640 Speaker 1: a better chance at helping our clients and hopefully our 427 00:27:21,680 --> 00:27:26,120 Speaker 1: analysts benefit from working with our economics team. So this 428 00:27:26,240 --> 00:27:28,600 Speaker 1: is an area where a lot of people have tried 429 00:27:28,720 --> 00:27:32,399 Speaker 1: to build businesses and have failed. You guys have managed 430 00:27:32,440 --> 00:27:35,880 Speaker 1: to succeed in the space where competitors have dropped off 431 00:27:36,560 --> 00:27:40,400 Speaker 1: time and time again. What do you attribute this consistent 432 00:27:40,560 --> 00:27:43,680 Speaker 1: success level when lots and lots of people who are 433 00:27:44,040 --> 00:27:47,639 Speaker 1: in the same space just aren't making it well, There 434 00:27:47,720 --> 00:27:51,840 Speaker 1: really aren't many people doing what we've done. Um, So 435 00:27:51,920 --> 00:27:57,080 Speaker 1: we we've grown UH from a group of macro products, 436 00:27:57,480 --> 00:28:01,920 Speaker 1: you know, policy, economics, techno, goal strategy, and now we 437 00:28:02,000 --> 00:28:07,359 Speaker 1: have those plus UH authority fundamental teams and so there's 438 00:28:07,359 --> 00:28:10,719 Speaker 1: really no one has gone quite this path. And the 439 00:28:10,720 --> 00:28:12,439 Speaker 1: reason we were able to do it was because we 440 00:28:12,480 --> 00:28:14,960 Speaker 1: had a lot of momentum, and then we took advantage 441 00:28:15,480 --> 00:28:20,880 Speaker 1: of the split between banking and research, freeing up analysts 442 00:28:20,920 --> 00:28:23,600 Speaker 1: to work in an environment like ours, which is very 443 00:28:23,800 --> 00:28:29,720 Speaker 1: research focused, very research friendly. UH Bernstein is the main 444 00:28:29,840 --> 00:28:33,560 Speaker 1: firm UH maybe Jeffreys that has the same sort of 445 00:28:33,560 --> 00:28:36,720 Speaker 1: footprint that we have, and and they're quite a bit 446 00:28:36,760 --> 00:28:39,440 Speaker 1: larger than than we are. So we're moving ahead and 447 00:28:39,440 --> 00:28:42,840 Speaker 1: now with our ever core connection, it just makes us stronger. 448 00:28:43,120 --> 00:28:47,320 Speaker 1: So Bernstein was brought by UM, was it Alliance or Alliance? 449 00:28:47,560 --> 00:28:50,760 Speaker 1: And UM Jeffrey is still independent. Jefferies is independent, but 450 00:28:50,800 --> 00:28:56,480 Speaker 1: they have a Lucadia connection. UM. So you keep talking 451 00:28:56,520 --> 00:28:59,719 Speaker 1: about your various teams. Tell us about some of your teams, 452 00:29:00,120 --> 00:29:02,680 Speaker 1: who they are, how did you pull them together? How 453 00:29:02,720 --> 00:29:06,000 Speaker 1: do you manage so many disparate groups. We'll have a 454 00:29:06,040 --> 00:29:11,160 Speaker 1: strong management group. Uh and the our first analyst was 455 00:29:11,240 --> 00:29:15,080 Speaker 1: Dave Rosso and industrials and virtually all of our analysts 456 00:29:15,080 --> 00:29:18,560 Speaker 1: are number one ranked. We have uh in the II 457 00:29:18,600 --> 00:29:23,000 Speaker 1: magazine ranking. Our firm last year was number five. It's 458 00:29:23,040 --> 00:29:26,320 Speaker 1: the first time a non bulge bracket firm, a non 459 00:29:26,480 --> 00:29:29,320 Speaker 1: big bank firm has been in the top five since 460 00:29:29,680 --> 00:29:34,080 Speaker 1: UH two thousand and that was d L j uh So. 461 00:29:34,160 --> 00:29:37,440 Speaker 1: I'm very proud of of our guys and every single 462 00:29:37,640 --> 00:29:41,240 Speaker 1: I'll mention some sectors, but please every single sector we do. 463 00:29:41,520 --> 00:29:45,760 Speaker 1: We're the best in uh SO Banks Glenn Shore, he's 464 00:29:45,800 --> 00:29:48,880 Speaker 1: the best, number one ranked. I he's not number one ranked, 465 00:29:48,880 --> 00:29:51,000 Speaker 1: but he will be. But he also because I know 466 00:29:51,080 --> 00:29:55,440 Speaker 1: the industry, he is very highly regarded. Steve Sokkua does 467 00:29:55,520 --> 00:30:00,240 Speaker 1: Riets Rules of Space, Greg Malick does Retail number one 468 00:30:00,440 --> 00:30:04,640 Speaker 1: in two Spaces, or Marsad does Luxury number one, and 469 00:30:04,720 --> 00:30:06,960 Speaker 1: those goes on and on. Our healthcare team is the 470 00:30:07,040 --> 00:30:10,840 Speaker 1: killer team. Uh so we've I'm very proud of the 471 00:30:10,880 --> 00:30:12,280 Speaker 1: of the guys that I have a chance to work 472 00:30:12,320 --> 00:30:16,080 Speaker 1: with jury team. So what's the secret to pulling together 473 00:30:16,240 --> 00:30:19,040 Speaker 1: these top guys? How do you manage to you know? 474 00:30:19,040 --> 00:30:22,440 Speaker 1: Because look, you look at we just watched um the 475 00:30:22,480 --> 00:30:26,400 Speaker 1: basketball finals. Hey, some teams have a Lebron James, but 476 00:30:26,480 --> 00:30:30,720 Speaker 1: not everybody has the seven Yankees, where everybody in the 477 00:30:30,760 --> 00:30:33,600 Speaker 1: lineup couldn't hit a you know, a crushing home run. 478 00:30:34,080 --> 00:30:37,120 Speaker 1: So again, you know, we we had a momentum. Uh 479 00:30:37,240 --> 00:30:40,360 Speaker 1: then you had the separation of banking and research, which 480 00:30:40,400 --> 00:30:43,920 Speaker 1: so you think you're saying the regulatory shift created an opportunity, 481 00:30:43,920 --> 00:30:47,520 Speaker 1: and and then the then the financial crisis has been 482 00:30:47,560 --> 00:30:51,320 Speaker 1: really tough on the on the bulish bracket firms. And 483 00:30:51,320 --> 00:30:55,000 Speaker 1: and we are a research place. That's what we do, 484 00:30:55,200 --> 00:30:57,440 Speaker 1: that's our passion. So it's not one of a hundred 485 00:30:57,440 --> 00:31:02,280 Speaker 1: different things. This is your only focus and possible. Research 486 00:31:02,360 --> 00:31:07,800 Speaker 1: started out in the seventies with smaller firms like Morgan, Stanley, Dale, 487 00:31:07,880 --> 00:31:11,720 Speaker 1: J Goldman, Sachs, C. J. Lawrence where I worked Mitchell, Hutchins, 488 00:31:12,520 --> 00:31:16,480 Speaker 1: Baker Weeks on and on of Alex Brown, and they 489 00:31:16,560 --> 00:31:22,040 Speaker 1: all disappeared or were absorbed into another organization bigger, and 490 00:31:22,560 --> 00:31:25,080 Speaker 1: that's the way it was. I have a feeling that 491 00:31:25,240 --> 00:31:30,840 Speaker 1: research UH is happier in a smaller unit where it 492 00:31:30,960 --> 00:31:33,440 Speaker 1: is the focus of the unit, not part of a 493 00:31:33,520 --> 00:31:37,640 Speaker 1: hundred thousand or two thousand UH employee firm. What once 494 00:31:37,680 --> 00:31:41,160 Speaker 1: research becomes part of a bigger event, it's it's no 495 00:31:41,240 --> 00:31:46,600 Speaker 1: longer independent. The whole energy changes. So I don't know, 496 00:31:46,640 --> 00:31:51,200 Speaker 1: it's just the size might make a difference in our business. UH. 497 00:31:51,360 --> 00:31:56,040 Speaker 1: We make money because we have to, that's our only business. 498 00:31:56,080 --> 00:31:59,920 Speaker 1: In the bulsh bracket firms, they often view research at 499 00:32:00,080 --> 00:32:04,200 Speaker 1: a cost as opposed to something profit. Gotcha, so you 500 00:32:04,280 --> 00:32:07,200 Speaker 1: mentioned you you began in the nineteen seventies. I would 501 00:32:07,200 --> 00:32:11,640 Speaker 1: be remiss if I didn't mention or ask you what 502 00:32:11,680 --> 00:32:13,800 Speaker 1: was it like to start work in the early seventies. 503 00:32:13,800 --> 00:32:16,880 Speaker 1: You began, you said seventy two right before the huge 504 00:32:16,920 --> 00:32:20,200 Speaker 1: crash in nine seventy three. What was that decade like 505 00:32:20,320 --> 00:32:23,280 Speaker 1: that had to be a really tough period for both 506 00:32:23,320 --> 00:32:27,440 Speaker 1: investors and researchers. As as hard as it is to believe, 507 00:32:28,040 --> 00:32:30,600 Speaker 1: I really don't think the industry has changed that much 508 00:32:31,080 --> 00:32:35,240 Speaker 1: since nineteen seventy two. Really the biggest change is the 509 00:32:35,320 --> 00:32:40,960 Speaker 1: frequency of information and the hedge fund participation industry. Uh, 510 00:32:41,000 --> 00:32:42,720 Speaker 1: there are a lot more players now. It was a 511 00:32:42,800 --> 00:32:45,840 Speaker 1: much simpler business. I think it's much much more difficult 512 00:32:46,360 --> 00:32:51,560 Speaker 1: for investors to provide alpha, to provide a leg up 513 00:32:51,600 --> 00:32:56,760 Speaker 1: on other people. But what the cell side does today 514 00:32:57,080 --> 00:32:59,680 Speaker 1: is trying to help the clients is pretty much what 515 00:32:59,720 --> 00:33:04,880 Speaker 1: it did back then. And the our clients investors seem 516 00:33:05,040 --> 00:33:11,840 Speaker 1: to be totally uh uh formatted to working with sell 517 00:33:11,960 --> 00:33:18,080 Speaker 1: side firms. So our clients don't need Mark Schaanbaum, who 518 00:33:18,160 --> 00:33:20,800 Speaker 1: is our health care analyst, They don't need him to 519 00:33:20,880 --> 00:33:23,880 Speaker 1: work for them necessarily, but they definitely want to be 520 00:33:23,920 --> 00:33:27,360 Speaker 1: able to pick his brain. And and so you have 521 00:33:28,760 --> 00:33:31,720 Speaker 1: at at many firms, you have these experts like myself 522 00:33:32,160 --> 00:33:36,360 Speaker 1: or Mark Shawmbomb or Steve Sakua who does reats, who 523 00:33:36,720 --> 00:33:41,080 Speaker 1: are used by our clients to try and improve their 524 00:33:41,160 --> 00:33:46,240 Speaker 1: mosaic of information and come up with a better investment results. 525 00:33:46,240 --> 00:33:49,920 Speaker 1: So so you're saying that that basic approach unchanged over 526 00:33:49,960 --> 00:33:53,440 Speaker 1: the past. It's called it forty years. Uh. The only 527 00:33:53,440 --> 00:33:55,920 Speaker 1: thing has changed has gotten more competitive because there's so 528 00:33:55,960 --> 00:33:58,320 Speaker 1: many more players, and it's much more difficult, I think 529 00:33:58,480 --> 00:34:02,080 Speaker 1: than saying when Peter Lynch was was king of the roost. Uh, 530 00:34:02,120 --> 00:34:04,720 Speaker 1: it's it's much more difficult. Top. So, so in the 531 00:34:04,800 --> 00:34:08,240 Speaker 1: last couple of minutes we have I have a vague 532 00:34:08,280 --> 00:34:11,600 Speaker 1: recollection in the nineteen seventies, I was still in school, 533 00:34:12,120 --> 00:34:14,960 Speaker 1: but I remember that being a really tough economy. The 534 00:34:15,040 --> 00:34:19,440 Speaker 1: market had gone nowhere, interest rates had spiked, inflation was tough. 535 00:34:19,960 --> 00:34:23,080 Speaker 1: You're saying that wasn't a more challenging environment than what 536 00:34:23,120 --> 00:34:26,239 Speaker 1: people are dealing with today, Well, it's for a researcher, right, 537 00:34:26,520 --> 00:34:30,080 Speaker 1: Well I would say that, Uh, when people look at 538 00:34:30,120 --> 00:34:34,000 Speaker 1: how challenging it is today, I tell him go back 539 00:34:34,000 --> 00:34:39,719 Speaker 1: to the seventies. That was also very challenging, and so 540 00:34:39,920 --> 00:34:43,279 Speaker 1: they were both the same. But uh, I would when 541 00:34:43,280 --> 00:34:45,920 Speaker 1: I've thought about it, the seventies was tougher than it 542 00:34:46,000 --> 00:34:48,640 Speaker 1: is today. And that's a very big statement because the 543 00:34:48,760 --> 00:34:52,759 Speaker 1: day is also very difficult with Europe and China, the 544 00:34:52,800 --> 00:34:56,000 Speaker 1: banks under siege here quantitative easing. It's a it's a 545 00:34:56,080 --> 00:35:00,000 Speaker 1: very complicated, but I'm not sure it's much more difficult. 546 00:35:00,000 --> 00:35:03,719 Speaker 1: Halt then it was was then very interesting. We've been 547 00:35:03,760 --> 00:35:06,400 Speaker 1: speaking with Ed Hyman. He's the chairman of Evercore I 548 00:35:06,680 --> 00:35:09,640 Speaker 1: s I. If you enjoy this conversation, be sure and 549 00:35:09,719 --> 00:35:13,879 Speaker 1: check out our podcast extras where we continue chatting, letting 550 00:35:13,880 --> 00:35:16,480 Speaker 1: the tape roll. Be sure and check out all of 551 00:35:16,520 --> 00:35:20,120 Speaker 1: our other conversations. You can find them at Bloomberg dot com, 552 00:35:20,200 --> 00:35:24,640 Speaker 1: Apple iTunes and SoundCloud. See my daily column on Bloomberg 553 00:35:24,719 --> 00:35:28,440 Speaker 1: View dot com, or follow me on Twitter at Rit Halts. 554 00:35:28,560 --> 00:35:31,600 Speaker 1: I'm Barry Richlts. You're listening to Masters in Business. I'm 555 00:35:31,600 --> 00:35:35,760 Speaker 1: Bloomberg Radio. Welcome to the podcast Extras. I'm Barry Rihlts, 556 00:35:35,840 --> 00:35:39,319 Speaker 1: and my special guest this week is Ed Hyman. He 557 00:35:39,480 --> 00:35:41,760 Speaker 1: is the founder of I s I and currently chairman 558 00:35:41,800 --> 00:35:44,440 Speaker 1: of Evercore I s I. Ed, thank you so much 559 00:35:44,480 --> 00:35:48,080 Speaker 1: for doing this. I really appreciate my pleasure. Thank you. Um. 560 00:35:48,120 --> 00:35:50,520 Speaker 1: I know you don't do a lot of media. You've 561 00:35:50,600 --> 00:35:53,160 Speaker 1: done enough in your day, but it's something that you 562 00:35:53,280 --> 00:35:56,239 Speaker 1: don't really do uh a whole lot of lately. So 563 00:35:56,280 --> 00:36:00,480 Speaker 1: I um, I went through maybe the teen years. I 564 00:36:00,520 --> 00:36:03,800 Speaker 1: didn't do any fifteen years really and at lest it 565 00:36:03,880 --> 00:36:08,520 Speaker 1: really hurt your business. So early on, uh I was 566 00:36:08,600 --> 00:36:11,439 Speaker 1: I was on Wall Street Week more than anybody else 567 00:36:11,520 --> 00:36:17,360 Speaker 1: with Lewis we had earlier this year we had Anthony 568 00:36:17,360 --> 00:36:22,000 Speaker 1: Scaramucci who just bought the rights. I started up to 569 00:36:22,640 --> 00:36:25,480 Speaker 1: Wall Street Week, which was really kind of interesting, and 570 00:36:25,600 --> 00:36:32,319 Speaker 1: Liz and Saunders who occasionally guest hosted for So what 571 00:36:32,400 --> 00:36:35,000 Speaker 1: was it like doing uh that show back in the 572 00:36:35,080 --> 00:36:38,920 Speaker 1: day when there wasn't daily too? It wasn't you know, 573 00:36:38,960 --> 00:36:41,600 Speaker 1: the media landscape was so different. There was none, and 574 00:36:41,680 --> 00:36:44,799 Speaker 1: so Wall Street Week was so good because it was 575 00:36:44,840 --> 00:36:48,319 Speaker 1: the only show and uh Lou rook As there was 576 00:36:48,360 --> 00:36:54,239 Speaker 1: a real professional uh terrific uh interviewer and see her 577 00:36:55,120 --> 00:36:59,520 Speaker 1: uh great intellect. And so that show was what everybody. 578 00:36:59,560 --> 00:37:02,600 Speaker 1: Everybody watched it and everybody wanted to be on it. 579 00:37:03,040 --> 00:37:05,719 Speaker 1: And I was on it because I started so young 580 00:37:06,600 --> 00:37:08,560 Speaker 1: and I would do twenty three right out of school 581 00:37:08,560 --> 00:37:13,720 Speaker 1: something like well maybe, but so I just by stand 582 00:37:13,760 --> 00:37:15,279 Speaker 1: up time, I was on it a lot of it, 583 00:37:15,960 --> 00:37:21,120 Speaker 1: and that ran from I want to say, gies was 584 00:37:21,600 --> 00:37:26,440 Speaker 1: somewhere two thousand and some he passed away about a decade. 585 00:37:27,080 --> 00:37:28,959 Speaker 1: It's really really quite is it? That? Is it longer 586 00:37:29,000 --> 00:37:32,920 Speaker 1: than that? That? Wow, that's amazing. So um one of 587 00:37:32,920 --> 00:37:35,960 Speaker 1: the things I didn't get to ask about. So in 588 00:37:36,000 --> 00:37:38,000 Speaker 1: the early days of I s I, you were both 589 00:37:38,080 --> 00:37:42,799 Speaker 1: managing assets in a separate entity and doing research. How 590 00:37:42,800 --> 00:37:44,920 Speaker 1: do you juggle both of those? So I had a 591 00:37:45,000 --> 00:37:48,680 Speaker 1: very strong partner who led the asset management business, uh, 592 00:37:48,719 --> 00:37:52,120 Speaker 1: and we've just sold that that business didn't fit into 593 00:37:52,160 --> 00:37:55,080 Speaker 1: the ever Core is SI. Who was a partner and 594 00:37:55,080 --> 00:37:59,440 Speaker 1: who end up selling it? Al Metta, It was familiar 595 00:37:59,520 --> 00:38:02,680 Speaker 1: who is fick fixed income guy and is a firm 596 00:38:02,719 --> 00:38:04,600 Speaker 1: out of South South Africa that we sold it to. 597 00:38:04,800 --> 00:38:08,240 Speaker 1: And you also sold I s I. Bloomberg reported last 598 00:38:08,320 --> 00:38:11,120 Speaker 1: year that I s I was sold to ever Core 599 00:38:11,360 --> 00:38:15,400 Speaker 1: for a number of theoretically worth north of four million dollars. 600 00:38:15,560 --> 00:38:18,600 Speaker 1: Is that a real number or is that a just 601 00:38:18,719 --> 00:38:23,200 Speaker 1: a you know, a rough estimate. So, uh, Ralph Schlosstein 602 00:38:23,480 --> 00:38:26,400 Speaker 1: is the business operator. He is the person that is 603 00:38:26,520 --> 00:38:30,680 Speaker 1: driving ever Core and and he is the visionary for 604 00:38:30,719 --> 00:38:34,759 Speaker 1: putting this together. And so we have a five year 605 00:38:35,560 --> 00:38:39,279 Speaker 1: UH program with Evercore where our shares in I s 606 00:38:39,360 --> 00:38:42,960 Speaker 1: I vest into evercre uh in years one to three, 607 00:38:43,000 --> 00:38:46,640 Speaker 1: four and five, depending on performance metrics. And if we 608 00:38:46,840 --> 00:38:50,399 Speaker 1: meet all of our performance metrics, UH, it'll be over 609 00:38:51,400 --> 00:38:56,480 Speaker 1: dollars uh. And it's a terrific example of capitalism. Everybody's incentivize, 610 00:38:56,760 --> 00:39:00,239 Speaker 1: everybody's incentives are lined up perfectly to make the thing work. 611 00:39:00,280 --> 00:39:02,520 Speaker 1: Every corps wants it to work. You wanted to work. 612 00:39:02,600 --> 00:39:06,040 Speaker 1: I wanted to work. Everybody I I wants it to work. Uh. 613 00:39:06,040 --> 00:39:10,120 Speaker 1: And so we essentially have gone public. So now I'm 614 00:39:10,120 --> 00:39:12,279 Speaker 1: part of a publicly traded company. That that has to 615 00:39:12,360 --> 00:39:15,360 Speaker 1: be deeply satisfying after so many I mean this was 616 00:39:15,480 --> 00:39:20,719 Speaker 1: decades and suddenly for someone to say, look, clearly, you 617 00:39:20,880 --> 00:39:25,239 Speaker 1: have received accolades professionally for years and years. But at 618 00:39:25,280 --> 00:39:27,640 Speaker 1: a certain point when someone puts a dollar figure on 619 00:39:27,680 --> 00:39:30,320 Speaker 1: it and says, hey, what ED and team have built 620 00:39:30,480 --> 00:39:34,200 Speaker 1: is so valuable, here's what we want to pay them, 621 00:39:34,520 --> 00:39:36,359 Speaker 1: that has to be like, Wow, I guess we really 622 00:39:36,360 --> 00:39:39,160 Speaker 1: did this the right way. And what I've take the 623 00:39:39,200 --> 00:39:43,200 Speaker 1: deepest pride in is that the employees on half the 624 00:39:43,239 --> 00:39:47,239 Speaker 1: company and so this is a great experience for all 625 00:39:47,280 --> 00:39:50,600 Speaker 1: of us. UH. And because we now are vesting into 626 00:39:50,600 --> 00:39:54,000 Speaker 1: every course stock. Uh I really want ever course stock 627 00:39:54,080 --> 00:39:57,280 Speaker 1: to go up. So if it was a double uh, 628 00:39:57,520 --> 00:40:00,960 Speaker 1: it's theoretically more half the employ half of the company. 629 00:40:01,000 --> 00:40:04,960 Speaker 1: I s I stock was owned by employees. How typical 630 00:40:05,080 --> 00:40:07,920 Speaker 1: is that? Uh? Well, the whole thing is very is 631 00:40:08,040 --> 00:40:13,600 Speaker 1: very unique. You don't hear fifty. There's a disproportionate share 632 00:40:13,680 --> 00:40:15,680 Speaker 1: usually at the top, and then a little bit of 633 00:40:15,719 --> 00:40:20,440 Speaker 1: a stock plan. But that that's a huge I guess 634 00:40:20,560 --> 00:40:24,360 Speaker 1: everybody is aligned at that point. So by everybody. We 635 00:40:24,400 --> 00:40:27,600 Speaker 1: have fifty partners that on that and we have total 636 00:40:27,600 --> 00:40:33,200 Speaker 1: employees of about to fifty. But our keep after something 637 00:40:33,239 --> 00:40:39,120 Speaker 1: like this. The main problem is retention. And so you 638 00:40:39,120 --> 00:40:41,640 Speaker 1: speak to Google, you speak to athletes, speak to Facebook 639 00:40:42,120 --> 00:40:45,279 Speaker 1: or micro. In a previous generation, Microsoft and in Te 640 00:40:45,320 --> 00:40:48,200 Speaker 1: Francisco they had the same issue. At a certain point, 641 00:40:48,640 --> 00:40:51,319 Speaker 1: people start to have so much money they might why 642 00:40:51,320 --> 00:40:54,239 Speaker 1: do I have to work anymore? So uh so we 643 00:40:54,320 --> 00:40:57,160 Speaker 1: have a five or five year investing plan. So I 644 00:40:57,160 --> 00:41:01,080 Speaker 1: have have I guess almost at four and a half 645 00:41:01,160 --> 00:41:03,520 Speaker 1: years now in front of me. Okay, well, let's let's 646 00:41:03,520 --> 00:41:07,000 Speaker 1: hope you keep on to hold onto all your key, 647 00:41:07,040 --> 00:41:10,239 Speaker 1: all your key people, so you had mentioned some of 648 00:41:10,280 --> 00:41:16,760 Speaker 1: your early mentors. Who else were key mentors to you? So, um, 649 00:41:16,880 --> 00:41:20,880 Speaker 1: these these guys at M I T were really started 650 00:41:20,880 --> 00:41:24,719 Speaker 1: to change my life. At COUP and Paul Kotner or 651 00:41:24,880 --> 00:41:28,640 Speaker 1: two professors there, and then Otto Wegstein, who's such a 652 00:41:28,680 --> 00:41:32,279 Speaker 1: fabulous guy and I was so lucky to work for him. 653 00:41:32,320 --> 00:41:35,640 Speaker 1: And then I went to work for Jim Moltz at C. J. 654 00:41:35,800 --> 00:41:40,279 Speaker 1: Lawrence and he's just been a fabulous mentor for me, 655 00:41:40,560 --> 00:41:44,960 Speaker 1: you know, all all through this this time. And so 656 00:41:45,000 --> 00:41:49,360 Speaker 1: those were the guys that really formed my my my career. 657 00:41:49,880 --> 00:41:52,960 Speaker 1: Let me digress about mentoring because this has been something 658 00:41:53,040 --> 00:41:56,960 Speaker 1: I've thought about in the past. There was earlier in 659 00:41:57,080 --> 00:42:02,400 Speaker 1: the history of Wall Street a fairly robust mentoring sort 660 00:42:02,480 --> 00:42:06,360 Speaker 1: of mindset, and one of the things I've noticed is 661 00:42:06,440 --> 00:42:09,640 Speaker 1: that seems to have slipped away. You know, do do 662 00:42:09,719 --> 00:42:13,640 Speaker 1: you see that same sort of mentoring approach today on 663 00:42:13,680 --> 00:42:16,640 Speaker 1: the street that might have existed let's call it twenty 664 00:42:16,719 --> 00:42:20,920 Speaker 1: or thirty years ago. So, as I mentioned, it's possible 665 00:42:20,960 --> 00:42:26,240 Speaker 1: that research thrives best uh in a smaller, medium sized environment, 666 00:42:26,400 --> 00:42:29,040 Speaker 1: not a hundred thousand or two hundred thousand people who 667 00:42:29,040 --> 00:42:33,880 Speaker 1: are mentoring becomes more difficult just by nature size. Uh. 668 00:42:34,200 --> 00:42:38,920 Speaker 1: We've been uh growing so rapidly for the past twenty 669 00:42:39,000 --> 00:42:41,759 Speaker 1: something years. I don't think we've done a good job 670 00:42:41,800 --> 00:42:45,160 Speaker 1: of mentoring. Really, we've because we've just been pushing and 671 00:42:45,200 --> 00:42:48,680 Speaker 1: we've been hiring the best analysts in each space. Uh, 672 00:42:48,880 --> 00:42:51,960 Speaker 1: everyone who don't necessarily need a lot of mentoring at 673 00:42:52,000 --> 00:42:54,479 Speaker 1: that point, they don't need mentoring that at that point, 674 00:42:54,480 --> 00:42:59,720 Speaker 1: they've already been mentored. Uh. Ralph Schlastein at ever Cores 675 00:43:00,239 --> 00:43:06,480 Speaker 1: is really passionate about mentoring and growing talent from from within. 676 00:43:07,040 --> 00:43:09,800 Speaker 1: And so we've and they have had a much stronger 677 00:43:09,800 --> 00:43:14,200 Speaker 1: program than we've had. And so we are now launching 678 00:43:14,200 --> 00:43:18,719 Speaker 1: a career development Committee and a program specifically aimed at 679 00:43:18,800 --> 00:43:22,120 Speaker 1: mentoring people to give people a path forward. Well, well, 680 00:43:22,160 --> 00:43:24,000 Speaker 1: if you can't find anybody in to mentor, you can 681 00:43:24,040 --> 00:43:28,520 Speaker 1: always mentor me. I'm happy to assume those responsibilities. So 682 00:43:28,680 --> 00:43:32,200 Speaker 1: let's talk a little bit about UM. The investors who 683 00:43:32,280 --> 00:43:36,239 Speaker 1: influenced you. We mentioned Peter Lynch earlier on UM. What 684 00:43:36,360 --> 00:43:40,719 Speaker 1: other invents investors have you found to be influential to 685 00:43:40,760 --> 00:43:43,680 Speaker 1: your thought process? How you look at market cycles, how 686 00:43:43,680 --> 00:43:49,239 Speaker 1: you look at business cycles. So UM, Jim Maltz ran C. J. 687 00:43:49,400 --> 00:43:55,120 Speaker 1: Lawrence and is a great investor and strategist, and so 688 00:43:55,200 --> 00:43:58,920 Speaker 1: he influenced me a great deal. We also had a 689 00:43:58,960 --> 00:44:02,480 Speaker 1: strategist there name Stan Salixon who's unfortunately passed away, but 690 00:44:02,520 --> 00:44:06,279 Speaker 1: he was uh sort of nova on the scene while 691 00:44:06,320 --> 00:44:09,080 Speaker 1: he was with us, and then he went on to 692 00:44:09,160 --> 00:44:12,640 Speaker 1: Merrill Lynch to become their strategist and then an investor. 693 00:44:13,600 --> 00:44:18,240 Speaker 1: Uh Stan Drucket Miller has influenced me more than anybody else. 694 00:44:19,280 --> 00:44:22,640 Speaker 1: And um Drugon Mill is really an interesting, um gentleman. 695 00:44:22,719 --> 00:44:25,239 Speaker 1: Some of the work he's doing currently is quite uh 696 00:44:25,400 --> 00:44:31,360 Speaker 1: quite fascinating. And so that that group of of players 697 00:44:32,160 --> 00:44:35,680 Speaker 1: who I've been fortunate enough to work with have influenced 698 00:44:35,680 --> 00:44:40,280 Speaker 1: me a great deal. Louis Bacon is another one. Stevie 699 00:44:40,320 --> 00:44:43,839 Speaker 1: Cohen is another one. Paul Tutor Jones this this is 700 00:44:43,920 --> 00:44:46,239 Speaker 1: like the Hall of Fame. You're you're listing here. Well, 701 00:44:46,280 --> 00:44:48,640 Speaker 1: I've been lucky enough to spend some time with them 702 00:44:48,719 --> 00:44:52,200 Speaker 1: and study how they operate, and I've learned a lot 703 00:44:52,280 --> 00:44:55,759 Speaker 1: from them and try and uh put some of the 704 00:44:55,800 --> 00:44:58,160 Speaker 1: ideas that they used to work in my own work. 705 00:44:58,680 --> 00:45:03,640 Speaker 1: Bob Ferrell was a technician at Meryll Farrell's famous ten 706 00:45:03,760 --> 00:45:07,320 Speaker 1: Laws of of Markets. Yeah, I'll send you a copy 707 00:45:07,360 --> 00:45:11,440 Speaker 1: of it. Our mutual friend Dave Rosenberg had put out 708 00:45:11,440 --> 00:45:15,400 Speaker 1: a piece with the first time eversord printed ten Rules 709 00:45:15,520 --> 00:45:18,759 Speaker 1: of Bob Farrell and um, I ended up posting on 710 00:45:18,800 --> 00:45:21,880 Speaker 1: the internet because it was not publicly available anywhere. He 711 00:45:22,000 --> 00:45:26,520 Speaker 1: still puts out regularly. Agreed him every single week, and 712 00:45:26,800 --> 00:45:33,040 Speaker 1: so he uh, I have a pretty strong technical uh window, 713 00:45:33,440 --> 00:45:37,800 Speaker 1: and he helped me form that. People like Lee Cooperman 714 00:45:38,200 --> 00:45:41,000 Speaker 1: is a real role model for me and met mentor. 715 00:45:41,360 --> 00:45:44,920 Speaker 1: So Lee Cooperman was the best strategist on the street 716 00:45:45,239 --> 00:45:47,120 Speaker 1: when he was the Goldman Sachs. He was a sales 717 00:45:47,160 --> 00:45:50,040 Speaker 1: side before he before he launched Omega. Right, we have 718 00:45:50,160 --> 00:45:53,600 Speaker 1: him coming up next month, So he's uh, he's been 719 00:45:53,640 --> 00:45:59,120 Speaker 1: a legendary. Your list is really well, I've been lucky. 720 00:45:59,280 --> 00:46:01,799 Speaker 1: That's an amazing And I don't run mentors. I don't 721 00:46:01,840 --> 00:46:05,319 Speaker 1: just say I've learned a lot from from Bill Bill 722 00:46:05,360 --> 00:46:11,720 Speaker 1: Miller has I've always enjoyed his thought, his thought process, 723 00:46:11,800 --> 00:46:15,840 Speaker 1: His streak is he his streak is second only to yours. 724 00:46:16,200 --> 00:46:21,600 Speaker 1: He beat the SNPI fifteen consecutive years. Nobody's come remotely 725 00:46:21,640 --> 00:46:23,719 Speaker 1: close to it, although I don't know who the hell 726 00:46:23,800 --> 00:46:27,960 Speaker 1: is ever gonna beat a thirty five years accounting. No 727 00:46:28,000 --> 00:46:31,600 Speaker 1: one wants to. Well, you'd be surprised. I bet people 728 00:46:31,640 --> 00:46:34,360 Speaker 1: would be thrilled, thrilled to do it. Um, let me 729 00:46:34,360 --> 00:46:36,680 Speaker 1: ask you about some of the other interests you have. 730 00:46:36,800 --> 00:46:40,160 Speaker 1: There's a run of different committees and things are on. 731 00:46:40,560 --> 00:46:42,440 Speaker 1: Tell us about the China Institute. What do you do 732 00:46:42,520 --> 00:46:45,799 Speaker 1: with them? So when when we started I s I 733 00:46:46,480 --> 00:46:54,000 Speaker 1: the name is International International Strategy and Investments and so, UH, 734 00:46:54,160 --> 00:46:57,680 Speaker 1: you know that the world is becoming much more international, 735 00:46:57,760 --> 00:47:01,280 Speaker 1: much more globalized, and so that we had that focus. 736 00:47:01,840 --> 00:47:05,439 Speaker 1: And I think the emerging economies are going to play 737 00:47:05,480 --> 00:47:08,600 Speaker 1: a major role in the next decade two decades in 738 00:47:08,640 --> 00:47:12,240 Speaker 1: the way the world economy develops, and China is simply 739 00:47:13,040 --> 00:47:15,680 Speaker 1: the biggest, strongest one of them. So we have a 740 00:47:15,760 --> 00:47:20,000 Speaker 1: China research team. Don Strassheim heads that up, and UH, 741 00:47:20,120 --> 00:47:22,640 Speaker 1: I have a deep interest in China and some on 742 00:47:22,680 --> 00:47:25,160 Speaker 1: the board of the China Institute, and that gives me 743 00:47:25,360 --> 00:47:27,919 Speaker 1: a little extra window into into what's going on there. 744 00:47:28,160 --> 00:47:30,279 Speaker 1: Not too long ago I spoke to you and you 745 00:47:30,320 --> 00:47:32,919 Speaker 1: were either going to China or coming back from How 746 00:47:32,920 --> 00:47:35,880 Speaker 1: often do you, um, on that side of the world. Uh, 747 00:47:36,200 --> 00:47:39,600 Speaker 1: once once once a year. And and what do you 748 00:47:39,640 --> 00:47:43,960 Speaker 1: do when you are in country in China? Uh? Either 749 00:47:44,719 --> 00:47:48,880 Speaker 1: visit investors there or visit companies there. Quite fascinating. Do 750 00:47:48,960 --> 00:47:52,600 Speaker 1: you find anything that you witness when you have boots 751 00:47:52,600 --> 00:47:55,440 Speaker 1: on the ground. Is that different than just looking at 752 00:47:55,520 --> 00:48:01,400 Speaker 1: charts and looking at data? Changes the perspective, right, I'm um. 753 00:48:01,440 --> 00:48:06,640 Speaker 1: I'm definitely a hands on observer of the condition, and 754 00:48:06,719 --> 00:48:09,960 Speaker 1: so I really like traveling to places and seeing from 755 00:48:09,960 --> 00:48:12,320 Speaker 1: my own through my own eyes what's going on, talking 756 00:48:12,320 --> 00:48:15,399 Speaker 1: to people who are there. Uh. And I enjoyed talking 757 00:48:15,400 --> 00:48:17,759 Speaker 1: to investors. I think I learned from talking to investors 758 00:48:17,760 --> 00:48:21,680 Speaker 1: about what's happening. But I definitely love I travel. Uh, 759 00:48:21,880 --> 00:48:24,560 Speaker 1: not a huge amount of travel, about sixty six sixty 760 00:48:24,640 --> 00:48:27,439 Speaker 1: five days a year, which it's more than two months. 761 00:48:27,480 --> 00:48:31,959 Speaker 1: That's but for people, people will travel two months months, right, exactly. So, 762 00:48:32,400 --> 00:48:36,320 Speaker 1: but I feel like I'm learning uh on those trips. 763 00:48:36,400 --> 00:48:38,600 Speaker 1: I got into a debate with someone not too long 764 00:48:38,600 --> 00:48:41,160 Speaker 1: ago who was insisting the US is still in a 765 00:48:41,200 --> 00:48:47,400 Speaker 1: recession really bearished negative long gold short equities, and I 766 00:48:47,440 --> 00:48:49,200 Speaker 1: asked him, when was the last time you left your 767 00:48:49,200 --> 00:48:52,319 Speaker 1: trading tarret. Well, I got too much stuff going on 768 00:48:52,360 --> 00:48:54,319 Speaker 1: and go. Have you been to Seattle? Have you been 769 00:48:54,360 --> 00:48:57,719 Speaker 1: to Dallas? Have you been to San Francisco, Silicon Valley? 770 00:48:58,000 --> 00:49:00,719 Speaker 1: You can't. You can't go through Nebraska, o Iowa, or 771 00:49:00,760 --> 00:49:04,040 Speaker 1: South Dakota and tell me we're in a recession still 772 00:49:04,080 --> 00:49:06,960 Speaker 1: you if you get out from behind your desk and 773 00:49:07,000 --> 00:49:09,560 Speaker 1: look at what's going on in the real world, parts 774 00:49:09,560 --> 00:49:13,120 Speaker 1: of the country are just booming now. It's not evenly distributed. 775 00:49:13,160 --> 00:49:14,879 Speaker 1: I don't have to tell you. Lots of stuff are 776 00:49:14,880 --> 00:49:19,040 Speaker 1: still below par. But the folks who never seem to 777 00:49:19,120 --> 00:49:22,279 Speaker 1: leave their desk, I think they get. We call it 778 00:49:22,320 --> 00:49:26,560 Speaker 1: a fluorescent view of the world. And it's not very accurate, 779 00:49:26,640 --> 00:49:28,839 Speaker 1: is it. Yeah, Well, I'm very in tune with you 780 00:49:28,880 --> 00:49:32,040 Speaker 1: on that. First, I have our company surveys, which are uh, 781 00:49:32,080 --> 00:49:36,120 Speaker 1: you're asking somebody who is running a company, how's your business? 782 00:49:36,840 --> 00:49:38,520 Speaker 1: And people have if they have to look it up, 783 00:49:38,640 --> 00:49:41,960 Speaker 1: I'm not talking to the right person. They know it. Uh. 784 00:49:42,000 --> 00:49:46,759 Speaker 1: And that is better than anything in ten. It's not 785 00:49:46,840 --> 00:49:49,160 Speaker 1: quite as good as oh five and oh six, but 786 00:49:49,200 --> 00:49:54,600 Speaker 1: it's pretty good. But when I travel around the US, UH, 787 00:49:54,680 --> 00:49:58,080 Speaker 1: almost every place I go, when I talk to locals. 788 00:49:58,160 --> 00:50:02,120 Speaker 1: They say, it is booming, it's amazing, And I say, 789 00:50:02,160 --> 00:50:07,480 Speaker 1: places like New Orleans or Minneapolis or Nashville that you 790 00:50:07,480 --> 00:50:11,320 Speaker 1: wouldn't think of right off the bat. Uh as having 791 00:50:11,560 --> 00:50:15,839 Speaker 1: that response are pretty strong. So I think the main 792 00:50:15,920 --> 00:50:20,759 Speaker 1: message here is that the the odds that the US 793 00:50:20,840 --> 00:50:25,680 Speaker 1: economy is in recession are very very low. What about 794 00:50:25,719 --> 00:50:28,680 Speaker 1: falling into recession in the next few quarters or year? 795 00:50:29,320 --> 00:50:33,120 Speaker 1: So um, and I know we're not we don't want 796 00:50:33,120 --> 00:50:35,480 Speaker 1: to talk about forecasts. I said, Hey, we really don't 797 00:50:35,480 --> 00:50:39,440 Speaker 1: do forecasts. But in context of people who have missed 798 00:50:39,520 --> 00:50:43,560 Speaker 1: this bullmarket and are waiting for the next collapse, what 799 00:50:43,600 --> 00:50:47,600 Speaker 1: do you say to folks like that? So this isn't uh, 800 00:50:47,760 --> 00:50:50,040 Speaker 1: this isn't so much a forecast as though. It's an 801 00:50:50,040 --> 00:50:54,479 Speaker 1: observation about where we are in the business cycle. And 802 00:50:54,719 --> 00:50:59,040 Speaker 1: so this is something you can study and uh, in 803 00:50:59,120 --> 00:51:01,160 Speaker 1: terms of where we are, we're still early in the 804 00:51:01,200 --> 00:51:04,719 Speaker 1: business cycle. Say, for example, housing starts are barely over 805 00:51:04,760 --> 00:51:08,440 Speaker 1: a million, the FED hasn't started to tighten yet, wages 806 00:51:08,440 --> 00:51:12,239 Speaker 1: haven't started to accelerate yet. So these are all conditions 807 00:51:12,280 --> 00:51:17,080 Speaker 1: that suggests the next recession is maybe five years out. Really, Uh, 808 00:51:18,520 --> 00:51:21,920 Speaker 1: every single one of these conditions and wages fed tightening 809 00:51:22,640 --> 00:51:27,480 Speaker 1: housing all suggests that the recession is way out. So, uh, 810 00:51:27,520 --> 00:51:31,560 Speaker 1: that's my starting point, and you change that if conditions changed. 811 00:51:31,600 --> 00:51:33,840 Speaker 1: The biggest thing that could change would be if inflation 812 00:51:34,200 --> 00:51:38,120 Speaker 1: were to really come on strong. And at the moment, 813 00:51:38,360 --> 00:51:41,040 Speaker 1: I think it's picking up on the wage side, but 814 00:51:41,160 --> 00:51:43,920 Speaker 1: that's about it so far. So I think we're still 815 00:51:44,640 --> 00:51:46,520 Speaker 1: you know, if you had to have a scientific answer 816 00:51:46,520 --> 00:51:49,719 Speaker 1: about when the next recession is five years out, is 817 00:51:49,760 --> 00:51:53,560 Speaker 1: the best guess. The yield curve is NOE near inverted. 818 00:51:53,800 --> 00:51:56,960 Speaker 1: And when we look at most of the metrics, they're 819 00:51:57,080 --> 00:52:01,400 Speaker 1: continuing to creep up, They're continuing to improve. Like I'm 820 00:52:01,480 --> 00:52:03,920 Speaker 1: always scratching my head trying to figure out is it 821 00:52:04,080 --> 00:52:07,799 Speaker 1: just confirmation bias and people who are positioned wrong are 822 00:52:07,920 --> 00:52:11,160 Speaker 1: rooting for something? Or I'm amazed when I talk to 823 00:52:11,200 --> 00:52:15,040 Speaker 1: people who have been, you know, just so much on 824 00:52:15,080 --> 00:52:17,239 Speaker 1: the wrong side of the trade. I think that I 825 00:52:17,239 --> 00:52:23,000 Speaker 1: think it's hard to overestimate the impact of O eight 826 00:52:23,000 --> 00:52:28,040 Speaker 1: oh nine psychology. Uh. And then you know, there are 827 00:52:28,080 --> 00:52:31,640 Speaker 1: a lot of negatives, like you know, Greece is an 828 00:52:31,680 --> 00:52:36,520 Speaker 1: uncertainty uh and China is an uncertainty and profit margins 829 00:52:36,560 --> 00:52:41,440 Speaker 1: are very high, and the way that quantitative easing plays 830 00:52:41,480 --> 00:52:46,640 Speaker 1: out these are unknowable. But I think investors are sort 831 00:52:46,680 --> 00:52:51,560 Speaker 1: of positioned for negative outcomes on those and if they 832 00:52:51,560 --> 00:52:54,920 Speaker 1: were to be positive outcomes like or even neutral or neutral, 833 00:52:55,560 --> 00:52:58,799 Speaker 1: then then the market is probably okay. But on on 834 00:52:58,840 --> 00:53:01,400 Speaker 1: the economy, which someone different than the market. But on 835 00:53:01,440 --> 00:53:07,120 Speaker 1: the economy, I'm sure it's okay today. And the destabilizers 836 00:53:07,160 --> 00:53:12,800 Speaker 1: are inflation, which we don't have now, UH, FED FED tightening, 837 00:53:13,080 --> 00:53:15,200 Speaker 1: which we don't have now, although we could see that. 838 00:53:15,320 --> 00:53:18,840 Speaker 1: The theory is that that starts later this year fighting 839 00:53:18,960 --> 00:53:26,239 Speaker 1: I mean by aggressive FED tightening, um, and that's way off. Yeah, 840 00:53:26,280 --> 00:53:30,600 Speaker 1: they're gonna start, but they'll go from ultra easy too 841 00:53:30,600 --> 00:53:33,799 Speaker 1: extremely easy. We have to work our way up two 842 00:53:33,880 --> 00:53:38,440 Speaker 1: merely easy, is what you're saying. And um, so we we. 843 00:53:38,560 --> 00:53:41,680 Speaker 1: I asked you about the China Institute. Tell me what 844 00:53:41,719 --> 00:53:45,440 Speaker 1: you do with the New York Public Libraries financial services? 845 00:53:45,480 --> 00:53:50,560 Speaker 1: So that just participating in a speaker's program, it's they 846 00:53:50,560 --> 00:53:55,840 Speaker 1: have about twitter people at each UH sessions a breakfast session, 847 00:53:56,280 --> 00:54:00,560 Speaker 1: and they get some great speakers in and I interesting 848 00:54:00,600 --> 00:54:03,919 Speaker 1: to go and I pick a group of clients, uh 849 00:54:03,960 --> 00:54:07,200 Speaker 1: and it's a nice venue for seeing people that you 850 00:54:07,239 --> 00:54:11,000 Speaker 1: wouldn't ordinarily see in another setting. So Warren Buffett, Bill 851 00:54:11,040 --> 00:54:14,960 Speaker 1: Clinton have been speakers and it's a nice way to 852 00:54:14,960 --> 00:54:19,640 Speaker 1: see uh some ideas that you wouldn't otherwise get very interesting. 853 00:54:19,640 --> 00:54:22,200 Speaker 1: And I know you do something similar in your own 854 00:54:22,200 --> 00:54:25,080 Speaker 1: office where you have people come in and present in 855 00:54:25,120 --> 00:54:29,320 Speaker 1: your in your morning meetings as well. Um, the leadership forum, 856 00:54:29,480 --> 00:54:32,399 Speaker 1: what what do you do with that? Uh, that's not 857 00:54:32,480 --> 00:54:35,080 Speaker 1: much of a what is the leadership forum? I have 858 00:54:35,080 --> 00:54:38,840 Speaker 1: no idea. I'm sorry, that is the it's the leadership forum? 859 00:54:38,880 --> 00:54:44,960 Speaker 1: Is the public library? All right? Son? That into a second. 860 00:54:45,960 --> 00:54:47,759 Speaker 1: So it's a leadership forum at the New York Public 861 00:54:47,800 --> 00:54:51,520 Speaker 1: Libraries Financial Services Advisory Committee. I can't read my own 862 00:54:51,520 --> 00:54:54,880 Speaker 1: typing about the the Economic Club of New York. So 863 00:54:54,960 --> 00:54:57,640 Speaker 1: it's a it's a very different thing than the than 864 00:54:57,680 --> 00:55:01,719 Speaker 1: the library program. But uh, they've been going since the 865 00:55:01,760 --> 00:55:07,680 Speaker 1: eighteen hundreds and um they get speakers like hundred forty 866 00:55:07,680 --> 00:55:11,560 Speaker 1: six speakers so far, and it's a great forum for 867 00:55:11,680 --> 00:55:14,920 Speaker 1: New York to have people come in. The last speaker 868 00:55:15,120 --> 00:55:20,239 Speaker 1: was was Jack was Jack Ma Ali Baba's founders Ali 869 00:55:20,320 --> 00:55:23,440 Speaker 1: Baba's Finder And it's it's just they have a great roster, 870 00:55:23,719 --> 00:55:26,560 Speaker 1: you know, the chairman, the fit comes on a regular basis, 871 00:55:27,080 --> 00:55:29,560 Speaker 1: and so it's just a it's a place that it's 872 00:55:29,560 --> 00:55:32,839 Speaker 1: a large form. There's a thousand people and so it's 873 00:55:33,000 --> 00:55:38,160 Speaker 1: but it's a big room. It's a big room. Very interesting. Um, 874 00:55:38,239 --> 00:55:40,879 Speaker 1: let me keep working through my list. By the way, 875 00:55:40,960 --> 00:55:44,920 Speaker 1: these last half dozen or so questions I'm saving are 876 00:55:44,960 --> 00:55:47,600 Speaker 1: are the same questions I ask everybody. Let me go 877 00:55:47,719 --> 00:55:52,480 Speaker 1: through some of the questions that, um wow, you answered 878 00:55:52,680 --> 00:55:54,840 Speaker 1: two of them. You answered where we are in the 879 00:55:54,880 --> 00:55:58,440 Speaker 1: economic cycle? You answered that you're really a hybrid between 880 00:55:58,480 --> 00:56:07,040 Speaker 1: a strategists and an economist, and uh what, there was 881 00:56:07,080 --> 00:56:11,560 Speaker 1: no eureka moment. You basically just started just kept on almight, Tya, 882 00:56:11,640 --> 00:56:16,720 Speaker 1: and kept going, Um, so you you hinted about quee 883 00:56:17,040 --> 00:56:19,479 Speaker 1: and the Federal Reserve, So let's explore that a little bit. 884 00:56:19,800 --> 00:56:23,840 Speaker 1: So what makes QUI so unique? What makes the unwind 885 00:56:23,880 --> 00:56:27,520 Speaker 1: of QUEI so unique? And can't the Fed just hold 886 00:56:27,560 --> 00:56:30,920 Speaker 1: this um fixed income paper until maturity? I think the 887 00:56:30,960 --> 00:56:33,840 Speaker 1: average uration is seven years. Do they have to actually 888 00:56:33,920 --> 00:56:37,080 Speaker 1: unwind QI or can they just let it run off naturally? 889 00:56:37,840 --> 00:56:40,920 Speaker 1: So they they can and will I think let it 890 00:56:40,960 --> 00:56:44,200 Speaker 1: run off naturally over the next five or six years. 891 00:56:44,360 --> 00:56:47,480 Speaker 1: The paper is something like a six year duration, so 892 00:56:48,239 --> 00:56:53,160 Speaker 1: it should mature over time. The the Federal Reserve has 893 00:56:53,200 --> 00:56:57,799 Speaker 1: become much more important because we have so limited we've 894 00:56:57,840 --> 00:57:01,600 Speaker 1: limited maneuvering room on fiscal pile. Right the Congress is 895 00:57:01,640 --> 00:57:05,240 Speaker 1: basically just grid locked and doing nothing, and the budget deficit. 896 00:57:05,880 --> 00:57:08,319 Speaker 1: It barely gets back to a balance and then we 897 00:57:08,400 --> 00:57:11,879 Speaker 1: go back into deficit. So we we don't have many 898 00:57:11,920 --> 00:57:14,640 Speaker 1: degrees of freedom when it comes to fiscal policy. So 899 00:57:14,719 --> 00:57:17,120 Speaker 1: as a result, we've had to operate more and more 900 00:57:17,360 --> 00:57:20,920 Speaker 1: on monetary policy. And and that's why the FED has 901 00:57:20,960 --> 00:57:26,320 Speaker 1: become a much more prominent institution UH in our country, 902 00:57:26,640 --> 00:57:29,240 Speaker 1: with you know, giving speeches all the time, different members 903 00:57:29,280 --> 00:57:32,000 Speaker 1: and sort of like rock stars in the system. They 904 00:57:32,200 --> 00:57:34,600 Speaker 1: always used to give speeches, nobody paid attention to, nobody 905 00:57:34,600 --> 00:57:37,360 Speaker 1: covered it. It It was just really inside baseball sort and 906 00:57:37,400 --> 00:57:39,880 Speaker 1: they didn't give as many speeches. There are much more 907 00:57:39,920 --> 00:57:42,480 Speaker 1: and more today in a bigger forum each time they 908 00:57:42,520 --> 00:57:47,440 Speaker 1: give it. UH. In terms of qwe UH the UH. 909 00:57:47,600 --> 00:57:50,200 Speaker 1: The overarching problem first is that it's not only QUI 910 00:57:50,320 --> 00:57:54,720 Speaker 1: here is QUI and the ECB in Europe and KWI 911 00:57:54,840 --> 00:57:57,560 Speaker 1: in Japan. Uh. So we're gonna end up with something 912 00:57:57,600 --> 00:58:01,800 Speaker 1: like twelve trillion dollars uh and que in a year 913 00:58:01,880 --> 00:58:03,880 Speaker 1: or year year and a half round between all three 914 00:58:04,000 --> 00:58:07,320 Speaker 1: all three, and so then the question is, you know, 915 00:58:07,360 --> 00:58:11,400 Speaker 1: how can we unwind our que? I think that when 916 00:58:11,440 --> 00:58:17,560 Speaker 1: the Fed tightens, uh, there'll be a moment of silence 917 00:58:18,280 --> 00:58:21,280 Speaker 1: to see if we're still alive. And if we are, 918 00:58:21,400 --> 00:58:24,880 Speaker 1: people are going to relax some that we got the shot, 919 00:58:25,520 --> 00:58:28,080 Speaker 1: it didn't kill us uh, and then they'll start to 920 00:58:28,160 --> 00:58:30,240 Speaker 1: think about, well, the next tightening, the tightening act of that, 921 00:58:30,320 --> 00:58:32,840 Speaker 1: and whether they'll let the fifth balance sheet run off 922 00:58:32,840 --> 00:58:35,880 Speaker 1: and whether that creates a problem in and of itself. Uh. 923 00:58:35,920 --> 00:58:38,040 Speaker 1: So we're gonna go from tightening and as soon as 924 00:58:38,080 --> 00:58:40,640 Speaker 1: one is under a belt, people are gonna start looking 925 00:58:40,680 --> 00:58:43,320 Speaker 1: forward at the at the next tightening, and it'll be 926 00:58:43,560 --> 00:58:45,439 Speaker 1: it's gonna to the next, to the next. It's gonna 927 00:58:45,440 --> 00:58:50,080 Speaker 1: be constant discussion. The FIT is indicated very strongly that 928 00:58:50,120 --> 00:58:55,280 Speaker 1: they will have a more uh responsive function to tightening 929 00:58:55,520 --> 00:58:58,760 Speaker 1: as opposed to every meeting twenty five basis points and 930 00:58:58,800 --> 00:59:02,840 Speaker 1: so uh if that's what happens, there'll be much discussion 931 00:59:03,040 --> 00:59:06,080 Speaker 1: before every meeting or they're gonna pass this meeting or 932 00:59:06,120 --> 00:59:08,480 Speaker 1: tighten this meeting because they go fifty. And then when 933 00:59:08,480 --> 00:59:10,280 Speaker 1: you get down the road, ifn FED funds are two, 934 00:59:10,560 --> 00:59:12,680 Speaker 1: there might even be a notion they might even cut 935 00:59:12,800 --> 00:59:15,080 Speaker 1: rates at the next meeting. So that's going to be 936 00:59:16,120 --> 00:59:20,840 Speaker 1: I think that having Stan Fisher the Vice Chairman of 937 00:59:20,840 --> 00:59:25,480 Speaker 1: the Fed UH there UH will be a great addition 938 00:59:26,200 --> 00:59:31,680 Speaker 1: to yelling and Dudley uh in giving the world some 939 00:59:31,920 --> 00:59:35,439 Speaker 1: vision about how the US might unwind its balance sheet. 940 00:59:35,840 --> 00:59:38,840 Speaker 1: And then if we can do it, UH, they'll give 941 00:59:39,080 --> 00:59:41,280 Speaker 1: a big leg up for Europe and Japan to think 942 00:59:41,280 --> 00:59:44,120 Speaker 1: about whether they can unwind their balance sheets. But those are, 943 00:59:44,520 --> 00:59:46,920 Speaker 1: you know, three or four or five years out. So 944 00:59:47,040 --> 00:59:52,040 Speaker 1: two is really fairly accommodat if we take it, take 945 00:59:52,120 --> 00:59:56,439 Speaker 1: FED funds rates up to two, that's still relatively low 946 00:59:56,520 --> 01:00:02,320 Speaker 1: rates historically. Can the economy absorb a two percent funds right? Well, first, 947 01:00:02,720 --> 01:00:04,919 Speaker 1: we don't have to answer that question today. We'll we'll 948 01:00:04,960 --> 01:00:08,960 Speaker 1: see day by day. Still data dependent, data dependent, and 949 01:00:10,640 --> 01:00:12,240 Speaker 1: it seems as though it should be able to. There's 950 01:00:12,280 --> 01:00:15,320 Speaker 1: one point I'd like to raise here is that we 951 01:00:15,400 --> 01:00:18,720 Speaker 1: talk about the one or two percent funds rate and 952 01:00:19,320 --> 01:00:22,800 Speaker 1: we also have a four train dollar balance sheet, or 953 01:00:22,840 --> 01:00:25,000 Speaker 1: maybe it goes to three trillion, But we have a 954 01:00:25,040 --> 01:00:29,320 Speaker 1: huge balance sheet, and there's the New York Fed in 955 01:00:29,320 --> 01:00:33,280 Speaker 1: particular has done work, uh that having that big a 956 01:00:33,320 --> 01:00:37,400 Speaker 1: balance sheet means that the funds rate isn't zero, that 957 01:00:37,520 --> 01:00:41,800 Speaker 1: it's negative. So when I walked over here, I was thinking, 958 01:00:41,800 --> 01:00:45,640 Speaker 1: I'm in a funds rate that's minus three percent, not zero, 959 01:00:45,720 --> 01:00:48,320 Speaker 1: and so how do you get to minus? The New 960 01:00:48,400 --> 01:00:52,040 Speaker 1: York Fed said that relative it's real terms, not nominal terms. 961 01:00:52,120 --> 01:00:56,440 Speaker 1: Is that just in norminal terms, that bion is the 962 01:00:56,480 --> 01:01:00,080 Speaker 1: equivalent to cutting the funds rate fifty basis points? So 963 01:01:00,120 --> 01:01:04,280 Speaker 1: it's easy to fifty basis points. But at zero you 964 01:01:04,280 --> 01:01:07,160 Speaker 1: can't cut a fifty basis points. But we've we've now 965 01:01:07,240 --> 01:01:11,959 Speaker 1: done three trillion in in quantity of easing. Obviously that's 966 01:01:12,520 --> 01:01:18,120 Speaker 1: six six and that's three basis points. So well that's 967 01:01:18,120 --> 01:01:21,560 Speaker 1: even close. I do think that there's uh that the 968 01:01:21,560 --> 01:01:27,200 Speaker 1: funds rate might be in negative territory, uh in a sense. 969 01:01:27,280 --> 01:01:28,800 Speaker 1: And so when they start to tighten, if they get 970 01:01:28,800 --> 01:01:31,920 Speaker 1: to say two, and the balance sheet is you know, 971 01:01:32,280 --> 01:01:35,240 Speaker 1: has been shrunk by a trillion dollars, the funds rate 972 01:01:35,280 --> 01:01:38,080 Speaker 1: could still be one and a half or something, and 973 01:01:38,120 --> 01:01:42,360 Speaker 1: that's before we start talking. Hey, we're a one inflation environment, 974 01:01:42,800 --> 01:01:47,960 Speaker 1: so zero adjusted for one inflation is also a negative 975 01:01:48,760 --> 01:01:51,520 Speaker 1: a negative number. So the next the next big event 976 01:01:51,600 --> 01:01:54,680 Speaker 1: in this space, UH is where they're not wages. Wages 977 01:01:54,720 --> 01:01:58,840 Speaker 1: are accelerating, and it looks as though they are. So 978 01:01:58,920 --> 01:02:01,440 Speaker 1: it's been it's been very public that we've seen some 979 01:02:01,520 --> 01:02:05,520 Speaker 1: of the minimum wages go up. We've had the McDonald's announcement, 980 01:02:05,520 --> 01:02:09,600 Speaker 1: we've had the Walmart announcement. UH. San Francisco, Seattle, Los 981 01:02:09,680 --> 01:02:14,920 Speaker 1: Angeles all raised their minimum wage. And but depending on 982 01:02:15,160 --> 01:02:18,920 Speaker 1: whose data use, it's not an insubstantial number of people 983 01:02:19,040 --> 01:02:22,720 Speaker 1: earning the minimum wage. But the bulk of Americans, the 984 01:02:22,760 --> 01:02:26,520 Speaker 1: bulk of middle middle class America UM, don't earn the 985 01:02:26,520 --> 01:02:29,440 Speaker 1: minimum wage. There they're the median income is about fifty 986 01:02:29,480 --> 01:02:32,760 Speaker 1: three thousand dollars or so a year. When does middle 987 01:02:32,800 --> 01:02:38,920 Speaker 1: America start to see real wage gains? Now? Now? So 988 01:02:39,160 --> 01:02:43,680 Speaker 1: in the past, wages have accelerated when unemployment has come 989 01:02:43,720 --> 01:02:47,840 Speaker 1: below five and a half. So we're we're there, and 990 01:02:48,080 --> 01:02:51,200 Speaker 1: these wage increases you mentioned would seem to be the 991 01:02:51,240 --> 01:02:54,160 Speaker 1: smoke that would occur when you're starting to get a 992 01:02:54,160 --> 01:02:57,840 Speaker 1: tighter labor market. There's an employment cost index, the gunment 993 01:02:57,880 --> 01:03:02,080 Speaker 1: measure that's moved from one eight to two six, and 994 01:03:02,120 --> 01:03:05,880 Speaker 1: then average generally earnings, another measure has moved from two 995 01:03:05,920 --> 01:03:11,640 Speaker 1: to two point three. And this morning the UK wages 996 01:03:11,680 --> 01:03:14,320 Speaker 1: came out and they're up to two point nine and 997 01:03:14,360 --> 01:03:17,040 Speaker 1: their uneployment rate also is five and a half. So 998 01:03:17,200 --> 01:03:20,520 Speaker 1: I think when we look back at this time five 999 01:03:20,600 --> 01:03:24,080 Speaker 1: years from now, we'll say this was about when US 1000 01:03:24,120 --> 01:03:27,680 Speaker 1: wages started to accelerate. And that's a big deal because 1001 01:03:27,720 --> 01:03:29,720 Speaker 1: I think a lot of the feeling we talked about 1002 01:03:29,760 --> 01:03:33,600 Speaker 1: earlier about the economy not doing well, it's because people 1003 01:03:33,640 --> 01:03:36,520 Speaker 1: are not getting pay increases. If the average pay is 1004 01:03:36,600 --> 01:03:39,560 Speaker 1: up two, then a lot of people didn't get a 1005 01:03:39,560 --> 01:03:42,160 Speaker 1: pay increase. They're flat with inflation or they got one, 1006 01:03:42,320 --> 01:03:46,360 Speaker 1: and their costs relative to increase health care and increased 1007 01:03:46,920 --> 01:03:50,880 Speaker 1: education expenses, what Middle America is paying for feels like 1008 01:03:50,920 --> 01:03:52,520 Speaker 1: you all these things are going up and I'm staying 1009 01:03:52,560 --> 01:03:55,400 Speaker 1: the same. It's also psychology. You know, if you go 1010 01:03:55,480 --> 01:03:59,200 Speaker 1: home and say, hey, I got a one pay increase, 1011 01:04:01,000 --> 01:04:03,280 Speaker 1: it doesn't make you feel like you're a star. And 1012 01:04:03,320 --> 01:04:06,200 Speaker 1: so I think if if wages pick up. It'll make 1013 01:04:06,200 --> 01:04:10,720 Speaker 1: the economy feel better in addition to just making retail 1014 01:04:10,760 --> 01:04:13,000 Speaker 1: sales better. So how does that was the next question 1015 01:04:13,080 --> 01:04:17,440 Speaker 1: is how do how does the beginning of rising wages 1016 01:04:17,800 --> 01:04:21,920 Speaker 1: impact the overall economy? Is it just retail sales? Can 1017 01:04:21,960 --> 01:04:25,160 Speaker 1: we get a virtuous cycle where people start spending more, 1018 01:04:25,600 --> 01:04:29,320 Speaker 1: companies higher and do more capex and good things. Well, 1019 01:04:29,360 --> 01:04:32,919 Speaker 1: this is in my view, we have been in an 1020 01:04:32,920 --> 01:04:37,400 Speaker 1: evolutionary mode for six years now. You know where things 1021 01:04:37,800 --> 01:04:41,640 Speaker 1: change a little bit over time. Uh, the places and 1022 01:04:41,680 --> 01:04:45,160 Speaker 1: I mentioned like a Seattle, their economy gets better, and 1023 01:04:45,200 --> 01:04:47,920 Speaker 1: then you can see it's getting better and employment is 1024 01:04:47,960 --> 01:04:52,000 Speaker 1: now up, uh, well above his prior peak. I've been 1025 01:04:52,000 --> 01:04:58,280 Speaker 1: watching lately employment of young people thirty four and that's 1026 01:04:58,320 --> 01:05:01,640 Speaker 1: gotten strong. It's up three and a half sent now. Uh, 1027 01:05:01,680 --> 01:05:03,840 Speaker 1: and it's well above it's up three three million, or 1028 01:05:03,840 --> 01:05:06,560 Speaker 1: about ten percent from the low point five years ago. 1029 01:05:07,160 --> 01:05:11,600 Speaker 1: And so these are these are hard to overlook improvements. 1030 01:05:12,200 --> 01:05:14,400 Speaker 1: And that was a segment that was lagging the moment. 1031 01:05:15,040 --> 01:05:18,720 Speaker 1: In that group, recent college graduates. Bad did not feel right. 1032 01:05:18,800 --> 01:05:22,600 Speaker 1: Bad is okay, that's no sugarcoating it. They really felt 1033 01:05:22,640 --> 01:05:25,880 Speaker 1: that they were living with their parents. They weren't forming households, 1034 01:05:25,880 --> 01:05:28,240 Speaker 1: they weren't getting married, they weren't moving out of their 1035 01:05:28,280 --> 01:05:31,760 Speaker 1: parents house. Is that another part of the cycle that 1036 01:05:31,760 --> 01:05:33,920 Speaker 1: that's ahead of us. That's that's what we're looking at. 1037 01:05:34,200 --> 01:05:37,760 Speaker 1: So that's this five year notion. Really, there are a 1038 01:05:37,800 --> 01:05:40,520 Speaker 1: lot of things that are ticking up here that make 1039 01:05:40,600 --> 01:05:46,320 Speaker 1: that a very plausible decision. It's not just a random number. 1040 01:05:46,360 --> 01:05:49,080 Speaker 1: You're looking at all these other metrics that all have 1041 01:05:49,160 --> 01:05:51,360 Speaker 1: a lot of runway ahead of them. The main the 1042 01:05:51,360 --> 01:05:54,840 Speaker 1: main metrics that give you the five years. Uh, we 1043 01:05:54,880 --> 01:05:58,280 Speaker 1: haven't had wages inflation yet, we haven't had fit tightening 1044 01:05:58,400 --> 01:06:01,680 Speaker 1: yet we have, and it had housing starts well over 1045 01:06:01,720 --> 01:06:05,080 Speaker 1: a million yet. And after those things happen, is when 1046 01:06:05,360 --> 01:06:08,880 Speaker 1: you start the clock for five years, and then you say, well, 1047 01:06:08,920 --> 01:06:13,000 Speaker 1: what's going to drive it for five years? And the 1048 01:06:13,240 --> 01:06:16,640 Speaker 1: employment and in the millennials could drive it. Household formation 1049 01:06:16,920 --> 01:06:19,760 Speaker 1: could drive it. Technology, you could drive it. Uh. So 1050 01:06:19,920 --> 01:06:21,760 Speaker 1: those are the things that could make it go for 1051 01:06:21,840 --> 01:06:24,439 Speaker 1: five years. And those to me, I feel like they're 1052 01:06:24,560 --> 01:06:28,640 Speaker 1: they're starting to fall in place. And wages also will 1053 01:06:29,080 --> 01:06:32,600 Speaker 1: be a driver, uh if they start to accelerate. So 1054 01:06:33,440 --> 01:06:35,240 Speaker 1: let's take the look at the other side. Of it. 1055 01:06:35,280 --> 01:06:37,160 Speaker 1: And I'm on the same side of the street as 1056 01:06:37,200 --> 01:06:40,880 Speaker 1: you are in terms of being very negative during the 1057 01:06:41,360 --> 01:06:46,120 Speaker 1: last bubble during seven oh eight and just seeing everything 1058 01:06:46,160 --> 01:06:49,320 Speaker 1: starts to fall apart, and I'm seeing all the things 1059 01:06:49,360 --> 01:06:52,320 Speaker 1: you're seeing. I see a lot of positives, but that 1060 01:06:52,320 --> 01:06:54,919 Speaker 1: always makes me nervous. What should we be looking at 1061 01:06:55,400 --> 01:06:59,080 Speaker 1: if we want to start to hedge our bets or 1062 01:06:59,160 --> 01:07:03,240 Speaker 1: start to get an early warning if things don't work out. 1063 01:07:03,280 --> 01:07:06,080 Speaker 1: What sort of data points would you suggest people pay 1064 01:07:06,120 --> 01:07:09,240 Speaker 1: attention to. Well, first, as I mentioned, you know, there 1065 01:07:09,240 --> 01:07:15,360 Speaker 1: are a lot of of significant negatives now, like Europe 1066 01:07:15,520 --> 01:07:19,440 Speaker 1: might not work and I don't want The odds are 1067 01:07:19,480 --> 01:07:21,040 Speaker 1: one in a hundred or one in a million, or 1068 01:07:21,080 --> 01:07:23,400 Speaker 1: one in ten, but it's a non zero now, it's 1069 01:07:23,400 --> 01:07:27,959 Speaker 1: a non zero. And if I tell you the chance 1070 01:07:28,000 --> 01:07:29,960 Speaker 1: of me getting run over by a bus when I 1071 01:07:30,000 --> 01:07:31,960 Speaker 1: walk back to my office is one in a hundred. 1072 01:07:33,000 --> 01:07:36,600 Speaker 1: If I told you that, I just stay here. Uh. 1073 01:07:36,680 --> 01:07:38,840 Speaker 1: And so you know there's a there's a risk there, 1074 01:07:39,360 --> 01:07:41,640 Speaker 1: and that will probably get resolved in the next year. 1075 01:07:41,720 --> 01:07:44,720 Speaker 1: As to where not you know, the Greek exit occurs 1076 01:07:44,800 --> 01:07:48,160 Speaker 1: or not, China is a is a concern they're going 1077 01:07:48,200 --> 01:07:51,720 Speaker 1: through three different problems at once, and whether they can 1078 01:07:51,720 --> 01:07:55,040 Speaker 1: pull that off is a concern. So let me guess 1079 01:07:55,040 --> 01:07:58,640 Speaker 1: what the three problems in China are so aside from 1080 01:07:58,680 --> 01:08:02,640 Speaker 1: demographics unless you can insider that problem. Um. One, their 1081 01:08:02,640 --> 01:08:06,160 Speaker 1: economy has been slowing, although slowing to seven or eight 1082 01:08:06,160 --> 01:08:12,400 Speaker 1: percent isn't but down from that's a issue. Second, whether 1083 01:08:12,440 --> 01:08:15,600 Speaker 1: you talk to Jim Chanos or any number of different people, 1084 01:08:16,080 --> 01:08:19,479 Speaker 1: it certainly looks like their stock market is, if not 1085 01:08:19,640 --> 01:08:24,439 Speaker 1: in a bubble, well price and and extended relative to 1086 01:08:24,920 --> 01:08:28,960 Speaker 1: everybody else's uh stock market. And I can't even guess 1087 01:08:28,960 --> 01:08:34,800 Speaker 1: with the third one, So um my three problems. I 1088 01:08:34,840 --> 01:08:39,679 Speaker 1: also think Jim Chanos is is a very bright guy, 1089 01:08:39,720 --> 01:08:42,559 Speaker 1: and I've learned a lot from him about China, uh, 1090 01:08:43,439 --> 01:08:47,439 Speaker 1: very early on identifying problems there before anybody else or 1091 01:08:47,800 --> 01:08:51,760 Speaker 1: so in my view, the three problems are First, they 1092 01:08:51,760 --> 01:08:55,479 Speaker 1: have corruption, and that's trying to grout that out, and 1093 01:08:55,520 --> 01:08:59,360 Speaker 1: that's endemic, systemic corruption throughout the whole country, not just 1094 01:09:00,000 --> 01:09:03,599 Speaker 1: pockets here are there. Second, they have the environmental issues, 1095 01:09:04,040 --> 01:09:07,280 Speaker 1: which are well the water, the air shure. They had 1096 01:09:07,320 --> 01:09:09,919 Speaker 1: to shut the factories for eight months before the Olympics. 1097 01:09:10,000 --> 01:09:12,720 Speaker 1: I don't even you kind of forget about that, but 1098 01:09:13,520 --> 01:09:16,680 Speaker 1: that you're looking at that as a really substantial problem 1099 01:09:16,400 --> 01:09:20,720 Speaker 1: with and oncology is a growth business and one they 1100 01:09:20,760 --> 01:09:23,360 Speaker 1: have to fix. I mean, this is not I was 1101 01:09:23,479 --> 01:09:27,320 Speaker 1: at the at the Olympics and every day the sky 1102 01:09:27,479 --> 01:09:32,840 Speaker 1: was blue bird right because they shut it down. Uh, 1103 01:09:32,880 --> 01:09:35,800 Speaker 1: they set all the factories down, trucks didn't run. But 1104 01:09:35,880 --> 01:09:37,880 Speaker 1: it's it's that's not the way it is now when 1105 01:09:37,960 --> 01:09:42,400 Speaker 1: it's when everything is running just smog and is it 1106 01:09:42,560 --> 01:09:46,080 Speaker 1: that really that bad? Yes, And there's water, you've seen 1107 01:09:46,120 --> 01:09:50,000 Speaker 1: the lakes and and the and the third is, as 1108 01:09:50,120 --> 01:09:55,040 Speaker 1: Jim Channels correctly points out, uh, you've never had investment 1109 01:09:55,160 --> 01:09:59,919 Speaker 1: over of the GDP and not have a major contraction 1110 01:10:00,040 --> 01:10:05,400 Speaker 1: the economy. So they have capital China now China stock market, 1111 01:10:06,680 --> 01:10:10,480 Speaker 1: no capital spending, and that they've had this investment boom 1112 01:10:10,600 --> 01:10:14,439 Speaker 1: and so investment got over GDP. So they're trying to 1113 01:10:14,439 --> 01:10:18,479 Speaker 1: rebalance the economy, fight corruption, and fight environmental issues all 1114 01:10:18,520 --> 01:10:22,000 Speaker 1: at once. Uh that sounds like as a challenge. And 1115 01:10:22,040 --> 01:10:26,679 Speaker 1: so those are some of the issues. But then you're asking, uh, 1116 01:10:26,760 --> 01:10:30,799 Speaker 1: you know what, Uh those are more uh deep seated issues. 1117 01:10:31,520 --> 01:10:35,120 Speaker 1: Then you're saying, well, what could happen that would make 1118 01:10:35,160 --> 01:10:40,160 Speaker 1: it happen, make a negative outcome quickly. And the one 1119 01:10:40,200 --> 01:10:44,680 Speaker 1: that I'm most interested in right now is a discontinuity 1120 01:10:44,760 --> 01:10:48,719 Speaker 1: in the bond market. Uh. There's a constant discussion about 1121 01:10:49,000 --> 01:10:53,160 Speaker 1: the reduced liquidity in the fixed income markets that dealers 1122 01:10:53,800 --> 01:10:57,160 Speaker 1: UH have maybe a fifth or a tenth of the 1123 01:10:57,240 --> 01:11:00,320 Speaker 1: inventory of bonds they had six or seven years ago. 1124 01:11:00,560 --> 01:11:04,400 Speaker 1: The market is very thin, and that's liquidly crisis that 1125 01:11:04,479 --> 01:11:09,120 Speaker 1: people have been talking about now for months. Yes, and 1126 01:11:09,560 --> 01:11:13,880 Speaker 1: when the German bond yield went from something like fifty 1127 01:11:13,880 --> 01:11:16,240 Speaker 1: basis points to a hundred basis points, you half a 1128 01:11:16,280 --> 01:11:20,479 Speaker 1: percent to one percent in three days, people are going, 1129 01:11:20,479 --> 01:11:23,400 Speaker 1: oh my gosh, this is this could be yet. And 1130 01:11:23,600 --> 01:11:27,040 Speaker 1: so that's that's a risk that I watched every every morning. 1131 01:11:27,080 --> 01:11:29,439 Speaker 1: I checked the German bond yield out to see if 1132 01:11:29,439 --> 01:11:32,920 Speaker 1: it's starting to have a discontinuity. That that's an important 1133 01:11:33,880 --> 01:11:36,720 Speaker 1: factor to look at the German bond yield spread in 1134 01:11:36,800 --> 01:11:39,599 Speaker 1: order to give a sense of what liquidity issues there 1135 01:11:39,640 --> 01:11:44,320 Speaker 1: are and influence our our bond yield trades tick for 1136 01:11:44,400 --> 01:11:47,599 Speaker 1: tick every day off of their bond bond yield. Really yeah, 1137 01:11:47,640 --> 01:11:49,880 Speaker 1: so I fires are if there's is up three basis points, 1138 01:11:50,120 --> 01:11:52,799 Speaker 1: ours will be up three basis points. So yet there's 1139 01:11:52,840 --> 01:11:56,679 Speaker 1: is so much lower than ours. Why is the German 1140 01:11:56,960 --> 01:12:01,519 Speaker 1: bonds yielding so much less than it's strictly a function 1141 01:12:01,960 --> 01:12:04,880 Speaker 1: of the volume of US bonds, or how do we 1142 01:12:04,960 --> 01:12:10,120 Speaker 1: trade so much higher yield than than there? So this 1143 01:12:10,200 --> 01:12:16,040 Speaker 1: gets back to a business cycle um observation. So bond 1144 01:12:16,080 --> 01:12:20,680 Speaker 1: yields should in the long term be roughly equal to 1145 01:12:20,920 --> 01:12:25,360 Speaker 1: nominal GDP growth. So in the US, nominal GDP growth 1146 01:12:25,439 --> 01:12:29,719 Speaker 1: is probably three two percent real GDP maybe one percent, 1147 01:12:29,760 --> 01:12:36,320 Speaker 1: inflation three maybe four that neighborhood. And in Europe, uh, 1148 01:12:36,479 --> 01:12:39,680 Speaker 1: real GDP has been about one and inflation has been 1149 01:12:39,720 --> 01:12:44,280 Speaker 1: about zero, so nominal GDP growth has been about one. 1150 01:12:44,439 --> 01:12:48,280 Speaker 1: So we see Switzerland essentially zero. That means that their 1151 01:12:48,280 --> 01:12:51,679 Speaker 1: growth is also uh, their nominal growth is about zero. 1152 01:12:51,800 --> 01:12:54,960 Speaker 1: Same with Japan. Yes, it doesn't have to work or 1153 01:12:55,040 --> 01:12:59,599 Speaker 1: doesn't work you know on daily or weekly, quarterly basis period. 1154 01:12:59,640 --> 01:13:03,120 Speaker 1: That's but that's what you're tracking toward. And so nomal 1155 01:13:03,240 --> 01:13:07,479 Speaker 1: GDP and Japan has been close to zero for twenty 1156 01:13:07,560 --> 01:13:10,640 Speaker 1: five years and their bond yields have been close to 1157 01:13:10,720 --> 01:13:15,920 Speaker 1: zero for twenty years. So basically the spread between the 1158 01:13:15,920 --> 01:13:20,240 Speaker 1: German yield uh at say one percent and our yields 1159 01:13:20,240 --> 01:13:23,160 Speaker 1: at two And it can be largely explained by that 1160 01:13:23,240 --> 01:13:27,439 Speaker 1: first difference that our economy grows fast and there's a 1161 01:13:27,439 --> 01:13:31,040 Speaker 1: little bit faster than there. That's that's really amazing. Um 1162 01:13:31,120 --> 01:13:34,320 Speaker 1: let's talk a little bit about books, right. I assume 1163 01:13:34,439 --> 01:13:36,240 Speaker 1: that you're a bit of a reader. When I walked 1164 01:13:36,240 --> 01:13:41,360 Speaker 1: into your office, you had bookshelves and and what what 1165 01:13:41,400 --> 01:13:44,719 Speaker 1: are some of your favorite books? Both finance and nine 1166 01:13:44,960 --> 01:13:51,640 Speaker 1: non fans related. Well, uh, almost everything I read is 1167 01:13:51,680 --> 01:13:55,519 Speaker 1: related to what I do for work. So I shouldn't 1168 01:13:55,520 --> 01:13:58,200 Speaker 1: feel bad about that because my wife is like, why 1169 01:13:58,200 --> 01:14:02,200 Speaker 1: don't you have a pick up a fiction book? Fast? Yeah, 1170 01:14:02,240 --> 01:14:05,240 Speaker 1: this is this is good. So I wrote on some 1171 01:14:05,280 --> 01:14:09,400 Speaker 1: books that I've enjoyed recently. So there was one uh 1172 01:14:09,520 --> 01:14:16,599 Speaker 1: Coming Apart by Charles Murray and and uh so this 1173 01:14:16,680 --> 01:14:20,439 Speaker 1: is a description about the way the US was in 1174 01:14:20,479 --> 01:14:24,200 Speaker 1: the sixties and the way it is today and uh 1175 01:14:24,320 --> 01:14:29,200 Speaker 1: more socially focused. It's a social commentary and uh the 1176 01:14:29,240 --> 01:14:32,760 Speaker 1: way the country is coming apart and uh that I 1177 01:14:32,800 --> 01:14:35,320 Speaker 1: spent a lot of time thinking about that were recently. 1178 01:14:36,040 --> 01:14:38,640 Speaker 1: Uh Andy McAfee, who's a professor at m. I. T. 1179 01:14:39,400 --> 01:14:42,840 Speaker 1: Has done a lot of work on robotics and uh. 1180 01:14:42,840 --> 01:14:44,880 Speaker 1: He and his colleague wrote a book called The Second 1181 01:14:44,920 --> 01:14:52,160 Speaker 1: Machine Age, and they uh so I spent time working 1182 01:14:52,200 --> 01:14:56,000 Speaker 1: with them and and thinking about uh. And their view 1183 01:14:56,280 --> 01:15:00,040 Speaker 1: is that this time is different, that robots are a 1184 01:15:00,720 --> 01:15:06,320 Speaker 1: destroy jobs and so they have a provocative of your angle. 1185 01:15:06,600 --> 01:15:09,320 Speaker 1: You're starting to see it happened already in a number 1186 01:15:09,360 --> 01:15:14,000 Speaker 1: of different areas. Um, they're no longer a pertinent to jobs. 1187 01:15:14,000 --> 01:15:16,840 Speaker 1: They're now replacing jobs. Well, I don't I don't agree 1188 01:15:16,840 --> 01:15:19,680 Speaker 1: with them on that. You don't know, but that's uh, 1189 01:15:19,920 --> 01:15:22,040 Speaker 1: we'll find out in the next three or four years, 1190 01:15:23,000 --> 01:15:27,400 Speaker 1: not that that's happening. Um. There's a a doctor who's 1191 01:15:27,439 --> 01:15:31,439 Speaker 1: written two books I've loved, UH named Gowandhi. I knew 1192 01:15:31,439 --> 01:15:34,479 Speaker 1: you were gouldn't go there. The checklist was that the 1193 01:15:34,479 --> 01:15:37,519 Speaker 1: most recent one? Yes, do you know that one? Um, 1194 01:15:37,560 --> 01:15:41,639 Speaker 1: because it's on my on my bookshelf. It's like number 1195 01:15:41,680 --> 01:15:46,400 Speaker 1: four in my queue waiting to be read. The book 1196 01:15:46,439 --> 01:15:50,479 Speaker 1: he did before that, Yes, Better Medicine was really got 1197 01:15:50,600 --> 01:15:54,639 Speaker 1: fantastic reviews, and um, it was one of those things 1198 01:15:54,640 --> 01:15:56,640 Speaker 1: that all right, I'll get around to that. But the 1199 01:15:56,720 --> 01:15:59,080 Speaker 1: checklist looks like it has well. His first one I 1200 01:15:59,080 --> 01:16:02,080 Speaker 1: think is better than the check List. See the checklist 1201 01:16:02,120 --> 01:16:05,320 Speaker 1: looks like it's applicable to everything it is, and better 1202 01:16:05,360 --> 01:16:09,479 Speaker 1: medicine would look like a very specific sector discussion. But 1203 01:16:09,520 --> 01:16:12,479 Speaker 1: he's a great writer. And then I've really enjoyed the 1204 01:16:12,640 --> 01:16:18,680 Speaker 1: book by by Talib called Anti Fragile and Uh, I 1205 01:16:18,720 --> 01:16:21,160 Speaker 1: think he's a brilliant guy. And I've I haven't quite 1206 01:16:21,160 --> 01:16:24,840 Speaker 1: finished that one, but he's He's so fooled. Button Randomness 1207 01:16:25,160 --> 01:16:28,280 Speaker 1: was a really interesting read by him, but it's not 1208 01:16:28,360 --> 01:16:31,320 Speaker 1: a fast read. You have to kind of pick it up, 1209 01:16:31,400 --> 01:16:33,240 Speaker 1: read a couple of chapters, put it down, and think 1210 01:16:33,280 --> 01:16:36,720 Speaker 1: about the same thing with the Black Swan. It's it's 1211 01:16:36,720 --> 01:16:39,439 Speaker 1: it's not. You know. I love Michael Lewis's stuff. I 1212 01:16:39,439 --> 01:16:41,240 Speaker 1: could pick up a book of his cloth through it 1213 01:16:41,320 --> 01:16:46,680 Speaker 1: in an afternoon. Talib not not really requires some digestion. Well, 1214 01:16:46,760 --> 01:16:49,679 Speaker 1: I think on his books you can go either way. 1215 01:16:49,800 --> 01:16:52,559 Speaker 1: You can just get the gist of it and move on, 1216 01:16:54,000 --> 01:16:57,400 Speaker 1: or you can go through you know, each page in 1217 01:16:57,439 --> 01:17:00,519 Speaker 1: each chapter, which have some real nugget as you go 1218 01:17:00,600 --> 01:17:05,479 Speaker 1: through it. Uh. And then I do find money, money 1219 01:17:05,479 --> 01:17:08,720 Speaker 1: Ball and the Big Short by Michael Lewis to be 1220 01:17:09,520 --> 01:17:15,559 Speaker 1: books I think back on frequently. Moneyball was one of 1221 01:17:15,600 --> 01:17:19,679 Speaker 1: the most interesting books I've ever read. If you like 1222 01:17:19,880 --> 01:17:22,840 Speaker 1: Michael Lewis, I'm going to tell you a book I 1223 01:17:23,400 --> 01:17:25,599 Speaker 1: read that I don't think a lot of people read, 1224 01:17:26,040 --> 01:17:28,680 Speaker 1: and one that I'm waiting to read. So I have 1225 01:17:29,000 --> 01:17:32,080 Speaker 1: so money Ball was about football, was about baseball, but 1226 01:17:32,200 --> 01:17:36,200 Speaker 1: he did a football book called The blind Side. I 1227 01:17:36,240 --> 01:17:39,240 Speaker 1: have not read that. My cue waiting to be read. 1228 01:17:39,400 --> 01:17:41,800 Speaker 1: Not as not as good as money Ball, well, not 1229 01:17:41,880 --> 01:17:46,520 Speaker 1: as quantitative, not as applicable to every aspect of life. 1230 01:17:46,680 --> 01:17:52,200 Speaker 1: So in and our business at EVERCREI s I uh, 1231 01:17:52,439 --> 01:17:56,640 Speaker 1: you see many many examples of where you can apply Moneyball. 1232 01:17:58,080 --> 01:18:00,840 Speaker 1: That's what made it so fascinating. It was so universal. 1233 01:18:00,960 --> 01:18:03,240 Speaker 1: The other book of so I've read everything of his 1234 01:18:03,880 --> 01:18:07,000 Speaker 1: except The Blindside. The book of his that I really 1235 01:18:07,080 --> 01:18:09,360 Speaker 1: liked that I don't know a lot of people have 1236 01:18:09,520 --> 01:18:14,040 Speaker 1: read was the book called The New New Thing. And 1237 01:18:14,439 --> 01:18:18,160 Speaker 1: you know everybody's read you know, Liars Poker, everybody's read 1238 01:18:18,200 --> 01:18:21,640 Speaker 1: The Big Short. I really enjoyed Flashboys. I thought Flashboys 1239 01:18:21,680 --> 01:18:24,360 Speaker 1: was despite the criticism, despite the pushback, I thought that 1240 01:18:24,400 --> 01:18:27,120 Speaker 1: was really interesting. But The New New Thing was one 1241 01:18:27,160 --> 01:18:30,160 Speaker 1: of his books that sort of slipped in under the radar, 1242 01:18:30,800 --> 01:18:35,400 Speaker 1: and it's also really fascinating. So all these things, Uh, 1243 01:18:35,439 --> 01:18:38,960 Speaker 1: you know, the world is changing very rapidly. I'm not 1244 01:18:39,000 --> 01:18:43,760 Speaker 1: sure we uh we discussed it enough or think about it. 1245 01:18:43,800 --> 01:18:49,920 Speaker 1: But say in the area of economics, Uh, it's just 1246 01:18:50,040 --> 01:18:52,880 Speaker 1: changing because there's so much more data now all the 1247 01:18:52,960 --> 01:18:58,000 Speaker 1: time for people to study and say, like in investments, Uh, 1248 01:18:58,040 --> 01:19:02,599 Speaker 1: there are many, many more people doing investments now, which 1249 01:19:02,600 --> 01:19:08,000 Speaker 1: makes it more difficult. Chanos said that there are, um, 1250 01:19:08,560 --> 01:19:12,120 Speaker 1: there are ten thousand hedge funds today. Back when he started, 1251 01:19:12,120 --> 01:19:14,680 Speaker 1: there were a hundred and fifty hedge funds, but all 1252 01:19:14,720 --> 01:19:17,160 Speaker 1: the office still being created by those same hundred and 1253 01:19:17,160 --> 01:19:19,960 Speaker 1: fifty hedge funds. I don't know how true that is, 1254 01:19:20,000 --> 01:19:23,760 Speaker 1: but it certainly means that there's more competition for employees, 1255 01:19:23,760 --> 01:19:27,320 Speaker 1: there's more competition for capital, there's more competition for for 1256 01:19:27,360 --> 01:19:30,920 Speaker 1: everything now, and it's it's still more difficult when you 1257 01:19:30,960 --> 01:19:34,599 Speaker 1: have that many more people playing. I would I would 1258 01:19:34,800 --> 01:19:38,839 Speaker 1: imagine at the very least, it's the challenges of managing 1259 01:19:38,880 --> 01:19:43,040 Speaker 1: that have to be increasing. Right, So let's let's keep 1260 01:19:43,040 --> 01:19:45,599 Speaker 1: blowing through. Any other books on the list, any classic 1261 01:19:45,680 --> 01:19:49,280 Speaker 1: books that you. Uh so everything you've mentioned is relatively 1262 01:19:49,360 --> 01:19:53,160 Speaker 1: new any of the old classics really? Uh? Well, you 1263 01:19:53,200 --> 01:19:57,040 Speaker 1: know I liked I liked I like the stuff that 1264 01:19:57,120 --> 01:20:01,400 Speaker 1: John Maynard Kein's has written, and I find him as 1265 01:20:01,400 --> 01:20:04,600 Speaker 1: an economist, I find him very fascinating. But because he 1266 01:20:04,840 --> 01:20:07,240 Speaker 1: operated in so many different spheres, you know, he was 1267 01:20:07,720 --> 01:20:11,920 Speaker 1: an accomplished investor, very successful investor, people don't realize how 1268 01:20:11,960 --> 01:20:14,720 Speaker 1: good of an investor he was. And obviously, you know, 1269 01:20:15,680 --> 01:20:19,400 Speaker 1: a complete thought leader in his field and had a 1270 01:20:19,400 --> 01:20:21,880 Speaker 1: big political role in life. And he should really get 1271 01:20:21,920 --> 01:20:27,720 Speaker 1: him on the show. Um, good luck. Um. You know 1272 01:20:27,760 --> 01:20:31,240 Speaker 1: what I'm embarrassed to admit I've never read. It's literally 1273 01:20:31,320 --> 01:20:33,560 Speaker 1: on my night table. What's the next book in my 1274 01:20:33,720 --> 01:20:37,400 Speaker 1: queue is? Where Are the Customer's Yachts? That's been something 1275 01:20:37,439 --> 01:20:41,200 Speaker 1: that I've been waiting to read for forever and I 1276 01:20:41,240 --> 01:20:46,000 Speaker 1: foundly once I finished the I'm reading Failer's Misbehaving The 1277 01:20:46,000 --> 01:20:49,240 Speaker 1: Founding of Behavioral Economics. Once I'm done with that, Customers 1278 01:20:49,320 --> 01:20:51,639 Speaker 1: Yachts are are next? What else do you have queued 1279 01:20:51,720 --> 01:20:53,599 Speaker 1: up to read? What else are you looking forward to reading. 1280 01:20:55,439 --> 01:20:59,000 Speaker 1: I'm looking forward to finishing Anti Fragile and the same 1281 01:20:59,080 --> 01:21:03,559 Speaker 1: with the the check checklist. Oh so you will you 1282 01:21:03,600 --> 01:21:06,320 Speaker 1: read multiple books at a time. Yes, that's one of 1283 01:21:06,360 --> 01:21:10,679 Speaker 1: my worst habits because I have different ten books I'm 1284 01:21:10,680 --> 01:21:14,559 Speaker 1: working on. But there's a book, if you haven't read it, 1285 01:21:14,600 --> 01:21:19,439 Speaker 1: called Reminiscences of a stock Operator Edward lafarv yes on 1286 01:21:19,439 --> 01:21:23,720 Speaker 1: on the I read that many years ago, fascinating. It's 1287 01:21:23,760 --> 01:21:25,720 Speaker 1: it's as good today if you pick it up and 1288 01:21:25,760 --> 01:21:28,960 Speaker 1: read a couple of pages. So there's a new there's 1289 01:21:29,000 --> 01:21:36,000 Speaker 1: a new book that's a bio of um Esse live 1290 01:21:36,080 --> 01:21:40,000 Speaker 1: More called Um the Boy Plunger, and it's it's basically 1291 01:21:40,280 --> 01:21:43,080 Speaker 1: a it's not written with the same sort of style 1292 01:21:43,439 --> 01:21:46,880 Speaker 1: that that Reminiscence was, But that just arrived in the 1293 01:21:46,920 --> 01:21:48,479 Speaker 1: mail the of the day. I don't know when I'll 1294 01:21:48,520 --> 01:21:51,320 Speaker 1: get to that. But I read Reminiscences a while ago 1295 01:21:51,400 --> 01:21:54,519 Speaker 1: and just thought it was really that I started on 1296 01:21:54,520 --> 01:21:57,280 Speaker 1: a trading desk. That might have been one of the 1297 01:21:57,320 --> 01:22:01,000 Speaker 1: first five books I read. Good for you, Market Wizards 1298 01:22:01,040 --> 01:22:04,320 Speaker 1: was the first book the head head trader said, here 1299 01:22:04,400 --> 01:22:07,439 Speaker 1: go read this that that was my training. Here, take 1300 01:22:07,439 --> 01:22:09,800 Speaker 1: a look at this. So any anything else that you 1301 01:22:09,800 --> 01:22:11,920 Speaker 1: have tied up that you want to uh, you want 1302 01:22:11,920 --> 01:22:16,160 Speaker 1: to read anytime soon. I just read constantly. That is 1303 01:22:16,200 --> 01:22:21,400 Speaker 1: not um. That is not such a rare thing amongst 1304 01:22:21,479 --> 01:22:28,720 Speaker 1: people who are regarded as excellent investors, excellent strategists, excellent economists. 1305 01:22:28,880 --> 01:22:32,599 Speaker 1: You read what Charlie Munger and Warren Buffett say. They 1306 01:22:32,600 --> 01:22:36,080 Speaker 1: say they spend their time reading that. That's just amazing 1307 01:22:36,160 --> 01:22:40,760 Speaker 1: to think about. You're so used to people with technology 1308 01:22:40,840 --> 01:22:47,719 Speaker 1: and Twitter and everything else, being so hyperactive four four 1309 01:22:47,760 --> 01:22:49,720 Speaker 1: out of five hours during the day. These guys are 1310 01:22:49,720 --> 01:22:54,200 Speaker 1: sitting around reading books. It's amazing. So I read the 1311 01:22:54,280 --> 01:22:58,519 Speaker 1: Jeff Bezos book UM that came out a couple of 1312 01:22:58,600 --> 01:23:02,400 Speaker 1: years ago and uh, which is great, a great read. 1313 01:23:03,160 --> 01:23:06,720 Speaker 1: And in the end it had a page on the 1314 01:23:06,760 --> 01:23:10,360 Speaker 1: books that he had read and they're all these books 1315 01:23:10,479 --> 01:23:13,840 Speaker 1: like good to great and etcetera. Well, are they all 1316 01:23:13,840 --> 01:23:19,439 Speaker 1: business books? These are all business books. Charlie Munger also 1317 01:23:19,479 --> 01:23:24,920 Speaker 1: has about a forty page speech he gave right on 1318 01:23:25,520 --> 01:23:28,400 Speaker 1: behavioral psychology and the way it plays into the market. 1319 01:23:28,439 --> 01:23:32,679 Speaker 1: I've seen that, which is where it's it's really excellent. 1320 01:23:32,760 --> 01:23:35,880 Speaker 1: The speech may actually be on YouTube. I'm gonna have 1321 01:23:35,960 --> 01:23:39,600 Speaker 1: to dig that up. Another book sitting on my bookshelf, 1322 01:23:39,680 --> 01:23:42,919 Speaker 1: not even on the night table. Is port Charlie's Almanac 1323 01:23:43,040 --> 01:23:46,599 Speaker 1: that I'm waiting to pack. It's this thick and it's 1324 01:23:46,640 --> 01:23:49,880 Speaker 1: basically a collection of a lot of his thoughts, a 1325 01:23:49,880 --> 01:23:52,360 Speaker 1: lot of his speeches, and it's one of these things 1326 01:23:52,360 --> 01:23:54,280 Speaker 1: that you could get lost in for three months. So 1327 01:23:54,400 --> 01:23:57,799 Speaker 1: it's it's waiting. I just haven't. Maybe that's a winter 1328 01:23:57,880 --> 01:24:00,400 Speaker 1: project this year. So let me keep more thinking through 1329 01:24:00,439 --> 01:24:06,320 Speaker 1: some of my favorite um questions. You mentioned how the 1330 01:24:06,400 --> 01:24:11,639 Speaker 1: pace of changes accelerating. Everything is happening more data faster. 1331 01:24:12,280 --> 01:24:14,880 Speaker 1: What what other major shifts do you see coming up 1332 01:24:14,960 --> 01:24:19,680 Speaker 1: for research and economics? So I thought about that, and 1333 01:24:20,120 --> 01:24:24,120 Speaker 1: I don't. I thought about the question. Nothing comes to mind. 1334 01:24:24,600 --> 01:24:28,439 Speaker 1: It just seems as though it slowly is getting faster 1335 01:24:29,160 --> 01:24:35,400 Speaker 1: and faster as electronic information becomes more and more available 1336 01:24:35,439 --> 01:24:41,799 Speaker 1: and consumable by people. Oddly enough, trading volumes have gotten 1337 01:24:41,840 --> 01:24:47,240 Speaker 1: slower and slower. Uh, so there's more news. But in 1338 01:24:47,360 --> 01:24:51,200 Speaker 1: the in the equity markets, it's it's gotten. People have 1339 01:24:51,240 --> 01:24:54,240 Speaker 1: been trading less. What what explains that? That's really an 1340 01:24:54,280 --> 01:24:58,960 Speaker 1: interesting The first first is muscle memory, you know people, 1341 01:25:00,000 --> 01:25:05,040 Speaker 1: And second active management has been doing poorly, and so 1342 01:25:05,400 --> 01:25:09,200 Speaker 1: people haven't been winning by making moves. So they less, 1343 01:25:09,280 --> 01:25:12,760 Speaker 1: they do less and uh, and then money has been 1344 01:25:12,800 --> 01:25:17,040 Speaker 1: flowing from active to passive, which generates less trading in 1345 01:25:17,080 --> 01:25:22,880 Speaker 1: that space. Dango just passed three that's that's an amazing number. 1346 01:25:23,600 --> 01:25:27,800 Speaker 1: And there are two thirds passive. So that's just a tremendous, 1347 01:25:27,840 --> 01:25:32,040 Speaker 1: tremendous heart of fathom number. And so it really is 1348 01:25:32,040 --> 01:25:38,800 Speaker 1: a staggering development. Trading volume was ten billion shares a 1349 01:25:38,880 --> 01:25:43,679 Speaker 1: day h five years ago and now it's six billion. 1350 01:25:44,360 --> 01:25:48,200 Speaker 1: You started mentioning ets. Does that having an impact? That's 1351 01:25:48,400 --> 01:25:52,080 Speaker 1: less less less trading? So so you could one transaction, 1352 01:25:52,160 --> 01:25:55,400 Speaker 1: you're buying the whole SMP. You don't need to to 1353 01:25:56,160 --> 01:25:59,000 Speaker 1: purchase the individual stocks and the odds. Are you going 1354 01:25:59,040 --> 01:26:00,840 Speaker 1: to sit with that over time time and not jump 1355 01:26:00,880 --> 01:26:03,080 Speaker 1: in and out so that you know, I don't I 1356 01:26:03,080 --> 01:26:07,080 Speaker 1: don't want that's a permanent condition or uh. And we've 1357 01:26:07,080 --> 01:26:11,639 Speaker 1: gone through it's been stable now for about two three years. 1358 01:26:12,120 --> 01:26:14,640 Speaker 1: What does that mean in terms of money flowing to 1359 01:26:14,760 --> 01:26:17,600 Speaker 1: research dollars because it has to be used to be 1360 01:26:17,680 --> 01:26:20,960 Speaker 1: research was paid for with trading commissions that they still 1361 01:26:21,000 --> 01:26:25,000 Speaker 1: that's exactly our business trading. So so how do you 1362 01:26:25,040 --> 01:26:27,280 Speaker 1: structure that to you? Is there a minimum amount is 1363 01:26:27,320 --> 01:26:30,080 Speaker 1: it hard dollar or is it all soft dollar commissions? 1364 01:26:30,080 --> 01:26:34,080 Speaker 1: So it's it's not all soft dollar commissions, but it's 1365 01:26:34,439 --> 01:26:39,559 Speaker 1: virtually all soft collar commissions. Uh. And so it just 1366 01:26:39,640 --> 01:26:43,240 Speaker 1: made it a much more difficult environment for everybody in 1367 01:26:43,240 --> 01:26:45,240 Speaker 1: the business. So that turn it into a little bit 1368 01:26:45,280 --> 01:26:47,160 Speaker 1: of a winner take all. You have a handful of 1369 01:26:47,240 --> 01:26:50,320 Speaker 1: firms if the volume is dropping that much, but there's 1370 01:26:50,479 --> 01:26:53,120 Speaker 1: x amount of research people are looking to buy. That 1371 01:26:53,160 --> 01:26:56,040 Speaker 1: means any firm that's on the fringe or on the 1372 01:26:56,320 --> 01:27:01,200 Speaker 1: edge is not going to capture those those trading dollars. Uh. 1373 01:27:01,280 --> 01:27:04,960 Speaker 1: It hasn't quite worked out that way because you have UH. 1374 01:27:05,360 --> 01:27:08,639 Speaker 1: So we were on the edge and we were doing 1375 01:27:08,680 --> 01:27:14,559 Speaker 1: fine because we were taking commissions from the the guys 1376 01:27:14,600 --> 01:27:19,280 Speaker 1: in the middle. And now we're not in the middle, 1377 01:27:19,280 --> 01:27:23,400 Speaker 1: but we're in the inner circle. But we're still you know, 1378 01:27:23,439 --> 01:27:26,519 Speaker 1: gaining market share. But it's a very difficult business. But 1379 01:27:26,640 --> 01:27:29,400 Speaker 1: it's uniform across the industry. So it's not like, you know, 1380 01:27:29,439 --> 01:27:32,120 Speaker 1: it's sunny in some spaces and reigning and others. It's 1381 01:27:32,160 --> 01:27:35,280 Speaker 1: just it's tough. It's tough everywhere. So it doesn't it 1382 01:27:35,320 --> 01:27:38,920 Speaker 1: doesn't put us at a competitive disadvantage or advantage either, 1383 01:27:38,960 --> 01:27:41,559 Speaker 1: I don't think so. You said something interesting earlier. I 1384 01:27:41,560 --> 01:27:44,920 Speaker 1: want to come back and revisit. You said much of 1385 01:27:45,160 --> 01:27:50,240 Speaker 1: the industry has not changed since the nineties seventies. You 1386 01:27:50,320 --> 01:27:53,960 Speaker 1: alluded to that, how is that possible? Given technology and 1387 01:27:53,960 --> 01:27:57,639 Speaker 1: given everything all that's all that's changed. But the basic 1388 01:27:57,720 --> 01:28:02,120 Speaker 1: players uh, or you have people in my space, you 1389 01:28:02,160 --> 01:28:08,080 Speaker 1: have people doing research and they interface with investors at 1390 01:28:08,080 --> 01:28:12,639 Speaker 1: the at the big institutional accounts. That is pretty similar 1391 01:28:12,720 --> 01:28:17,400 Speaker 1: to what it was, except they're more investors. Uh. There's 1392 01:28:17,439 --> 01:28:22,000 Speaker 1: also UH, keep in mind, there's a ton of money 1393 01:28:22,120 --> 01:28:26,320 Speaker 1: that didn't exist in the seventies, so there's although the 1394 01:28:26,320 --> 01:28:29,559 Speaker 1: the vibes are down, there's still a lot of trading 1395 01:28:29,560 --> 01:28:34,759 Speaker 1: going on, but they're that basic interface, Uh is pretty 1396 01:28:34,800 --> 01:28:37,719 Speaker 1: much the same as it as it was. The industry 1397 01:28:37,760 --> 01:28:42,200 Speaker 1: started to grow as pools of money began to accumulate. UH. 1398 01:28:42,840 --> 01:28:46,000 Speaker 1: When you say pools, you mean big pension funds, foundations 1399 01:28:46,040 --> 01:28:49,800 Speaker 1: that sort of stuff, or just assets. The size of 1400 01:28:49,840 --> 01:28:53,120 Speaker 1: the stock exchanges, the size of the equity markets in 1401 01:28:53,120 --> 01:28:55,760 Speaker 1: the US, so the size of those are feeding off 1402 01:28:55,800 --> 01:28:59,560 Speaker 1: of what you mentioned the first the pension funds, mute 1403 01:28:59,640 --> 01:29:05,280 Speaker 1: mutual ones you mentioned like Vanguard and so as those 1404 01:29:05,960 --> 01:29:10,160 Speaker 1: moneys came together, Uh, it really gave birth to institutional 1405 01:29:10,320 --> 01:29:14,759 Speaker 1: research and starting pretty much with Donaldson, Lufkin and Jenrette 1406 01:29:15,160 --> 01:29:19,240 Speaker 1: in the late fifties early sixties. How did that How 1407 01:29:19,240 --> 01:29:21,200 Speaker 1: did that have such an impact on on the world 1408 01:29:21,280 --> 01:29:25,160 Speaker 1: of research. As as pools of money developed, you had 1409 01:29:26,040 --> 01:29:29,960 Speaker 1: professional investors now able to shepherd that money. So you 1410 01:29:30,040 --> 01:29:34,160 Speaker 1: had research people at City Bank, and so they started 1411 01:29:34,160 --> 01:29:37,439 Speaker 1: to need some research from the street and the whole 1412 01:29:37,640 --> 01:29:41,479 Speaker 1: dance began. And it's pretty much the same today. It's 1413 01:29:41,520 --> 01:29:46,680 Speaker 1: just gotten bigger, fascinating. UM. So the next question was 1414 01:29:46,720 --> 01:29:48,519 Speaker 1: is this a good or a bad thing? But you're 1415 01:29:48,560 --> 01:29:52,080 Speaker 1: really saying it's neither. It's just the size is increasing. 1416 01:29:52,600 --> 01:29:56,719 Speaker 1: The main the main problem is that active management has 1417 01:29:56,760 --> 01:29:59,760 Speaker 1: not done well for I don't know how many years. 1418 01:29:59,760 --> 01:30:01,960 Speaker 1: But why do you think that is? Because there's so 1419 01:30:01,960 --> 01:30:06,679 Speaker 1: many players. It's very difficult. It's UM. Charlie Ellis said 1420 01:30:08,120 --> 01:30:12,679 Speaker 1: that when you have this many smart, competitive people out there, 1421 01:30:13,240 --> 01:30:16,640 Speaker 1: and he was the chairman of the Yelle Endowment for 1422 01:30:16,680 --> 01:30:19,839 Speaker 1: a long time, UM and a board member of Vanguard, 1423 01:30:20,400 --> 01:30:22,800 Speaker 1: when there's so many really smart people out there, they 1424 01:30:22,880 --> 01:30:25,280 Speaker 1: all just end up canceling each other. Out and that's 1425 01:30:25,320 --> 01:30:30,120 Speaker 1: how you have a period where nobody's generating alpha because 1426 01:30:30,640 --> 01:30:33,400 Speaker 1: everybody is trying to and it's just you know, it's 1427 01:30:33,400 --> 01:30:36,080 Speaker 1: like stepping out into the field with the New York giants. 1428 01:30:36,479 --> 01:30:40,639 Speaker 1: You're you're not very well out there, and so that's uh, 1429 01:30:41,479 --> 01:30:45,240 Speaker 1: we'll see how that plays out. Uh. Usually that's somewhat 1430 01:30:45,240 --> 01:30:49,040 Speaker 1: cyclical though, and so we'll see. There has been one 1431 01:30:49,479 --> 01:30:54,280 Speaker 1: aspect that's not been discussed much, is that of people 1432 01:30:54,320 --> 01:30:59,720 Speaker 1: have been more successful doing asset allocation, which doesn't show 1433 01:30:59,840 --> 01:31:02,640 Speaker 1: up in generating alpha or not. You're always looking at 1434 01:31:02,640 --> 01:31:05,760 Speaker 1: a portfolio stocks and are you outperforming the SMP or 1435 01:31:05,840 --> 01:31:07,960 Speaker 1: something like that. But in terms of you know, can 1436 01:31:08,000 --> 01:31:15,160 Speaker 1: you put together a a portfolio of private equity and 1437 01:31:15,680 --> 01:31:22,559 Speaker 1: equities and bonds, uh, real estate that outperforms and uh, 1438 01:31:22,600 --> 01:31:24,320 Speaker 1: I think there's been a number of people that have 1439 01:31:24,400 --> 01:31:27,960 Speaker 1: done an excellent job of that. Any anyone in particular 1440 01:31:28,000 --> 01:31:32,840 Speaker 1: you want to mention or is it just just just 1441 01:31:32,920 --> 01:31:35,600 Speaker 1: the shift. I mean you have to look at Vanguard 1442 01:31:35,640 --> 01:31:39,120 Speaker 1: as a beneficiary of that. They have huge beneficiary right 1443 01:31:39,160 --> 01:31:42,479 Speaker 1: because if you want an instant, low cost exposure to 1444 01:31:43,400 --> 01:31:46,720 Speaker 1: a region, a sector of this or that that they 1445 01:31:46,760 --> 01:31:51,200 Speaker 1: offer enough funds and at eleven basis points and things 1446 01:31:51,240 --> 01:31:55,480 Speaker 1: like that. You get exposure to any of those things instantaneously. 1447 01:31:55,520 --> 01:31:59,280 Speaker 1: It's really, it's really quite amazing. Um what what are 1448 01:31:59,320 --> 01:32:02,400 Speaker 1: some of your favorite miss on Wall Street that refused 1449 01:32:02,400 --> 01:32:04,599 Speaker 1: to die? I looked at that one very I don't. 1450 01:32:04,680 --> 01:32:08,080 Speaker 1: I don't see any myths that refused it. I thought 1451 01:32:08,080 --> 01:32:11,400 Speaker 1: about it, the Super Bowl Indicator, any of that stuff. Well, 1452 01:32:11,439 --> 01:32:15,080 Speaker 1: you don't. You just don't pay attention to. Um So, 1453 01:32:15,400 --> 01:32:19,000 Speaker 1: last two questions. Let me ask you to a millennial 1454 01:32:19,280 --> 01:32:22,360 Speaker 1: or someone just coming out of college. Now, what sort 1455 01:32:22,360 --> 01:32:24,840 Speaker 1: of career advice would you give them if they were 1456 01:32:24,880 --> 01:32:31,519 Speaker 1: interested in in finance or investment? So? Um So, First, 1457 01:32:31,680 --> 01:32:36,759 Speaker 1: I would say, go fast? What does that mean? Go fast? 1458 01:32:36,840 --> 01:32:40,000 Speaker 1: Just whatever you want to do, do it, you know, 1459 01:32:40,080 --> 01:32:45,120 Speaker 1: try and uh. It's hard to know what to do. Uh. 1460 01:32:45,200 --> 01:32:49,400 Speaker 1: And there are good arguments that you should, you know, 1461 01:32:49,479 --> 01:32:52,000 Speaker 1: take your time. You're gonna live a long time compared 1462 01:32:52,080 --> 01:32:55,920 Speaker 1: to why people lived a hundred years ago. Uh, And 1463 01:32:55,960 --> 01:32:58,160 Speaker 1: I think there's truth in that. But I think you 1464 01:32:58,160 --> 01:33:01,760 Speaker 1: should still try and go fast. Let's say you go 1465 01:33:01,840 --> 01:33:04,080 Speaker 1: fast by reading a lot of books all of a sudden, right, 1466 01:33:04,360 --> 01:33:06,799 Speaker 1: But as I can tell you are you're going fast 1467 01:33:06,840 --> 01:33:12,600 Speaker 1: at reading and so whatever you do, go at it. 1468 01:33:12,600 --> 01:33:15,200 Speaker 1: It would be one idea that comes to my mind. 1469 01:33:15,800 --> 01:33:17,600 Speaker 1: This way you could discover if you like it or 1470 01:33:17,640 --> 01:33:19,240 Speaker 1: you don't like it, you move on to the next. 1471 01:33:19,280 --> 01:33:22,320 Speaker 1: What what's the thinking behind go fast? Just go fast? 1472 01:33:22,320 --> 01:33:24,200 Speaker 1: So do you you get as much you have a 1473 01:33:24,240 --> 01:33:28,200 Speaker 1: good time to get a much experience as possible. Um, 1474 01:33:28,800 --> 01:33:31,400 Speaker 1: maybe go fastest to you know, go and live in 1475 01:33:31,439 --> 01:33:34,400 Speaker 1: Thailand for five five years just to see what it's like. 1476 01:33:34,720 --> 01:33:38,960 Speaker 1: But you're doing it. It's experience, so you're what you realize. 1477 01:33:38,960 --> 01:33:42,960 Speaker 1: What I'm really hearing from you is be decisive, do something. 1478 01:33:43,560 --> 01:33:45,360 Speaker 1: Just don't sit around and wait for the world to 1479 01:33:45,400 --> 01:33:49,040 Speaker 1: come to you. Right, Okay? That the things that I've 1480 01:33:49,160 --> 01:33:51,240 Speaker 1: when I look at the people that do well in 1481 01:33:51,240 --> 01:33:55,599 Speaker 1: this business, the first one that comes up is the 1482 01:33:55,640 --> 01:34:01,400 Speaker 1: most trite, which is is work hard. And everybody that 1483 01:34:01,680 --> 01:34:07,680 Speaker 1: I see the succeeds. They simply outwork other players. I 1484 01:34:07,720 --> 01:34:11,080 Speaker 1: think Michael Bloomberg is a great example of that, where 1485 01:34:11,120 --> 01:34:17,000 Speaker 1: he's he's just full of life and is a concredible worker. Well, 1486 01:34:17,080 --> 01:34:18,519 Speaker 1: let's see if we can get him on the show. 1487 01:34:19,080 --> 01:34:22,599 Speaker 1: Keep asking, he keeps turning me down. Um, work hard, 1488 01:34:22,880 --> 01:34:26,439 Speaker 1: clearly go fast. The goal go fast is sort of 1489 01:34:26,439 --> 01:34:30,400 Speaker 1: a general condition that work hard. UH. And then I 1490 01:34:30,439 --> 01:34:34,679 Speaker 1: think you have to be competitive. You have to whatever. 1491 01:34:35,360 --> 01:34:38,519 Speaker 1: Different people are competitive in different ways. Some are overtly 1492 01:34:38,560 --> 01:34:42,439 Speaker 1: competitive and some are quietly competitive. But that whatever that 1493 01:34:42,560 --> 01:34:47,799 Speaker 1: instinct is to win UH in this business is definitely 1494 01:34:47,800 --> 01:34:51,200 Speaker 1: necessary in the investi business and as frankly true in 1495 01:34:51,400 --> 01:34:54,599 Speaker 1: most businesses. I take a look at UH. And then 1496 01:34:54,800 --> 01:34:58,000 Speaker 1: the third one I think is critical is to be flexible, 1497 01:34:58,920 --> 01:35:03,680 Speaker 1: to say this isn't working something, I'm going fast not 1498 01:35:03,760 --> 01:35:07,960 Speaker 1: the right direction. And particularly for fund managers, those three 1499 01:35:08,040 --> 01:35:13,400 Speaker 1: characteristics are the ones that I find every time. They're 1500 01:35:13,479 --> 01:35:18,200 Speaker 1: very competitive, hard working, and they're oddly flexible. You know, 1501 01:35:18,200 --> 01:35:20,240 Speaker 1: when they have a bad idea, they're able to get 1502 01:35:20,320 --> 01:35:22,920 Speaker 1: rid of it moving. In my office we call that 1503 01:35:23,560 --> 01:35:27,000 Speaker 1: strong opinions weekly health, so that you can really have 1504 01:35:27,280 --> 01:35:29,080 Speaker 1: a strong belief in it. But as soon as you 1505 01:35:29,120 --> 01:35:32,080 Speaker 1: see proof you're wrong, you gotta It's okay to be wrong, 1506 01:35:32,120 --> 01:35:34,439 Speaker 1: it's not okay to stay wrong, is what I learned 1507 01:35:34,439 --> 01:35:36,880 Speaker 1: on a trading desk. I heard that early on, but 1508 01:35:37,160 --> 01:35:41,000 Speaker 1: that's the same concept, is to be flexible. And now 1509 01:35:41,000 --> 01:35:44,080 Speaker 1: we're up to our last question, what do you wish 1510 01:35:44,120 --> 01:35:48,639 Speaker 1: you knew about investing today? What do you wish when 1511 01:35:48,880 --> 01:35:51,960 Speaker 1: when you began? Rephrase it, then, when you began, what 1512 01:35:51,960 --> 01:35:53,559 Speaker 1: do you know today you wish you knew when you 1513 01:35:53,600 --> 01:35:56,120 Speaker 1: started out? So, man, I very I got your list 1514 01:35:56,120 --> 01:35:58,040 Speaker 1: of questions. I looked at that one and it just 1515 01:35:58,120 --> 01:36:01,519 Speaker 1: has me stumped. I thought about coming over here, and 1516 01:36:01,760 --> 01:36:07,040 Speaker 1: nothing just wells up that that there's something that you 1517 01:36:07,120 --> 01:36:11,599 Speaker 1: figured out today that would have been of assistance right 1518 01:36:11,640 --> 01:36:15,400 Speaker 1: out of school. Nothing came to mind. You know, someone said, 1519 01:36:15,479 --> 01:36:17,559 Speaker 1: gave me an answer to that once, and the answer 1520 01:36:17,640 --> 01:36:21,360 Speaker 1: what have you gotten the path? See? For me? So 1521 01:36:21,560 --> 01:36:24,519 Speaker 1: the answer that I found intriguing was, gee, what I 1522 01:36:24,600 --> 01:36:27,519 Speaker 1: know today? I had to take a certain path to learn? 1523 01:36:28,200 --> 01:36:30,240 Speaker 1: And if I knew that when I started, well, then 1524 01:36:30,240 --> 01:36:34,599 Speaker 1: where's the path? Where's the the accumulation of wisdom? That 1525 01:36:34,720 --> 01:36:39,960 Speaker 1: the journey is itself the value? Sort of a Zen philosophy. 1526 01:36:39,960 --> 01:36:43,920 Speaker 1: I don't remember who answered it that way, but I 1527 01:36:43,960 --> 01:36:46,800 Speaker 1: found that sort of Maybe it was Bobby Flight. I 1528 01:36:46,840 --> 01:36:51,320 Speaker 1: thought it was kind of an intriguing Okay, that's very philosophically. 1529 01:36:51,360 --> 01:36:56,600 Speaker 1: I've been I'm have you life as a as a 1530 01:36:56,680 --> 01:37:02,120 Speaker 1: journey not a destination, as they put it, and and 1531 01:37:02,200 --> 01:37:07,240 Speaker 1: I have. I've been extremely lucky and that my journey 1532 01:37:07,320 --> 01:37:12,000 Speaker 1: has been pretty much in a straight line um as 1533 01:37:12,000 --> 01:37:15,800 Speaker 1: we've talked about today. So I don't there's nothing, there's 1534 01:37:15,800 --> 01:37:19,599 Speaker 1: no So the journey was that. That's a similar answer 1535 01:37:19,640 --> 01:37:23,080 Speaker 1: to what somebody else said, which was the journey was 1536 01:37:23,120 --> 01:37:25,320 Speaker 1: what they learned and is you have to kind of 1537 01:37:25,360 --> 01:37:28,080 Speaker 1: live it. You can't go back to square one with Okay, 1538 01:37:28,080 --> 01:37:31,000 Speaker 1: here's everything I've learned. I would have done it differently, right, 1539 01:37:31,040 --> 01:37:32,920 Speaker 1: It's it's how to you how to take that process 1540 01:37:32,960 --> 01:37:35,320 Speaker 1: to get what you You couldn't be here today if 1541 01:37:35,320 --> 01:37:38,639 Speaker 1: you didn't take that route. So, ED, thank you so 1542 01:37:38,720 --> 01:37:41,160 Speaker 1: much for being so generous with your time and spending 1543 01:37:41,280 --> 01:37:44,120 Speaker 1: my place so much time with us. I really for 1544 01:37:44,120 --> 01:37:47,479 Speaker 1: for listeners. You should realize ED doesn't do a lot 1545 01:37:47,520 --> 01:37:50,559 Speaker 1: of media, and I really kind of hunted you down 1546 01:37:50,640 --> 01:37:54,360 Speaker 1: for for a while trying to cajole you into doing this, 1547 01:37:54,400 --> 01:37:58,720 Speaker 1: and I really appreciate it. So thank you. Um you've 1548 01:37:58,720 --> 01:38:01,799 Speaker 1: been listening to Masters and in Business on Bloomberg Radio. 1549 01:38:02,240 --> 01:38:05,400 Speaker 1: If you want to hear more conversations like this, just 1550 01:38:05,560 --> 01:38:08,240 Speaker 1: look up or down an inch or so on your 1551 01:38:08,960 --> 01:38:14,000 Speaker 1: um iTunes or Bloomberg dot com. UM. I want to 1552 01:38:14,040 --> 01:38:18,360 Speaker 1: thank Charlie Vohmer, our producer and Matt our engineer, and 1553 01:38:18,400 --> 01:38:20,600 Speaker 1: Mike bat Nick, the head of research, who helps us 1554 01:38:20,640 --> 01:38:24,200 Speaker 1: put together all these questions. Uh, be sure and check 1555 01:38:24,240 --> 01:38:27,360 Speaker 1: out my daily column on Bloomberg View and follow me 1556 01:38:27,400 --> 01:38:30,439 Speaker 1: on Twitter at rid Halts. You've been listening to Masters 1557 01:38:30,439 --> 01:38:32,400 Speaker 1: in Business on Bloomberg Radio.