1 00:00:00,160 --> 00:00:02,440 Speaker 1: The future may not be clear, but our commitment is 2 00:00:02,600 --> 00:00:04,440 Speaker 1: so when you sit with an advisor at Merrill Lynch, 3 00:00:04,519 --> 00:00:07,160 Speaker 1: we'll put your interests first. Visit mL dot com and 4 00:00:07,240 --> 00:00:09,640 Speaker 1: learn more about Merrill Lynch, an affiliative Bank of America. 5 00:00:09,760 --> 00:00:12,240 Speaker 1: Mery Lynch makes available products and services offered by Merrill Lynch. 6 00:00:12,280 --> 00:00:14,600 Speaker 1: Pierce Veteran Smith Incorporated or Registered Broker Dealer. Remember s 7 00:00:14,640 --> 00:00:20,599 Speaker 1: I p c V is Masters in Business with Very 8 00:00:20,680 --> 00:00:26,799 Speaker 1: Riddholtz on Boomberg Radio. This week on the podcast, we 9 00:00:26,880 --> 00:00:29,680 Speaker 1: have an extra special guest. His name is Ned Davis. 10 00:00:29,680 --> 00:00:33,000 Speaker 1: He is the founder of the highly regarded Ned Davis 11 00:00:33,000 --> 00:00:36,680 Speaker 1: Research and author of numerous books. Will talk about that later. 12 00:00:37,200 --> 00:00:42,240 Speaker 1: Quick interesting story. Long before Masters in Business came along, 13 00:00:42,440 --> 00:00:46,000 Speaker 1: I had been kicking an idea around about finding these 14 00:00:46,000 --> 00:00:51,080 Speaker 1: really successful, articulate, intelligent people and sitting down and having 15 00:00:51,080 --> 00:00:54,480 Speaker 1: a conversation with them, and I think Ned. I'll include 16 00:00:54,480 --> 00:00:57,960 Speaker 1: the link to this on on the blog post. Ned 17 00:00:58,000 --> 00:01:01,320 Speaker 1: may have been the very first person and I spoke 18 00:01:01,400 --> 00:01:04,160 Speaker 1: to UM. We didn't on the radio. We did it 19 00:01:04,440 --> 00:01:08,360 Speaker 1: uh unedited. It was pretty much straight through. It's very rough, 20 00:01:08,480 --> 00:01:11,920 Speaker 1: but the concept for this show pretty much came from 21 00:01:11,920 --> 00:01:15,120 Speaker 1: a conversation I had with him. Uh. He is one 22 00:01:15,160 --> 00:01:19,280 Speaker 1: of the best regarded technicians around, a technicians technician. If 23 00:01:19,319 --> 00:01:24,000 Speaker 1: you were at all interested in quantitative technical trading, UM, 24 00:01:24,080 --> 00:01:27,039 Speaker 1: you're gonna love this. So, with no further ado, my 25 00:01:27,200 --> 00:01:36,240 Speaker 1: conversation with Ned Davis. My special guest today is Ned Davis. 26 00:01:36,520 --> 00:01:41,080 Speaker 1: He is the founder of renowned technical research firm ned 27 00:01:41,200 --> 00:01:45,680 Speaker 1: Davis re Research. Ned was a regular on This Week 28 00:01:45,840 --> 00:01:49,800 Speaker 1: with Lewis Rukeiser. He frequently graces the pages of Barons 29 00:01:49,880 --> 00:01:53,880 Speaker 1: and other financial publications. He founded ned Davis Research in 30 00:01:54,800 --> 00:01:58,200 Speaker 1: and now employees well over a hundred people. He is 31 00:01:58,240 --> 00:02:03,520 Speaker 1: the author of the Triumph of Contrarian Investing, Markets in 32 00:02:03,600 --> 00:02:07,240 Speaker 1: Motion and being Right or Making Money, and he's probably 33 00:02:07,360 --> 00:02:12,399 Speaker 1: best known as a technicians technician. Ned Davis, Welcome to Bloomberg. 34 00:02:12,800 --> 00:02:16,440 Speaker 1: Thank you for having me. Uh. You know, it's it's 35 00:02:16,440 --> 00:02:18,600 Speaker 1: really interesting that we have you here because when I 36 00:02:18,720 --> 00:02:22,800 Speaker 1: first started doing this, before we were broadcasting them on 37 00:02:22,840 --> 00:02:24,720 Speaker 1: the radio, you were one of the first people I 38 00:02:24,800 --> 00:02:27,600 Speaker 1: spoke with, uh, and we did a phone interview. I 39 00:02:27,600 --> 00:02:30,320 Speaker 1: want to say that was like eight or ten years ago. 40 00:02:30,480 --> 00:02:33,840 Speaker 1: A lot of stuff has happened since then. Let's let's 41 00:02:33,880 --> 00:02:37,280 Speaker 1: talk a little bit about your background. You were studying 42 00:02:37,600 --> 00:02:42,120 Speaker 1: French and I believe it was Paris when you decided, um, 43 00:02:42,160 --> 00:02:45,680 Speaker 1: I'm gonna change my career direction. Tell us, tell us 44 00:02:45,680 --> 00:02:48,320 Speaker 1: about that incident. Well, actually, I was at the University 45 00:02:48,360 --> 00:02:51,560 Speaker 1: of North Carolina and I had decided I wanted to 46 00:02:51,600 --> 00:02:54,000 Speaker 1: be a doctor, and so I was a chemistry major. 47 00:02:54,200 --> 00:02:57,880 Speaker 1: And then I decided did not want to be a doctor. 48 00:02:58,080 --> 00:03:01,880 Speaker 1: And I had was spinning part of a year in France, 49 00:03:02,000 --> 00:03:05,160 Speaker 1: and uh, so I had to graduate with something else. 50 00:03:05,160 --> 00:03:08,720 Speaker 1: And I really liked French literature, so uh that's the 51 00:03:08,760 --> 00:03:13,000 Speaker 1: way I graduated as a French major. Um, I wasn't 52 00:03:13,040 --> 00:03:15,560 Speaker 1: really sure what I wanted to do. So they have these, 53 00:03:15,720 --> 00:03:20,160 Speaker 1: uh I guess psychological tests that test your aptitude and 54 00:03:20,320 --> 00:03:24,440 Speaker 1: your interests, and they said my aptitude was in math, 55 00:03:25,000 --> 00:03:27,680 Speaker 1: but I didn't wasn't interested in math. And what I 56 00:03:27,720 --> 00:03:29,799 Speaker 1: was interested in it was verbal, but I wasn't any 57 00:03:29,800 --> 00:03:32,960 Speaker 1: good at verbal. So I's thinking. I had had two 58 00:03:33,080 --> 00:03:34,960 Speaker 1: jobs in the summer at a company called J. C. 59 00:03:35,080 --> 00:03:38,200 Speaker 1: Bradford Company as an intern, and I really liked that 60 00:03:38,240 --> 00:03:40,520 Speaker 1: you're able to write and read and write, and uh, 61 00:03:40,640 --> 00:03:42,880 Speaker 1: you be able to use your math skills. I said, well, 62 00:03:42,920 --> 00:03:45,360 Speaker 1: this is this is a perfect for me. So then 63 00:03:45,400 --> 00:03:47,520 Speaker 1: I ended up going to Harvard Business School, which I 64 00:03:47,560 --> 00:03:49,720 Speaker 1: thought I was going to learn business, but it's actually 65 00:03:49,720 --> 00:03:52,400 Speaker 1: a management school, which is not what I wanted. So 66 00:03:53,120 --> 00:03:55,840 Speaker 1: then I worked went to work full time Bradford Company. 67 00:03:55,920 --> 00:03:58,040 Speaker 1: So somewhere in the middle of that, I recall you 68 00:03:58,160 --> 00:04:02,880 Speaker 1: telling a story about study French and France. Someone made 69 00:04:02,880 --> 00:04:06,240 Speaker 1: a reference about your southern accent and you were kind 70 00:04:06,240 --> 00:04:09,000 Speaker 1: of thinking, really, I'm not sure if this is for me, 71 00:04:09,080 --> 00:04:13,680 Speaker 1: am I misremembering, Well, it was. I really did not 72 00:04:13,840 --> 00:04:16,080 Speaker 1: know much French one. And when I went to France 73 00:04:16,120 --> 00:04:18,719 Speaker 1: and uh, you know, I was trying to learn the 74 00:04:18,800 --> 00:04:21,760 Speaker 1: language is best I could. And uh we had a 75 00:04:21,800 --> 00:04:25,040 Speaker 1: class and the teacher said, oh, thank you for saying that. 76 00:04:25,480 --> 00:04:27,960 Speaker 1: Uh this was in French, of course, and she said, 77 00:04:27,960 --> 00:04:31,560 Speaker 1: I always wondered what Lyndon Johnson would sound like speaking French, 78 00:04:31,600 --> 00:04:34,040 Speaker 1: and now I know, and I'm thinking, Lyndon Johnson can 79 00:04:34,080 --> 00:04:39,240 Speaker 1: barely speak English. So I decided that, uh, speaking French 80 00:04:39,360 --> 00:04:41,560 Speaker 1: was not going to be my skill set. So you 81 00:04:41,640 --> 00:04:44,799 Speaker 1: go to j C. Bradford, you start penning a daily 82 00:04:45,279 --> 00:04:50,279 Speaker 1: technical report. What will your go to indicators or charts 83 00:04:50,320 --> 00:04:52,880 Speaker 1: back at that time. I think I was pretty much 84 00:04:52,880 --> 00:04:56,680 Speaker 1: a traditional chartist at that time and just looking at 85 00:04:56,760 --> 00:05:00,359 Speaker 1: chart patterns and uh trying to pick out stocks and 86 00:05:00,440 --> 00:05:02,680 Speaker 1: up trends and stay away from stocks and down trends. 87 00:05:02,720 --> 00:05:05,119 Speaker 1: But of course I was studying a lot of other 88 00:05:06,080 --> 00:05:09,200 Speaker 1: uh i'd say, independent research at the time, so I 89 00:05:09,240 --> 00:05:11,520 Speaker 1: was trying to learn from that. So I pretty much 90 00:05:12,200 --> 00:05:15,880 Speaker 1: I selt self taught myself my field. What was it like, 91 00:05:16,360 --> 00:05:20,239 Speaker 1: really beginning your education in the field in what turned 92 00:05:20,279 --> 00:05:22,839 Speaker 1: out to be a pretty long bear market in the 93 00:05:22,880 --> 00:05:28,240 Speaker 1: sixties and seventies. Yeah, I actually I think that makes 94 00:05:28,240 --> 00:05:30,760 Speaker 1: a big difference when you ask people what your outlook 95 00:05:30,800 --> 00:05:32,920 Speaker 1: is on the market, and I said, when when did 96 00:05:32,920 --> 00:05:35,279 Speaker 1: you start in the business, And if you started in 97 00:05:35,360 --> 00:05:38,640 Speaker 1: sixty eight like I did, you were going to live 98 00:05:38,680 --> 00:05:42,280 Speaker 1: the first fourteen years and a really grueling bear market. 99 00:05:42,440 --> 00:05:45,479 Speaker 1: So a quote of yours goes something like this, We 100 00:05:45,560 --> 00:05:48,960 Speaker 1: are on the We are in the business of making mistakes. 101 00:05:49,000 --> 00:05:52,279 Speaker 1: The only difference between the winners and the losers is 102 00:05:52,320 --> 00:05:55,640 Speaker 1: that the winners make small mistakes while the losers make 103 00:05:55,680 --> 00:06:00,680 Speaker 1: big mistakes. Discuss that a bit the whole. One Buffet's 104 00:06:00,720 --> 00:06:03,719 Speaker 1: got a quote and he says his rules. Two rules 105 00:06:03,760 --> 00:06:06,880 Speaker 1: for making money. And he said rule number one, don't 106 00:06:06,920 --> 00:06:10,040 Speaker 1: lose money. And he said rule number two, don't never 107 00:06:10,080 --> 00:06:14,800 Speaker 1: forget rule number one. So, uh, it's all about compounding 108 00:06:14,880 --> 00:06:17,320 Speaker 1: interest and compounding your returns. And if you take a 109 00:06:17,400 --> 00:06:21,000 Speaker 1: horrible loss, uh, you know, if you lose fifty on 110 00:06:21,040 --> 00:06:24,039 Speaker 1: a stock, u's not a fifty percent rise, it gets 111 00:06:24,080 --> 00:06:26,480 Speaker 1: you back to even it's a it's a hundred percent rise. 112 00:06:27,040 --> 00:06:29,440 Speaker 1: So if you have a big loss, it it's really 113 00:06:29,480 --> 00:06:33,279 Speaker 1: hard to compound your returns. So I knew there was 114 00:06:33,279 --> 00:06:36,040 Speaker 1: gonna be mistakes in the business. I'm just trying to, 115 00:06:36,640 --> 00:06:38,719 Speaker 1: you know, is find out a mistake and cut it 116 00:06:38,760 --> 00:06:42,160 Speaker 1: as quickly as possible. I think that's the key. And 117 00:06:42,440 --> 00:06:45,760 Speaker 1: early in your career you had made a number of calls, 118 00:06:45,760 --> 00:06:48,640 Speaker 1: some of which were very big calls. But I have 119 00:06:48,960 --> 00:06:51,880 Speaker 1: been following your career and reading you for so long. 120 00:06:52,360 --> 00:06:56,920 Speaker 1: I know you're thinking on predictions and forecasting has evolved 121 00:06:56,920 --> 00:07:00,800 Speaker 1: a lot. Tell us a little bit about that. Yes, 122 00:07:01,160 --> 00:07:04,080 Speaker 1: you know, it's a business of forecasting. That's what clients 123 00:07:04,120 --> 00:07:06,279 Speaker 1: want to want you to do. So that's what I 124 00:07:06,320 --> 00:07:09,560 Speaker 1: tried to do. And I studied forecasts, and I saw 125 00:07:09,600 --> 00:07:15,000 Speaker 1: a lot of forecasters make some dramatically correct forecasts, but generally, 126 00:07:15,520 --> 00:07:18,120 Speaker 1: uh they would make a great forecast and a couple 127 00:07:18,120 --> 00:07:20,320 Speaker 1: of years later make a terrible forecast. And it was 128 00:07:20,360 --> 00:07:22,160 Speaker 1: just like a flame out in the night. And I 129 00:07:22,200 --> 00:07:24,680 Speaker 1: didn't want my career to be that way. And I 130 00:07:25,680 --> 00:07:29,160 Speaker 1: was lucky enough to have some some some really good forecasts, 131 00:07:29,200 --> 00:07:31,600 Speaker 1: but I still was suspicious. And when you go back 132 00:07:31,640 --> 00:07:35,960 Speaker 1: and study the forecasting record, For example, the Federal Reserve 133 00:07:36,040 --> 00:07:40,680 Speaker 1: Board of Philadelphia has been studying for fifty years consensus 134 00:07:40,680 --> 00:07:44,960 Speaker 1: a professional economists and they look at their forecast for 135 00:07:45,000 --> 00:07:49,840 Speaker 1: the following year. There's been seven recessions since nine seventy 136 00:07:50,000 --> 00:07:54,520 Speaker 1: and the economists as a group, obviously individual economists have 137 00:07:54,600 --> 00:07:57,720 Speaker 1: done better, but as a group they called none, not 138 00:07:57,960 --> 00:08:01,680 Speaker 1: a single one of the seven recessions. And interestingly enough, 139 00:08:01,840 --> 00:08:05,320 Speaker 1: in the last since two thousand and one, they've been 140 00:08:05,840 --> 00:08:09,640 Speaker 1: eighty I think eighty six percent of the time they've 141 00:08:09,680 --> 00:08:13,440 Speaker 1: been too low on their forecast. Excuse me, the forecasts 142 00:08:13,440 --> 00:08:15,920 Speaker 1: have been too high for what the economy has actually done. 143 00:08:16,160 --> 00:08:19,800 Speaker 1: So it's a very tough field forecasting. You launched your 144 00:08:19,840 --> 00:08:25,000 Speaker 1: firm in really a couple of recessions, A long bear market. 145 00:08:25,560 --> 00:08:28,400 Speaker 1: That must have been a really challenging time to launch 146 00:08:28,440 --> 00:08:33,880 Speaker 1: a new uh services fun Well, actually, you know, we 147 00:08:33,880 --> 00:08:37,559 Speaker 1: were we sell ourselves as risk managers, and it had 148 00:08:37,640 --> 00:08:40,800 Speaker 1: been such a long period of high risk that uh 149 00:08:41,200 --> 00:08:46,200 Speaker 1: people were looking around for risk managers. And uh also 150 00:08:46,480 --> 00:08:49,160 Speaker 1: it just so happened after that period long period of 151 00:08:49,160 --> 00:08:52,319 Speaker 1: time six haiti. Most of the time I was with J. C. Bradford, 152 00:08:52,320 --> 00:08:56,520 Speaker 1: And of course retail brokerage firms are historically bullish and 153 00:08:56,920 --> 00:09:00,640 Speaker 1: should be. But uh So, anyway, us to the time 154 00:09:00,720 --> 00:09:03,200 Speaker 1: that I was there, I was negative and it was 155 00:09:03,280 --> 00:09:07,319 Speaker 1: just about the early period that I was turning more 156 00:09:07,360 --> 00:09:10,040 Speaker 1: bulish on the long term out look. So that that 157 00:09:10,200 --> 00:09:14,400 Speaker 1: was a very fortunate thing. And um so I left there. 158 00:09:14,520 --> 00:09:19,000 Speaker 1: I was a partner Bradford's, but I wanted to, I 159 00:09:19,000 --> 00:09:24,240 Speaker 1: guess my contribution to the businesses that uh this was 160 00:09:24,320 --> 00:09:27,360 Speaker 1: really before computers had taken over. In fact, they had 161 00:09:27,400 --> 00:09:31,040 Speaker 1: just started over, taking over the back offices, and uh 162 00:09:31,280 --> 00:09:33,440 Speaker 1: so I wanted to make the research that I do 163 00:09:33,600 --> 00:09:36,280 Speaker 1: computerized so that I could test some of these things 164 00:09:36,320 --> 00:09:39,840 Speaker 1: that that people saw on charts and see if any 165 00:09:39,880 --> 00:09:43,360 Speaker 1: of them worked. So you've got a lot of pushback 166 00:09:43,400 --> 00:09:46,200 Speaker 1: from Bradford saying, hey, I really think we should adapt 167 00:09:46,200 --> 00:09:49,199 Speaker 1: the new technology to our practice. They weren't very keen 168 00:09:49,280 --> 00:09:52,920 Speaker 1: on that. Well that the answer basically was if if 169 00:09:52,920 --> 00:09:55,319 Speaker 1: it ain't broke, don't fix it, which is which is 170 00:09:55,360 --> 00:09:57,840 Speaker 1: a good answer. But this is something I wanted to do. 171 00:09:58,040 --> 00:10:00,600 Speaker 1: And there were a couple of Bradford broker ed Mendel 172 00:10:00,679 --> 00:10:03,200 Speaker 1: and Kent Reagan Stein that they wanted to go out 173 00:10:03,200 --> 00:10:05,920 Speaker 1: and try this, and uh, we already had a pretty 174 00:10:05,920 --> 00:10:09,880 Speaker 1: good following, so uh, we were were We were nervous 175 00:10:09,920 --> 00:10:14,280 Speaker 1: about it obviously, but we um, we didn't use any 176 00:10:14,360 --> 00:10:16,760 Speaker 1: debt and we put up our own money and uh, 177 00:10:16,920 --> 00:10:18,920 Speaker 1: you know, we had enough customers and we made a 178 00:10:18,960 --> 00:10:21,319 Speaker 1: go of it from the beginning, launching with a handful 179 00:10:21,360 --> 00:10:23,400 Speaker 1: of customers or a decent number of customers. How to 180 00:10:23,440 --> 00:10:28,640 Speaker 1: make that transition fairly even? What were the first fairly easy? 181 00:10:28,760 --> 00:10:31,720 Speaker 1: What were the first couple of years like, um, when 182 00:10:31,720 --> 00:10:35,600 Speaker 1: you were building the business? Well, you know it was 183 00:10:36,640 --> 00:10:39,840 Speaker 1: I'm not a manager, I I'm a research nerd and 184 00:10:39,880 --> 00:10:42,960 Speaker 1: that's what I like to do. So uh, Eddie and 185 00:10:43,040 --> 00:10:46,400 Speaker 1: Kent were in Atlanta, Georgia, which Eddie Mendel and Kent 186 00:10:46,600 --> 00:10:49,120 Speaker 1: Reagan Stein, and they were. They were in Atlanta, which 187 00:10:49,160 --> 00:10:52,679 Speaker 1: is where the sales were, and I was in, uh, 188 00:10:52,720 --> 00:10:57,240 Speaker 1: just outside of Sarasota, Florida, where I lived, and so anyway, 189 00:10:57,280 --> 00:11:00,680 Speaker 1: I had to put together some people and was uh 190 00:11:00,840 --> 00:11:03,600 Speaker 1: it was it was fun being a Being a starting 191 00:11:03,600 --> 00:11:05,600 Speaker 1: manager is not something that I liked doing, but it 192 00:11:05,679 --> 00:11:08,800 Speaker 1: was fun. So after a few years you developed quite 193 00:11:08,800 --> 00:11:11,720 Speaker 1: a reputation. And one of the things that Davis Research 194 00:11:12,640 --> 00:11:18,120 Speaker 1: was known for was these specific research projects requested by clients. 195 00:11:18,120 --> 00:11:22,160 Speaker 1: In fact, uh recently they were doing more than two 196 00:11:22,240 --> 00:11:27,720 Speaker 1: thousand UH client generated research projects a year. How did 197 00:11:27,760 --> 00:11:32,840 Speaker 1: that approach develop and how how how do people approach 198 00:11:32,920 --> 00:11:35,000 Speaker 1: you with, Hey, I has an idea I want to 199 00:11:35,000 --> 00:11:38,440 Speaker 1: test out. Well, once we built our own software and 200 00:11:38,520 --> 00:11:43,280 Speaker 1: had the computers around, you know, my idea actually was 201 00:11:43,360 --> 00:11:46,760 Speaker 1: building a company similar to what Value Line had built 202 00:11:46,760 --> 00:11:51,120 Speaker 1: in the fundamental research area. UH. And I remember specifically 203 00:11:51,160 --> 00:11:54,600 Speaker 1: the date, the date that Arnold Bernhard died because Value 204 00:11:54,640 --> 00:11:58,079 Speaker 1: Line stock went up big that day, and I thought, this, 205 00:11:58,080 --> 00:11:59,880 Speaker 1: this is the kind of firm you want to be 206 00:12:00,000 --> 00:12:03,120 Speaker 1: old that people want your data, they want your charts, 207 00:12:03,160 --> 00:12:07,160 Speaker 1: they want your studies. They aren't necessarily looking for you know, 208 00:12:07,559 --> 00:12:11,280 Speaker 1: a guru that walks on water. They so I decided 209 00:12:11,320 --> 00:12:13,480 Speaker 1: to try to build a company like that. So yes, 210 00:12:13,520 --> 00:12:17,720 Speaker 1: we set up a client services department where we would say, 211 00:12:18,120 --> 00:12:21,360 Speaker 1: you have research questions, you bring them here and we'll 212 00:12:21,400 --> 00:12:24,199 Speaker 1: do the research for you. And we actually we won't 213 00:12:24,240 --> 00:12:27,000 Speaker 1: share the research with our own research team. It's it's 214 00:12:27,000 --> 00:12:30,560 Speaker 1: your proprietary product, and uh it's it's been a good 215 00:12:30,559 --> 00:12:34,240 Speaker 1: product for us. And we've come up. Actually, you know, 216 00:12:34,360 --> 00:12:36,560 Speaker 1: I don't know come we've come up. I've come up 217 00:12:36,600 --> 00:12:38,120 Speaker 1: with a lot of ideas on my own, but we 218 00:12:38,400 --> 00:12:42,000 Speaker 1: probably we say we're client driven, and uh, some of 219 00:12:42,000 --> 00:12:45,560 Speaker 1: the best ideas I've had, we're client ideas. Give us 220 00:12:45,760 --> 00:12:49,640 Speaker 1: an example of some typical client client requests or some 221 00:12:49,720 --> 00:12:53,280 Speaker 1: unusual client requests. Well, you know a lot of times 222 00:12:53,320 --> 00:12:55,080 Speaker 1: that we'll have a chart and they'll want to see 223 00:12:55,120 --> 00:12:57,040 Speaker 1: it back further or they'll want to see a different 224 00:12:57,160 --> 00:13:01,719 Speaker 1: version of it. Uh um. But you know, we had 225 00:13:01,720 --> 00:13:05,000 Speaker 1: a lot of crisis events when I got into the business, 226 00:13:05,040 --> 00:13:08,840 Speaker 1: and people said, what did the market do after there's 227 00:13:09,040 --> 00:13:12,040 Speaker 1: a major crisis event? So we went back and you know, 228 00:13:12,040 --> 00:13:14,800 Speaker 1: we tried to study history, and you know, there was 229 00:13:14,840 --> 00:13:18,720 Speaker 1: Pearl Harbor and there was JFK's assassination. I got in 230 00:13:18,720 --> 00:13:21,160 Speaker 1: the business. You know, Martin Luther King and Robert Kennedy 231 00:13:21,200 --> 00:13:24,480 Speaker 1: died the first assassinated the first year, and then you 232 00:13:24,520 --> 00:13:27,640 Speaker 1: had Penn Central and and and on and on. So 233 00:13:27,679 --> 00:13:30,040 Speaker 1: we put all this together and I saw what the 234 00:13:30,080 --> 00:13:34,040 Speaker 1: market did, and and uh, it was fascinating. Generally there 235 00:13:34,240 --> 00:13:37,480 Speaker 1: was a a sell off, as you would expect on 236 00:13:37,559 --> 00:13:41,679 Speaker 1: the news, but very short term and almost you know, 237 00:13:41,960 --> 00:13:44,280 Speaker 1: six months to a year later, the market was almost 238 00:13:44,320 --> 00:13:47,199 Speaker 1: always higher. So we had we had put this study together, 239 00:13:47,440 --> 00:13:49,640 Speaker 1: and uh we had shown it a couple of times 240 00:13:49,640 --> 00:13:53,600 Speaker 1: in publications, and then uh, on nine eleven, um, we 241 00:13:53,679 --> 00:13:56,040 Speaker 1: got a call from We put it out again and 242 00:13:56,280 --> 00:13:58,600 Speaker 1: we got a call from Barns and they wanted to 243 00:13:58,720 --> 00:14:02,520 Speaker 1: use it. And uh, you know it as terrible as 244 00:14:02,559 --> 00:14:06,600 Speaker 1: that tragedy was, the study was very timely and that 245 00:14:06,760 --> 00:14:08,520 Speaker 1: you know, there was a week cell often it was 246 00:14:08,559 --> 00:14:11,920 Speaker 1: a very scary time. But uh, the market did recover 247 00:14:12,000 --> 00:14:16,440 Speaker 1: after that pretty well. So in response to unexpected geopolitical events, 248 00:14:17,080 --> 00:14:20,880 Speaker 1: markets wobble and then go about resuming the prior trends exactly. 249 00:14:20,960 --> 00:14:24,600 Speaker 1: Sometimes sometimes you know, they do better. Uh, it's it's 250 00:14:24,720 --> 00:14:28,000 Speaker 1: it's the logic's a little difficult to understand. But if 251 00:14:28,080 --> 00:14:31,840 Speaker 1: you're a nervous holder of stock and some bad news comes, uh, 252 00:14:32,240 --> 00:14:36,040 Speaker 1: you panic out, and uh, then who's left or are 253 00:14:36,120 --> 00:14:39,400 Speaker 1: strongholders of stock? So you know, it's at that point 254 00:14:39,400 --> 00:14:42,040 Speaker 1: it's it's hard to get people to sell. After you've 255 00:14:42,040 --> 00:14:46,560 Speaker 1: gotten the nervous people out, you've got good strongholders of stock. Counterintuitive, 256 00:14:46,640 --> 00:14:49,040 Speaker 1: but you get a wash out and then you're only 257 00:14:49,120 --> 00:14:52,960 Speaker 1: left with with people who are not likely to to 258 00:14:53,120 --> 00:14:56,800 Speaker 1: jump out at any given moment. When the exception to this, 259 00:14:57,000 --> 00:15:00,680 Speaker 1: of course really and they're not many, but the exception 260 00:15:00,760 --> 00:15:04,840 Speaker 1: was Lehman, which was a panic event that uh there 261 00:15:04,920 --> 00:15:08,000 Speaker 1: was systemic and I think that that is a key 262 00:15:08,080 --> 00:15:11,080 Speaker 1: when you're looking at crisis events. If if if it's 263 00:15:11,120 --> 00:15:14,160 Speaker 1: going to uh take down the financial system, then and 264 00:15:14,400 --> 00:15:19,280 Speaker 1: the study is not gonna work. But pretty much anything else, wars, bombings, 265 00:15:19,880 --> 00:15:22,520 Speaker 1: terror attacks, uh you know, the worst things you can 266 00:15:22,560 --> 00:15:26,960 Speaker 1: think of, assassination of a president. Uh, these things pretty 267 00:15:27,000 --> 00:15:29,760 Speaker 1: much all fit the same pattern. Even Lehman Brothers was 268 00:15:29,800 --> 00:15:34,840 Speaker 1: September eight. Markets had peaked October oh seven, so it 269 00:15:34,880 --> 00:15:38,880 Speaker 1: had been practically a year of downtrend that wouldn't the 270 00:15:38,920 --> 00:15:42,600 Speaker 1: only real difference between the trend is Lehman just precipitated 271 00:15:42,600 --> 00:15:46,120 Speaker 1: in an acceleration. That's partly true, but I think the 272 00:15:46,840 --> 00:15:51,560 Speaker 1: systemic part to the banking systems critical. Let's talk a 273 00:15:51,640 --> 00:15:56,640 Speaker 1: little bit about um technical analysis. So you were an 274 00:15:56,640 --> 00:16:01,080 Speaker 1: early adopter not only of technical analysis, it of technology 275 00:16:01,160 --> 00:16:04,640 Speaker 1: as well. Tell us how that changed the way you 276 00:16:04,720 --> 00:16:08,720 Speaker 1: looked at markets. Well, you know, you start off you 277 00:16:08,800 --> 00:16:12,200 Speaker 1: read Edwards and McGee, a technical analysis book or a 278 00:16:12,200 --> 00:16:16,359 Speaker 1: lot of other really well written books on chart patterns, 279 00:16:16,520 --> 00:16:20,840 Speaker 1: and uh, then you start applying that and you, uh 280 00:16:21,880 --> 00:16:24,320 Speaker 1: you see a head and shoulders bottom, and you say, oh, 281 00:16:24,360 --> 00:16:27,720 Speaker 1: my goodness, is stuck is turning up? And then you're 282 00:16:27,720 --> 00:16:30,720 Speaker 1: reading another report and somebody's looking at the same chart 283 00:16:30,800 --> 00:16:32,480 Speaker 1: and they say, oh, no, that's that's a head and 284 00:16:32,480 --> 00:16:37,400 Speaker 1: shoulders top, and uh it was almost like, uh, you 285 00:16:37,520 --> 00:16:39,960 Speaker 1: made your own reality. You looked at a chart and 286 00:16:40,040 --> 00:16:43,680 Speaker 1: you saw what you wanted to see. So uh, I 287 00:16:43,720 --> 00:16:46,920 Speaker 1: said that I can't do this. I have to uh 288 00:16:47,120 --> 00:16:50,600 Speaker 1: have it more quantitative. I've got to test these things 289 00:16:50,680 --> 00:16:52,680 Speaker 1: and see whether they work or not. So that that 290 00:16:52,760 --> 00:16:56,400 Speaker 1: was the idea really of going to technology. I also 291 00:16:56,440 --> 00:17:01,120 Speaker 1: at that point had gotten interested in other people that 292 00:17:01,200 --> 00:17:04,639 Speaker 1: seemed very successful in the business. One of my mentors 293 00:17:04,680 --> 00:17:08,040 Speaker 1: was a guy named Edson Gould and Uh. He was 294 00:17:08,080 --> 00:17:13,240 Speaker 1: a technician, UM, but he also really believed that the 295 00:17:13,240 --> 00:17:16,640 Speaker 1: stock market and the economy were driven by crowd psychology, 296 00:17:17,119 --> 00:17:19,240 Speaker 1: and he was also a study or of the Federal 297 00:17:19,240 --> 00:17:24,000 Speaker 1: Reserve Board. Also became good friends with Marty's why. He 298 00:17:24,080 --> 00:17:27,200 Speaker 1: started out as a sentiment guy too, and he ended 299 00:17:27,280 --> 00:17:30,240 Speaker 1: up like me, don't fight the Fed, don't fight the tape. 300 00:17:30,320 --> 00:17:33,879 Speaker 1: So so Marty's wage is always my answer to the 301 00:17:34,000 --> 00:17:37,520 Speaker 1: question how come there are no rich technicians? And the 302 00:17:37,600 --> 00:17:41,160 Speaker 1: answer is there are a ton of very successful people 303 00:17:41,160 --> 00:17:45,800 Speaker 1: who use technicals as a fundamental basis of their trading 304 00:17:45,840 --> 00:17:48,520 Speaker 1: and their investment strategy. Did you get a lot of 305 00:17:48,560 --> 00:17:55,160 Speaker 1: pushback from your work from the fundamental community? I think originally, uh, 306 00:17:56,000 --> 00:18:00,840 Speaker 1: there were only a handful Alan Shaw Feral. They were 307 00:18:00,840 --> 00:18:05,120 Speaker 1: really only a handful of technicians that that were UH 308 00:18:05,160 --> 00:18:08,280 Speaker 1: in high regard, and so it was difficult at first. 309 00:18:08,320 --> 00:18:11,000 Speaker 1: But you know, again, once you go through a bear market, 310 00:18:11,119 --> 00:18:13,800 Speaker 1: people look around and say, you know, I need to Uh, 311 00:18:14,160 --> 00:18:16,399 Speaker 1: I can't just buy and hold all the time without 312 00:18:16,520 --> 00:18:19,720 Speaker 1: concern over anything. I have to, you know, manage my risks, 313 00:18:19,760 --> 00:18:24,360 Speaker 1: and so it's gotten obviously a lot more popular. How 314 00:18:24,400 --> 00:18:31,400 Speaker 1: did technicals differ at the institutional level and the retail level. Well, 315 00:18:31,520 --> 00:18:34,560 Speaker 1: I think retail was, you know, more interested in just 316 00:18:35,000 --> 00:18:40,359 Speaker 1: you know, short term movements and stocks, and uh, institutionals 317 00:18:40,359 --> 00:18:44,439 Speaker 1: are more interested in a big picture, uh, maybe tying 318 00:18:44,480 --> 00:18:47,000 Speaker 1: it in with the macro and and and the FED 319 00:18:47,760 --> 00:18:51,080 Speaker 1: and sentiment and a lot longer term things. And I 320 00:18:51,119 --> 00:18:55,440 Speaker 1: had also gotten interested uh you know in the in 321 00:18:55,520 --> 00:18:59,879 Speaker 1: the FED, Federal Reserve boards. Uh, you know, emphasis on 322 00:19:00,040 --> 00:19:02,800 Speaker 1: in the stock market, and so trying to put things 323 00:19:02,840 --> 00:19:06,560 Speaker 1: in perspective. Guy named Hamilton's Bolton with the bike credit 324 00:19:06,560 --> 00:19:09,560 Speaker 1: analysts had put together a monetary thermometer which was really 325 00:19:10,040 --> 00:19:13,720 Speaker 1: one of the first models that they had timing model 326 00:19:14,160 --> 00:19:17,880 Speaker 1: using a Federal Reserve statistics and I was really fascinated 327 00:19:17,920 --> 00:19:23,240 Speaker 1: by that. So these days there's a near infinite amount 328 00:19:23,320 --> 00:19:27,520 Speaker 1: of charting software. You could pretty much access a ton 329 00:19:27,600 --> 00:19:33,520 Speaker 1: of really highly detailed um technical studies, some of which 330 00:19:33,560 --> 00:19:37,240 Speaker 1: are are free, some of which are fairly modest modestly priced. 331 00:19:37,840 --> 00:19:41,000 Speaker 1: What has the ubiquity of computing power and all the 332 00:19:41,080 --> 00:19:45,639 Speaker 1: software done to the world of trading and investing. Well, 333 00:19:45,880 --> 00:19:48,240 Speaker 1: it's a it's a it's a good question, and the 334 00:19:48,359 --> 00:19:52,280 Speaker 1: answers complicated. Uh, there's a lot of good ideas. You know, 335 00:19:52,359 --> 00:19:55,080 Speaker 1: this happens to be one that fits my psyche on 336 00:19:55,160 --> 00:19:57,120 Speaker 1: how to invest. But there's a lot of good ideas 337 00:19:57,840 --> 00:20:00,159 Speaker 1: about how to invest and how to make money. The 338 00:20:00,240 --> 00:20:04,240 Speaker 1: one key problem is if something gets too popular, it's 339 00:20:04,280 --> 00:20:08,080 Speaker 1: gonna hurt its effectiveness. So um, but this is true 340 00:20:08,119 --> 00:20:11,359 Speaker 1: of anything. I remember in the nineteen eighties, which was 341 00:20:12,440 --> 00:20:14,720 Speaker 1: a big period because it was the start of my company, 342 00:20:14,720 --> 00:20:17,400 Speaker 1: and uh it was it was a bullmarket period and 343 00:20:18,000 --> 00:20:20,879 Speaker 1: people didn't need risk advisors for a while, and and 344 00:20:21,080 --> 00:20:25,760 Speaker 1: uh we got into seven and uh I got really, 345 00:20:26,080 --> 00:20:29,320 Speaker 1: uh really worried about derivatives and what they could do 346 00:20:29,440 --> 00:20:32,800 Speaker 1: to the market. But anyway, that are your friends of 347 00:20:32,880 --> 00:20:37,240 Speaker 1: portfolio insurance or something broad portfolio insurance, which was part 348 00:20:37,280 --> 00:20:40,240 Speaker 1: of part of using derivatives to do portfolio insurance. And 349 00:20:40,320 --> 00:20:43,560 Speaker 1: actually I thought portfolio insurance is one of the coolest 350 00:20:43,600 --> 00:20:47,480 Speaker 1: ideas I've ever heard of it and actually fit exactly 351 00:20:47,520 --> 00:20:51,280 Speaker 1: what I want to do with my heads work. I want, 352 00:20:51,359 --> 00:20:53,440 Speaker 1: you know, I want to protect my portfolio and a 353 00:20:53,520 --> 00:20:56,320 Speaker 1: downtrend and so it was a great idea and it 354 00:20:56,400 --> 00:20:59,520 Speaker 1: was widely sold on Wall Street and then uh, you know, 355 00:20:59,600 --> 00:21:02,560 Speaker 1: the mark it started down and unfortunately I was able 356 00:21:02,600 --> 00:21:05,840 Speaker 1: to to sort to sort of see this one. So 357 00:21:06,200 --> 00:21:08,520 Speaker 1: anyway that we had, we had a crash that I 358 00:21:08,560 --> 00:21:11,560 Speaker 1: think was calls really by a great idea that got 359 00:21:11,600 --> 00:21:15,600 Speaker 1: too popular. So, um, this is the thing when technical 360 00:21:15,640 --> 00:21:19,200 Speaker 1: analysis gets so popular. Everybody's looking at the same patterns 361 00:21:19,240 --> 00:21:21,960 Speaker 1: and the same breakouts and acting on them. It's not 362 00:21:22,000 --> 00:21:24,200 Speaker 1: going to act as well as if you could find 363 00:21:24,280 --> 00:21:27,439 Speaker 1: something that nobody's looking at. Let's talk a little bit 364 00:21:27,480 --> 00:21:32,639 Speaker 1: about the stock market and what separates good investors from 365 00:21:32,640 --> 00:21:36,560 Speaker 1: not so good investors. Uh, you wrote something not too 366 00:21:36,560 --> 00:21:38,720 Speaker 1: long ago in one of your books, or maybe it 367 00:21:38,760 --> 00:21:42,639 Speaker 1: was a little while ago. Good investors, successful investors have 368 00:21:42,720 --> 00:21:48,199 Speaker 1: four basic traits. Their objective, their disciplines, they're flexible, and 369 00:21:48,240 --> 00:21:51,280 Speaker 1: their risk averse. Is it that simple, It's just those 370 00:21:51,280 --> 00:21:53,560 Speaker 1: four things. You do that and you're good to be 371 00:21:53,600 --> 00:21:57,480 Speaker 1: a good investor. Yes, it's complicated when you say those 372 00:21:57,520 --> 00:22:01,600 Speaker 1: things together because people think, well, discipline is the opposite 373 00:22:01,600 --> 00:22:04,840 Speaker 1: of flexible. But when we use the term flexible really 374 00:22:04,840 --> 00:22:07,920 Speaker 1: really thinking about open mindedness and and This is one 375 00:22:07,960 --> 00:22:10,119 Speaker 1: of the curses in my life, or one of the 376 00:22:10,160 --> 00:22:13,520 Speaker 1: gifts in my life, is that if there's a debate, 377 00:22:13,560 --> 00:22:16,720 Speaker 1: I could pretty well take both sides, uh and do 378 00:22:16,760 --> 00:22:19,520 Speaker 1: a pretty good job. That means you're objective. I have 379 00:22:19,640 --> 00:22:21,959 Speaker 1: a gift of being able to see both sides. The 380 00:22:21,960 --> 00:22:24,639 Speaker 1: negative is it's it's hard to be a hundred percent 381 00:22:25,119 --> 00:22:29,600 Speaker 1: black or white when you can see the world's actually gray. 382 00:22:30,280 --> 00:22:33,480 Speaker 1: What about what about risk of verse because we're taught 383 00:22:33,520 --> 00:22:36,400 Speaker 1: that risk aversion often leads people to be too quick 384 00:22:36,440 --> 00:22:38,879 Speaker 1: to jump out of equities when they should be a 385 00:22:38,920 --> 00:22:42,879 Speaker 1: little more risk embracing. Yes, well, that's a good question 386 00:22:42,960 --> 00:22:46,439 Speaker 1: because it happens to be the one piece of my 387 00:22:46,560 --> 00:22:50,160 Speaker 1: philosophy that it has changed over the years because there's 388 00:22:50,240 --> 00:22:52,040 Speaker 1: a lot of risk takers that have made a lot 389 00:22:52,119 --> 00:22:55,719 Speaker 1: of money. But what they do is they manage their risks. 390 00:22:55,760 --> 00:22:59,240 Speaker 1: So they'll they'll take a big position, but if it 391 00:22:59,320 --> 00:23:01,920 Speaker 1: if it goes hour or the news changes that they 392 00:23:01,960 --> 00:23:05,000 Speaker 1: get out. So it's still a matter. It's still a 393 00:23:05,000 --> 00:23:07,600 Speaker 1: matter of risk management. But I think the term risk 394 00:23:07,640 --> 00:23:13,840 Speaker 1: averse was came from being in the market from two 395 00:23:13,920 --> 00:23:18,199 Speaker 1: frankly so, speaking of which those who study history are 396 00:23:18,200 --> 00:23:22,320 Speaker 1: contemned to repeat its mistakes. How difficult is it for 397 00:23:22,400 --> 00:23:28,040 Speaker 1: investors to learn the lessons that history presents to us? Well, 398 00:23:28,200 --> 00:23:31,520 Speaker 1: it's tricky because you want to learn the correct lessons 399 00:23:31,520 --> 00:23:33,359 Speaker 1: and you don't want to learn the bad lessons, and 400 00:23:33,400 --> 00:23:36,520 Speaker 1: it's a little hard to know, uh, which it is. 401 00:23:36,520 --> 00:23:38,879 Speaker 1: So what happens is there will be a period of 402 00:23:38,960 --> 00:23:41,760 Speaker 1: time and there was a mistake during that period of time, 403 00:23:41,800 --> 00:23:43,959 Speaker 1: and everybody learns and says, well, I won't make that 404 00:23:44,040 --> 00:23:47,720 Speaker 1: mistake again. And then times change and periods change in 405 00:23:47,800 --> 00:23:52,439 Speaker 1: areas change, and uh, everybody's learned that the lesson of 406 00:23:52,520 --> 00:23:55,399 Speaker 1: that period, but not the next period. So again, I 407 00:23:55,440 --> 00:23:59,399 Speaker 1: think the real lesson is studying, Uh, studying history is 408 00:24:00,160 --> 00:24:06,040 Speaker 1: seeing Mania's bubbles saying, uh, you know extremes from extreme 409 00:24:06,160 --> 00:24:11,520 Speaker 1: pessimism to extreme optimism, and uh, how these end up? 410 00:24:11,720 --> 00:24:14,679 Speaker 1: How how they end up? And uh, that's the lesson. 411 00:24:14,720 --> 00:24:19,000 Speaker 1: It's not just put oh portfolio insurances is something I'll 412 00:24:19,000 --> 00:24:21,920 Speaker 1: never do again. That that's not really the lesson. The 413 00:24:22,040 --> 00:24:25,879 Speaker 1: lesson is it got too popular, the market got too high, 414 00:24:25,920 --> 00:24:28,600 Speaker 1: there was too much optimism, and that that that is 415 00:24:28,640 --> 00:24:31,919 Speaker 1: a terrible combination. That's the lesson to learn. So so 416 00:24:32,040 --> 00:24:37,359 Speaker 1: between the extremes of of too much pessimism like we 417 00:24:37,400 --> 00:24:40,719 Speaker 1: saw in eighty seven and seventy three, seventy four and 418 00:24:41,480 --> 00:24:45,680 Speaker 1: oh three and oh nine, and too much optimism with 419 00:24:45,880 --> 00:24:49,040 Speaker 1: sixty six, and go through the list sixty six and 420 00:24:49,080 --> 00:24:52,160 Speaker 1: two thousand and then again in in oh seven, although 421 00:24:52,160 --> 00:24:54,360 Speaker 1: I don't know if that was as much too much 422 00:24:54,359 --> 00:24:58,040 Speaker 1: optimism as as you mentioned a systemic problem. Where are 423 00:24:58,080 --> 00:25:01,560 Speaker 1: we in that spectrum between too much negativity and too 424 00:25:01,640 --> 00:25:05,520 Speaker 1: much enthusiasm? Yes, I mean it was Templeton that said, uh, 425 00:25:05,720 --> 00:25:11,160 Speaker 1: bull markets are born and pessimism. They rise on skepticism, 426 00:25:11,320 --> 00:25:15,760 Speaker 1: they mature on optimism, and they die on euphoria. And uh, 427 00:25:15,880 --> 00:25:19,720 Speaker 1: I think that's pretty much what we've seen. Uh since 428 00:25:19,760 --> 00:25:22,760 Speaker 1: two thousand nine, we've gone through those phases. And I 429 00:25:22,800 --> 00:25:26,800 Speaker 1: think after the election, for for whatever reason, we got 430 00:25:26,840 --> 00:25:29,680 Speaker 1: we went into the euphoric stage. And you can see this, 431 00:25:29,960 --> 00:25:34,560 Speaker 1: uh in all kinds of consumer confidence, business confidence, UH 432 00:25:34,960 --> 00:25:41,240 Speaker 1: CEO confidence, UH soft sentiment data got way way higher 433 00:25:41,280 --> 00:25:43,920 Speaker 1: than it was for it. But we just this isn't 434 00:25:44,000 --> 00:25:46,600 Speaker 1: this is an early phase of euphoria. So I don't 435 00:25:46,680 --> 00:25:49,480 Speaker 1: I don't necessarily think this is the end, but I 436 00:25:49,520 --> 00:25:52,119 Speaker 1: think you can certainly seem see euphour you and that 437 00:25:52,280 --> 00:25:55,480 Speaker 1: that's uh, that's a high risk phase. So so what 438 00:25:55,560 --> 00:25:59,119 Speaker 1: should investors do to manage their risk? What's what's the 439 00:25:59,160 --> 00:26:02,439 Speaker 1: best approach for someone's listening to this, they have a 440 00:26:02,440 --> 00:26:04,159 Speaker 1: couple of million dollars in the four oh one K 441 00:26:04,359 --> 00:26:09,160 Speaker 1: and their investment portfolios, how should they manage that? Well, 442 00:26:09,200 --> 00:26:12,200 Speaker 1: you know, as if if you're a chartist and that's 443 00:26:12,240 --> 00:26:17,040 Speaker 1: your your background, you can see formations, you see demand 444 00:26:17,119 --> 00:26:20,879 Speaker 1: on a chart, or you see trend lines and UM 445 00:26:21,000 --> 00:26:25,720 Speaker 1: or you just use stop losses below important lows and uh, 446 00:26:26,040 --> 00:26:28,840 Speaker 1: if the market turns down, you you just get stopped out. 447 00:26:29,600 --> 00:26:34,040 Speaker 1: Other people might want to right now, the protection the 448 00:26:34,160 --> 00:26:39,040 Speaker 1: insurance portfolio insurance for portfolios, the vix is very low. 449 00:26:39,160 --> 00:26:41,720 Speaker 1: Vix is how much it costs to buy options. The 450 00:26:41,800 --> 00:26:43,720 Speaker 1: vix is very low. You can buy some puts to 451 00:26:43,720 --> 00:26:48,240 Speaker 1: protect your portfolio, uh, some hedge fund short stocks, you 452 00:26:48,280 --> 00:26:51,440 Speaker 1: can use, put some money in cash and wait for pullback. 453 00:26:51,520 --> 00:26:53,640 Speaker 1: So there's a lot lots of things you can do. 454 00:26:54,840 --> 00:26:59,600 Speaker 1: So is an interesting um question that comes up with 455 00:26:59,640 --> 00:27:05,200 Speaker 1: the eyes of technical technical analysis, which is thanks to computers, 456 00:27:05,200 --> 00:27:08,440 Speaker 1: we could pretty much put anything on a chart. How 457 00:27:08,480 --> 00:27:13,560 Speaker 1: how advisable is it to chart everything you possibly can make? 458 00:27:13,600 --> 00:27:16,080 Speaker 1: You look at earnings, you could look at everything from 459 00:27:16,119 --> 00:27:19,200 Speaker 1: GDP to what have you. There really isn't any data 460 00:27:19,280 --> 00:27:22,640 Speaker 1: series that can't be put on a chart. Now, and 461 00:27:22,800 --> 00:27:25,200 Speaker 1: that's what we do. I mean, that's what my business 462 00:27:25,240 --> 00:27:28,879 Speaker 1: does pretty much. And we we actually analyze the economy 463 00:27:29,240 --> 00:27:31,359 Speaker 1: pretty much the same way we do the stock market, 464 00:27:31,400 --> 00:27:35,119 Speaker 1: and we use centimon indicators, we use trend indicators. Uh. 465 00:27:35,160 --> 00:27:38,560 Speaker 1: In the economy, there's a lot of indicators that tend 466 00:27:38,600 --> 00:27:41,680 Speaker 1: to lead the economy, So we put most of our 467 00:27:41,720 --> 00:27:45,200 Speaker 1: emphasis on the leading and leading economic indicators. And when 468 00:27:45,200 --> 00:27:49,080 Speaker 1: they're turning up and are strong, then that's a good sign. 469 00:27:49,119 --> 00:27:51,600 Speaker 1: So we I do this somewhat. In the stock market, 470 00:27:51,920 --> 00:27:55,920 Speaker 1: there's certain groups and sectors that tend to lead the market, uh, 471 00:27:55,960 --> 00:27:58,600 Speaker 1: and so we put our main emphasis on those the 472 00:27:58,640 --> 00:28:01,920 Speaker 1: trend of those all. So we look for the economy 473 00:28:02,200 --> 00:28:04,359 Speaker 1: or the stock market, we look for the Federal Reserve 474 00:28:04,440 --> 00:28:06,639 Speaker 1: Board and what are they doing? Because they control the 475 00:28:06,680 --> 00:28:09,520 Speaker 1: cost of money and the availability of money, And if 476 00:28:09,520 --> 00:28:12,520 Speaker 1: you're looking at supplying demand, which is what technical analysis 477 00:28:12,560 --> 00:28:15,640 Speaker 1: is all about, how can you ignore the Federal Reserve Board? 478 00:28:15,640 --> 00:28:18,560 Speaker 1: You really can't talk to me about big MO. It's 479 00:28:18,560 --> 00:28:21,359 Speaker 1: one of my favorite charts of yours. How did how 480 00:28:21,400 --> 00:28:23,439 Speaker 1: did the idea come about? And what tell us what 481 00:28:23,480 --> 00:28:26,439 Speaker 1: it actually depicts? Okay, Big MO is just the trend 482 00:28:26,440 --> 00:28:30,439 Speaker 1: of a hundred hundred industry groups, hundreds of industry groups, 483 00:28:30,440 --> 00:28:33,439 Speaker 1: and it's the cyclical trends. So we're talking, you know, 484 00:28:33,520 --> 00:28:37,280 Speaker 1: a year or two kind of trends. Uh, But I 485 00:28:37,560 --> 00:28:40,120 Speaker 1: called it and put the MO in there. We also 486 00:28:40,200 --> 00:28:43,440 Speaker 1: look at rates of change, how fast a group is 487 00:28:43,560 --> 00:28:48,800 Speaker 1: rising or falling in the momentum indicators UM are trends sensitive, 488 00:28:48,880 --> 00:28:52,920 Speaker 1: but they're not exactly trend indicators, so they can be early. 489 00:28:53,080 --> 00:28:55,880 Speaker 1: So when you put the trend following indicators and uh, 490 00:28:56,640 --> 00:28:59,720 Speaker 1: the momentum indicators together, I think you can get a 491 00:28:59,760 --> 00:29:02,880 Speaker 1: little closer to tops and bottoms, and big motto right 492 00:29:02,920 --> 00:29:06,240 Speaker 1: now shows about of those industry groups are still in 493 00:29:06,320 --> 00:29:10,400 Speaker 1: strong uptrends and and that that's a decent figure. It's 494 00:29:10,600 --> 00:29:13,560 Speaker 1: high neutral, I would say, mili bullish, and we we 495 00:29:13,760 --> 00:29:17,640 Speaker 1: use below fifty as as a warning sign. So you 496 00:29:17,680 --> 00:29:22,680 Speaker 1: mentioned UM the rising sentiment indicators earlier. H Someone did 497 00:29:22,680 --> 00:29:25,840 Speaker 1: a study not too long ago that showed the largest 498 00:29:25,880 --> 00:29:33,400 Speaker 1: gap ever between soft survey sentiment information and hard actual data. 499 00:29:34,400 --> 00:29:35,840 Speaker 1: What do you what do you think of that gap 500 00:29:35,920 --> 00:29:41,760 Speaker 1: between between the two. Well, I think clearly the soft 501 00:29:41,800 --> 00:29:45,560 Speaker 1: tends to be leading UH leads the hard. So the 502 00:29:45,600 --> 00:29:48,480 Speaker 1: fact that the soft is strong in the heart is 503 00:29:49,200 --> 00:29:54,640 Speaker 1: weak UH is not necessarily a bad sign. However, this 504 00:29:54,720 --> 00:29:58,720 Speaker 1: works much better depending on where you are in a cycle. 505 00:29:59,200 --> 00:30:02,520 Speaker 1: If you're coming out of a recession and there's a 506 00:30:02,520 --> 00:30:05,480 Speaker 1: lot of unused labor, unused capital, there's a lot of 507 00:30:05,520 --> 00:30:10,200 Speaker 1: savings around UH, and then sentiment source will people have 508 00:30:10,320 --> 00:30:13,760 Speaker 1: the ability to go out and and spend. And we 509 00:30:13,800 --> 00:30:16,600 Speaker 1: saw this in two thousand nine, two thousand ten. Now 510 00:30:16,600 --> 00:30:19,720 Speaker 1: we're getting the same kind of sentiment readings now, but 511 00:30:19,800 --> 00:30:22,880 Speaker 1: we've had nine years of an expansion and and people 512 00:30:22,920 --> 00:30:25,920 Speaker 1: have very little savings. They're up to their teeth. Uh. 513 00:30:26,040 --> 00:30:28,920 Speaker 1: You got over a treeon dollars in student debt. You know, 514 00:30:28,960 --> 00:30:30,960 Speaker 1: I've got a tree in dollars a credit card debt, 515 00:30:30,960 --> 00:30:34,400 Speaker 1: and you've got a tree in dollars in auto debt. Uh. 516 00:30:34,720 --> 00:30:37,960 Speaker 1: So it's a lot different things. So, yes, I think 517 00:30:38,000 --> 00:30:39,800 Speaker 1: the hard we think the hard debt is going to 518 00:30:39,880 --> 00:30:43,600 Speaker 1: come on, but not by much so since we're talking 519 00:30:43,600 --> 00:30:47,800 Speaker 1: about sentiment. How noisy is the series of sentiment data. 520 00:30:47,880 --> 00:30:52,040 Speaker 1: It seems that there's a lot of fairly wild swings 521 00:30:52,080 --> 00:30:55,960 Speaker 1: over short periods of time. Well, it just depends on 522 00:30:56,040 --> 00:30:58,840 Speaker 1: who you're you know, what your survey is. If it's 523 00:30:58,880 --> 00:31:03,400 Speaker 1: futures traders, they're gonna be pretty quick. Uh. You know 524 00:31:03,640 --> 00:31:07,040 Speaker 1: a C e O s don't change their opinion that often. 525 00:31:07,120 --> 00:31:12,040 Speaker 1: So it depends. But there there are small surveys and uh, 526 00:31:12,280 --> 00:31:15,160 Speaker 1: if Trump proved anything, he proved that you know that 527 00:31:15,280 --> 00:31:20,080 Speaker 1: polls aren't always right. So what we do, Uh, we 528 00:31:20,360 --> 00:31:22,440 Speaker 1: look at a lot of polls. We also look at 529 00:31:22,440 --> 00:31:26,000 Speaker 1: what people are doing in terms of option trading, Uh, 530 00:31:26,440 --> 00:31:31,160 Speaker 1: how optimistic people are, upside volume versus downside volume, a 531 00:31:31,200 --> 00:31:34,400 Speaker 1: lot of measures of activity. And we put all these 532 00:31:34,440 --> 00:31:37,800 Speaker 1: together in a composite model. I think we Uh, one 533 00:31:37,840 --> 00:31:40,080 Speaker 1: of the ones we use as twenty eight indicators in it. 534 00:31:40,160 --> 00:31:42,720 Speaker 1: So if some of them are are fake news, then 535 00:31:43,320 --> 00:31:46,920 Speaker 1: you hope the majority picks up the correct picture. What's 536 00:31:46,960 --> 00:31:50,080 Speaker 1: what's the name of that particular charter And well we 537 00:31:50,120 --> 00:31:53,320 Speaker 1: have the indie our crowd sentiment poll. We have been 538 00:31:53,360 --> 00:31:57,040 Speaker 1: speaking with Nid Davis, co founder of nid Davis Research. 539 00:31:57,520 --> 00:32:00,480 Speaker 1: If you enjoy this conversation, be sure as stick around 540 00:32:00,480 --> 00:32:03,280 Speaker 1: for the podcast extras, where we keep the digital tape 541 00:32:03,360 --> 00:32:06,840 Speaker 1: rolling and continue to talk about all things technical. Be 542 00:32:06,920 --> 00:32:09,920 Speaker 1: sure and check out my daily column at Bloomberg View 543 00:32:09,960 --> 00:32:14,040 Speaker 1: dot com. Follow me on Twitter at rid Holts. I'm 544 00:32:14,080 --> 00:32:17,200 Speaker 1: Barry rid Holts. You're listening to Masters in Business on 545 00:32:17,240 --> 00:32:26,640 Speaker 1: Bloomberg Radio. What could your future hold more than you 546 00:32:26,680 --> 00:32:28,600 Speaker 1: think because at Merrill Lynch we work with you to 547 00:32:28,680 --> 00:32:31,680 Speaker 1: create a strategy built around your priorities. Visit mL dot 548 00:32:31,680 --> 00:32:34,000 Speaker 1: com and learn more about Merrill Lynch. An affiliated Bank 549 00:32:34,040 --> 00:32:36,560 Speaker 1: of America. Merrill Lynch makes available products and services offered 550 00:32:36,560 --> 00:32:38,560 Speaker 1: by Merrill Lynch. Pierce, Feder and Smith Incorporated, a registered 551 00:32:38,560 --> 00:32:44,840 Speaker 1: broker dealer. Remember s I PC. Welcome to the podcast. 552 00:32:44,880 --> 00:32:47,560 Speaker 1: Thank you so much, ned for doing this. I have 553 00:32:47,680 --> 00:32:52,840 Speaker 1: to share the funny story. When I first started writing 554 00:32:52,880 --> 00:32:56,920 Speaker 1: for Bloomberg about three or four years ago, they came 555 00:32:56,960 --> 00:32:59,800 Speaker 1: to me and said, what would you like to do? 556 00:33:00,080 --> 00:33:04,479 Speaker 1: There was a whole long story, and the takeaway was 557 00:33:04,880 --> 00:33:07,720 Speaker 1: I want to sit down with accomplished, intelligent people and 558 00:33:07,800 --> 00:33:11,719 Speaker 1: have a conversation about their career and their impact on 559 00:33:11,840 --> 00:33:15,000 Speaker 1: markets and business and what have you. You were one of, 560 00:33:15,400 --> 00:33:19,400 Speaker 1: if not the first interview I had done, and so 561 00:33:19,560 --> 00:33:22,680 Speaker 1: I said, like this, like this Ned Davis interview. Here, 562 00:33:22,720 --> 00:33:25,560 Speaker 1: here's a SoundCloud in bed. Take a look at it. 563 00:33:26,000 --> 00:33:29,480 Speaker 1: And in hindsight, it's very rough. It's on the phone. 564 00:33:31,040 --> 00:33:38,440 Speaker 1: The old um the reference from Malcolm Gladwell in Outliers. 565 00:33:38,480 --> 00:33:41,120 Speaker 1: You do something for ten thousand hours, you eventually get 566 00:33:41,120 --> 00:33:43,720 Speaker 1: good at it. I haven't quite done a full ten 567 00:33:43,800 --> 00:33:47,440 Speaker 1: thousand hours, but you're about a hundred and fifty something. 568 00:33:47,480 --> 00:33:49,920 Speaker 1: We've been doing this now for three years. And when 569 00:33:49,960 --> 00:33:53,360 Speaker 1: I listened to that interview in preparation for this interview, 570 00:33:53,880 --> 00:33:55,840 Speaker 1: I have to say you were very patient, very kind, 571 00:33:55,880 --> 00:33:59,240 Speaker 1: because I was just got awful then. UM, but I 572 00:33:59,280 --> 00:34:03,600 Speaker 1: really appreciate you coming back and and letting, uh, someone 573 00:34:03,640 --> 00:34:08,879 Speaker 1: improved version of me have this conversation. UM. So thank 574 00:34:08,920 --> 00:34:11,560 Speaker 1: you very much for for flying up for this. I've 575 00:34:11,560 --> 00:34:14,360 Speaker 1: been a fan of your work for forever. We didn't 576 00:34:14,400 --> 00:34:18,880 Speaker 1: get to talk about the books during the broadcast portion, 577 00:34:19,400 --> 00:34:21,480 Speaker 1: but I have to ask you a few questions about 578 00:34:21,520 --> 00:34:26,960 Speaker 1: these because these are really very significant books in the 579 00:34:27,000 --> 00:34:30,000 Speaker 1: world of investing. The first one that I have to 580 00:34:30,040 --> 00:34:33,920 Speaker 1: talk about is this one being right, we're making money 581 00:34:34,480 --> 00:34:37,120 Speaker 1: now collector's edition, you can't find that. I've I've had 582 00:34:37,160 --> 00:34:41,080 Speaker 1: this for I don't know how long underlined and highlighted. 583 00:34:41,560 --> 00:34:46,520 Speaker 1: What was the thinking behind writing that book? Well, again, 584 00:34:46,560 --> 00:34:49,320 Speaker 1: I was, you know, trying to outline my philosophy mainly 585 00:34:49,360 --> 00:34:54,880 Speaker 1: for clients. But uh that spending time on trying to 586 00:34:54,960 --> 00:34:59,319 Speaker 1: forecast and be right is interesting. I certainly continue to 587 00:34:59,400 --> 00:35:02,799 Speaker 1: do that, but really the focus should be on how 588 00:35:02,840 --> 00:35:06,879 Speaker 1: to make money and so uh and again we use 589 00:35:07,040 --> 00:35:10,720 Speaker 1: the tape, the trend, the sentiment, and the Federal Reserve 590 00:35:10,760 --> 00:35:14,680 Speaker 1: Board uh to make money. But I think the one 591 00:35:14,719 --> 00:35:17,279 Speaker 1: of the big things is, as I mentioned it early, 592 00:35:17,440 --> 00:35:20,000 Speaker 1: is the magic of compound interest and and this is 593 00:35:20,040 --> 00:35:22,839 Speaker 1: just a simple math thing that every kid should learn 594 00:35:22,880 --> 00:35:25,880 Speaker 1: in school. But again, if you have a draw down 595 00:35:25,960 --> 00:35:30,480 Speaker 1: like twenty nine to thirty two in stocks was eight percent, 596 00:35:30,640 --> 00:35:33,600 Speaker 1: you have to you have to uh go up five 597 00:35:33,680 --> 00:35:37,760 Speaker 1: hundred to get back to even. And it took many, 598 00:35:37,800 --> 00:35:42,399 Speaker 1: many years. So uh, I don't want we didn't want 599 00:35:42,440 --> 00:35:46,120 Speaker 1: big drawdowns. That's that's the key to making money. And 600 00:35:46,400 --> 00:35:49,359 Speaker 1: one of the things that I've been thinking about since 601 00:35:49,400 --> 00:35:52,600 Speaker 1: I read this book so long ago was when people 602 00:35:52,680 --> 00:35:57,320 Speaker 1: make forecasts, there's a tendency to marry those forecasts, meaning 603 00:35:57,520 --> 00:36:01,680 Speaker 1: despite evidence coming their way that they're wrong, they stick 604 00:36:01,760 --> 00:36:07,040 Speaker 1: with the forecast regardless and don't adjust their portfolio appropriately. 605 00:36:07,080 --> 00:36:10,239 Speaker 1: In other words, they're willing to lose money in order 606 00:36:10,280 --> 00:36:13,200 Speaker 1: to hang around long enough for their forecast to eventually 607 00:36:13,960 --> 00:36:18,960 Speaker 1: come true. How dangerous is that? Well, you know, we 608 00:36:19,040 --> 00:36:21,400 Speaker 1: have another expression that we'd like to use in my 609 00:36:21,440 --> 00:36:24,800 Speaker 1: shop is we all make our own reality. And this 610 00:36:24,800 --> 00:36:26,879 Speaker 1: this was shocking the first time I heard it, because 611 00:36:26,880 --> 00:36:30,520 Speaker 1: I figured reality's reality. But sometimes when I'll be before 612 00:36:30,560 --> 00:36:33,920 Speaker 1: an audience, I'll say, how many of you are sports fans? 613 00:36:34,000 --> 00:36:37,239 Speaker 1: Let's say, are you Knicks fans? And I'm in New 614 00:36:37,320 --> 00:36:39,640 Speaker 1: York And they'll say yes, And I'll say, well, how 615 00:36:39,640 --> 00:36:41,560 Speaker 1: many of you have ever gone to a game and 616 00:36:41,600 --> 00:36:45,920 Speaker 1: thought the referee favored the other team? And of course nobody, 617 00:36:45,960 --> 00:36:49,200 Speaker 1: nobody raises their hand because we see what we want 618 00:36:49,239 --> 00:36:51,920 Speaker 1: to see. Uh, you know, we want the Knicks or 619 00:36:51,960 --> 00:36:55,040 Speaker 1: whoever our team is, to win, so we always go 620 00:36:55,120 --> 00:36:57,440 Speaker 1: to the game and think the referees, uh were for 621 00:36:57,480 --> 00:37:01,200 Speaker 1: the other team. When the NBA's NBA's actually done studies 622 00:37:01,239 --> 00:37:04,880 Speaker 1: that show, if anything, it's very slight, but there is 623 00:37:04,920 --> 00:37:07,719 Speaker 1: a small favor Uh, there's a small advantage for the 624 00:37:07,760 --> 00:37:10,600 Speaker 1: home team and the calls in an average game. So 625 00:37:10,880 --> 00:37:13,840 Speaker 1: this is something we see with our own eyes. So 626 00:37:13,960 --> 00:37:17,000 Speaker 1: it's very easy. You have a position, you want it 627 00:37:17,040 --> 00:37:20,680 Speaker 1: to work. You tend to read things that confirm your 628 00:37:20,760 --> 00:37:24,319 Speaker 1: opinion and you don't read things that may not. So 629 00:37:24,800 --> 00:37:27,600 Speaker 1: this again goes back to that flexibility thing. This is 630 00:37:27,840 --> 00:37:31,799 Speaker 1: is important. Uh, or or even just say hey, I'm 631 00:37:31,800 --> 00:37:33,960 Speaker 1: gonna put a stop loss there. If i made a mistake, 632 00:37:34,040 --> 00:37:37,840 Speaker 1: I made a mistake, I'm done. The sports metaphor is 633 00:37:37,880 --> 00:37:41,040 Speaker 1: so perfect. I'm a basketball fan. I'm a Knicks fan, 634 00:37:41,480 --> 00:37:44,480 Speaker 1: and of course Patrick Ewing would never got the call, 635 00:37:44,600 --> 00:37:47,080 Speaker 1: but Shack and Jordan, No, he's did. I'm not a 636 00:37:47,120 --> 00:37:52,440 Speaker 1: big college basketball fan. But Joe Besseker of Emerald Asset 637 00:37:52,480 --> 00:37:55,600 Speaker 1: Management is a huge fan and doing the n I T. 638 00:37:55,920 --> 00:37:57,799 Speaker 1: I think it was the finals that are played at 639 00:37:57,800 --> 00:38:00,440 Speaker 1: the Garden. He I get a call one day, Hey, 640 00:38:00,440 --> 00:38:02,880 Speaker 1: I'm I got courtside seats. You want to come see this. 641 00:38:03,640 --> 00:38:05,279 Speaker 1: I'm not a basketball fan. If you I'm not a 642 00:38:05,280 --> 00:38:08,360 Speaker 1: college hoops fan, he goes. If you've never watched the 643 00:38:08,400 --> 00:38:11,800 Speaker 1: game in the garden courtside, you have to come see this. Okay, 644 00:38:11,840 --> 00:38:15,640 Speaker 1: So we go watch this really exciting game pretty close. Um, 645 00:38:15,719 --> 00:38:18,880 Speaker 1: only he's a fan of his alma mater who actually 646 00:38:18,920 --> 00:38:21,920 Speaker 1: made it. And I'm watching the game and Joe is 647 00:38:22,040 --> 00:38:27,200 Speaker 1: just distraught because every call is absolutely the worst call 648 00:38:27,280 --> 00:38:31,359 Speaker 1: ever made to mankind. And RALF, come on, the guy 649 00:38:31,400 --> 00:38:34,440 Speaker 1: took six steps. He's walking. I have no dog in 650 00:38:34,480 --> 00:38:37,080 Speaker 1: the fight. I could care less. And I'm like, hey, Joe, 651 00:38:37,280 --> 00:38:39,000 Speaker 1: that was a step and a half. It's a layup. 652 00:38:39,040 --> 00:38:43,120 Speaker 1: You're allowed to And it was a moment of clarity that, oh, 653 00:38:43,200 --> 00:38:46,319 Speaker 1: your subjectivity really affects the way you perceived the wall. 654 00:38:46,360 --> 00:38:48,960 Speaker 1: It was. It was amazing going to a game where 655 00:38:49,000 --> 00:38:53,000 Speaker 1: you didn't care who won and watching people's reaction. Yes, 656 00:38:53,080 --> 00:38:56,280 Speaker 1: I think it was extraordinary. Population Madness of Crowds McKay 657 00:38:57,040 --> 00:38:59,839 Speaker 1: wrote it, and he said, Uh, an individual taken by 658 00:38:59,840 --> 00:39:03,680 Speaker 1: themselves is rational. When you put the individual on a crowd, 659 00:39:03,719 --> 00:39:08,040 Speaker 1: it becomes a blockhead. Uh you know, it's it's just 660 00:39:08,160 --> 00:39:13,520 Speaker 1: totally Crowd psychology is really really strong. It's overwhelming, it 661 00:39:13,600 --> 00:39:17,200 Speaker 1: takes all of us over and uh, it's it's really 662 00:39:17,320 --> 00:39:20,920 Speaker 1: a very different than than an individual psychology. So another 663 00:39:20,960 --> 00:39:23,880 Speaker 1: book I wanted to ask you about was the triumph 664 00:39:23,920 --> 00:39:28,680 Speaker 1: of contrarian investing crowds man is and beating the market 665 00:39:28,719 --> 00:39:32,480 Speaker 1: by going against the grain. So a question I always 666 00:39:32,480 --> 00:39:37,640 Speaker 1: have about contraining investing investing is, well, Mark's markets have 667 00:39:37,719 --> 00:39:40,839 Speaker 1: a tendency to go up over the long haul, and 668 00:39:40,880 --> 00:39:43,680 Speaker 1: we have a tendency to see these long trends. Can 669 00:39:43,760 --> 00:39:47,000 Speaker 1: you be a contrarian in the midst of a ten 670 00:39:47,120 --> 00:39:50,920 Speaker 1: or twenty year bull market? Yes, well, that that you know, 671 00:39:51,640 --> 00:39:54,040 Speaker 1: we like to say we go with the flow. In 672 00:39:54,120 --> 00:39:56,800 Speaker 1: other ways, we go with the crowd until they reach 673 00:39:56,840 --> 00:40:00,440 Speaker 1: an extreme and begin to reverse. And it's at that 674 00:40:00,440 --> 00:40:03,200 Speaker 1: that small moment of time where it pays to be 675 00:40:03,239 --> 00:40:06,800 Speaker 1: a contrarian. So it's it's a it's a bad mistake 676 00:40:06,880 --> 00:40:09,320 Speaker 1: to say I'm just gonna go against the crowd. That 677 00:40:09,320 --> 00:40:11,440 Speaker 1: that will not get you anywhere. You've got to really 678 00:40:11,520 --> 00:40:16,160 Speaker 1: wait for extremes. And a question I didn't get to 679 00:40:16,400 --> 00:40:20,319 Speaker 1: during the broadcast portion was about competitors you launched in. 680 00:40:21,680 --> 00:40:25,560 Speaker 1: Were there any real technicians doing the sort of work 681 00:40:25,600 --> 00:40:28,480 Speaker 1: you were doing? Then? Who were your competitors as a 682 00:40:28,560 --> 00:40:33,799 Speaker 1: research firm? I don't think there were really any uh 683 00:40:34,320 --> 00:40:40,320 Speaker 1: competitors doing technical research. Uh I mentioned earlier, Hamilton Bolton 684 00:40:40,360 --> 00:40:43,520 Speaker 1: and the bank credit analysts. They did a little bit 685 00:40:43,520 --> 00:40:48,479 Speaker 1: of technical, a lot of monetary. Uh. And certainly they're 686 00:40:48,600 --> 00:40:51,120 Speaker 1: they're one of our competitors. You know, I'd like to 687 00:40:51,160 --> 00:40:54,359 Speaker 1: compete with I s I uh ed Hyman because it's 688 00:40:54,400 --> 00:40:59,920 Speaker 1: just a champion. Uh And uh there's now Cornerstone Macro Research, 689 00:41:00,160 --> 00:41:02,680 Speaker 1: there's Rin Maak, Jeff de Grafs, a friend of mine, 690 00:41:03,200 --> 00:41:07,960 Speaker 1: and uh so I would say that those all now 691 00:41:08,080 --> 00:41:11,759 Speaker 1: have a technical element to them. So it's broadened out. 692 00:41:12,120 --> 00:41:15,520 Speaker 1: Given the change in the commission structure that's out there 693 00:41:15,680 --> 00:41:21,960 Speaker 1: and the shrinking of institutional sales desks. Is this end 694 00:41:22,000 --> 00:41:24,920 Speaker 1: of the industry getting smaller and less competitive or is 695 00:41:24,960 --> 00:41:28,520 Speaker 1: it just consolidating with a handful of firms that seems 696 00:41:28,560 --> 00:41:34,000 Speaker 1: to have figured out how to add value to the process. Uh. 697 00:41:34,040 --> 00:41:38,200 Speaker 1: You know, it was concentrated by Wall Street banks and 698 00:41:38,280 --> 00:41:42,160 Speaker 1: now there's there's a lot of independent firms that are 699 00:41:42,200 --> 00:41:45,680 Speaker 1: doing a great job. So, uh, I don't know it. 700 00:41:45,680 --> 00:41:49,320 Speaker 1: It has changed. Certainly, commissions have changed. They were fixed 701 00:41:49,360 --> 00:41:52,399 Speaker 1: when I got into the business. And uh. Uh so 702 00:41:53,000 --> 00:41:57,160 Speaker 1: it's gotten harder, but the business has changed. It's always changing. 703 00:41:57,719 --> 00:42:00,239 Speaker 1: So let's talk a little it's always changing. That's that's 704 00:42:00,280 --> 00:42:05,600 Speaker 1: pretty sage advice. Let's talk about the rise of quantitative 705 00:42:06,120 --> 00:42:09,480 Speaker 1: and indexing. What what does the rise of low cost 706 00:42:09,920 --> 00:42:13,680 Speaker 1: passive index in mean to the world of active investing 707 00:42:13,719 --> 00:42:16,400 Speaker 1: And what does that mean to a firm that sells 708 00:42:16,440 --> 00:42:21,080 Speaker 1: its research to to money managers. Well, you know, if 709 00:42:21,200 --> 00:42:24,960 Speaker 1: if everybody's an active manager and they're competing with each other, 710 00:42:25,160 --> 00:42:29,520 Speaker 1: then um, it's gonna be a horror. It's gonna be 711 00:42:29,640 --> 00:42:33,680 Speaker 1: very difficult to beat the averages. So they're charging high 712 00:42:33,760 --> 00:42:37,200 Speaker 1: fees to be active managers, and some of them are 713 00:42:37,280 --> 00:42:41,439 Speaker 1: very successful, but on average they're they're not doing any 714 00:42:41,480 --> 00:42:45,040 Speaker 1: better than the market averages. So I think John Bogel 715 00:42:45,120 --> 00:42:49,200 Speaker 1: had a great idea that to put these index together 716 00:42:49,440 --> 00:42:53,120 Speaker 1: and uh, low fees and uh this would be a 717 00:42:53,160 --> 00:42:55,520 Speaker 1: better investment for most people over the long run. And 718 00:42:55,600 --> 00:42:59,280 Speaker 1: I think I think that's that's true. However, I noticed 719 00:42:59,320 --> 00:43:01,359 Speaker 1: today I just up and to see a Bloomberg thing 720 00:43:01,360 --> 00:43:03,960 Speaker 1: where there was a chart and they said there's more 721 00:43:04,000 --> 00:43:08,560 Speaker 1: index funds now than there are stocks, and uh. So 722 00:43:08,600 --> 00:43:11,720 Speaker 1: again this is a popular idea. It's a good idea, 723 00:43:12,239 --> 00:43:14,800 Speaker 1: there's nothing wrong with it, but if it gets too popular, 724 00:43:14,960 --> 00:43:18,560 Speaker 1: it will blow up, just like all the other big ideas. 725 00:43:18,960 --> 00:43:22,040 Speaker 1: When does this get too popular? What do we Vanguard 726 00:43:22,120 --> 00:43:25,640 Speaker 1: is four trillion, three trillion of which is passive, black 727 00:43:25,719 --> 00:43:29,480 Speaker 1: Rock is five trillion, most of that is passive. At 728 00:43:29,520 --> 00:43:31,880 Speaker 1: what point, or much of that, I should say, is passive? 729 00:43:32,200 --> 00:43:36,960 Speaker 1: At what point does this get to be too big? Well, 730 00:43:36,960 --> 00:43:39,880 Speaker 1: you know, after Al Gore invented the internet, uh no, 731 00:43:40,080 --> 00:43:43,320 Speaker 1: and we had all the dot com stocks, I I thought, gosh, 732 00:43:43,440 --> 00:43:47,360 Speaker 1: this has got to be a bubble, certainly, and and 733 00:43:47,360 --> 00:43:50,160 Speaker 1: of course it continued for for for a number of years, 734 00:43:50,160 --> 00:43:54,520 Speaker 1: and it's even bigger today. Uh But uh So, I 735 00:43:54,560 --> 00:43:59,319 Speaker 1: think you can't just say, uh, it's extremely popular. You 736 00:43:59,400 --> 00:44:01,640 Speaker 1: have to wait till the trends give up a little bit. 737 00:44:01,840 --> 00:44:03,760 Speaker 1: You have to wait till the FED becomes a little 738 00:44:03,760 --> 00:44:05,839 Speaker 1: more hostile. And at that point, I think you make 739 00:44:05,880 --> 00:44:08,279 Speaker 1: the bet passive investing it is done. And I think 740 00:44:08,280 --> 00:44:12,440 Speaker 1: it's a late phase, lead phase. Okay, nothing nothing nothing 741 00:44:12,480 --> 00:44:15,879 Speaker 1: wrong with passive investing, nothing wrong with portfolio insurance. There's 742 00:44:15,880 --> 00:44:18,680 Speaker 1: nothing wrong with growth stocks. It's just when they get 743 00:44:18,840 --> 00:44:22,560 Speaker 1: too too popular and and we're still not there yet, 744 00:44:22,600 --> 00:44:28,880 Speaker 1: you're saying we're getting there, which raises which raises the question, 745 00:44:28,960 --> 00:44:32,040 Speaker 1: and you've written about this a lot, is the role 746 00:44:32,080 --> 00:44:36,719 Speaker 1: of emotions in investing? How First, how important is it 747 00:44:36,760 --> 00:44:40,440 Speaker 1: to keep emotions out? And then second what can investor 748 00:44:40,520 --> 00:44:44,480 Speaker 1: do to to maintain that? Yes, well, that's that's why 749 00:44:44,520 --> 00:44:47,440 Speaker 1: we put together these sentiment composites. And they ask go 750 00:44:47,600 --> 00:44:50,239 Speaker 1: Warren Buffett one time the secret of success? And you 751 00:44:50,280 --> 00:44:54,719 Speaker 1: know he's a fundamental individual value investor, and he said, Oh, 752 00:44:54,800 --> 00:44:58,440 Speaker 1: our secret is we we try to buy when everybody's fearful, 753 00:44:58,480 --> 00:45:02,640 Speaker 1: and we try to sell when everybody is greedy. Uh 754 00:45:02,680 --> 00:45:05,799 Speaker 1: and U. Which is not a fundamental It's not a 755 00:45:05,840 --> 00:45:07,920 Speaker 1: fundamental thing at all. In fact, to me, it's a 756 00:45:08,040 --> 00:45:12,480 Speaker 1: very technical thing because when everybody's optimistic, they've already bought, 757 00:45:12,719 --> 00:45:16,200 Speaker 1: and so who's left to buy? And when everybody's pessimistic again, 758 00:45:16,280 --> 00:45:18,879 Speaker 1: you've run off all the nervous sellers, so you've got 759 00:45:18,920 --> 00:45:23,560 Speaker 1: strong sellers of stock. So that's the idea is actually 760 00:45:23,600 --> 00:45:26,799 Speaker 1: the same thing that Buffett did. Uh. We we try 761 00:45:26,840 --> 00:45:29,040 Speaker 1: to put these sentiment polls together to see when there's 762 00:45:29,080 --> 00:45:31,680 Speaker 1: fear and greed, and we try to tell ourselves, oh, 763 00:45:31,760 --> 00:45:35,319 Speaker 1: I know the news is terrible, but you know, you know, 764 00:45:35,400 --> 00:45:39,000 Speaker 1: sometimes cloud's part and uh, you know, it's a good 765 00:45:39,000 --> 00:45:41,640 Speaker 1: time to buy. And by the way, our poll got 766 00:45:41,760 --> 00:45:45,799 Speaker 1: very very cautious before the election, and uh it uh 767 00:45:46,000 --> 00:45:49,600 Speaker 1: marks done pretty will since before the election. Is um 768 00:45:49,640 --> 00:45:53,640 Speaker 1: So you really essentially saying one Buffet is a closet technician? 769 00:45:53,760 --> 00:45:58,240 Speaker 1: Is that one? Absolutely? Absolutely? And John Templeton I mentioned 770 00:45:58,239 --> 00:46:00,120 Speaker 1: earlier he was also supposed to be a on a 771 00:46:00,200 --> 00:46:04,239 Speaker 1: menalist and he described the market and and another one 772 00:46:04,440 --> 00:46:08,879 Speaker 1: uh uh Buffett said that has really struck home with me. 773 00:46:09,480 --> 00:46:13,000 Speaker 1: He said, you know, it's not that I like pessimism. 774 00:46:13,040 --> 00:46:17,000 Speaker 1: I just like the values that pessimism produces. So there 775 00:46:17,040 --> 00:46:20,800 Speaker 1: you've measure, You've put together now fundamentals, which are values, 776 00:46:21,239 --> 00:46:24,680 Speaker 1: and you've put together sentiment, which I think is technical. 777 00:46:24,800 --> 00:46:27,840 Speaker 1: So you do when there's a lot of pessimism, you 778 00:46:27,840 --> 00:46:30,239 Speaker 1: tend to get better values, and when there's a lot 779 00:46:30,280 --> 00:46:33,560 Speaker 1: of euphoria, you tend to get an overvalued market. So 780 00:46:34,040 --> 00:46:37,480 Speaker 1: it's really there's not really a struggle here in the 781 00:46:37,520 --> 00:46:40,719 Speaker 1: long run between the technician and a fundamentalist. All right, 782 00:46:40,760 --> 00:46:44,560 Speaker 1: so let's shift over to my ten favorite questions. I 783 00:46:44,600 --> 00:46:49,280 Speaker 1: asked these of all my guests, UM tell us about 784 00:46:49,280 --> 00:46:56,040 Speaker 1: the most important thing people don't know about your background. Uh, 785 00:46:56,280 --> 00:47:00,200 Speaker 1: they probably don't know that I speak French. Do you 786 00:47:00,239 --> 00:47:05,440 Speaker 1: still speak French? I speak French and so so what 787 00:47:05,440 --> 00:47:08,960 Speaker 1: what don't they know about you? You once spoke French, 788 00:47:09,040 --> 00:47:13,879 Speaker 1: but pretty much that's uh, that's faded, you know. I 789 00:47:13,880 --> 00:47:19,080 Speaker 1: I'm really uh very uh persistent in my work, have 790 00:47:19,200 --> 00:47:21,640 Speaker 1: been doing this for fifty years. I'm very focused on 791 00:47:21,719 --> 00:47:24,680 Speaker 1: my work. But uh, I try to have some balance 792 00:47:24,719 --> 00:47:26,920 Speaker 1: in my life. And uh I have four kids and 793 00:47:26,960 --> 00:47:30,879 Speaker 1: two grandkids, and uh I don't know exactly what what 794 00:47:31,080 --> 00:47:34,080 Speaker 1: role I had except being there, but uh, I'm very 795 00:47:34,080 --> 00:47:36,239 Speaker 1: proud of them, So I think that gives my life 796 00:47:36,239 --> 00:47:41,920 Speaker 1: some balance. Tell us about some of your early mentors. Well, 797 00:47:41,960 --> 00:47:48,000 Speaker 1: I mentioned UH Hamilton Bolton, I mentioned UH Edson Gould. 798 00:47:49,000 --> 00:47:54,600 Speaker 1: UH to really outstanding pioneers. UH named Marty's Waga talked 799 00:47:54,640 --> 00:47:58,359 Speaker 1: about and we did some research in conjunction with each other. UH. 800 00:47:58,440 --> 00:48:01,839 Speaker 1: Norman FoST Back UH another guy that did a lot 801 00:48:01,840 --> 00:48:04,520 Speaker 1: of to try to put technicals into studies and test 802 00:48:04,520 --> 00:48:07,800 Speaker 1: them historically. Stock Market Logic was the name of his book. 803 00:48:08,680 --> 00:48:15,239 Speaker 1: And U right now people still doing technical analysis that 804 00:48:15,280 --> 00:48:18,400 Speaker 1: I do like I do successfully. Jim Stack, who's invest 805 00:48:18,440 --> 00:48:21,600 Speaker 1: tech and and there's guy Dan Sullivan who does the 806 00:48:21,680 --> 00:48:25,120 Speaker 1: charters service that has a real time track record that's terrific. 807 00:48:25,239 --> 00:48:30,799 Speaker 1: And uh so you mentioned Jeff Dera, Um any other 808 00:48:30,840 --> 00:48:33,880 Speaker 1: technicians We've We've spoken to Jeff de Graf, We've spoken 809 00:48:33,920 --> 00:48:36,520 Speaker 1: to John Roke. Who else? Who else do you think 810 00:48:36,600 --> 00:48:42,080 Speaker 1: is an interesting you know? I really, Um, well, I 811 00:48:42,080 --> 00:48:46,000 Speaker 1: I read a lot. I I try not to. Uh again, 812 00:48:46,200 --> 00:48:48,600 Speaker 1: it's it's the thing about being at the game, the 813 00:48:48,600 --> 00:48:51,959 Speaker 1: crowd psychology. Uh. I try to let my charts talk 814 00:48:52,000 --> 00:48:54,200 Speaker 1: to me, and so I try not to read to 815 00:48:54,360 --> 00:48:58,520 Speaker 1: too many competitors. Were So you mentioned a number of 816 00:48:58,520 --> 00:49:02,800 Speaker 1: people who influenced your roach to technical analysis. Any other 817 00:49:02,840 --> 00:49:08,360 Speaker 1: technicians that were formative to you in your early days. Um, 818 00:49:08,400 --> 00:49:13,840 Speaker 1: I really like Bob Farrell and Merrill Lynch he uh, 819 00:49:13,920 --> 00:49:17,560 Speaker 1: you know, Bob Farrell had an opinion, but he uh 820 00:49:17,600 --> 00:49:21,400 Speaker 1: he would give both sides. Uh, he would give a 821 00:49:21,400 --> 00:49:24,160 Speaker 1: balanced view and and uh sort of lean one way 822 00:49:24,239 --> 00:49:26,800 Speaker 1: or the other. And that really appealed to me. I 823 00:49:27,040 --> 00:49:30,240 Speaker 1: I just did not like the approach that the world's 824 00:49:30,280 --> 00:49:33,440 Speaker 1: all black or all white. It's a bullish or you know, 825 00:49:33,560 --> 00:49:36,120 Speaker 1: sell everything. And I just don't think the world worked 826 00:49:36,160 --> 00:49:38,520 Speaker 1: that way and he was able to pull it off. 827 00:49:38,560 --> 00:49:41,720 Speaker 1: And uh he he had a lot of good, good 828 00:49:41,840 --> 00:49:45,799 Speaker 1: rules and uh the ten rules of market investing man, 829 00:49:46,000 --> 00:49:50,680 Speaker 1: and they're excellent. And you mentioned Alan Shaw earlier, right 830 00:49:51,160 --> 00:49:54,120 Speaker 1: some people. I believe he was the co founder of 831 00:49:54,160 --> 00:49:58,680 Speaker 1: the Market Technicians Association and very much an influential UM 832 00:49:58,719 --> 00:50:03,839 Speaker 1: technico analyst. Um. What what's your relationship with Alan? Uh? 833 00:50:04,040 --> 00:50:05,680 Speaker 1: I know him and I used to you know, I 834 00:50:05,719 --> 00:50:08,360 Speaker 1: get I used to read his work and uh again 835 00:50:08,440 --> 00:50:11,279 Speaker 1: he's a he's a level headed uh and he's a 836 00:50:11,360 --> 00:50:14,279 Speaker 1: nice guy. He's an honest guy. And uh he helped 837 00:50:14,320 --> 00:50:16,280 Speaker 1: a lot of people in the business to get into 838 00:50:16,320 --> 00:50:19,880 Speaker 1: it and taught him stuff. And uh so let's talk 839 00:50:19,920 --> 00:50:24,080 Speaker 1: a little bit about books. What you mentioned, um, Uh 840 00:50:24,239 --> 00:50:29,120 Speaker 1: Edwards and McGee Edwards and McGee, Yes, and uh, Charles 841 00:50:29,200 --> 00:50:33,920 Speaker 1: McKay had the extraordinary popular delusions in the Madness of Crowd. 842 00:50:34,200 --> 00:50:36,560 Speaker 1: There's been some other books written about manias. I think 843 00:50:36,600 --> 00:50:40,719 Speaker 1: these are all very very useful books. Uh. A guy 844 00:50:40,800 --> 00:50:43,040 Speaker 1: named Sobel wrote a book on the Big Board, which 845 00:50:43,080 --> 00:50:46,239 Speaker 1: is a history of the New York Stock Exchange. Uh So, 846 00:50:46,760 --> 00:50:49,680 Speaker 1: he's gone over a lot a lot of periods. I 847 00:50:49,760 --> 00:50:53,680 Speaker 1: like history books. Uh. And then Marty's Way Head, Winning 848 00:50:53,680 --> 00:50:56,480 Speaker 1: on All Street and Norman Foss pat Market Logic and 849 00:50:57,040 --> 00:50:59,160 Speaker 1: would be some of my favorites. Uh. What do you 850 00:50:59,280 --> 00:51:01,480 Speaker 1: what do you read to relax? Do you read anything 851 00:51:01,520 --> 00:51:06,120 Speaker 1: that's not technical analysis, markets or history? You know? I 852 00:51:06,200 --> 00:51:09,919 Speaker 1: read like sports. I read about sports. Uh. I don't 853 00:51:09,960 --> 00:51:13,080 Speaker 1: like to discuss politics, but I like politics. I really 854 00:51:13,160 --> 00:51:17,080 Speaker 1: liked it. It's gotten more and more fascinating. And um 855 00:51:17,920 --> 00:51:21,280 Speaker 1: some other fiction I really don't read a lot. Uh. 856 00:51:21,440 --> 00:51:24,200 Speaker 1: I read just recently my kids maybe read A Boys 857 00:51:24,239 --> 00:51:26,239 Speaker 1: in the Boat which is a story of rowing and 858 00:51:26,440 --> 00:51:30,920 Speaker 1: uh uh Washington State that went on and won the Olympics. 859 00:51:31,080 --> 00:51:36,000 Speaker 1: Uh and uh it's a fascinating book, quite quite interesting. 860 00:51:36,560 --> 00:51:40,000 Speaker 1: Um So tell us what's changed since you joined the industry. 861 00:51:40,000 --> 00:51:42,920 Speaker 1: What do you think are the most significant shifts that 862 00:51:42,960 --> 00:51:47,719 Speaker 1: we've witnessed over the past few decades. Well, it's it's 863 00:51:47,760 --> 00:51:51,359 Speaker 1: the same thing any anybody would know that we've gone from, 864 00:51:51,440 --> 00:51:54,600 Speaker 1: you know, uh, drawing with paper and pen and and 865 00:51:54,800 --> 00:52:01,480 Speaker 1: uh absolutely everybody has about Alan Shaw, uh, Ralph Alkumpora. 866 00:52:01,880 --> 00:52:06,759 Speaker 1: They all talk tell about charting by hands. What does 867 00:52:06,800 --> 00:52:08,840 Speaker 1: that do for? Not only that I had a big 868 00:52:09,120 --> 00:52:11,680 Speaker 1: I had a big wall in my office. Basically my 869 00:52:11,800 --> 00:52:15,560 Speaker 1: wallpaper were charts that I put up and and mark 870 00:52:15,680 --> 00:52:19,959 Speaker 1: by hand. And now, of course everything is technology, and 871 00:52:20,160 --> 00:52:24,360 Speaker 1: uh so I'd say that's that's the biggest change. And 872 00:52:24,960 --> 00:52:26,920 Speaker 1: there were a lot of I think there were a 873 00:52:26,920 --> 00:52:30,239 Speaker 1: lot more inefficiencies when I started in the business. If 874 00:52:30,280 --> 00:52:33,080 Speaker 1: you wanted to study market inefficiencies, you could you could 875 00:52:33,080 --> 00:52:37,840 Speaker 1: find them. And uh, with algorithms and computers, uh, and 876 00:52:37,920 --> 00:52:40,319 Speaker 1: all these bright guys doing this stuff, I think there's 877 00:52:40,320 --> 00:52:44,319 Speaker 1: a there's a lot less of that. So from that standpoint, 878 00:52:44,320 --> 00:52:46,360 Speaker 1: I think that the business has gotten a lot tougher, 879 00:52:46,400 --> 00:52:48,400 Speaker 1: and you have to be flexible and you have to 880 00:52:48,440 --> 00:52:52,239 Speaker 1: adjust because it's changing all the time. When when you 881 00:52:52,280 --> 00:52:55,400 Speaker 1: were charting by hands versus doing it today where you 882 00:52:55,480 --> 00:52:58,440 Speaker 1: just push a button on a computer, do you lose 883 00:52:58,480 --> 00:53:02,360 Speaker 1: anything in the process of not day by day spending 884 00:53:02,400 --> 00:53:06,120 Speaker 1: forty five minutes putting together however many hundred charts you 885 00:53:06,160 --> 00:53:09,279 Speaker 1: were doing by hand each day. What's lost when you 886 00:53:09,480 --> 00:53:14,839 Speaker 1: when that goes away? I gets I thin guess there's 887 00:53:14,880 --> 00:53:17,240 Speaker 1: some kind of feel, But if you go through enough charts, 888 00:53:17,280 --> 00:53:19,120 Speaker 1: I think you get the same kind of field. So no, 889 00:53:19,239 --> 00:53:21,440 Speaker 1: I don't think I don't think I've lost much from that. 890 00:53:22,160 --> 00:53:27,360 Speaker 1: Um So, given that technology has been the prime driver 891 00:53:27,560 --> 00:53:30,279 Speaker 1: of changes in the past, what do you think the 892 00:53:30,320 --> 00:53:35,799 Speaker 1: next major shifts are going to be in the industry. Well, 893 00:53:35,920 --> 00:53:40,320 Speaker 1: here's the thing. You know, in every age, there's something 894 00:53:40,400 --> 00:53:45,600 Speaker 1: that comes along that catches people's narrative. And uh, what 895 00:53:45,680 --> 00:53:48,759 Speaker 1: you wanna do is be in a position that when that, 896 00:53:49,239 --> 00:53:52,520 Speaker 1: when that changes, that you can take advantage of it. 897 00:53:52,600 --> 00:53:56,000 Speaker 1: And and you'll read rules. I have rules, and I 898 00:53:56,520 --> 00:54:00,400 Speaker 1: teach rules and philosophy. But again, if they get too popular, 899 00:54:00,719 --> 00:54:03,239 Speaker 1: they quit working. And so that's what makes us a 900 00:54:03,280 --> 00:54:06,840 Speaker 1: fascinating business. It makes it so difficult to forecast. Alan 901 00:54:06,880 --> 00:54:09,480 Speaker 1: Abelson had this line one time, and I loved it. 902 00:54:09,520 --> 00:54:11,879 Speaker 1: He said, just just about the time you you learn 903 00:54:11,960 --> 00:54:15,560 Speaker 1: how to play the game, they change the rules. And uh, 904 00:54:15,680 --> 00:54:18,080 Speaker 1: so I think there's a lot of truth in that. 905 00:54:18,239 --> 00:54:20,879 Speaker 1: And so I think that you know what we need 906 00:54:20,920 --> 00:54:24,440 Speaker 1: to do is is stay flexible, uh, disciplined and um 907 00:54:25,120 --> 00:54:30,560 Speaker 1: and go against whatever gets overly done. Professor Andrew Low 908 00:54:30,600 --> 00:54:33,680 Speaker 1: and m I t called it adaptive markets. No matter 909 00:54:33,800 --> 00:54:38,480 Speaker 1: what the circumstances are, eventually markets adapt to it, and 910 00:54:38,840 --> 00:54:42,239 Speaker 1: those rules stopped working. Um tell us about a time 911 00:54:42,320 --> 00:54:44,680 Speaker 1: you uh you failed and what you learned from it? 912 00:54:44,760 --> 00:54:47,399 Speaker 1: What what was something where gee that didn't work out 913 00:54:47,480 --> 00:54:52,080 Speaker 1: is expected? What was the takeaway? Well, you know again, uh, 914 00:54:52,120 --> 00:54:54,040 Speaker 1: I said, one of my rules is don't don't fight 915 00:54:54,080 --> 00:54:57,600 Speaker 1: the Fed. Well, uh, you know, the FED was tightening 916 00:54:58,440 --> 00:55:02,640 Speaker 1: right into to thousand and into two thousand seven, and 917 00:55:02,640 --> 00:55:06,279 Speaker 1: and as soon as uh, well as bear Stearns blew up, 918 00:55:06,320 --> 00:55:09,560 Speaker 1: they started easing. So you said, well, the market can't 919 00:55:09,560 --> 00:55:12,880 Speaker 1: go down because the Fed's gonna, you know, gonna protect it. 920 00:55:12,920 --> 00:55:15,000 Speaker 1: And that's that's one of my key rules. Well, the 921 00:55:15,040 --> 00:55:17,799 Speaker 1: FED kept easy and the market kept going down. So 922 00:55:19,120 --> 00:55:22,319 Speaker 1: I didn't This is not a mistake because I saw 923 00:55:22,440 --> 00:55:26,799 Speaker 1: the trend turning down and I saw the sentiment where 924 00:55:26,840 --> 00:55:30,279 Speaker 1: it was with with the housing bubble, and uh so 925 00:55:30,480 --> 00:55:33,840 Speaker 1: that didn't throw me off. But in the late nineteen nineties, 926 00:55:34,160 --> 00:55:38,640 Speaker 1: uh one of Ghoul's indicators was the dividend yield on 927 00:55:38,640 --> 00:55:40,680 Speaker 1: the doll and he said, when it gets down below 928 00:55:40,840 --> 00:55:43,840 Speaker 1: you know, three percent, the markets in trouble. Well it 929 00:55:43,960 --> 00:55:46,799 Speaker 1: did that in late nine and that I think that's 930 00:55:46,840 --> 00:55:50,759 Speaker 1: one of the reasons. Uh, you know, the Greenspan said 931 00:55:50,800 --> 00:55:55,040 Speaker 1: irrational exuberance. But the market kept going up. So uh, 932 00:55:55,080 --> 00:55:57,400 Speaker 1: that was an indicator that I think it never failed 933 00:55:57,400 --> 00:55:59,560 Speaker 1: and it felt in that case and it got me 934 00:55:59,640 --> 00:56:03,320 Speaker 1: too ushes too soon. So what do you do outside 935 00:56:03,320 --> 00:56:06,799 Speaker 1: of the office to keep either mentally or physically fit? 936 00:56:06,880 --> 00:56:09,520 Speaker 1: What do you what do you do to relax? Well, 937 00:56:09,560 --> 00:56:11,560 Speaker 1: I try to work out. We actually have a gym 938 00:56:11,600 --> 00:56:14,400 Speaker 1: at our at our office, and so I try to 939 00:56:14,440 --> 00:56:16,760 Speaker 1: do that. I play a little golf and then uh, 940 00:56:17,080 --> 00:56:19,680 Speaker 1: you know, we we live on the west coast of Florida, 941 00:56:19,760 --> 00:56:22,719 Speaker 1: and uh, we do quite a bit of boating. My 942 00:56:22,719 --> 00:56:26,360 Speaker 1: my younger boys are both big fisherman, so I pretty 943 00:56:26,440 --> 00:56:29,520 Speaker 1: much have to have to get out on the water. 944 00:56:29,880 --> 00:56:31,840 Speaker 1: You don't fish, you're on the gulf. So I was so, 945 00:56:31,880 --> 00:56:34,240 Speaker 1: I was gonna say, they're looking for tarpon and bone 946 00:56:34,280 --> 00:56:37,919 Speaker 1: fish and what else? Do you ever go with them fishing? Well? Sometimes, yeah, 947 00:56:38,200 --> 00:56:40,840 Speaker 1: what what what are they? What do they take? Tarpan 948 00:56:40,920 --> 00:56:43,279 Speaker 1: is one of the favorites. But we're a grouper and 949 00:56:43,320 --> 00:56:47,799 Speaker 1: snapper area. We got some really good fish, full edible. 950 00:56:48,560 --> 00:56:52,520 Speaker 1: You catch and release the rest we release everything that's 951 00:56:52,520 --> 00:56:55,560 Speaker 1: not good eating. Yeah, for sure. What sort of advice 952 00:56:55,600 --> 00:56:58,400 Speaker 1: would you give to a millennial or a recent college 953 00:56:58,440 --> 00:57:03,080 Speaker 1: graduate who's just beginning their career in markets or interested 954 00:57:03,120 --> 00:57:08,960 Speaker 1: in technico analysis, how would you advise them? Well, you know, 955 00:57:10,000 --> 00:57:13,279 Speaker 1: I got into this business, uh, at the at the 956 00:57:13,320 --> 00:57:16,800 Speaker 1: beginning of an incredible bull market. So I would say, 957 00:57:16,840 --> 00:57:18,920 Speaker 1: you know, I've had a lot of luck from from 958 00:57:18,960 --> 00:57:23,040 Speaker 1: a timing standpoint, but I could have quit this business 959 00:57:23,040 --> 00:57:26,080 Speaker 1: a long time ago, and I continue to work. Uh. 960 00:57:26,320 --> 00:57:28,320 Speaker 1: And the reason is because I love it and and 961 00:57:28,320 --> 00:57:31,600 Speaker 1: what I love about it is that one year it's 962 00:57:32,160 --> 00:57:35,600 Speaker 1: energy that's driving the stock market, and the next year 963 00:57:35,720 --> 00:57:38,840 Speaker 1: it's housing, so I gotta be a housing expert, and 964 00:57:38,880 --> 00:57:43,240 Speaker 1: the next year it's geopolitical and and it's just always changing. 965 00:57:43,720 --> 00:57:46,840 Speaker 1: So I'm a person that loves to learn the world's 966 00:57:46,920 --> 00:57:50,800 Speaker 1: changing and and it's fascinating. I can get an education, 967 00:57:50,880 --> 00:57:53,840 Speaker 1: a new education every year, and I get paid paid 968 00:57:53,840 --> 00:57:57,240 Speaker 1: well to do it. And the markets are fascinating, and uh, 969 00:57:57,520 --> 00:57:59,320 Speaker 1: you know, to go into an industry, let's say you 970 00:57:59,440 --> 00:58:01,600 Speaker 1: go into the ill industry and you're stuck there for 971 00:58:01,600 --> 00:58:04,840 Speaker 1: fourty or fifty years. I mean, I'm in a different 972 00:58:04,840 --> 00:58:09,480 Speaker 1: industry or there's a different industry, technology, whatever that's driving 973 00:58:09,800 --> 00:58:13,520 Speaker 1: the market every year. So I think it's a fascinating business. 974 00:58:13,560 --> 00:58:17,240 Speaker 1: I think people should go in it and uh um, 975 00:58:17,280 --> 00:58:20,400 Speaker 1: you know I love it. And our final question, what 976 00:58:20,480 --> 00:58:24,160 Speaker 1: do you know about technical analysis and markets today that 977 00:58:24,240 --> 00:58:28,800 Speaker 1: you wish you knew back in the early seventies when 978 00:58:28,840 --> 00:58:32,480 Speaker 1: you when you first started Well, as I said earlier, 979 00:58:32,520 --> 00:58:34,800 Speaker 1: I I started out as a forecaster, and I think 980 00:58:34,800 --> 00:58:36,880 Speaker 1: that's uh that's a good way to lose money and 981 00:58:37,800 --> 00:58:42,120 Speaker 1: be wrong. So uh uh so I I that's one 982 00:58:42,120 --> 00:58:46,360 Speaker 1: thing I would have gotten into that earlier obviously, And uh, 983 00:58:46,480 --> 00:58:49,160 Speaker 1: I do think when you look at charts just is 984 00:58:49,720 --> 00:58:52,640 Speaker 1: the pure technician. A lot of times you see what 985 00:58:52,760 --> 00:58:54,560 Speaker 1: you want to see, and so I think you've got 986 00:58:54,560 --> 00:58:58,720 Speaker 1: to try to quantify it, uh as much as possible. 987 00:58:58,880 --> 00:59:04,280 Speaker 1: So how closely have you followed the field of behavioral 988 00:59:04,320 --> 00:59:08,000 Speaker 1: economics as it's developed of the past let's call it 989 00:59:08,080 --> 00:59:11,120 Speaker 1: thirty thirty five years, Because a lot of what you 990 00:59:11,240 --> 00:59:15,360 Speaker 1: reference on the technical side very much tracks what what 991 00:59:15,440 --> 00:59:20,000 Speaker 1: the guys like Danny Kahneman and Bob Shiller and Richard 992 00:59:20,040 --> 00:59:23,400 Speaker 1: Thaller have been saying for for quite a while. You know, 993 00:59:23,480 --> 00:59:25,080 Speaker 1: there's a lot, like I said, there's a lot of 994 00:59:25,080 --> 00:59:27,560 Speaker 1: good ideas out there. I think though, if you don't 995 00:59:27,560 --> 00:59:31,280 Speaker 1: put it in a big macro con context. If you 996 00:59:31,400 --> 00:59:36,360 Speaker 1: just take one area and you focus on it, then, uh, 997 00:59:36,400 --> 00:59:39,400 Speaker 1: that's a mistake. So you gotta put it in context. Uh. 998 00:59:39,760 --> 00:59:42,560 Speaker 1: For example, right now, I'm I'm a I was a 999 00:59:42,640 --> 00:59:45,960 Speaker 1: huge well I'm a huge fan of the Laugher curve. 1000 00:59:46,720 --> 00:59:50,200 Speaker 1: And Kennedy did it and it worked wonderfully. Cut rates 1001 00:59:50,200 --> 00:59:53,160 Speaker 1: from one to seventy. Reagan came in, he cut them 1002 00:59:53,200 --> 00:59:55,920 Speaker 1: from seventy to fifty. Then he cut them from fifty eight. 1003 00:59:56,000 --> 00:59:57,480 Speaker 1: We had a boom in the sixties, we had a 1004 00:59:57,480 --> 01:00:01,120 Speaker 1: boom in the eighties. Great idea, right, Well, then George 1005 01:00:01,120 --> 01:00:05,840 Speaker 1: Bush tried it in two thousand. Didn't work and because 1006 01:00:05,840 --> 01:00:08,680 Speaker 1: we were in a different phase of the cycle. So 1007 01:00:09,200 --> 01:00:12,240 Speaker 1: when you have a rule and everybody's got a rule, 1008 01:00:12,280 --> 01:00:15,439 Speaker 1: a Kinesian rule, Yes, there was a good, good, good 1009 01:00:15,480 --> 01:00:18,480 Speaker 1: reason for deficits and bailots at one point, right, but 1010 01:00:18,560 --> 01:00:21,920 Speaker 1: it doesn't work at another point in time. So I 1011 01:00:21,960 --> 01:00:25,080 Speaker 1: think this is the problem with this kind of thing, 1012 01:00:25,200 --> 01:00:27,400 Speaker 1: just getting focused on one area. You've got to put 1013 01:00:27,440 --> 01:00:29,960 Speaker 1: it in context. Let me push back on the Laugher 1014 01:00:30,080 --> 01:00:33,200 Speaker 1: rule for a second. When you have very high taxes 1015 01:00:33,240 --> 01:00:37,160 Speaker 1: and you cut them significantly. You get a huge impact. 1016 01:00:37,560 --> 01:00:41,360 Speaker 1: Exactly when when you make minor changes. What did Bush do? 1017 01:00:42,760 --> 01:00:47,520 Speaker 1: Exactly what Trump wants to do thirty five exactly? Nobody 1018 01:00:47,680 --> 01:00:51,960 Speaker 1: remember when when Reagan came in, they were all manner 1019 01:00:52,240 --> 01:00:59,600 Speaker 1: of um, tax shelters and deferments. His tax change immediately 1020 01:00:59,680 --> 01:01:04,440 Speaker 1: led to a whole range of behavioral changes. Accountants, lawyers, investors, Hey, 1021 01:01:04,480 --> 01:01:07,600 Speaker 1: this real estate shell do you have? It's done? You 1022 01:01:07,680 --> 01:01:09,520 Speaker 1: better move your money elsewhere. And a lot of it 1023 01:01:09,560 --> 01:01:12,720 Speaker 1: finds its way into but three or four percent nobody 1024 01:01:12,840 --> 01:01:16,080 Speaker 1: is doing a wholesale revision of it. It's an incentive, 1025 01:01:16,080 --> 01:01:19,720 Speaker 1: but it's very small. It's I you ask pump people, 1026 01:01:19,760 --> 01:01:23,000 Speaker 1: if you drop your next dollar from nine to seventy, 1027 01:01:23,600 --> 01:01:25,760 Speaker 1: what would that make you want to work hard? Yeah? 1028 01:01:25,960 --> 01:01:27,560 Speaker 1: And then you say, wait, what about if you went 1029 01:01:27,600 --> 01:01:31,080 Speaker 1: from thirty nine to thirty five? They went, really, yeah, 1030 01:01:31,240 --> 01:01:33,960 Speaker 1: I'll take the extra cash, but I'm certainly not changing 1031 01:01:34,040 --> 01:01:39,680 Speaker 1: my entire Kennedy did it after two recessions eight and sixty, 1032 01:01:39,680 --> 01:01:42,920 Speaker 1: and Reagan did it after two recessions eighty and eighty two. 1033 01:01:43,560 --> 01:01:45,720 Speaker 1: And now we've had a nine year expansion and we're 1034 01:01:45,720 --> 01:01:49,720 Speaker 1: gonna now we're gonna stimulate cutting taxes. So I just say, 1035 01:01:49,920 --> 01:01:53,640 Speaker 1: there's nothing wrong with the rule, there's nothing wrong with 1036 01:01:53,680 --> 01:01:58,200 Speaker 1: the incentives, but it depends on when it happens, what 1037 01:01:58,400 --> 01:02:01,880 Speaker 1: error went, what the cyclists. That's the problem with having 1038 01:02:02,400 --> 01:02:07,240 Speaker 1: a set mindset. You you referenced your following politics from Afar. 1039 01:02:07,760 --> 01:02:11,200 Speaker 1: Who else do you think has some interesting political theories 1040 01:02:11,840 --> 01:02:19,280 Speaker 1: as to what's going on these days? Uh? You know, 1041 01:02:19,840 --> 01:02:23,080 Speaker 1: I there was a commission that and I think this 1042 01:02:23,160 --> 01:02:27,120 Speaker 1: was Obama's really biggest mistake. But anyway, he had a 1043 01:02:27,120 --> 01:02:32,400 Speaker 1: commission to to look at the fiscal monetary structure Simpson bowls. 1044 01:02:32,880 --> 01:02:37,600 Speaker 1: And it was bipartisan, last bipartisan commission we've had, and 1045 01:02:37,880 --> 01:02:41,240 Speaker 1: uh almost I mean nobody liked it because somebody was 1046 01:02:41,280 --> 01:02:45,600 Speaker 1: getting gored somewhere, was getting something taken away. But uh, 1047 01:02:45,720 --> 01:02:48,520 Speaker 1: I personally felt like that that was a great idea, 1048 01:02:49,240 --> 01:02:53,560 Speaker 1: and uh they just neither the Democrats nor Republicans would 1049 01:02:53,600 --> 01:02:56,920 Speaker 1: do it. But I think essentially that was a lot 1050 01:02:56,920 --> 01:02:59,320 Speaker 1: of the things we needed to do. We have been 1051 01:02:59,360 --> 01:03:03,280 Speaker 1: speaking to Ned Davis of ned Davis Research. If you 1052 01:03:03,400 --> 01:03:06,240 Speaker 1: enjoy this conversation, be sure and check out our other 1053 01:03:07,240 --> 01:03:09,200 Speaker 1: past three years. I don't even know how many we've 1054 01:03:09,200 --> 01:03:13,400 Speaker 1: had of conversations. I would be remiss if I did 1055 01:03:13,480 --> 01:03:17,400 Speaker 1: not think Taylor Riggs, my book of producer, and Michael Batnick, 1056 01:03:17,920 --> 01:03:21,120 Speaker 1: our head of research. Be sure and check out all 1057 01:03:21,160 --> 01:03:25,600 Speaker 1: our other conversations. You can find them on SoundCloud, Bloomberg 1058 01:03:25,640 --> 01:03:30,720 Speaker 1: dot com, Apple iTunes. We love your comments, feedback and 1059 01:03:30,800 --> 01:03:35,560 Speaker 1: suggestions right to us at m IB podcast at Bloomberg 1060 01:03:35,680 --> 01:03:39,640 Speaker 1: dot net. I'm Barry Ridholts. You've been listening to Masters 1061 01:03:39,640 --> 01:03:47,840 Speaker 1: in Business on Bloomberg Radio. Our world is always moving, 1062 01:03:47,960 --> 01:03:50,120 Speaker 1: so with Mery Lynch you can get access to financial 1063 01:03:50,120 --> 01:03:53,200 Speaker 1: guidance online, in person or through the Apple. Visit mL 1064 01:03:53,240 --> 01:03:55,560 Speaker 1: dot com and learn more about Mery Lynch. An affiliated 1065 01:03:55,560 --> 01:03:58,000 Speaker 1: Bank of America. Mary Lynch makes available products and services 1066 01:03:58,040 --> 01:04:00,560 Speaker 1: offered by Merrill Lynch. Pierce Federan Smith Incorporated, Richister Broker 1067 01:04:00,600 --> 01:04:01,520 Speaker 1: Dealer Member s I PC