1 00:00:00,080 --> 00:00:06,080 Speaker 1: M. This is Mesters in Business with Very Renaults on 2 00:00:06,240 --> 00:00:10,560 Speaker 1: Bluebird Radio this weekend. On the podcast, I have a 3 00:00:10,600 --> 00:00:13,920 Speaker 1: special guest. His name is Campbell Harvey and he is 4 00:00:14,080 --> 00:00:18,280 Speaker 1: a professor at Duke University School of Business. He's also 5 00:00:18,520 --> 00:00:22,680 Speaker 1: the author of a fascinating book co author really of 6 00:00:22,720 --> 00:00:26,480 Speaker 1: a fascinating book called Defy and the Future of Finance. 7 00:00:26,840 --> 00:00:29,520 Speaker 1: And if you are at all crypto curious, if you're 8 00:00:29,520 --> 00:00:33,720 Speaker 1: wondering why bitcoin is near sixty dollars, why n f 9 00:00:33,760 --> 00:00:37,120 Speaker 1: t s have gone crazy, and while lots and lots 10 00:00:37,120 --> 00:00:42,960 Speaker 1: of banks and financial institutions have been embracing crypto, well, 11 00:00:43,000 --> 00:00:48,360 Speaker 1: then you're going to find this conversation absolutely fascinating. Um. 12 00:00:49,000 --> 00:00:53,400 Speaker 1: Campbell Harvey is a traditional finance professor, or at least 13 00:00:53,440 --> 00:00:58,680 Speaker 1: that's how he presents to the outside world, studying behavioral finance, uh, 14 00:00:58,720 --> 00:01:02,720 Speaker 1: the yield curve and recessions and separating luck and skill 15 00:01:02,800 --> 00:01:06,360 Speaker 1: and investment decisions. All this stuff sounds pretty run of 16 00:01:06,360 --> 00:01:08,800 Speaker 1: the mill, middle of the road sort of stuff. But 17 00:01:09,000 --> 00:01:14,520 Speaker 1: then back in he was crypto curious and started doing 18 00:01:14,560 --> 00:01:18,800 Speaker 1: some research and ended up doing a presentation to one 19 00:01:18,840 --> 00:01:23,360 Speaker 1: of his classes, and really it had a massive impact 20 00:01:23,400 --> 00:01:26,720 Speaker 1: on him because you know, at the end of the period, 21 00:01:26,760 --> 00:01:28,800 Speaker 1: he expects the whole class to get up and leave, 22 00:01:28,959 --> 00:01:33,440 Speaker 1: and you know, spoiler alert, nobody leaves, and half the 23 00:01:33,520 --> 00:01:36,160 Speaker 1: class rushes the podium to ask him a bunch of 24 00:01:36,240 --> 00:01:41,520 Speaker 1: questions about this, and he, you know, really comes to recognize, Oh, 25 00:01:41,640 --> 00:01:46,600 Speaker 1: so this is striking a chord with students. There's something 26 00:01:46,720 --> 00:01:49,520 Speaker 1: here I need to spend some more time and effort 27 00:01:49,520 --> 00:01:52,600 Speaker 1: going into it. Um That part of that part of 28 00:01:52,600 --> 00:01:56,040 Speaker 1: the interview was really fascinating. He tells about what he 29 00:01:56,080 --> 00:01:59,560 Speaker 1: does with crypto, where he was giving bitcoin away to 30 00:02:00,000 --> 00:02:02,960 Speaker 1: each of his students um so that they had to 31 00:02:02,960 --> 00:02:05,800 Speaker 1: set up a coin base account and you know, make 32 00:02:05,840 --> 00:02:08,480 Speaker 1: a promise to return the coin at the end of 33 00:02:08,560 --> 00:02:12,079 Speaker 1: the term and what ends up happening is pretty pretty 34 00:02:12,160 --> 00:02:16,160 Speaker 1: hilarious and fascinating. Anyway, if if you're remotely interested in 35 00:02:16,240 --> 00:02:20,040 Speaker 1: anything from the world of defy, from crypto, n f T, 36 00:02:20,360 --> 00:02:22,919 Speaker 1: stable coins. God, I could have spoken to him for 37 00:02:22,960 --> 00:02:28,440 Speaker 1: another three hours. I kept this fairly um accessible. I 38 00:02:28,520 --> 00:02:32,480 Speaker 1: had lots and lots of deeper, wonkier questions, but as 39 00:02:32,520 --> 00:02:34,760 Speaker 1: we were going on through this, it really became clear 40 00:02:34,760 --> 00:02:37,440 Speaker 1: to me, Oh, this is a great primer for people 41 00:02:37,480 --> 00:02:40,760 Speaker 1: who really wanna put a toe in the water of crypto. 42 00:02:41,560 --> 00:02:44,639 Speaker 1: I found it fascinating and I think you will also so, 43 00:02:45,360 --> 00:02:50,919 Speaker 1: with no further ado, my conversation with Duke University's few 44 00:02:51,040 --> 00:02:57,920 Speaker 1: Quass School of Business Professor Campbell Harvey. This is Mesters 45 00:02:57,960 --> 00:03:03,680 Speaker 1: in Business with Very Results on Bloomberg Radio. My extra 46 00:03:03,760 --> 00:03:06,720 Speaker 1: special guest this week is cam Harvey. He is a 47 00:03:06,760 --> 00:03:11,920 Speaker 1: professor at Duke University's Fuquas School of Business. He's best 48 00:03:11,960 --> 00:03:15,360 Speaker 1: known for his work on yield curve inversion and recessions, 49 00:03:15,760 --> 00:03:19,240 Speaker 1: as well as the thorny problem of separating luck from 50 00:03:19,280 --> 00:03:24,280 Speaker 1: skill in investing. He is a research associate at the 51 00:03:24,360 --> 00:03:27,360 Speaker 1: National Bureau of Economic Research, as well as a partner 52 00:03:27,360 --> 00:03:31,480 Speaker 1: and see in your Advisor at Research Affiliates. He is 53 00:03:31,520 --> 00:03:35,480 Speaker 1: the author of a brand new book titled Defy and 54 00:03:35,560 --> 00:03:40,760 Speaker 1: the Future of Finance. Campbell Harvey, Welcome to Bloomberg. It's 55 00:03:40,760 --> 00:03:42,760 Speaker 1: great to be on the show. It's great having you. 56 00:03:42,880 --> 00:03:47,480 Speaker 1: So you're a pretty traditional finance guy, Duke n b R. 57 00:03:48,120 --> 00:03:50,480 Speaker 1: How did you get interested in Defy? When did this 58 00:03:50,600 --> 00:03:55,040 Speaker 1: start and what prompted it. I'm not too sure. I'm 59 00:03:55,080 --> 00:04:00,480 Speaker 1: a traditional of finance guy. Uh. Indeed, uh five years 60 00:04:00,480 --> 00:04:05,160 Speaker 1: ago I announced that half of the empirical research and 61 00:04:05,240 --> 00:04:09,800 Speaker 1: finance was likely false. So I don't think I'm traditional 62 00:04:09,880 --> 00:04:15,040 Speaker 1: in any way, but I totally agree that decentralized finance 63 00:04:15,120 --> 00:04:20,400 Speaker 1: seems far away from inverted deal curves and luck versus 64 00:04:20,400 --> 00:04:23,440 Speaker 1: skill and back testing and things like that. So let 65 00:04:23,480 --> 00:04:26,240 Speaker 1: me let me tell you the story about how I 66 00:04:26,279 --> 00:04:29,320 Speaker 1: got involved in this space. And I've been involved in 67 00:04:29,320 --> 00:04:32,880 Speaker 1: this space quite a while. I was on a seven 68 00:04:32,960 --> 00:04:37,280 Speaker 1: year teaching hiatus because I was editing the Journal of 69 00:04:37,320 --> 00:04:39,640 Speaker 1: Finance and it was a full time job. When I 70 00:04:39,680 --> 00:04:43,960 Speaker 1: came back to my asset management course after seven years, 71 00:04:44,000 --> 00:04:48,560 Speaker 1: I decided to scrap the syllabus and and basically start over. 72 00:04:49,000 --> 00:04:54,600 Speaker 1: But certain topics I had to include, like four X 73 00:04:55,480 --> 00:04:59,160 Speaker 1: and I wanted to do the leading edge stuff, and 74 00:04:59,200 --> 00:05:02,480 Speaker 1: I thought, well, there's this new thing I've heard of 75 00:05:02,640 --> 00:05:08,880 Speaker 1: called bitcoin. And this isn't two thousand fourteen, so it 76 00:05:09,000 --> 00:05:13,440 Speaker 1: was below the radar screen definitely, but I'd heard about it, 77 00:05:13,680 --> 00:05:16,279 Speaker 1: and I just said, well, if I'm doing the euro, 78 00:05:16,680 --> 00:05:22,000 Speaker 1: the pound, the dollar again, one not at a cryptocurrency. 79 00:05:22,080 --> 00:05:25,560 Speaker 1: So that's where I actually started. And I began to 80 00:05:25,760 --> 00:05:30,640 Speaker 1: research this idea, and the more I researched it, the 81 00:05:30,720 --> 00:05:36,080 Speaker 1: more I realized that this was something really big, and 82 00:05:36,120 --> 00:05:38,680 Speaker 1: they spent a lot of time, and it was a single, 83 00:05:38,920 --> 00:05:42,479 Speaker 1: like two hour lecture in my course. Uh And I 84 00:05:42,600 --> 00:05:47,200 Speaker 1: spent more time preparing that lecture than the sum of 85 00:05:47,279 --> 00:05:49,880 Speaker 1: all of the other lectures in my course. And I 86 00:05:50,000 --> 00:05:55,160 Speaker 1: was nervous because, and as I management, I've researched this 87 00:05:55,200 --> 00:05:58,680 Speaker 1: stuff for a long time. I've been very fortunate to 88 00:05:58,880 --> 00:06:02,840 Speaker 1: have real relationships with some of the leading edge firms. 89 00:06:03,400 --> 00:06:05,680 Speaker 1: Uh So I kind of what goes on in the 90 00:06:05,760 --> 00:06:10,840 Speaker 1: practice also, and very comfortable fielding questions from my students. 91 00:06:11,040 --> 00:06:13,719 Speaker 1: And of course I can't answer every single question, but 92 00:06:13,800 --> 00:06:17,120 Speaker 1: I I'm confident I could find somebody very quickly that 93 00:06:17,200 --> 00:06:20,880 Speaker 1: could help me with the answer. But with this crypto stuff, 94 00:06:21,960 --> 00:06:25,440 Speaker 1: I'm in the position where I'm giving a lecture and 95 00:06:25,520 --> 00:06:28,920 Speaker 1: as possible, some of the students know far more than 96 00:06:29,000 --> 00:06:32,920 Speaker 1: I do. So I sought some help. Um and I 97 00:06:33,080 --> 00:06:37,240 Speaker 1: practiced the lecture all this stuff, and then I gave 98 00:06:37,680 --> 00:06:42,680 Speaker 1: this lecture, and again it was probably the most stressful 99 00:06:43,040 --> 00:06:47,120 Speaker 1: lecture I've ever given. Uh And and you know the 100 00:06:47,160 --> 00:06:52,640 Speaker 1: way it is at at college where rate at the 101 00:06:52,880 --> 00:06:56,320 Speaker 1: end of the lecture everybody gets up and leaves rate 102 00:06:56,440 --> 00:07:00,080 Speaker 1: on the minute that is supposed to end. Nobody the 103 00:07:00,760 --> 00:07:05,000 Speaker 1: stays late. They just get out of there. And you know, 104 00:07:05,040 --> 00:07:08,080 Speaker 1: I've taught for many years that's exactly what happens. But 105 00:07:09,120 --> 00:07:14,040 Speaker 1: after giving this talk on crypto, people were just sitting there, 106 00:07:14,920 --> 00:07:18,080 Speaker 1: and I thought, oh, well, maybe I ended the lecture 107 00:07:18,880 --> 00:07:21,000 Speaker 1: like a way before I should have. But I looked 108 00:07:21,000 --> 00:07:24,800 Speaker 1: at the clock and we were exactly at time, people 109 00:07:24,960 --> 00:07:28,080 Speaker 1: just sitting there, And I said, oh, I must have 110 00:07:28,160 --> 00:07:31,120 Speaker 1: really bombed this lecture. It was a disaster, I guess. 111 00:07:31,960 --> 00:07:35,560 Speaker 1: And and and I'm standing there shell shot because it 112 00:07:35,600 --> 00:07:39,880 Speaker 1: worked so hard and and for it to fail it 113 00:07:40,000 --> 00:07:43,120 Speaker 1: was very disappointing. But then students started to come to 114 00:07:43,200 --> 00:07:46,400 Speaker 1: the front to talk to me, and and they said, 115 00:07:46,440 --> 00:07:51,360 Speaker 1: but we are shell shocked, like this is a transformational 116 00:07:51,520 --> 00:07:55,200 Speaker 1: topic that and and I numbered them said this was 117 00:07:55,320 --> 00:08:00,480 Speaker 1: the most important lecture of their education, and that this 118 00:08:00,760 --> 00:08:04,560 Speaker 1: cannot be just one lecture. It needs to be a 119 00:08:04,680 --> 00:08:10,280 Speaker 1: broader learning experience and uh and and so it deserves 120 00:08:10,320 --> 00:08:13,440 Speaker 1: at least a full course. And that's where I started. 121 00:08:13,480 --> 00:08:18,600 Speaker 1: So um I developed the next year into a full course, 122 00:08:18,680 --> 00:08:22,960 Speaker 1: which was the first blockchain based course taught at a 123 00:08:23,080 --> 00:08:27,400 Speaker 1: leading school, and then I've just continued it and uh 124 00:08:27,440 --> 00:08:31,600 Speaker 1: and one thing with the space, uh is changing all 125 00:08:31,640 --> 00:08:35,160 Speaker 1: the time. So what I was teaching seven years ago 126 00:08:35,400 --> 00:08:38,480 Speaker 1: was much different than what I teach today. So let's 127 00:08:38,559 --> 00:08:41,240 Speaker 1: let's go back to that first lecture where where the 128 00:08:41,320 --> 00:08:47,160 Speaker 1: students were pretty um enthusiastic and and maybe even dumbfounded. First, 129 00:08:47,160 --> 00:08:50,280 Speaker 1: did anybody come to the podium and say, Hey, I 130 00:08:50,320 --> 00:08:51,960 Speaker 1: own a bunch of bitcoin and I don't know what 131 00:08:52,080 --> 00:08:55,600 Speaker 1: to do with it? And be were you buying bitcoin 132 00:08:55,800 --> 00:09:02,479 Speaker 1: all the way back in? So no student had any bitcoin? Um, 133 00:09:02,520 --> 00:09:07,040 Speaker 1: but I actually bought some, and I bought them I 134 00:09:07,120 --> 00:09:10,960 Speaker 1: think a three a coin. Uh And and this is 135 00:09:11,400 --> 00:09:15,920 Speaker 1: one of the greatest investment mistakes of my life, um, 136 00:09:15,960 --> 00:09:20,240 Speaker 1: I decided. I was on the phone with a reporter 137 00:09:20,640 --> 00:09:25,080 Speaker 1: from a leading media outlet who was covering crypto also, 138 00:09:25,559 --> 00:09:30,520 Speaker 1: and I asked him whether he owned any bitcoin, and 139 00:09:30,559 --> 00:09:32,920 Speaker 1: he said, well, just a small amount, because I'm worried 140 00:09:32,920 --> 00:09:35,840 Speaker 1: about conflict of interest. And I was thinking, made the 141 00:09:35,880 --> 00:09:38,959 Speaker 1: same thing. If I'm teaching it, I'll have a small amount. 142 00:09:39,280 --> 00:09:44,080 Speaker 1: And indeed, um, I was giving it out. So my student, 143 00:09:44,080 --> 00:09:45,880 Speaker 1: when what do you mean giving it out? Giving it 144 00:09:45,920 --> 00:09:49,080 Speaker 1: to students. Okay, yeah, so let me tell this story. 145 00:09:50,080 --> 00:09:52,640 Speaker 1: Uh an interest. Wait, so you're paying them to go 146 00:09:52,720 --> 00:09:56,800 Speaker 1: to school. What I did was to give ten dollars 147 00:09:57,040 --> 00:10:01,880 Speaker 1: words of bitcoin to everybody. Ended deal was the following Uh. 148 00:10:01,920 --> 00:10:04,280 Speaker 1: They had to set up an account and at that 149 00:10:04,320 --> 00:10:07,640 Speaker 1: time it was the coin base. I would give ten 150 00:10:07,679 --> 00:10:11,720 Speaker 1: dollars and then at the end of the course, um, 151 00:10:11,760 --> 00:10:14,120 Speaker 1: they would send it back to me, and then I 152 00:10:14,160 --> 00:10:18,880 Speaker 1: would donate it to the university. So that would donation 153 00:10:19,040 --> 00:10:22,479 Speaker 1: my annual donation to the university. So it was basically 154 00:10:22,520 --> 00:10:25,600 Speaker 1: just to get them set up with something in their wallet. 155 00:10:26,360 --> 00:10:32,520 Speaker 1: So I discovered this one complication and and that is 156 00:10:32,600 --> 00:10:36,280 Speaker 1: that once you give a crypto to somebody, there's no 157 00:10:36,320 --> 00:10:40,760 Speaker 1: way to enforce giving it back. So many of the 158 00:10:40,800 --> 00:10:49,679 Speaker 1: students didn't give that because it had Yeah you know 159 00:10:49,679 --> 00:10:53,079 Speaker 1: where I'm going, Like sometimes I get an odd email 160 00:10:53,520 --> 00:10:57,520 Speaker 1: or oh, um, I remember you gave me, uh whatever, 161 00:10:57,559 --> 00:11:00,000 Speaker 1: it was like point one of a big coin um 162 00:11:00,080 --> 00:11:02,160 Speaker 1: back in two thousand and fourteen, I forgot to give 163 00:11:02,200 --> 00:11:07,240 Speaker 1: it back and yeah, here it is and it's you know, 164 00:11:07,400 --> 00:11:15,320 Speaker 1: four thousand dollars so um. So basically what's happened is 165 00:11:15,600 --> 00:11:20,520 Speaker 1: a lot of students didn't give back, and uh, and 166 00:11:20,960 --> 00:11:24,400 Speaker 1: we're trying to remind them to do that because it's 167 00:11:24,440 --> 00:11:27,200 Speaker 1: a couple of hundred thousand dollars and and kind of 168 00:11:27,280 --> 00:11:31,200 Speaker 1: lost donations to the school. So it's not that they 169 00:11:31,200 --> 00:11:33,480 Speaker 1: didn't give it back because it had appreciated so much. 170 00:11:33,480 --> 00:11:36,040 Speaker 1: At the end of the semester, they just like, it's 171 00:11:36,080 --> 00:11:38,400 Speaker 1: ten dollars and who's who wants to bother and they 172 00:11:38,480 --> 00:11:41,920 Speaker 1: just got lazies. Is that what I'm hearing? Yeah, that's 173 00:11:41,960 --> 00:11:45,880 Speaker 1: what I think. So many of them just forgot about it. 174 00:11:45,920 --> 00:11:52,760 Speaker 1: But again, that ten dollars is massively appreciated. That's unbelievable. 175 00:11:52,840 --> 00:11:56,079 Speaker 1: So we're gonna talk in more detail about the book 176 00:11:56,800 --> 00:12:00,320 Speaker 1: Defy in the Future of Finance, but just of us 177 00:12:00,360 --> 00:12:03,880 Speaker 1: a broad overview. What's the basic premise And I get 178 00:12:03,920 --> 00:12:07,920 Speaker 1: the sense you're going to talk about how transformational this 179 00:12:08,040 --> 00:12:13,959 Speaker 1: technology is. Yeah, it's kind of interesting to me that 180 00:12:14,960 --> 00:12:19,600 Speaker 1: the financial system really isn't that much different today than 181 00:12:19,720 --> 00:12:22,760 Speaker 1: it was a hundred years ago, Like the the exception 182 00:12:22,880 --> 00:12:28,880 Speaker 1: is digitization, but the basic infrastructure is the same. And 183 00:12:29,240 --> 00:12:32,720 Speaker 1: I don't think that it's specific to finance. We kind 184 00:12:32,720 --> 00:12:38,040 Speaker 1: of know that technology will transform a number of businesses. 185 00:12:38,800 --> 00:12:42,400 Speaker 1: And right now, the way that we interact and finances 186 00:12:42,440 --> 00:12:48,199 Speaker 1: with um a brick and mortar intermediary. So you've got 187 00:12:48,200 --> 00:12:51,160 Speaker 1: a bank in the middle, you've got a broker in 188 00:12:51,240 --> 00:12:57,960 Speaker 1: the middle, and uh, that middle layer leads to transactions 189 00:12:58,000 --> 00:13:02,280 Speaker 1: that are more expensive. So so think of putting your 190 00:13:02,280 --> 00:13:06,040 Speaker 1: money in the savings account, that rate is maybe lower 191 00:13:07,000 --> 00:13:11,239 Speaker 1: uh than if you didn't have all of that middle layer, um, 192 00:13:11,880 --> 00:13:14,720 Speaker 1: the back office and all of this stuff. And the 193 00:13:14,840 --> 00:13:18,760 Speaker 1: same with the lending that the rates are are higher 194 00:13:19,080 --> 00:13:23,880 Speaker 1: and there's a spread that's effectively taken by the centralized player. 195 00:13:24,480 --> 00:13:31,000 Speaker 1: So what the centralized finances about is essentially returning to 196 00:13:31,040 --> 00:13:37,520 Speaker 1: where we began in market exchange. And that's barber and 197 00:13:37,720 --> 00:13:41,240 Speaker 1: it's peer one on one and yeah, and that's the key. 198 00:13:41,440 --> 00:13:45,760 Speaker 1: So you're you're dealing with your peer uh directly or 199 00:13:46,200 --> 00:13:51,840 Speaker 1: a portfolio peers and through an algorithm, and that's the key. 200 00:13:52,160 --> 00:13:57,319 Speaker 1: So the algorithm basically takes the place of the functioning 201 00:13:57,800 --> 00:14:01,440 Speaker 1: of a bank or a broke her And when you 202 00:14:01,520 --> 00:14:03,960 Speaker 1: do this, when you've just got an algorithm out there, 203 00:14:04,600 --> 00:14:10,680 Speaker 1: it makes things much more efficient. So without that middle layer, uh, 204 00:14:11,400 --> 00:14:14,960 Speaker 1: you're able to get this efficiency gain that's very important, 205 00:14:15,200 --> 00:14:19,240 Speaker 1: uh for the economy. So as many different aspects of this, 206 00:14:19,320 --> 00:14:24,640 Speaker 1: but the key idea is, let's deal with the algorithm directly. 207 00:14:24,960 --> 00:14:27,960 Speaker 1: And when we do that, it's going to reduce costs. 208 00:14:28,040 --> 00:14:33,680 Speaker 1: It's gonna make transactions uh much more transparent, secure, efficient, 209 00:14:33,760 --> 00:14:37,320 Speaker 1: all of these things. So so let me push back 210 00:14:37,360 --> 00:14:39,320 Speaker 1: a little bit. And and by the way, we'll talk 211 00:14:39,360 --> 00:14:41,120 Speaker 1: about a c H in a minute. We'll talk about 212 00:14:41,160 --> 00:14:43,520 Speaker 1: credit cards in a minute. But let me for a 213 00:14:43,600 --> 00:14:47,360 Speaker 1: moment take the other side of the argument that nothing's 214 00:14:47,440 --> 00:14:50,720 Speaker 1: changed in finance over a century. Today, I could trade 215 00:14:50,760 --> 00:14:55,080 Speaker 1: stocks effectively for free. I'm rebuilding a Tyhota FJ in 216 00:14:55,120 --> 00:15:00,160 Speaker 1: South America. I ship cash down using an app. It 217 00:15:00,200 --> 00:15:02,160 Speaker 1: costs me three dollars every time I want to send 218 00:15:02,160 --> 00:15:05,400 Speaker 1: three thousand dollars to South America. That used to be impossible. 219 00:15:05,440 --> 00:15:08,520 Speaker 1: I could get cash out of a machine seven. I 220 00:15:08,560 --> 00:15:10,320 Speaker 1: don't even have to go to the bank to deposit 221 00:15:10,360 --> 00:15:13,120 Speaker 1: a check. I take a photo with my phone and 222 00:15:13,120 --> 00:15:16,320 Speaker 1: and that's a deposit. And if we go to dinner 223 00:15:16,320 --> 00:15:18,480 Speaker 1: and we want to split the tab, I could venmo 224 00:15:18,600 --> 00:15:21,280 Speaker 1: whoever else is at dinner back and forth. It's like 225 00:15:21,640 --> 00:15:25,160 Speaker 1: so easy. I think about what technology lets me do 226 00:15:25,320 --> 00:15:29,560 Speaker 1: today versus I was in college when they first put 227 00:15:29,600 --> 00:15:33,400 Speaker 1: an a t M in the student union. It feels 228 00:15:33,440 --> 00:15:38,560 Speaker 1: to someone like me that the past forty years has 229 00:15:38,640 --> 00:15:44,200 Speaker 1: seen an endless array of incremental improvements in the financial system, 230 00:15:44,280 --> 00:15:47,080 Speaker 1: and then the Great Financial Crisis comes along and everybody 231 00:15:47,120 --> 00:15:51,480 Speaker 1: seems to lose their minds. Aren't we overstating it when 232 00:15:51,480 --> 00:15:58,280 Speaker 1: we say there's been no improvements in the world of finance. Well, 233 00:15:58,840 --> 00:16:03,760 Speaker 1: I did make an option with the digitization, but I 234 00:16:03,840 --> 00:16:11,240 Speaker 1: think there's been improvements digitization. Yeah. Look, you say, let 235 00:16:11,240 --> 00:16:14,120 Speaker 1: me go through your list that you can practice the 236 00:16:14,160 --> 00:16:20,560 Speaker 1: trade for free. So that is it is true that 237 00:16:20,880 --> 00:16:25,400 Speaker 1: transaction costs have a decreased. It is not true to 238 00:16:25,480 --> 00:16:28,120 Speaker 1: believe that if you trade on robin Hood you're trading 239 00:16:28,160 --> 00:16:31,400 Speaker 1: for free. It's just not the case. And then number two, 240 00:16:31,840 --> 00:16:35,680 Speaker 1: more importantly, for me to take ownership of a share 241 00:16:35,720 --> 00:16:41,800 Speaker 1: of stock, because the transfer the ownership that takes two days. 242 00:16:41,840 --> 00:16:44,960 Speaker 1: So even in this age of the Internet, in the 243 00:16:45,040 --> 00:16:49,800 Speaker 1: age of digitization, it takes two days to transfer the 244 00:16:49,840 --> 00:16:54,040 Speaker 1: ownership of let's say a hundred chairs of IBM. It's 245 00:16:54,120 --> 00:17:01,760 Speaker 1: just completely unsatisfactory, unrealistic and uh yet better in nineties, 246 00:17:01,880 --> 00:17:06,800 Speaker 1: it was like five days, um, and we've had a 247 00:17:06,920 --> 00:17:10,480 Speaker 1: change the three days and two days. But that's just 248 00:17:11,000 --> 00:17:16,600 Speaker 1: to me totally offside. So as for the cash apps, yeah, 249 00:17:16,760 --> 00:17:21,080 Speaker 1: there's many, uh, many things that have happened to make 250 00:17:21,119 --> 00:17:25,840 Speaker 1: it a little more efficient to actually do the transactions. 251 00:17:25,880 --> 00:17:30,159 Speaker 1: But uh, and I point this out in the book, UM, 252 00:17:30,359 --> 00:17:37,240 Speaker 1: the current wave of fintech largely uses the banking infrastructure 253 00:17:37,400 --> 00:17:41,720 Speaker 1: that exists today, the centralized banking infrastructure. And to make 254 00:17:41,800 --> 00:17:46,440 Speaker 1: the case in the book that look the traditional financial institutions, 255 00:17:46,920 --> 00:17:51,359 Speaker 1: they are being continuously disrupted and one wave of that 256 00:17:51,480 --> 00:17:57,040 Speaker 1: disruption is the fintech. So the neon banks, things like that, um, 257 00:17:57,160 --> 00:18:01,520 Speaker 1: that make it much more friendly for the user. But 258 00:18:01,720 --> 00:18:07,679 Speaker 1: given that they are using the same centralized infrastructure, in 259 00:18:07,760 --> 00:18:13,040 Speaker 1: my opinion, the current wave of fintech is fleeting. I 260 00:18:13,080 --> 00:18:18,040 Speaker 1: had a speaker in my course, UM, very prominent person 261 00:18:18,680 --> 00:18:23,399 Speaker 1: in the world of of DeFi who basically at the 262 00:18:23,560 --> 00:18:28,240 Speaker 1: end of his talk to my course, he said that 263 00:18:28,359 --> 00:18:32,520 Speaker 1: the current wave of fintech is like putting lipstick on 264 00:18:32,560 --> 00:18:36,760 Speaker 1: a pig. And if you think about it, what he's 265 00:18:36,800 --> 00:18:42,160 Speaker 1: saying is, yeah, it's an improvement, um, but you've got 266 00:18:42,160 --> 00:18:47,439 Speaker 1: the same constraints of that centralized infrastructure. And what DeFi 267 00:18:47,560 --> 00:18:53,320 Speaker 1: is doing is not doing an incremental improvement on the 268 00:18:53,359 --> 00:18:58,800 Speaker 1: current infrastructure, is actually building something that's fresh and new. 269 00:18:59,560 --> 00:19:04,520 Speaker 1: So I see looking forward that a fintech will definitely 270 00:19:05,440 --> 00:19:11,960 Speaker 1: disrupt the current financial system, but then eventually the centralized 271 00:19:12,000 --> 00:19:18,440 Speaker 1: fintech will be disrupted by decentralized algorithms. So so let's 272 00:19:18,480 --> 00:19:21,879 Speaker 1: talk about what I think is the most expansive part 273 00:19:22,000 --> 00:19:25,840 Speaker 1: of centralized finance. Personally, I could care less if a 274 00:19:26,200 --> 00:19:29,280 Speaker 1: h takes two days to clear stock trade. It doesn't 275 00:19:29,359 --> 00:19:31,120 Speaker 1: make any difference to me. I could buy and sell 276 00:19:31,200 --> 00:19:35,040 Speaker 1: that stock a thousand times before the first trade settles 277 00:19:35,119 --> 00:19:38,439 Speaker 1: and it doesn't cost me anything. But in the book 278 00:19:38,840 --> 00:19:43,520 Speaker 1: you use the specific example of credit card transactions and 279 00:19:43,560 --> 00:19:46,600 Speaker 1: that a hundred years ago there was about a three 280 00:19:46,640 --> 00:19:50,880 Speaker 1: percent cost to send money by wire, and today using 281 00:19:50,920 --> 00:19:54,879 Speaker 1: credit cards, a century later, it's still a three percent 282 00:19:54,920 --> 00:19:59,639 Speaker 1: credit card fig So why does that exist? Why hasn't 283 00:19:59,680 --> 00:20:03,720 Speaker 1: it been competed down yet? And what will DEFY do 284 00:20:04,680 --> 00:20:12,119 Speaker 1: about that three big which is the bane of retailers everywhere? Yeah, 285 00:20:12,280 --> 00:20:16,399 Speaker 1: it's it's remarkable. Uh, the example I use on my 286 00:20:16,520 --> 00:20:21,080 Speaker 1: book is not one hundred years. It's a hundred and 287 00:20:21,160 --> 00:20:26,400 Speaker 1: fifty years. And I show this Western Union wire transfer 288 00:20:26,760 --> 00:20:32,040 Speaker 1: from seventy three and it's for three hundred dollars. And 289 00:20:32,080 --> 00:20:35,720 Speaker 1: then there's another line for the fees, and the fees 290 00:20:35,760 --> 00:20:40,399 Speaker 1: are nine dollars. So it's like and I tell my 291 00:20:40,440 --> 00:20:46,440 Speaker 1: students that basically nothing has changed in this particular example, 292 00:20:46,560 --> 00:20:50,840 Speaker 1: nothing has changed. Uh, it's a three percent fee. So 293 00:20:51,880 --> 00:20:58,919 Speaker 1: the reason that the fees for credit cards are so high, Um, 294 00:20:58,960 --> 00:21:03,920 Speaker 1: there's many reasons. The leading reasons are the lack of security. 295 00:21:04,920 --> 00:21:08,159 Speaker 1: So if somebody steals your credit card, then the credit 296 00:21:08,160 --> 00:21:11,240 Speaker 1: card company is good for it, right, so you're not 297 00:21:11,240 --> 00:21:16,439 Speaker 1: gonna lose anything that cover um and all the chargebacks. 298 00:21:16,520 --> 00:21:21,639 Speaker 1: So uh that that's expensive. The security mechanisms are expensive, 299 00:21:22,000 --> 00:21:27,520 Speaker 1: and then of course just the brick and mortar back office, 300 00:21:27,800 --> 00:21:32,560 Speaker 1: all the systems, all of that is expensive. So um, 301 00:21:33,040 --> 00:21:36,640 Speaker 1: you put that together, it's three percent. We have had, 302 00:21:37,240 --> 00:21:42,479 Speaker 1: again with fintech, some some competition here. Uh that's driven 303 00:21:42,560 --> 00:21:47,480 Speaker 1: that three percent lower because credit cards offer cash back 304 00:21:48,000 --> 00:21:52,520 Speaker 1: and all of these other deals, and we've had innovations 305 00:21:52,640 --> 00:21:56,400 Speaker 1: like let's say Apple Pay, which is a great deal 306 00:21:56,520 --> 00:21:59,800 Speaker 1: for the credit card company. So instead of getting three percent, 307 00:22:00,000 --> 00:22:02,840 Speaker 1: they get two point five, and Apple gets point five. 308 00:22:03,280 --> 00:22:08,119 Speaker 1: But it's massively more secure really when you use that. 309 00:22:08,320 --> 00:22:11,800 Speaker 1: Oh yeah, because to pay with Apple Pay, um, you 310 00:22:11,880 --> 00:22:16,399 Speaker 1: do the facial recognition. If you're just swiping a credit card, um, 311 00:22:16,920 --> 00:22:20,800 Speaker 1: there's no pin, right, So in the United States we 312 00:22:20,840 --> 00:22:23,800 Speaker 1: don't use the pin for the credit cards. In Europe 313 00:22:23,800 --> 00:22:28,640 Speaker 1: a different story, but it's really much more secure. So 314 00:22:28,840 --> 00:22:31,840 Speaker 1: we see the fees being bid down a little bit, 315 00:22:32,359 --> 00:22:35,920 Speaker 1: but that that's the reason. So so let me let's 316 00:22:35,920 --> 00:22:38,560 Speaker 1: stay with Apple Pay for a second, because it's such 317 00:22:38,600 --> 00:22:44,679 Speaker 1: an interesting um example. As a user, I have no 318 00:22:44,800 --> 00:22:47,800 Speaker 1: insensive really to use Apple Pay over a credit card, 319 00:22:48,480 --> 00:22:51,400 Speaker 1: but it would It sounds like the credit card companies 320 00:22:51,400 --> 00:22:55,360 Speaker 1: have a massive incentive to have me use Apple Pay. 321 00:22:55,520 --> 00:23:01,520 Speaker 1: Why hasn't there or a similar biometric um security system. 322 00:23:01,600 --> 00:23:05,480 Speaker 1: Why hasn't there been a bigger push in that direction 323 00:23:05,800 --> 00:23:12,639 Speaker 1: by the credit card companies. So at the beginning, it 324 00:23:12,720 --> 00:23:16,640 Speaker 1: wasn't clear that they really understood. So it seems like, well, 325 00:23:16,680 --> 00:23:19,840 Speaker 1: instead again three we got to take a haircut to 326 00:23:19,920 --> 00:23:24,080 Speaker 1: two point five. And and maybe there was an expectation 327 00:23:24,720 --> 00:23:29,200 Speaker 1: that the regular credit card would have better biometrics or 328 00:23:29,359 --> 00:23:32,000 Speaker 1: or a minimum a pin. But given that we don't 329 00:23:32,040 --> 00:23:36,440 Speaker 1: have that, uh, it is way more secure to use 330 00:23:36,520 --> 00:23:39,240 Speaker 1: something like Apple Pay, where you were to use a 331 00:23:39,320 --> 00:23:43,800 Speaker 1: pin or use the facial recognition. So it's much more 332 00:23:43,880 --> 00:23:51,560 Speaker 1: difficult to to use like Apple pay, uh if you're 333 00:23:52,200 --> 00:23:58,240 Speaker 1: if you've stolen somebody's phone for example. So the security 334 00:23:58,280 --> 00:24:03,560 Speaker 1: cost um that's attributed to those that use the credit 335 00:24:03,560 --> 00:24:06,879 Speaker 1: card that Apple pay is way lower. So we have 336 00:24:06,960 --> 00:24:09,639 Speaker 1: seen a lot of growth. This is not my area 337 00:24:09,720 --> 00:24:14,200 Speaker 1: of expertise, uh, like credit card uh, you know, mechanics 338 00:24:14,240 --> 00:24:17,280 Speaker 1: and and the amount of sales that's Apple Pay or 339 00:24:17,720 --> 00:24:24,119 Speaker 1: uh Android versus just a regular swipe. But but it 340 00:24:24,359 --> 00:24:27,760 Speaker 1: is much more secure and and that's a major cost. 341 00:24:27,880 --> 00:24:33,240 Speaker 1: The insecurity is a major issue with not just credit 342 00:24:33,240 --> 00:24:37,879 Speaker 1: cards but banking in general. We were discussing what makes 343 00:24:38,000 --> 00:24:44,639 Speaker 1: decentralization so desirable um and so valuable in so many cases, 344 00:24:44,720 --> 00:24:49,120 Speaker 1: But the counter argument is centralization allows us to put 345 00:24:49,240 --> 00:24:53,720 Speaker 1: legal protections into place and security and anti money laundering. 346 00:24:54,280 --> 00:24:59,439 Speaker 1: How do we manage those around decentralization? What what's the advantage? 347 00:24:59,760 --> 00:25:06,240 Speaker 1: So it is a tradeoff, and I think that people 348 00:25:06,320 --> 00:25:13,080 Speaker 1: in decentralized finance understand uh these tradeoffs and there's nothing 349 00:25:13,119 --> 00:25:16,760 Speaker 1: that's perfect. There's always going to be some risk. But 350 00:25:17,920 --> 00:25:26,359 Speaker 1: decentralization is again putting people together, so you deal peer 351 00:25:26,400 --> 00:25:30,879 Speaker 1: to peer without this thick middle layer, and there's some 352 00:25:30,960 --> 00:25:37,840 Speaker 1: advantage to doing that. Um, you're correct that centralization does 353 00:25:37,920 --> 00:25:42,000 Speaker 1: have some advantages. So one advantage is that you can 354 00:25:42,040 --> 00:25:48,600 Speaker 1: move very quickly, whereas a decentralized protocol, if there's a 355 00:25:48,680 --> 00:25:51,439 Speaker 1: change the necessary and that protocol, that's got to go 356 00:25:51,480 --> 00:25:55,720 Speaker 1: to a vote of of the users or the owners 357 00:25:55,760 --> 00:26:00,000 Speaker 1: of the governance, so that could take a longer period. 358 00:26:00,000 --> 00:26:04,080 Speaker 1: At a time, Uh, the throughput in terms of the 359 00:26:04,160 --> 00:26:07,639 Speaker 1: number of transactions per second much greater if you've just 360 00:26:07,680 --> 00:26:14,320 Speaker 1: got one centralized clearinghouse. So there there are trade offs here. 361 00:26:14,480 --> 00:26:20,840 Speaker 1: But with centralization, uh, these institutions can do what they want. 362 00:26:21,720 --> 00:26:28,320 Speaker 1: And we were talking in the previous segment about credit cards. Um, 363 00:26:28,600 --> 00:26:32,560 Speaker 1: well what about like a wire transfer? I did one 364 00:26:32,680 --> 00:26:36,920 Speaker 1: last week and I had to send um some euros 365 00:26:37,359 --> 00:26:42,520 Speaker 1: to Europe for uh, you know, for for some repair bill. 366 00:26:43,280 --> 00:26:48,520 Speaker 1: And UH my bank said, oh, well you're a good customer, 367 00:26:48,560 --> 00:26:52,840 Speaker 1: We're gonna wave the wire transfer fee. But then they 368 00:26:52,920 --> 00:26:57,119 Speaker 1: quoted me the rate and I said, well that rate 369 00:26:57,400 --> 00:27:01,879 Speaker 1: is two point five off the market and it's a sorry, 370 00:27:01,960 --> 00:27:04,760 Speaker 1: that's the best we can do. So to send the 371 00:27:04,800 --> 00:27:08,880 Speaker 1: wire transfer was like swiping a credit card, no difference. 372 00:27:09,080 --> 00:27:13,280 Speaker 1: And they think, you know, they're convincing the customer that, oh, well, 373 00:27:13,320 --> 00:27:15,479 Speaker 1: this is a favor that we're doing it. No, so 374 00:27:15,640 --> 00:27:19,600 Speaker 1: they have got control, they've got market power. So these 375 00:27:19,680 --> 00:27:22,720 Speaker 1: large financial institutions, it doesn't matter who I go to, 376 00:27:23,000 --> 00:27:25,560 Speaker 1: it's going to be the same thing where they're going 377 00:27:25,640 --> 00:27:28,360 Speaker 1: to quote two point five percent off the market rate 378 00:27:28,800 --> 00:27:32,760 Speaker 1: and and I gotta pay it. So it's very direct 379 00:27:33,080 --> 00:27:37,480 Speaker 1: and very large cost. So they've got the power to 380 00:27:37,560 --> 00:27:40,960 Speaker 1: actually do that. When you go peer to peer, it's 381 00:27:41,040 --> 00:27:45,200 Speaker 1: nothing like that at all. UM, you're just interacting with 382 00:27:45,520 --> 00:27:48,560 Speaker 1: your peer. Somebody is buying, somebody is selling, and and 383 00:27:48,640 --> 00:27:54,680 Speaker 1: we're done. There's no spread. So again, the advantage of 384 00:27:55,200 --> 00:27:59,600 Speaker 1: UH centralized is that we're familiar with it. UH. It 385 00:27:59,680 --> 00:28:03,199 Speaker 1: appears to work, it does work to some degree with 386 00:28:03,320 --> 00:28:08,640 Speaker 1: our system, but it imposes these costs, and these costs 387 00:28:09,520 --> 00:28:17,159 Speaker 1: lead to, in my opinion, UM, opportunities that are not 388 00:28:17,240 --> 00:28:20,000 Speaker 1: pursued that we really need to pursue. And if I 389 00:28:20,000 --> 00:28:24,600 Speaker 1: could give an example of debt, you're a small entrepreneur. 390 00:28:25,160 --> 00:28:27,840 Speaker 1: You've got a great idea, you think the return on 391 00:28:28,000 --> 00:28:32,240 Speaker 1: investment is going to be percent a year, and you 392 00:28:32,320 --> 00:28:37,320 Speaker 1: go to your bank and basically asked for a loan 393 00:28:37,560 --> 00:28:41,520 Speaker 1: to get this going, and the bank says, well, you're 394 00:28:42,200 --> 00:28:45,640 Speaker 1: too small. We prefer larger customers. So we prefer one 395 00:28:45,720 --> 00:28:49,840 Speaker 1: large customer to a hundred customers like you. Um, so 396 00:28:49,920 --> 00:28:51,600 Speaker 1: we're not going to do the loan, even though we 397 00:28:51,680 --> 00:28:55,440 Speaker 1: like the idea. But oh here, here's a credit card 398 00:28:56,480 --> 00:29:00,160 Speaker 1: and we've extended the credit limit on it, and you 399 00:29:00,160 --> 00:29:03,080 Speaker 1: can just borrow on your credit card, and we know 400 00:29:03,160 --> 00:29:11,280 Speaker 1: what those rates are, so the rate right, the project 401 00:29:11,360 --> 00:29:15,120 Speaker 1: isn't pursued. And when the project isn't pursued, you've got 402 00:29:15,360 --> 00:29:19,400 Speaker 1: like a high growth project that isn't pursued. That's exactly 403 00:29:19,480 --> 00:29:25,000 Speaker 1: what our economy needs. We're stuck in two real GDP 404 00:29:25,160 --> 00:29:29,760 Speaker 1: growth and given the size of the obligations that the 405 00:29:29,800 --> 00:29:34,320 Speaker 1: government has taken on UM, there are not many good options. 406 00:29:35,240 --> 00:29:39,960 Speaker 1: So you could inflate by increasing the money supply. You 407 00:29:40,200 --> 00:29:44,600 Speaker 1: could tax, and that's not great for growth, but the 408 00:29:44,680 --> 00:29:49,480 Speaker 1: best way out is to increase growth. And given the 409 00:29:49,600 --> 00:29:52,920 Speaker 1: situation that we're facing today where we've got so many 410 00:29:52,960 --> 00:29:57,120 Speaker 1: people under banked. So under banking is the example I 411 00:29:57,160 --> 00:30:00,640 Speaker 1: gave where you're not able to get that loan even 412 00:30:00,640 --> 00:30:04,000 Speaker 1: though you've got a good idea. Uh that that is 413 00:30:04,040 --> 00:30:08,840 Speaker 1: a drag on economic growth. So in my opinion, if 414 00:30:08,920 --> 00:30:12,880 Speaker 1: we take these frictions out or reduce the frictions and 415 00:30:13,080 --> 00:30:18,239 Speaker 1: allow people to be treated equally and the judgment is 416 00:30:18,320 --> 00:30:22,160 Speaker 1: basically on the quality of the idea rather than how 417 00:30:22,240 --> 00:30:27,200 Speaker 1: much you've got, then that opens up the possibility of 418 00:30:27,360 --> 00:30:33,160 Speaker 1: substantially increased growth in our economy, and we really need that. 419 00:30:34,400 --> 00:30:38,000 Speaker 1: So so let's stick with unbanked. And it's funny what 420 00:30:38,120 --> 00:30:41,720 Speaker 1: you mentioned about doing the wire to Europe. I mentioned 421 00:30:41,760 --> 00:30:44,520 Speaker 1: the app that I can send money around the world 422 00:30:44,520 --> 00:30:47,720 Speaker 1: and it costs me nothing, but I'm limited to sending 423 00:30:47,840 --> 00:30:51,960 Speaker 1: three thousand dollars that's the cap. I think it's every 424 00:30:52,000 --> 00:30:55,280 Speaker 1: seven days or every five days, or and I think 425 00:30:55,360 --> 00:30:58,680 Speaker 1: that is a nod to the money launching rules. Let's 426 00:30:58,720 --> 00:31:02,560 Speaker 1: talk about how much of the world is unbanked and 427 00:31:02,600 --> 00:31:06,000 Speaker 1: what DEFY can do to give them access. There was 428 00:31:06,040 --> 00:31:09,080 Speaker 1: a giant story on sixty Minutes a couple of years 429 00:31:09,120 --> 00:31:12,400 Speaker 1: ago about some person who set up a way to 430 00:31:12,480 --> 00:31:16,160 Speaker 1: move money around by phones. In Africa, there's you know, 431 00:31:16,240 --> 00:31:18,640 Speaker 1: a huge swath of people who are in bank there 432 00:31:19,200 --> 00:31:23,400 Speaker 1: and and that technology has been making improvements. Tell us 433 00:31:23,440 --> 00:31:27,400 Speaker 1: a little bit about UM how defy can help people 434 00:31:27,440 --> 00:31:31,120 Speaker 1: who don't have access to centralized banking. So in the 435 00:31:31,160 --> 00:31:35,600 Speaker 1: world today, there are one point seven billion people that 436 00:31:35,640 --> 00:31:40,240 Speaker 1: are unbanked, and there's probably we don't have the exact 437 00:31:40,360 --> 00:31:44,920 Speaker 1: number on this, Probably more are underbanked. And my example 438 00:31:45,000 --> 00:31:47,800 Speaker 1: that I gave you with the entrepreneur, that entrepreneur had 439 00:31:47,840 --> 00:31:52,520 Speaker 1: a personal bank account, but they they were not able 440 00:31:52,560 --> 00:31:55,160 Speaker 1: to get alone that and that again is under banking. 441 00:31:55,640 --> 00:32:00,720 Speaker 1: So it is a very large proportion. Uh. One example 442 00:32:01,080 --> 00:32:04,120 Speaker 1: I'd like to give UM, and a lot of the 443 00:32:04,160 --> 00:32:09,160 Speaker 1: action here is happening outside of the US. So think 444 00:32:09,440 --> 00:32:14,560 Speaker 1: of a country like Venezuela that's in a hyper inflation 445 00:32:14,800 --> 00:32:19,720 Speaker 1: a situation. If you're really well off in Venezuela, that 446 00:32:19,800 --> 00:32:24,400 Speaker 1: hyper inflation really doesn't impact you that much because you've 447 00:32:24,400 --> 00:32:29,240 Speaker 1: got a US dollar bank account in Miami or somewhere 448 00:32:29,240 --> 00:32:35,680 Speaker 1: outside of Venezuela. So who is hit the hardest. It's 449 00:32:35,800 --> 00:32:41,680 Speaker 1: the the average person uh in Venezuela where they don't 450 00:32:41,680 --> 00:32:46,080 Speaker 1: have the opportunity to set up that bank account outside 451 00:32:46,240 --> 00:32:49,680 Speaker 1: or the amount of money that they've got isn't that large. 452 00:32:50,640 --> 00:32:55,640 Speaker 1: So again the world that decentralized finance comes in very 453 00:32:55,640 --> 00:33:00,920 Speaker 1: conveniently here where if you've got a mobile phone, a smartphone, 454 00:33:01,600 --> 00:33:06,800 Speaker 1: then that serves as your bank and you can hold 455 00:33:07,240 --> 00:33:11,640 Speaker 1: UH token, and you might choose to hold token that 456 00:33:11,840 --> 00:33:15,960 Speaker 1: is backed by U S dollars and effectively you've done 457 00:33:16,000 --> 00:33:21,240 Speaker 1: the same thing that you've protected yourself against a hyper 458 00:33:21,240 --> 00:33:26,240 Speaker 1: inflation in that country. And effectively, what will happen if 459 00:33:26,240 --> 00:33:31,120 Speaker 1: that country continues on its course is that people will 460 00:33:31,280 --> 00:33:35,440 Speaker 1: essentially abandon the native currency. So why do I need it? 461 00:33:36,440 --> 00:33:39,600 Speaker 1: I can pay with a US dollar token and it 462 00:33:39,640 --> 00:33:41,600 Speaker 1: doesn't have to be U S dollars. It could be anything. 463 00:33:41,760 --> 00:33:45,040 Speaker 1: It could be a traditional currency like the dollar or 464 00:33:45,080 --> 00:33:47,240 Speaker 1: the euro, but it could be a token that's back 465 00:33:47,280 --> 00:33:51,000 Speaker 1: by gold. So as many possibilities here, and this is 466 00:33:51,080 --> 00:33:56,400 Speaker 1: just an example of how to effectively bank UH the 467 00:33:56,560 --> 00:34:01,040 Speaker 1: unbanked and the underbanked. So let's talk a little bit 468 00:34:01,520 --> 00:34:04,680 Speaker 1: about the terminology in the space. So much of it 469 00:34:04,720 --> 00:34:10,000 Speaker 1: is so confusing block chains and forking and protocols and 470 00:34:10,239 --> 00:34:13,120 Speaker 1: n f t s and d os. For someone who's 471 00:34:13,160 --> 00:34:17,480 Speaker 1: interested in learning more about this ecosystem, where do they 472 00:34:17,480 --> 00:34:22,880 Speaker 1: even begin? So it is confusing right now, and this 473 00:34:23,080 --> 00:34:28,520 Speaker 1: is a one of the reasons that I'm doing what 474 00:34:28,560 --> 00:34:32,840 Speaker 1: I'm doing, so I teach this. I think it's important 475 00:34:33,320 --> 00:34:37,640 Speaker 1: for the future. But it's very confusing, And initially it 476 00:34:37,800 --> 00:34:41,120 Speaker 1: was even more confusing because very little material other than 477 00:34:41,480 --> 00:34:47,920 Speaker 1: some computer scientists writing about various protocols. Today there's a 478 00:34:48,040 --> 00:34:51,319 Speaker 1: huge amount of information on the internet about this, but 479 00:34:51,440 --> 00:34:54,759 Speaker 1: you need to be very careful because some of the 480 00:34:54,840 --> 00:34:59,359 Speaker 1: information is basically selling our product. You need to go 481 00:34:59,560 --> 00:35:04,279 Speaker 1: somewhere are that's kind of highly rated. I know. I'm 482 00:35:04,320 --> 00:35:10,200 Speaker 1: working on UM a fourth course sequence UH for corse 483 00:35:10,280 --> 00:35:16,880 Speaker 1: Era that takes UM takes the viewer or the student 484 00:35:17,040 --> 00:35:24,440 Speaker 1: through four different stages of understanding decentralized finance from the infrastructure, 485 00:35:24,560 --> 00:35:27,960 Speaker 1: the primitives, and then a deep dive on some of 486 00:35:27,960 --> 00:35:31,160 Speaker 1: the key protocols and decentralized finance and go through the 487 00:35:31,200 --> 00:35:35,040 Speaker 1: mechanics of those, and then the fourth courses about the 488 00:35:35,120 --> 00:35:39,640 Speaker 1: risks and opportunities in the space. So it is difficult, 489 00:35:39,680 --> 00:35:45,560 Speaker 1: and I kind of um come to the realization that well, 490 00:35:45,600 --> 00:35:49,680 Speaker 1: I might have a couple of hundred students at Duke University. Uh, 491 00:35:50,239 --> 00:35:54,360 Speaker 1: I want to have a broader impact, so also putting 492 00:35:54,760 --> 00:35:59,799 Speaker 1: this stuff up um for everybody to learn from. Let's 493 00:36:00,000 --> 00:36:02,760 Speaker 1: walk professor a little bit about your new book, Defy 494 00:36:02,840 --> 00:36:07,040 Speaker 1: in the Future of Finance. Give us an overview of 495 00:36:07,320 --> 00:36:11,120 Speaker 1: the basic premise. What will readers get from this book? 496 00:36:12,040 --> 00:36:16,640 Speaker 1: So the book is written for the millions of people 497 00:36:17,000 --> 00:36:21,640 Speaker 1: that either work in the field of finance or are 498 00:36:21,719 --> 00:36:28,920 Speaker 1: interested in that field. And they've heard of crypto, maybe 499 00:36:28,920 --> 00:36:33,040 Speaker 1: they own UH some crypto, maybe they don't, but they 500 00:36:33,160 --> 00:36:39,600 Speaker 1: want to learn more. And indeed, the motivation for actually 501 00:36:39,640 --> 00:36:43,560 Speaker 1: reading this book is something that I tell my students 502 00:36:44,239 --> 00:36:49,719 Speaker 1: at the end of my crypto course, And basically I 503 00:36:49,800 --> 00:36:55,520 Speaker 1: say to them that I want them to be disrupt ors, 504 00:36:56,200 --> 00:37:03,240 Speaker 1: not disrupt ese. And this is a highly disruptive technology. 505 00:37:03,280 --> 00:37:09,279 Speaker 1: It will change finance as we know it. And and 506 00:37:09,360 --> 00:37:13,879 Speaker 1: I thought it was important to take that message outside 507 00:37:14,280 --> 00:37:19,120 Speaker 1: the confines of a single university and put a book 508 00:37:19,160 --> 00:37:25,640 Speaker 1: together that is accessible to anyone. The language is somewhat 509 00:37:26,360 --> 00:37:32,279 Speaker 1: different than the language of traditional finance, but but everybody 510 00:37:32,719 --> 00:37:37,080 Speaker 1: going through the book can figure out the linkages between 511 00:37:37,600 --> 00:37:41,080 Speaker 1: some of the things that I talked about and UH 512 00:37:41,200 --> 00:37:45,280 Speaker 1: and in traditional finance and and see the advantages. And 513 00:37:45,760 --> 00:37:52,080 Speaker 1: of course it's also crucial with any new technology for 514 00:37:52,880 --> 00:37:57,720 Speaker 1: the reader to be fully versed on the risks. Uh. 515 00:37:57,760 --> 00:38:00,520 Speaker 1: This is definitely not a risk free as a situation. 516 00:38:00,960 --> 00:38:05,080 Speaker 1: This is disruptive, there's going to be many ups and downs. 517 00:38:05,120 --> 00:38:09,240 Speaker 1: But it's important to go in with your eyes wide open, 518 00:38:09,440 --> 00:38:13,640 Speaker 1: recognizing the sort of risks that you face. But this 519 00:38:13,760 --> 00:38:21,000 Speaker 1: is basically my way of trying to explain what's going on. 520 00:38:21,880 --> 00:38:26,640 Speaker 1: And when you're early in on the technology, it is 521 00:38:26,680 --> 00:38:31,279 Speaker 1: difficult to see what's really going on. And people in 522 00:38:31,320 --> 00:38:38,520 Speaker 1: the media often see bitcoin or doge coin and things 523 00:38:38,520 --> 00:38:42,640 Speaker 1: like that. It's all about the price of those two tokens. 524 00:38:42,960 --> 00:38:47,600 Speaker 1: And and decentralized finance has very little to do with bitcoin. 525 00:38:47,880 --> 00:38:51,279 Speaker 1: So let's focus on decentralized finance. In the book, you 526 00:38:51,360 --> 00:38:57,080 Speaker 1: talk about the five various flaws of traditional centralized finance. 527 00:38:57,680 --> 00:39:02,759 Speaker 1: What do you think define most successfully attacks UM in 528 00:39:02,840 --> 00:39:08,400 Speaker 1: terms of traditional centralized finance. Well, there are five things 529 00:39:08,440 --> 00:39:13,600 Speaker 1: that I mentioned in the book UM Centralized control, so basically, 530 00:39:13,920 --> 00:39:20,239 Speaker 1: you're at the mercy of your bank because they are 531 00:39:20,280 --> 00:39:24,920 Speaker 1: holding your funds uh. And and there's various other aspects 532 00:39:25,560 --> 00:39:31,000 Speaker 1: whereas decentralized, you are in total control. You own the bank. Effectively, 533 00:39:31,080 --> 00:39:33,959 Speaker 1: the bank is in your pocket and you can do 534 00:39:34,520 --> 00:39:38,200 Speaker 1: what you want. UH. Limited access we've already talked about 535 00:39:38,640 --> 00:39:43,280 Speaker 1: where this is a technology of financial democracy. Doesn't matter 536 00:39:43,560 --> 00:39:47,560 Speaker 1: who you are, you're treated equally as a peer. There's 537 00:39:47,600 --> 00:39:53,600 Speaker 1: no retail customer, broker, banker, uh sort of relationship. Everybody 538 00:39:53,800 --> 00:39:55,719 Speaker 1: is the same. It might be a banker, but that 539 00:39:55,760 --> 00:40:00,600 Speaker 1: bankers appear. It might be a retail customer, you're a peer. Uh. 540 00:40:00,640 --> 00:40:03,560 Speaker 1: Inefficiency we've talked about also with this two point five 541 00:40:03,640 --> 00:40:08,120 Speaker 1: or three percent all over the place, a ridiculous uh, 542 00:40:08,120 --> 00:40:12,280 Speaker 1: you know, lending rates on credit cards. Uh. There's definite 543 00:40:12,400 --> 00:40:16,720 Speaker 1: progress that decentralized finance makes. What we haven't talked about 544 00:40:17,080 --> 00:40:22,640 Speaker 1: is lack of interoperability as a problem in our current system, 545 00:40:22,719 --> 00:40:28,279 Speaker 1: where for me to transfer some funds to my broker, Uh, 546 00:40:28,360 --> 00:40:30,799 Speaker 1: that could take two or three days from my bank 547 00:40:30,840 --> 00:40:35,879 Speaker 1: to my broker. Uh. So and that delay doesn't make 548 00:40:35,880 --> 00:40:40,439 Speaker 1: any sense in the age of the internet and dig 549 00:40:40,440 --> 00:40:45,040 Speaker 1: a bit, uh, you know broadband. So Uh. With the 550 00:40:45,080 --> 00:40:49,919 Speaker 1: centralized finance, everything is linked together and it's seamless. Uh. 551 00:40:49,960 --> 00:40:54,440 Speaker 1: In terms of the transfers are are pretty well immediate. 552 00:40:54,640 --> 00:40:59,960 Speaker 1: And number five issue is uh opacity that you're dealing 553 00:41:00,040 --> 00:41:04,080 Speaker 1: with the bank. You don't really know UM the health 554 00:41:04,120 --> 00:41:07,520 Speaker 1: of the bank. You're relying upon the government the f 555 00:41:07,640 --> 00:41:11,800 Speaker 1: d i C to basically ensure you, but there's limits 556 00:41:12,040 --> 00:41:15,840 Speaker 1: to that insurance. And UH, the f d i C 557 00:41:16,120 --> 00:41:20,360 Speaker 1: and the regulators have a checkered record of detecting problems 558 00:41:20,760 --> 00:41:26,319 Speaker 1: in advance, whereas in decentralized finance, everything is open, so 559 00:41:27,200 --> 00:41:31,759 Speaker 1: you can see the balances of the people doing transactions, 560 00:41:31,840 --> 00:41:36,400 Speaker 1: you can see the code that is the algorithm that 561 00:41:36,440 --> 00:41:40,040 Speaker 1: you're trading with, you can see the liquidity. It is 562 00:41:40,160 --> 00:41:47,000 Speaker 1: completely transparent. So these five problems I think decentralized UH 563 00:41:47,040 --> 00:41:50,719 Speaker 1: finance deal with, and probably if you're asking me to 564 00:41:50,800 --> 00:41:55,360 Speaker 1: pick one, I would pick the inefficiency that because of 565 00:41:55,360 --> 00:42:00,600 Speaker 1: the thick layer of middle people in centralized finance, UH, 566 00:42:01,080 --> 00:42:05,239 Speaker 1: the probably the primary advantage is to get rid of that, 567 00:42:05,640 --> 00:42:08,360 Speaker 1: and when you're trading with an algorithm, it's much more efficient. 568 00:42:08,960 --> 00:42:12,880 Speaker 1: That's really interesting. I'm quite intrigued by the concept of 569 00:42:13,000 --> 00:42:17,200 Speaker 1: smart contracts. Let's discuss that a bit tell us what 570 00:42:17,360 --> 00:42:21,759 Speaker 1: smart contracts are and how they can be used. So 571 00:42:21,800 --> 00:42:26,719 Speaker 1: this is one of the main differences between Bitcoin and Ethereum. 572 00:42:26,760 --> 00:42:33,680 Speaker 1: So Bitcoin you can just transfer funds from one person 573 00:42:33,760 --> 00:42:39,719 Speaker 1: to another, whereas in the Theoryum there's another possibility. Uh, 574 00:42:39,760 --> 00:42:43,959 Speaker 1: in the theorem you can actually have an algorithm run 575 00:42:44,120 --> 00:42:48,080 Speaker 1: in the Ethereum blockchain. So the Theorium blockchain is more 576 00:42:48,160 --> 00:42:52,680 Speaker 1: like a computing platform, whereas the Bitcoin platform is just 577 00:42:53,080 --> 00:42:58,440 Speaker 1: purely for transactions. So in the Theoryum, you can actually 578 00:42:59,239 --> 00:43:04,160 Speaker 1: send funds, not just to another person, which of course 579 00:43:04,200 --> 00:43:08,040 Speaker 1: you can, but you can send them to an algorithm. 580 00:43:08,120 --> 00:43:12,920 Speaker 1: And that algorithm might actually uh be what's known as 581 00:43:13,080 --> 00:43:18,239 Speaker 1: a decentralized exchange or our decks uh the x and 582 00:43:18,680 --> 00:43:24,000 Speaker 1: that allows me to trade let's say, one token for 583 00:43:24,160 --> 00:43:27,960 Speaker 1: another token within that algorithm. So I send one token 584 00:43:28,239 --> 00:43:32,120 Speaker 1: to the algorithm, and the algorithm sends me another token. 585 00:43:32,600 --> 00:43:38,000 Speaker 1: It's a beautiful idea, and it's uh and it's remarkable 586 00:43:38,080 --> 00:43:42,000 Speaker 1: that the algorithm doesn't care who you are, how much 587 00:43:42,120 --> 00:43:45,080 Speaker 1: you're actually trading, and it doesn't care if you're a 588 00:43:45,080 --> 00:43:49,040 Speaker 1: buyer or a seller. In in addition, it is running. 589 00:43:51,080 --> 00:43:55,680 Speaker 1: So this is a very significant idea and uh and 590 00:43:55,680 --> 00:44:01,120 Speaker 1: and will be definitely disruptive. I'm kind of intrigued by 591 00:44:01,160 --> 00:44:06,359 Speaker 1: the concept of smart tickets for live events that that 592 00:44:06,480 --> 00:44:10,440 Speaker 1: really moves a lot of the control over who purchases, 593 00:44:10,560 --> 00:44:14,080 Speaker 1: who prices it, how much it gets marked up back 594 00:44:14,120 --> 00:44:19,840 Speaker 1: to the artist. Can can defy eventually create a world 595 00:44:19,960 --> 00:44:24,640 Speaker 1: where if Taylor Swift wants to sell tickets first to 596 00:44:24,800 --> 00:44:29,239 Speaker 1: her registered fans and allow them to resell it but 597 00:44:29,360 --> 00:44:32,480 Speaker 1: only up to a fixed price, uh, and they get 598 00:44:32,520 --> 00:44:38,040 Speaker 1: to split the profit between the the fan and the artist. 599 00:44:38,760 --> 00:44:42,680 Speaker 1: Are those sort of things feasible with with defy or 600 00:44:42,560 --> 00:44:47,239 Speaker 1: or are some of these really kind of futuristic pipe dreams? No? 601 00:44:47,560 --> 00:44:52,239 Speaker 1: And actually we talked about ticketing in my course, so 602 00:44:52,400 --> 00:44:58,000 Speaker 1: this is a broader application. So think of watchain technology 603 00:44:58,040 --> 00:45:02,560 Speaker 1: as a technology that will disrupt many areas of business 604 00:45:03,800 --> 00:45:09,920 Speaker 1: and that uh, the low hanging fruit is finance, but 605 00:45:10,320 --> 00:45:13,920 Speaker 1: we've also seen a lot of progress and other dimensions 606 00:45:13,960 --> 00:45:17,800 Speaker 1: like supply chain and things like that. And the supply 607 00:45:17,880 --> 00:45:21,760 Speaker 1: chain example is that you're shopping at your grocery store 608 00:45:22,040 --> 00:45:23,960 Speaker 1: because they had to let us with the q R 609 00:45:24,040 --> 00:45:27,640 Speaker 1: on it. You scan it. You know where that lettuce 610 00:45:27,719 --> 00:45:31,440 Speaker 1: was picked, the day it was picked, every whether the 611 00:45:31,440 --> 00:45:34,719 Speaker 1: farm is organic, every single hop on the supply chain, 612 00:45:34,920 --> 00:45:38,280 Speaker 1: and how long it's been on the shelf at the 613 00:45:38,280 --> 00:45:41,560 Speaker 1: grocery store. So that's what blockchain can do. And ticketing 614 00:45:42,000 --> 00:45:45,560 Speaker 1: is a great example. It's very similar. The dynamics are 615 00:45:45,600 --> 00:45:49,240 Speaker 1: similar that uh, you know, firms like Ticketmaster and stub 616 00:45:49,320 --> 00:45:56,680 Speaker 1: Hub they take of the ticket. Yeah, so it's very 617 00:45:56,800 --> 00:46:02,160 Speaker 1: little leftover for the artist. And there's something else that 618 00:46:02,280 --> 00:46:06,600 Speaker 1: happens that is really important to understand. It's not just 619 00:46:09,960 --> 00:46:14,360 Speaker 1: it's that the customer is dealing with Ticketmaster, they're not 620 00:46:14,480 --> 00:46:19,919 Speaker 1: dealing with the artist, So there is a separation. There's 621 00:46:19,960 --> 00:46:25,480 Speaker 1: no relationship between the concertgoer and the artist, just like 622 00:46:25,560 --> 00:46:29,600 Speaker 1: Amazon does with retail. So you buy something off Amazon, 623 00:46:29,719 --> 00:46:33,640 Speaker 1: you deal with Amazon, and there's no way for the 624 00:46:33,760 --> 00:46:37,280 Speaker 1: actual person selling the good to connect with the customer. 625 00:46:37,640 --> 00:46:41,000 Speaker 1: They only deal with Amazon. So you break that connection 626 00:46:41,480 --> 00:46:45,359 Speaker 1: and it's very very costly. Uh, particularly in the arts. 627 00:46:45,440 --> 00:46:49,560 Speaker 1: You can imagine a different system using blockchain technology. And 628 00:46:49,600 --> 00:46:52,760 Speaker 1: there are companies that actually do this. And the company 629 00:46:52,840 --> 00:46:57,239 Speaker 1: that I like um is called True Tickets, and I 630 00:46:57,280 --> 00:47:00,800 Speaker 1: believe they're sponsored by IBM right now, but they're offering 631 00:47:00,840 --> 00:47:05,080 Speaker 1: a solution where, uh, where you actually do have this 632 00:47:05,120 --> 00:47:11,320 Speaker 1: direct connection between the artist and and the just basically 633 00:47:11,320 --> 00:47:15,480 Speaker 1: the artist and the concert goer, and the synergies are 634 00:47:15,560 --> 00:47:19,359 Speaker 1: just remarkable that there could be a song that is 635 00:47:19,400 --> 00:47:23,200 Speaker 1: done outside of an album that's made available to the 636 00:47:23,239 --> 00:47:26,600 Speaker 1: people that are connected to the artist. There could be 637 00:47:26,640 --> 00:47:29,799 Speaker 1: information about the next tour, all of this stuff. There's 638 00:47:29,840 --> 00:47:33,680 Speaker 1: a direct connection with the artist, and that's what we 639 00:47:33,800 --> 00:47:36,880 Speaker 1: really need. Of course, you know that, uh in the 640 00:47:36,960 --> 00:47:43,760 Speaker 1: music industry, Uh, it's notorious for uh so little goes 641 00:47:43,840 --> 00:47:47,320 Speaker 1: to the artists. Really the only thing that's profitable is 642 00:47:47,800 --> 00:47:51,640 Speaker 1: the concert. And even the concert uh, the haircut is 643 00:47:51,640 --> 00:47:55,280 Speaker 1: is enormous. So there's so many layers of middle people. 644 00:47:55,840 --> 00:48:00,560 Speaker 1: And again you're you're onto exactly the right intuition. You 645 00:48:00,680 --> 00:48:07,240 Speaker 1: take that that that oligop balistic um or market power 646 00:48:07,480 --> 00:48:13,200 Speaker 1: out of this and connect people directly, then everybody is 647 00:48:13,239 --> 00:48:18,000 Speaker 1: better off. So yes, um, ticketing is low hanging fruit. 648 00:48:18,320 --> 00:48:23,160 Speaker 1: We will see some progress on this. But and this 649 00:48:23,239 --> 00:48:28,040 Speaker 1: is an important butt. The middle people are extremely powerful 650 00:48:28,600 --> 00:48:34,560 Speaker 1: and they will fight. Just like in the financial system, uh, 651 00:48:34,880 --> 00:48:39,560 Speaker 1: the banks, the exchanges, they'll try to delay this, whether 652 00:48:39,760 --> 00:48:43,759 Speaker 1: it's lobbying government for regulation and things like that. I'm 653 00:48:43,840 --> 00:48:47,840 Speaker 1: convinced that they realize what's coming. And let me just 654 00:48:47,880 --> 00:48:51,040 Speaker 1: give you a short story. UM this happened a little 655 00:48:51,080 --> 00:48:57,600 Speaker 1: before COVID happened. A major stock exchange, UM Global Stock 656 00:48:57,640 --> 00:49:00,719 Speaker 1: Exchange called me in to talk about crypto. It is 657 00:49:00,760 --> 00:49:04,480 Speaker 1: pretty vague agenda. I show up. It's their board of 658 00:49:04,520 --> 00:49:08,120 Speaker 1: directors and their senior management sitting in the room, and 659 00:49:08,160 --> 00:49:11,799 Speaker 1: they've got a single question for me. How long do 660 00:49:11,880 --> 00:49:19,400 Speaker 1: we have? So I think that people realize they can 661 00:49:19,440 --> 00:49:23,480 Speaker 1: see the trend and and ticketing is a very good 662 00:49:23,480 --> 00:49:27,720 Speaker 1: example of a system that it doesn't work for the artist, 663 00:49:28,560 --> 00:49:34,920 Speaker 1: it doesn't work for the concert goer, so we need 664 00:49:35,000 --> 00:49:39,359 Speaker 1: to fix it, and the technology exists to do that. 665 00:49:40,200 --> 00:49:43,440 Speaker 1: Let's talk a little bit about what's going on in 666 00:49:43,480 --> 00:49:47,760 Speaker 1: the crypto sector today. N f t s are on fire, 667 00:49:48,000 --> 00:49:52,600 Speaker 1: Bitcoin is approaching sixty THO. An investor who wants to 668 00:49:52,760 --> 00:49:55,959 Speaker 1: speculate with a little money in this area, how should 669 00:49:56,000 --> 00:50:00,439 Speaker 1: they put that money to work? So Number one, way 670 00:50:00,440 --> 00:50:04,320 Speaker 1: too much attention is paid to the price of bitcoin. 671 00:50:04,920 --> 00:50:09,160 Speaker 1: It goes up and down. And indeed, uh, it was 672 00:50:09,239 --> 00:50:12,920 Speaker 1: interesting when the price crashed in two thousand eighteen dropped. 673 00:50:14,440 --> 00:50:19,240 Speaker 1: What was most interesting to me was that the venture 674 00:50:19,680 --> 00:50:24,880 Speaker 1: capitalists that we're investing in de five there was no impact. 675 00:50:26,120 --> 00:50:31,200 Speaker 1: So even though the cryptos dropped by they were equally 676 00:50:31,239 --> 00:50:36,239 Speaker 1: as interested. And what I think are the most interesting 677 00:50:36,360 --> 00:50:40,799 Speaker 1: technologies are things that are below the radar screen. The 678 00:50:41,200 --> 00:50:44,840 Speaker 1: we hear in the news of a big clin and 679 00:50:45,239 --> 00:50:50,560 Speaker 1: Elon Musk tweeting about doge coin or or whatever. Uh 680 00:50:50,600 --> 00:50:53,960 Speaker 1: that there's a lot of other stuff that is really 681 00:50:54,040 --> 00:50:58,680 Speaker 1: interesting that's below the radar. In decentralized finance, it is 682 00:50:59,120 --> 00:51:03,640 Speaker 1: a very hot area. So for an investor, if you're 683 00:51:03,719 --> 00:51:07,239 Speaker 1: going to and I do encourage people to get a 684 00:51:07,239 --> 00:51:11,239 Speaker 1: wallet and to do some experimentation, but you need to 685 00:51:11,239 --> 00:51:17,680 Speaker 1: be careful that things like investing in bitcoin. The annualized 686 00:51:17,719 --> 00:51:22,960 Speaker 1: volatility is about nine so that's huge. So the stock 687 00:51:23,000 --> 00:51:27,160 Speaker 1: market is fifteen percent. Gold is let's say this is 688 00:51:27,160 --> 00:51:30,880 Speaker 1: an incredibly volatile asset, and then some people do margin trading. 689 00:51:32,080 --> 00:51:37,680 Speaker 1: So if you do margin, then the volatilities double. So 690 00:51:37,760 --> 00:51:39,759 Speaker 1: you need to be really careful Number one, that this 691 00:51:39,880 --> 00:51:44,880 Speaker 1: is an extremely volatile asset class, and you need to 692 00:51:44,920 --> 00:51:50,960 Speaker 1: be going into this uh without margin fully knowing that 693 00:51:51,200 --> 00:51:55,800 Speaker 1: we could have another situation where you lose crypto winters. 694 00:51:56,000 --> 00:51:59,360 Speaker 1: Is what what a lot of folks qualities? Yeah, exactly, 695 00:51:59,480 --> 00:52:02,359 Speaker 1: there's ups and downs and number two, you can't be 696 00:52:02,760 --> 00:52:07,040 Speaker 1: the so called bandwagon investor where you buy high and 697 00:52:07,040 --> 00:52:10,000 Speaker 1: and and sell low. So I think of those people 698 00:52:10,760 --> 00:52:14,520 Speaker 1: that we're buying at the peak in two thousand seventeen 699 00:52:15,560 --> 00:52:20,239 Speaker 1: at twenty thousand dollars and and then UH in two 700 00:52:20,239 --> 00:52:23,680 Speaker 1: thousand and eighteen the price crashes to five thousand. Think 701 00:52:23,680 --> 00:52:27,560 Speaker 1: about the people that bought at twenty and sold at 702 00:52:27,600 --> 00:52:31,759 Speaker 1: five thousand. The alternative, you buy at twenty and you 703 00:52:31,840 --> 00:52:35,960 Speaker 1: take a longer term perspective and look where you are today. 704 00:52:36,600 --> 00:52:39,680 Speaker 1: So so you need to have a longer term perspective. 705 00:52:39,719 --> 00:52:44,760 Speaker 1: That's number two. Number three and this is hopefully obvious, 706 00:52:45,160 --> 00:52:49,040 Speaker 1: that you should have a diversified portfolio. And that means 707 00:52:49,040 --> 00:52:51,480 Speaker 1: you don't don't put all your money into crypto, and 708 00:52:51,680 --> 00:52:55,960 Speaker 1: even within the crypto, you need to have a diversified portfolio, 709 00:52:56,480 --> 00:53:01,680 Speaker 1: so more than one, not just bitcoin UH And and 710 00:53:01,680 --> 00:53:06,680 Speaker 1: then number four is maybe the most important. You know 711 00:53:06,800 --> 00:53:10,400 Speaker 1: what you're investing, Understand what you're investing. You buy a 712 00:53:10,520 --> 00:53:14,640 Speaker 1: share of Apple, you you might have an iPhone or 713 00:53:14,680 --> 00:53:19,160 Speaker 1: a Mac, or you use iTunes. You understand the business 714 00:53:19,160 --> 00:53:22,480 Speaker 1: model and you believe that they're in a good position 715 00:53:23,080 --> 00:53:27,200 Speaker 1: to UH build profits in the future. You need to 716 00:53:27,280 --> 00:53:30,319 Speaker 1: do the same thing when you're investing in crypto. You 717 00:53:30,400 --> 00:53:32,920 Speaker 1: can't just take a tip from somebody, oh, well, this 718 00:53:33,120 --> 00:53:35,760 Speaker 1: is what I've got. You need to do your homework 719 00:53:36,160 --> 00:53:42,160 Speaker 1: and figure out what this token is really representing. Quite 720 00:53:42,239 --> 00:53:45,799 Speaker 1: interesting you mentioned earlier that you thought, um, a lot 721 00:53:45,800 --> 00:53:48,600 Speaker 1: of commercial banks are a bit worried about the risk 722 00:53:48,680 --> 00:53:52,040 Speaker 1: of defy, but we're starting to see some of these 723 00:53:52,080 --> 00:53:58,080 Speaker 1: giant financial institutions get involved. I think Visas spent dollars 724 00:53:58,120 --> 00:54:01,880 Speaker 1: on a crypto punk and some other banks have been 725 00:54:01,920 --> 00:54:07,160 Speaker 1: involved in fintech and and some seed companies as they 726 00:54:07,440 --> 00:54:12,480 Speaker 1: look to basically do an end run around around centralized 727 00:54:12,480 --> 00:54:16,160 Speaker 1: banking and disrupt finance. What do you think is going 728 00:54:16,200 --> 00:54:18,960 Speaker 1: to happen with these big financial institutions. Are they going 729 00:54:19,000 --> 00:54:22,279 Speaker 1: to sit on their hands and become disrupted or are 730 00:54:22,320 --> 00:54:24,880 Speaker 1: they going to try and muscle their way in and 731 00:54:25,239 --> 00:54:27,839 Speaker 1: keep a finger in the pie, so to speak. So 732 00:54:28,120 --> 00:54:34,279 Speaker 1: they totally understand this in my opinion, Um, they know 733 00:54:34,560 --> 00:54:39,279 Speaker 1: this disruption is coming and they will do what they 734 00:54:39,360 --> 00:54:44,120 Speaker 1: can to delay. So one thing that they can do 735 00:54:44,360 --> 00:54:51,920 Speaker 1: in the short term is to become more efficient. So, uh, 736 00:54:51,960 --> 00:54:57,719 Speaker 1: it's kind of interesting that we all heard a couple 737 00:54:57,719 --> 00:55:04,200 Speaker 1: of years ago Jamie Diamond saying that, uh that anybody 738 00:55:04,719 --> 00:55:08,760 Speaker 1: caught trading tript at JP Morgan was gonna be fired, 739 00:55:09,520 --> 00:55:12,839 Speaker 1: and and the reason for that is that they were 740 00:55:13,680 --> 00:55:18,520 Speaker 1: basically being stupid. Well, it's a completely different story today 741 00:55:18,960 --> 00:55:24,080 Speaker 1: where JP Morgan has got a stable coin, which is 742 00:55:24,200 --> 00:55:28,320 Speaker 1: a type of cryptocurrency, and they fully embraced everything about 743 00:55:28,360 --> 00:55:32,640 Speaker 1: this space. It's hard to ignore when the space is 744 00:55:33,120 --> 00:55:36,960 Speaker 1: capitalized that two trillion dollars, that this is an a 745 00:55:37,040 --> 00:55:42,280 Speaker 1: novelty anymore. So these banks will do a number of things, 746 00:55:42,719 --> 00:55:47,880 Speaker 1: so uh, they will use the space to their advantage. 747 00:55:48,560 --> 00:55:54,400 Speaker 1: And and these stable coins are basically hard back to 748 00:55:55,480 --> 00:56:01,759 Speaker 1: the era of a free banking where banks for quite 749 00:56:01,760 --> 00:56:04,480 Speaker 1: a while in the US, we're able to issue their 750 00:56:04,480 --> 00:56:09,799 Speaker 1: own currency backed by various things. So that's essentially what 751 00:56:09,840 --> 00:56:14,600 Speaker 1: the banks will do. They tried to do other things. 752 00:56:14,640 --> 00:56:20,880 Speaker 1: You mentioned crypto punk, but um Visa actually tried to 753 00:56:21,040 --> 00:56:24,960 Speaker 1: acquire Plaid for five point three billion dollars. And the 754 00:56:25,000 --> 00:56:29,799 Speaker 1: reason that they wanted Plaid was this lack of interoperability 755 00:56:30,160 --> 00:56:34,200 Speaker 1: that was one of the great disadvantages of centralized finance. 756 00:56:34,360 --> 00:56:36,920 Speaker 1: So it's really hard to move money from your broker 757 00:56:37,600 --> 00:56:40,920 Speaker 1: to your bank or vice versa. But that was blocked 758 00:56:41,440 --> 00:56:46,480 Speaker 1: um by the regulators. So so they completely get this 759 00:56:46,760 --> 00:56:51,279 Speaker 1: that both the combination of fintech and decentralized finance, this 760 00:56:51,400 --> 00:56:55,439 Speaker 1: is an existential threat to their business. So they will 761 00:56:55,520 --> 00:56:58,280 Speaker 1: try to do things. They'll make some investments, they'll work 762 00:56:58,280 --> 00:57:01,799 Speaker 1: on the politicians will try to do the maximum sort 763 00:57:01,800 --> 00:57:06,879 Speaker 1: of regulatory push. All of this are our tools um 764 00:57:07,040 --> 00:57:11,040 Speaker 1: that they will use fully, realizing that it is just 765 00:57:11,080 --> 00:57:15,000 Speaker 1: a matter of time. Huh, that's interesting. We haven't talked about. 766 00:57:15,040 --> 00:57:20,439 Speaker 1: The largest company in crypto is probably coin Base. They're 767 00:57:20,480 --> 00:57:23,480 Speaker 1: publicly traded, but it's kind of ironic. They're also a 768 00:57:23,600 --> 00:57:28,280 Speaker 1: centralized company. Tell us a bit about coin bases role 769 00:57:28,920 --> 00:57:33,040 Speaker 1: in the ecosystem. So coin based very important in terms 770 00:57:33,080 --> 00:57:38,360 Speaker 1: of the credibility of of crypto and coin Base made 771 00:57:38,360 --> 00:57:41,800 Speaker 1: it a lot easier for people to get into this space. 772 00:57:42,280 --> 00:57:46,600 Speaker 1: So instead of actually having to worry about your private 773 00:57:46,680 --> 00:57:50,840 Speaker 1: keys and securing them, you could use coin Base, a 774 00:57:50,920 --> 00:57:54,080 Speaker 1: third party to take care of that, just like we 775 00:57:54,240 --> 00:57:57,360 Speaker 1: use a broker um so we don't worry about the 776 00:57:57,400 --> 00:58:00,960 Speaker 1: actual physical ownership of a hundred chair to IBM, the 777 00:58:01,080 --> 00:58:05,080 Speaker 1: broker handles that for us, so a coin base was 778 00:58:05,240 --> 00:58:09,200 Speaker 1: very important in getting people in their fully regulated. There's 779 00:58:09,280 --> 00:58:13,000 Speaker 1: more than ten thousand exchanges in the world, and probably 780 00:58:13,000 --> 00:58:17,960 Speaker 1: more than nine of them UM are very questionable, especially 781 00:58:18,000 --> 00:58:20,880 Speaker 1: in terms of the volume that they report and the 782 00:58:20,920 --> 00:58:23,360 Speaker 1: sort of deal that you get when you're buying or 783 00:58:23,480 --> 00:58:28,800 Speaker 1: or selling big spreads. So coin base UM is also ensured, 784 00:58:29,640 --> 00:58:36,560 Speaker 1: which is interesting UM. And it is centralized. So the 785 00:58:36,640 --> 00:58:40,360 Speaker 1: way that I described comb base is UM, I call 786 00:58:40,440 --> 00:58:44,800 Speaker 1: it c defy so C E D E F HI, 787 00:58:45,440 --> 00:58:50,280 Speaker 1: so it's centralized centrilcement. So they deal in a lot 788 00:58:50,320 --> 00:58:55,040 Speaker 1: of decentralized financial protocols and tokens and stuff like that, 789 00:58:55,280 --> 00:59:00,680 Speaker 1: but they're centralized. And coin Base and Binance, they main 790 00:59:00,880 --> 00:59:08,240 Speaker 1: competition is what's known as decentralized exchange or decks. So 791 00:59:08,800 --> 00:59:12,240 Speaker 1: if you look at the amount of trading that's actually happening, 792 00:59:12,680 --> 00:59:16,280 Speaker 1: there's huge growth and this decks trading and the deck 793 00:59:16,440 --> 00:59:19,600 Speaker 1: is where you're trading with the algorithm, so there's no 794 00:59:19,720 --> 00:59:23,520 Speaker 1: mid person like coin base. The disadvantage of the decks, 795 00:59:24,560 --> 00:59:28,040 Speaker 1: maybe many were considered an advantage is that you hold 796 00:59:28,080 --> 00:59:31,840 Speaker 1: your your your private keys. Uh, there's no third party. 797 00:59:32,200 --> 00:59:36,640 Speaker 1: That's uh, that's actually UH in the middle UM. So 798 00:59:36,640 --> 00:59:39,720 Speaker 1: so let's stay with that a second, because there have 799 00:59:39,760 --> 00:59:43,960 Speaker 1: been all sorts of crazy stories about lost passwords, hundreds 800 00:59:43,960 --> 00:59:48,200 Speaker 1: of millions of individual dollars lost by some people, and 801 00:59:48,200 --> 00:59:53,640 Speaker 1: and I've seen estimates of of all um coins have 802 00:59:53,760 --> 00:59:58,120 Speaker 1: been lost due to either lost passwords or damage hard drives. 803 00:59:58,680 --> 01:00:01,240 Speaker 1: When you go through a coin base, they take the 804 01:00:01,280 --> 01:00:04,040 Speaker 1: liability of that off of you. In other words, you 805 01:00:04,080 --> 01:00:07,240 Speaker 1: don't have to worry about a damage drive or or 806 01:00:07,280 --> 01:00:11,640 Speaker 1: a lost password. They'll make sure you have access and 807 01:00:11,680 --> 01:00:15,400 Speaker 1: I'm assuming it's UM a very secure way to access, 808 01:00:15,880 --> 01:00:21,400 Speaker 1: as secure as a regular bank exactly. So they deal 809 01:00:21,440 --> 01:00:24,840 Speaker 1: with the custody. And this has also been a big 810 01:00:24,840 --> 01:00:31,160 Speaker 1: deal for investment funds. So they've seen the crypto complex 811 01:00:31,440 --> 01:00:37,360 Speaker 1: gro uh dramatically too, two trillion dollars, and they've been 812 01:00:37,400 --> 01:00:42,400 Speaker 1: struggling with the cost of the issue. So how how 813 01:00:42,400 --> 01:00:46,680 Speaker 1: do we secure these private keys? So the solution is 814 01:00:46,720 --> 01:00:50,480 Speaker 1: to have a custodian. And that's another thing that coin 815 01:00:50,560 --> 01:00:54,040 Speaker 1: base actually does very successfully, is that will serve as 816 01:00:54,080 --> 01:00:57,640 Speaker 1: a custodian for UH, like a hedge fund or a 817 01:00:57,760 --> 01:01:02,920 Speaker 1: mutual fund UM if they're interested investing in crypto. So 818 01:01:03,000 --> 01:01:07,080 Speaker 1: corn based. Again very important uh in terms of the evolution. 819 01:01:07,640 --> 01:01:11,040 Speaker 1: But I do see the trend, and the trend is 820 01:01:11,760 --> 01:01:18,480 Speaker 1: towards UM trading directly between peers, and then you do 821 01:01:18,720 --> 01:01:22,440 Speaker 1: need to worry about custody. Custody is a risk that 822 01:01:22,520 --> 01:01:25,720 Speaker 1: I go through in a lot of detail. UM. You 823 01:01:25,960 --> 01:01:29,200 Speaker 1: refer to kind of losing a password, and there's this 824 01:01:29,600 --> 01:01:33,280 Speaker 1: story in the New York Times where this programmer had 825 01:01:33,640 --> 01:01:38,240 Speaker 1: UM crypto in a hardware wallet, so that means that 826 01:01:38,400 --> 01:01:41,600 Speaker 1: the private keys were in the wallet, but then he 827 01:01:41,720 --> 01:01:46,480 Speaker 1: forgot the password. And the way that this hardware wallet 828 01:01:46,560 --> 01:01:51,560 Speaker 1: actually operates is that you get ten tries, and if 829 01:01:51,600 --> 01:01:56,960 Speaker 1: you fail on the tenth try, then the uh, the 830 01:01:57,000 --> 01:02:00,160 Speaker 1: hardware is physically destroyed, so you can never prepare over 831 01:02:00,600 --> 01:02:05,720 Speaker 1: what's in there. So so you basically you just tried 832 01:02:05,800 --> 01:02:09,000 Speaker 1: eight times, got two more, and over two hundred million 833 01:02:09,040 --> 01:02:12,440 Speaker 1: dollars a big coin is trapped there. So there are 834 01:02:12,520 --> 01:02:17,520 Speaker 1: other technologies today, So you can have just a regular custodian. UM, 835 01:02:17,600 --> 01:02:22,480 Speaker 1: you can have a shared KEYUH. So you split the 836 01:02:22,520 --> 01:02:26,840 Speaker 1: key into three pieces. You've got maybe one on your smartphone, 837 01:02:26,880 --> 01:02:30,240 Speaker 1: one on your desktop. UH, and then there's a custodian 838 01:02:30,280 --> 01:02:32,760 Speaker 1: that's got the other third, and you need two out 839 01:02:32,800 --> 01:02:36,680 Speaker 1: of three to reconstitute. So if you lose your mobile phone, 840 01:02:36,720 --> 01:02:39,480 Speaker 1: your computer crash is no big deal. You just put 841 01:02:39,520 --> 01:02:43,160 Speaker 1: it together. And this technology will be seamless in the future. 842 01:02:43,360 --> 01:02:45,960 Speaker 1: So right now it's a little clunky, and that's because 843 01:02:45,960 --> 01:02:48,720 Speaker 1: we're just so early in this technology, so we're less 844 01:02:48,720 --> 01:02:52,160 Speaker 1: than per cent in and there will be issues like this. 845 01:02:52,680 --> 01:02:55,600 Speaker 1: That's pretty amazing that there was another story, and I 846 01:02:55,600 --> 01:02:59,200 Speaker 1: think it was the BBC somebody throughout a drive when 847 01:02:59,240 --> 01:03:01,240 Speaker 1: they were cleaning their as didn't realize that it had 848 01:03:01,240 --> 01:03:04,920 Speaker 1: their crypto password on it. But the the bigger issue, 849 01:03:05,040 --> 01:03:07,960 Speaker 1: the longer term issue, is hey, you know, these are 850 01:03:08,000 --> 01:03:14,080 Speaker 1: really secure cryptography access keys today, but we're not that 851 01:03:14,200 --> 01:03:19,960 Speaker 1: far away from really quantum computing being more viable. What 852 01:03:20,160 --> 01:03:24,120 Speaker 1: happens in the future when we see a massive order 853 01:03:24,120 --> 01:03:28,920 Speaker 1: of magnitude improvement in computing power. What does that do 854 01:03:29,120 --> 01:03:33,120 Speaker 1: to these supposedly secure access keys. And I guess it's 855 01:03:33,160 --> 01:03:37,080 Speaker 1: as true for JP Morrigan and Wells Fargo as it 856 01:03:37,120 --> 01:03:45,720 Speaker 1: is for bitcoin and ethereum. Sure um, so let me 857 01:03:45,720 --> 01:03:49,800 Speaker 1: answer this. There's many different dimensions to your question. So 858 01:03:49,840 --> 01:03:53,760 Speaker 1: the first thing is that quantum computing isn't really a 859 01:03:53,840 --> 01:03:59,800 Speaker 1: threat to the current security in bitcoin or ethereum. So 860 01:04:00,320 --> 01:04:06,520 Speaker 1: the way that blocks are added is pretty well immune. Um, 861 01:04:06,600 --> 01:04:10,480 Speaker 1: and both bitcoin and ethereum use something that's called proof 862 01:04:10,480 --> 01:04:14,760 Speaker 1: of work, which is environmentally quite reckless. But Etheroryum has 863 01:04:14,800 --> 01:04:20,000 Speaker 1: got a strategy to migrate to a different system that 864 01:04:20,120 --> 01:04:23,360 Speaker 1: would be much more energy efficient. Uh, it would be 865 01:04:23,440 --> 01:04:28,680 Speaker 1: very energy friendly, frankly, so UM. So that's the first thing. 866 01:04:29,200 --> 01:04:34,480 Speaker 1: That The second thing is that UM it is true 867 01:04:35,520 --> 01:04:40,680 Speaker 1: that that with quantum computing in the future, it might 868 01:04:40,720 --> 01:04:45,920 Speaker 1: be possible to basically reverse engineer the private key. So 869 01:04:46,040 --> 01:04:50,880 Speaker 1: given that you've got the public address, that is possible 870 01:04:51,000 --> 01:04:54,919 Speaker 1: theoretically to go the other way. And you might think, oh, well, 871 01:04:54,960 --> 01:04:58,960 Speaker 1: that's a disaster, but it isn't. It's not really a 872 01:04:59,000 --> 01:05:07,320 Speaker 1: big deal because um already we've got quantum proof uh capabilities, 873 01:05:08,240 --> 01:05:12,840 Speaker 1: and it's really simple. When we get close. All you 874 01:05:12,880 --> 01:05:17,960 Speaker 1: need to do is to send your crypto to another 875 01:05:18,000 --> 01:05:21,600 Speaker 1: address that you own and just sign it with a 876 01:05:21,720 --> 01:05:24,880 Speaker 1: quantum proof of signature. So I'm not worried about that 877 01:05:25,280 --> 01:05:30,080 Speaker 1: at all. UM. It is kind of interesting that some 878 01:05:30,200 --> 01:05:33,800 Speaker 1: of those lost bitcoin you might be able to be 879 01:05:33,880 --> 01:05:39,160 Speaker 1: recovered with this huh really really intriguing. And I know 880 01:05:39,240 --> 01:05:41,240 Speaker 1: I only have you for a limited amount of time, 881 01:05:41,320 --> 01:05:44,480 Speaker 1: and I have to get to some of your previous 882 01:05:44,480 --> 01:05:48,440 Speaker 1: work before we get to our favorite five questions, and 883 01:05:48,480 --> 01:05:51,640 Speaker 1: I have to lean into let's talk a little bit 884 01:05:51,680 --> 01:05:55,760 Speaker 1: about yield curve inversion. What does that tell us about 885 01:05:55,840 --> 01:06:01,440 Speaker 1: the likelihood of a future recession? Well, actually was interesting. 886 01:06:01,600 --> 01:06:07,480 Speaker 1: The last time I was doing a podcast with Bloomberg 887 01:06:08,360 --> 01:06:12,680 Speaker 1: was two thousand nineteen. Uh, the beginning of July, the 888 01:06:12,720 --> 01:06:16,600 Speaker 1: eel curban inverted, and I made a recession call. For 889 01:06:18,160 --> 01:06:21,640 Speaker 1: little did I know that COVID what does strike and 890 01:06:21,640 --> 01:06:25,880 Speaker 1: and cause such an unusual recession? But this is my 891 01:06:26,000 --> 01:06:30,680 Speaker 1: dissertation work um at the University of Chicago that I 892 01:06:30,760 --> 01:06:35,880 Speaker 1: showed that eel curban versions proceed a recessions. At the 893 01:06:35,920 --> 01:06:41,040 Speaker 1: time when I'm defending my dissertation, the record was four 894 01:06:41,120 --> 01:06:44,880 Speaker 1: out of four with no fall signals that, yeah, it 895 01:06:44,960 --> 01:06:48,040 Speaker 1: could have been lucky. My committee was kind of skeptical, 896 01:06:48,240 --> 01:06:52,880 Speaker 1: but the theory behind the measure was sound. I passed. 897 01:06:53,440 --> 01:06:58,320 Speaker 1: And usually what happens after you publish an idea is 898 01:06:58,480 --> 01:07:02,840 Speaker 1: that if you're lucky, it becomes a weaker effect on 899 01:07:02,960 --> 01:07:06,720 Speaker 1: the sample and if you're not very lucky, it completely 900 01:07:06,760 --> 01:07:12,160 Speaker 1: goes away. But from my particular situation, the youth curban 901 01:07:12,280 --> 01:07:19,160 Speaker 1: versions predicted accurately the next four recessions, including the Global 902 01:07:19,160 --> 01:07:24,120 Speaker 1: financial crisis recession for a game advanced warning of a year. 903 01:07:24,560 --> 01:07:27,600 Speaker 1: So so it's eight for eight right now. I haven't 904 01:07:27,600 --> 01:07:30,840 Speaker 1: really done research in this area in quite a while, 905 01:07:31,360 --> 01:07:36,960 Speaker 1: but it's held up, and it's it's something completely unexpected 906 01:07:37,320 --> 01:07:40,440 Speaker 1: that I'd still be getting questions about my dissertation so 907 01:07:40,480 --> 01:07:44,120 Speaker 1: many years after I published it. Let's talk about another 908 01:07:44,240 --> 01:07:48,760 Speaker 1: area of research that you've you've worked in. Some people 909 01:07:48,800 --> 01:07:53,840 Speaker 1: have had outstanding investment results and they're lucky, and other 910 01:07:53,920 --> 01:07:59,200 Speaker 1: people have had an outstanding investment results because they're skillful. 911 01:08:00,000 --> 01:08:02,680 Speaker 1: How can we tell the difference when all we see 912 01:08:02,800 --> 01:08:07,240 Speaker 1: is effectively, Hey, that turned out to be a great investment. Yeah, 913 01:08:07,280 --> 01:08:11,640 Speaker 1: So this is my recent research stream is focused on 914 01:08:11,760 --> 01:08:17,000 Speaker 1: luck versus skill. And it's really hard to explain, but 915 01:08:17,080 --> 01:08:21,160 Speaker 1: I think people really want to believe in that upside. 916 01:08:21,160 --> 01:08:25,000 Speaker 1: They look at the back test and yeah, this looks 917 01:08:25,040 --> 01:08:27,760 Speaker 1: really good, and and I think that this is going 918 01:08:27,800 --> 01:08:31,639 Speaker 1: to repeat, and it often doesn't because the back tests 919 01:08:31,640 --> 01:08:36,720 Speaker 1: are are overfit. So in my recent research stream, I 920 01:08:36,840 --> 01:08:41,519 Speaker 1: proposed a number of different ideas UH to kind of 921 01:08:41,560 --> 01:08:48,080 Speaker 1: adjust back tests and and a protocol UH to really 922 01:08:48,160 --> 01:08:54,040 Speaker 1: understand the past performance. It comes down to the culture 923 01:08:54,479 --> 01:08:57,880 Speaker 1: at the asset management firm. Do they just want to 924 01:08:57,920 --> 01:09:00,439 Speaker 1: gather money in the short term and collect to see 925 01:09:01,320 --> 01:09:05,960 Speaker 1: uh it. It also comes down to investors asking the 926 01:09:06,040 --> 01:09:11,559 Speaker 1: right question. So so, for example, the presentation has been 927 01:09:11,640 --> 01:09:14,160 Speaker 1: given on a new product, and here's the back test, 928 01:09:14,760 --> 01:09:19,839 Speaker 1: and and what I do sometimes very uh strategic question. 929 01:09:20,960 --> 01:09:25,320 Speaker 1: I said, oh, this is pretty super interesting, very impressive work. 930 01:09:25,960 --> 01:09:32,240 Speaker 1: Uh oh did did you try variable X? And then 931 01:09:32,400 --> 01:09:35,280 Speaker 1: the response might be, oh, yeah, we tried that, but 932 01:09:35,360 --> 01:09:39,280 Speaker 1: it didn't work. So as soon as I hear that answer, 933 01:09:40,000 --> 01:09:44,479 Speaker 1: I know that there's been extensive data mining, and it 934 01:09:44,640 --> 01:09:48,599 Speaker 1: is like it's like seeing a cockroach in your house, 935 01:09:49,200 --> 01:09:52,200 Speaker 1: you know, when there's you see one that there's a 936 01:09:52,240 --> 01:09:58,679 Speaker 1: dozen behind the wall, and and that sort of small 937 01:09:58,840 --> 01:10:03,200 Speaker 1: indication is that this product in the back test has 938 01:10:03,240 --> 01:10:06,320 Speaker 1: been overfit. When it goes to live trading, you're going 939 01:10:06,360 --> 01:10:10,200 Speaker 1: to be disappointed. So so what do you actually want 940 01:10:10,680 --> 01:10:13,720 Speaker 1: is in the back test not to choose the best one. 941 01:10:13,920 --> 01:10:17,120 Speaker 1: The best one is the one that's most likely to 942 01:10:17,439 --> 01:10:21,679 Speaker 1: disappoint in in live treating. So you need to do 943 01:10:21,720 --> 01:10:25,720 Speaker 1: this in a way that minimizes, uh, the overfitting in 944 01:10:25,800 --> 01:10:28,519 Speaker 1: the back test. And what we what we want is 945 01:10:28,600 --> 01:10:33,280 Speaker 1: to invest in a product that will repeat it's past performance. 946 01:10:33,400 --> 01:10:37,200 Speaker 1: We don't want to invest in a product that you know, 947 01:10:37,240 --> 01:10:40,519 Speaker 1: the advertised sharp ratio is two and and we get 948 01:10:40,560 --> 01:10:44,439 Speaker 1: point to in live trading. So is this why you've 949 01:10:44,479 --> 01:10:48,439 Speaker 1: said half of all the financial research out there is 950 01:10:48,560 --> 01:10:54,639 Speaker 1: likely false a combination of overfitting and selection bias and 951 01:10:54,680 --> 01:10:58,519 Speaker 1: all the other fun reasons why back tests are can 952 01:10:58,560 --> 01:11:04,280 Speaker 1: be somewhat misleading. Yeah, and I said, uh, the half 953 01:11:04,320 --> 01:11:08,760 Speaker 1: of the empirical research and finance that has published in 954 01:11:08,800 --> 01:11:13,639 Speaker 1: academic journals. The key is to understand the incentives. So 955 01:11:14,040 --> 01:11:18,439 Speaker 1: the journal editors compete in terms of um what's known 956 01:11:18,439 --> 01:11:21,639 Speaker 1: as an impact factor, the number of times that their 957 01:11:21,840 --> 01:11:27,400 Speaker 1: articles and their journals are are cited by other journals. Uh. 958 01:11:27,439 --> 01:11:31,160 Speaker 1: And they know that if they publish a result that 959 01:11:32,040 --> 01:11:35,440 Speaker 1: is a non result. So you try a trading strategy, 960 01:11:35,479 --> 01:11:38,200 Speaker 1: for example, and it doesn't work. If they publish that, 961 01:11:38,240 --> 01:11:42,479 Speaker 1: nobody's going to cite it. So so the authors note 962 01:11:42,600 --> 01:11:47,240 Speaker 1: that they need to deliver something that's really interesting and 963 01:11:47,600 --> 01:11:50,240 Speaker 1: is what we call a positive result. So this trading 964 01:11:50,280 --> 01:11:55,920 Speaker 1: strategy delivers a very high um sharp ratio. So they 965 01:11:55,960 --> 01:12:02,360 Speaker 1: know that, and the data mining begins because these academics 966 01:12:02,800 --> 01:12:06,280 Speaker 1: they need to publish in the top journals to get promoted, 967 01:12:07,160 --> 01:12:10,320 Speaker 1: so so the data money begins. And then you get 968 01:12:10,320 --> 01:12:15,080 Speaker 1: a select sort of paper flow that's going in with 969 01:12:15,400 --> 01:12:20,280 Speaker 1: data mind results, and and you put this together, and 970 01:12:21,040 --> 01:12:27,080 Speaker 1: you combine that with a mistake that that many people 971 01:12:27,080 --> 01:12:30,800 Speaker 1: have made in kind of the execution of the statistics. 972 01:12:30,840 --> 01:12:34,160 Speaker 1: It might be that you try a hundred things and 973 01:12:34,360 --> 01:12:38,880 Speaker 1: there's one that works, uh, and and then you even 974 01:12:38,920 --> 01:12:43,639 Speaker 1: admit that you tried one hundred things, one hundred different 975 01:12:43,720 --> 01:12:47,040 Speaker 1: versions of the trading strategy, but this one works really well. 976 01:12:47,439 --> 01:12:52,120 Speaker 1: Well you expect that out of a hundred, five would 977 01:12:52,120 --> 01:12:55,920 Speaker 1: work just by random chance. So if you're presenting one, 978 01:12:56,360 --> 01:13:00,880 Speaker 1: it's probably uh, not significant, will not hold up in 979 01:13:00,960 --> 01:13:07,439 Speaker 1: live trading. So the incentives defined that really interesting result 980 01:13:08,160 --> 01:13:10,719 Speaker 1: that you know will be cite it and the journal 981 01:13:10,840 --> 01:13:14,400 Speaker 1: editor will like it. And you combine that with a 982 01:13:14,520 --> 01:13:19,080 Speaker 1: mistake of not adjusting for all of the possible things 983 01:13:19,080 --> 01:13:23,000 Speaker 1: that you tried. Then you get to this fifty percent number. 984 01:13:23,920 --> 01:13:28,120 Speaker 1: It is also important to realize that, in my opinion, 985 01:13:28,240 --> 01:13:31,720 Speaker 1: the problem is is less severe in the practice of management, 986 01:13:32,479 --> 01:13:35,680 Speaker 1: because in the practice of management, if you really overfit, 987 01:13:36,760 --> 01:13:40,800 Speaker 1: and if you get people to invest, and if your 988 01:13:41,040 --> 01:13:44,960 Speaker 1: arrangements are not just a fixed fee but an incentive 989 01:13:44,960 --> 01:13:50,519 Speaker 1: fee or performance fee um, then if the product doesn't perform, 990 01:13:50,640 --> 01:13:54,200 Speaker 1: you're not going to get any performance fee and you're 991 01:13:54,200 --> 01:13:59,280 Speaker 1: gonna lose a reputation. So in the practice of finance, 992 01:14:00,040 --> 01:14:05,559 Speaker 1: there's no equivalent to academic tenure, so you don't perform 993 01:14:05,640 --> 01:14:08,880 Speaker 1: your out. So I think the incentives are better aligned 994 01:14:09,200 --> 01:14:13,160 Speaker 1: in the practice of asset management and that sort of research, 995 01:14:13,600 --> 01:14:16,760 Speaker 1: much of which we don't see, so you don't publish 996 01:14:17,360 --> 01:14:23,280 Speaker 1: the mechanics of a really good training strategy. Renaissance Technologies 997 01:14:23,320 --> 01:14:25,920 Speaker 1: hasn't released any white papers as to how they're doing 998 01:14:27,400 --> 01:14:31,400 Speaker 1: a fees year after year. And and I want to add, 999 01:14:31,479 --> 01:14:37,240 Speaker 1: this sort of research issue is not just in academic finance, 1000 01:14:37,320 --> 01:14:41,200 Speaker 1: but it seems to be across you know, many many fields. 1001 01:14:41,479 --> 01:14:46,960 Speaker 1: Reproducibility of of results are very very challenging. So it's 1002 01:14:47,000 --> 01:14:50,959 Speaker 1: more than just form fitting. It's even the basic concept 1003 01:14:51,000 --> 01:14:55,160 Speaker 1: of research seems to be um somewhat problematic in in 1004 01:14:55,720 --> 01:15:00,559 Speaker 1: both academia and in the real world. So you're correct 1005 01:15:00,880 --> 01:15:05,080 Speaker 1: that other fields have actually uh come to this realization 1006 01:15:05,120 --> 01:15:09,559 Speaker 1: well before the field of finance medicine, for example, Uh, 1007 01:15:09,640 --> 01:15:13,960 Speaker 1: they fully realized that half of their research findings are false. 1008 01:15:14,240 --> 01:15:17,839 Speaker 1: And you could argue that that's way more important than finance. 1009 01:15:18,360 --> 01:15:22,080 Speaker 1: So and finance we're talking about like some alpha, and 1010 01:15:22,280 --> 01:15:27,920 Speaker 1: in medicine we're talking about life or death. So again 1011 01:15:28,000 --> 01:15:31,000 Speaker 1: we need to have a proper perspective on this. I 1012 01:15:31,040 --> 01:15:33,080 Speaker 1: know I only have you for a little while longer, 1013 01:15:33,200 --> 01:15:36,599 Speaker 1: so let's jump to our favorite questions that we ask 1014 01:15:37,200 --> 01:15:40,160 Speaker 1: all of our guests, starting with what have you been 1015 01:15:40,200 --> 01:15:44,720 Speaker 1: doing to stay entertained during the pandemic? Tell us what 1016 01:15:44,880 --> 01:15:48,719 Speaker 1: you're streaming, either Netflix or Amazon or anything you're listening 1017 01:15:48,760 --> 01:15:51,880 Speaker 1: to and enjoying. I'll tell you what I'm streaming on 1018 01:15:51,920 --> 01:15:59,040 Speaker 1: Netflix is a finish UM drama show called border townmmend 1019 01:15:59,080 --> 01:16:02,599 Speaker 1: it very interesting thing. It's it's dubbed, but it's it's 1020 01:16:02,640 --> 01:16:06,240 Speaker 1: well done. Um. But in terms of podcasts and things 1021 01:16:06,280 --> 01:16:11,080 Speaker 1: like that, Uh, really, what I'm I'm doing, I'm focusing 1022 01:16:11,120 --> 01:16:15,200 Speaker 1: on one particular podcast which is not for entertainment necessarily, 1023 01:16:15,240 --> 01:16:18,479 Speaker 1: but more in the DEEPI space, and it's called uh 1024 01:16:18,880 --> 01:16:23,559 Speaker 1: fine maddics, that's FI and E matics, and it's really 1025 01:16:24,000 --> 01:16:29,160 Speaker 1: uh nicely done where the presentations are like seventeen to 1026 01:16:29,200 --> 01:16:34,280 Speaker 1: twenty minutes long, animated, but really trying to understand some 1027 01:16:34,360 --> 01:16:38,960 Speaker 1: of these complicated concepts in uh in the crypto space. 1028 01:16:40,040 --> 01:16:43,160 Speaker 1: Really interesting. Tell us about some of your early mentors 1029 01:16:43,200 --> 01:16:48,120 Speaker 1: who who helped to shape your career. Well, I've just 1030 01:16:48,240 --> 01:16:53,120 Speaker 1: been so lucky, Uh it just my timing. I think 1031 01:16:53,160 --> 01:16:56,519 Speaker 1: I didn't realize that at the time was just so 1032 01:16:56,720 --> 01:17:02,320 Speaker 1: good um and and and UM just purely do to 1033 01:17:02,439 --> 01:17:07,439 Speaker 1: luck that I've had the opportunity, uh to interact with 1034 01:17:07,560 --> 01:17:12,439 Speaker 1: the greats of finance. So my chair um is Eugene 1035 01:17:12,520 --> 01:17:17,559 Speaker 1: Vama uh on my committee Martin Miller and Lars Hanson. 1036 01:17:18,600 --> 01:17:23,400 Speaker 1: But I also had, uh in half the opportunity to 1037 01:17:23,520 --> 01:17:29,479 Speaker 1: interact with Bill Sharp, my Marin shoals that role, Steve Ross, 1038 01:17:30,000 --> 01:17:34,360 Speaker 1: Bob Martin um and and even Fisher Black. And let 1039 01:17:34,360 --> 01:17:38,040 Speaker 1: me just briefly tell you my introductions of Fisher Black. 1040 01:17:39,000 --> 01:17:43,400 Speaker 1: I was an assistant professor, junior professor, and I was 1041 01:17:43,520 --> 01:17:46,800 Speaker 1: working late at the office while actually wasn't late for me, 1042 01:17:47,120 --> 01:17:50,519 Speaker 1: was bout nine pm and I get a phone call 1043 01:17:51,520 --> 01:17:54,280 Speaker 1: and Duke had one of the early call I d 1044 01:17:55,120 --> 01:17:57,880 Speaker 1: and I could see the calls coming from Goldman Sachs 1045 01:17:58,560 --> 01:18:03,320 Speaker 1: and I think it's a buddy of mine from Chicago 1046 01:18:03,680 --> 01:18:06,559 Speaker 1: that's working late, just like me. I pick up the phone, 1047 01:18:06,560 --> 01:18:10,639 Speaker 1: just assuming it's him, and and make some disparaging remarks 1048 01:18:11,360 --> 01:18:15,439 Speaker 1: and then there's a long silence and the person says, 1049 01:18:15,479 --> 01:18:19,080 Speaker 1: is this Campbell Harvey? And I realized, oh, somebody else? 1050 01:18:19,640 --> 01:18:22,800 Speaker 1: And then he said it's Fish or Black. And for 1051 01:18:22,840 --> 01:18:26,120 Speaker 1: a junior person to get a call from Black, who 1052 01:18:26,160 --> 01:18:29,200 Speaker 1: everybody knows it's going to win the Nobel Problems, it 1053 01:18:29,320 --> 01:18:33,559 Speaker 1: was shocking. So so he said, I'm reading your paper 1054 01:18:33,680 --> 01:18:39,240 Speaker 1: here and UM and your table too. I don't believe. 1055 01:18:40,000 --> 01:18:41,479 Speaker 1: I said, well, what do you mean you don't believe? 1056 01:18:41,680 --> 01:18:45,240 Speaker 1: So well, you've you've engaged in data mining to get 1057 01:18:45,439 --> 01:18:50,759 Speaker 1: this particular result and these results are not credible. And 1058 01:18:51,120 --> 01:18:54,599 Speaker 1: I said, no, there's no data mining. This is all 1059 01:18:54,640 --> 01:18:58,400 Speaker 1: I did, is exactly what I said. There was no 1060 01:18:58,920 --> 01:19:02,160 Speaker 1: uh going variable by variable. It was a predictive regression 1061 01:19:02,160 --> 01:19:07,080 Speaker 1: for the SMP UM that I just basically this is 1062 01:19:07,120 --> 01:19:09,360 Speaker 1: what people have done. And then I just I just 1063 01:19:09,479 --> 01:19:13,479 Speaker 1: presented that and he said, no, uh, it's it's not credible, 1064 01:19:13,840 --> 01:19:18,760 Speaker 1: not credible, and um so it was interesting. We had 1065 01:19:18,760 --> 01:19:23,040 Speaker 1: this conversation and many other conversations. Uh and and we 1066 01:19:23,160 --> 01:19:27,880 Speaker 1: developed a good relationship. Uh and and how did you 1067 01:19:27,920 --> 01:19:32,000 Speaker 1: convince him it was a legitimate research paper? So I couldn't. 1068 01:19:32,320 --> 01:19:38,479 Speaker 1: So it's just totally convinced. So uh many years later, 1069 01:19:39,640 --> 01:19:43,639 Speaker 1: I decided to basically do the out of sample test 1070 01:19:45,439 --> 01:19:50,920 Speaker 1: and uh so I replicated my Richard results and and 1071 01:19:51,000 --> 01:19:55,000 Speaker 1: I found using the I collected the data again and 1072 01:19:55,000 --> 01:19:57,760 Speaker 1: I found I got almost exactly the result in that 1073 01:19:57,800 --> 01:20:02,679 Speaker 1: table too. But then I did the other sample twenty 1074 01:20:02,720 --> 01:20:07,680 Speaker 1: five years apot a sample and the other sample there 1075 01:20:07,800 --> 01:20:14,360 Speaker 1: was zero predictability. Really, so Fisher Black was right. And 1076 01:20:14,920 --> 01:20:18,160 Speaker 1: the lesson that I've learned, and the lesson is I 1077 01:20:18,240 --> 01:20:22,080 Speaker 1: didn't do any data mining, so it was clear that 1078 01:20:22,120 --> 01:20:24,400 Speaker 1: I was telling the truth. I didn't. Even a legit 1079 01:20:24,479 --> 01:20:28,080 Speaker 1: paper can have structural problems in it. But what I 1080 01:20:28,120 --> 01:20:33,560 Speaker 1: did was I relied upon the results of other academics, 1081 01:20:34,600 --> 01:20:37,719 Speaker 1: so so basically they might have been doing the data mining, 1082 01:20:38,120 --> 01:20:41,000 Speaker 1: and then I just took their paper and then implemented 1083 01:20:41,040 --> 01:20:46,320 Speaker 1: it and and and basically it's it's essential delegation, right 1084 01:20:46,360 --> 01:20:50,599 Speaker 1: garage right, Yeah, so this is so he was he 1085 01:20:50,760 --> 01:20:56,200 Speaker 1: was correct and yeah, and obviously that experience was really 1086 01:20:56,240 --> 01:21:01,200 Speaker 1: important for me and shaping my research agenda. My presidential 1087 01:21:01,240 --> 01:21:04,559 Speaker 1: address to the American Finance Association is exactly on this topic. 1088 01:21:04,920 --> 01:21:11,520 Speaker 1: So he was extremely influential in terms of my development 1089 01:21:11,680 --> 01:21:16,559 Speaker 1: and the idea generation. Meanwhile, that's some murderous row of 1090 01:21:16,680 --> 01:21:19,200 Speaker 1: mentors you had over your career. It's really quite an 1091 01:21:19,240 --> 01:21:24,400 Speaker 1: amazing list. Let's jump to everybody's favorite question. Tell us 1092 01:21:24,439 --> 01:21:26,920 Speaker 1: about some of your favorite books. What are you reading 1093 01:21:26,960 --> 01:21:29,280 Speaker 1: now and what are some of your favorite books to 1094 01:21:29,320 --> 01:21:34,760 Speaker 1: recommend to students? Well, and probably won't be that interesting. Um. 1095 01:21:36,360 --> 01:21:40,040 Speaker 1: I I began thinking I was going to be an 1096 01:21:40,040 --> 01:21:45,320 Speaker 1: English major, so so I do read um and my 1097 01:21:45,479 --> 01:21:50,240 Speaker 1: tastes or maybe a little unusual. So I'm a James 1098 01:21:50,360 --> 01:21:54,439 Speaker 1: Joyce nut um in terms of reading everything that he's done, 1099 01:21:55,439 --> 01:22:00,439 Speaker 1: which is incredibly challenging to do, but very uh boarding 1100 01:22:00,800 --> 01:22:03,479 Speaker 1: for me. In terms of what I'm reading right now, 1101 01:22:04,760 --> 01:22:09,120 Speaker 1: I'm reading Danny Kahneman's book on Noise. I do work 1102 01:22:09,120 --> 01:22:12,760 Speaker 1: in behavioral finance also, and I've been struggling with some 1103 01:22:12,800 --> 01:22:17,240 Speaker 1: of the issues that are prominent in his book in 1104 01:22:17,360 --> 01:22:21,040 Speaker 1: terms of some of my recent research. So that, uh, 1105 01:22:21,479 --> 01:22:24,679 Speaker 1: that's something that interests me a lot. UM. And then 1106 01:22:24,840 --> 01:22:30,680 Speaker 1: I'm doing something really geeky UM that I'm trying to 1107 01:22:30,720 --> 01:22:34,479 Speaker 1: make my way through, um the third edition of The 1108 01:22:34,479 --> 01:22:37,479 Speaker 1: Golden Bow, and maybe some of your readers might our 1109 01:22:37,520 --> 01:22:41,200 Speaker 1: listeners will will pick up and take a look at 1110 01:22:41,240 --> 01:22:45,559 Speaker 1: what that is. It's all online, it's very long, UM, 1111 01:22:45,600 --> 01:22:49,479 Speaker 1: but it's the sort of thing that interests me, and 1112 01:22:49,520 --> 01:22:54,880 Speaker 1: it's essentially how people um come to believe in something. 1113 01:22:55,400 --> 01:23:00,280 Speaker 1: So expectations are something that I've thought about for a 1114 01:23:00,400 --> 01:23:04,879 Speaker 1: very long time. It's very important for our research. Uh. 1115 01:23:05,080 --> 01:23:09,360 Speaker 1: One of my research streams tries to measure those expectations. 1116 01:23:09,439 --> 01:23:14,920 Speaker 1: But this is much deeper analysis of how beliefs are 1117 01:23:14,960 --> 01:23:19,120 Speaker 1: actually form mythology and things like that. More than anticipating 1118 01:23:19,160 --> 01:23:23,679 Speaker 1: the pleasure of an event or purchase. You're talking about 1119 01:23:23,800 --> 01:23:33,160 Speaker 1: how we start to conceptualize entire frameworks or mythologies exactly, 1120 01:23:33,520 --> 01:23:36,960 Speaker 1: so very important, just the way that is presented, and 1121 01:23:36,960 --> 01:23:41,040 Speaker 1: and some thing's happened that might be random, but others 1122 01:23:41,080 --> 01:23:43,559 Speaker 1: are not. So before I go to the next question, 1123 01:23:43,600 --> 01:23:46,839 Speaker 1: I have to ask, how does the world of stock 1124 01:23:46,960 --> 01:23:50,840 Speaker 1: memes fit into this that that seems to be that 1125 01:23:51,080 --> 01:23:55,519 Speaker 1: sort of investment narrative seems to be dominant over the 1126 01:23:55,560 --> 01:23:58,320 Speaker 1: past five years. Do you do you look at those? 1127 01:23:58,600 --> 01:24:03,280 Speaker 1: What do you think of those? Sure? So this is 1128 01:24:03,479 --> 01:24:07,799 Speaker 1: extremely interesting to me because we've been on a trend 1129 01:24:08,640 --> 01:24:13,920 Speaker 1: where the retail investor has become a smaller and smaller 1130 01:24:14,120 --> 01:24:21,799 Speaker 1: part of the total amount of investing for many years. However, 1131 01:24:22,120 --> 01:24:27,360 Speaker 1: with the rise of certain fintech, it's been a lot 1132 01:24:27,479 --> 01:24:31,200 Speaker 1: easier for the retail investor to actually get into the 1133 01:24:31,240 --> 01:24:35,599 Speaker 1: market with apps like robin Hood for example. So we've 1134 01:24:35,640 --> 01:24:39,599 Speaker 1: seen a big turnaround. So the proportion of the retail 1135 01:24:39,640 --> 01:24:43,439 Speaker 1: investor of the total market maybe was ten, is up 1136 01:24:43,439 --> 01:24:47,000 Speaker 1: to fifteen, maybe it will be twenty over the next year. 1137 01:24:47,840 --> 01:24:52,759 Speaker 1: And and what happened there is that the retail investor 1138 01:24:53,479 --> 01:24:59,400 Speaker 1: doesn't have access to the sort of information that an 1139 01:24:59,400 --> 01:25:03,360 Speaker 1: institution well investor has got access to. They have the data, 1140 01:25:04,200 --> 01:25:07,280 Speaker 1: they don't have the computing capability, they're not working on 1141 01:25:07,320 --> 01:25:13,720 Speaker 1: this full time, but they've got the crowd. So you 1142 01:25:13,800 --> 01:25:17,280 Speaker 1: might have a dedicated team and a hedge fund working 1143 01:25:17,280 --> 01:25:20,760 Speaker 1: out a problem, but the retail investor, even though part 1144 01:25:20,800 --> 01:25:24,519 Speaker 1: time there might be you know, a hundred thousand people 1145 01:25:24,680 --> 01:25:30,600 Speaker 1: that are contributing so effectively, what we're seeing is the 1146 01:25:30,680 --> 01:25:35,080 Speaker 1: possibility of kind of a decentralized hedge fund, if you 1147 01:25:35,120 --> 01:25:39,560 Speaker 1: think about it that way. So I think it's very interesting, 1148 01:25:40,000 --> 01:25:44,479 Speaker 1: like how this space evolves. It is, uh, it has 1149 01:25:44,520 --> 01:25:50,800 Speaker 1: some downsides where a bandwagon has jumped on and it 1150 01:25:50,920 --> 01:25:55,040 Speaker 1: basically drives a stock well beyond its fundamentals. But usually 1151 01:25:55,640 --> 01:25:58,920 Speaker 1: you would have shorting going on and to bring the 1152 01:25:59,000 --> 01:26:03,240 Speaker 1: stock back down to its fundamental level. But some of 1153 01:26:03,240 --> 01:26:06,920 Speaker 1: these hedge funds, the risk of shorting has gone up dramatically. 1154 01:26:07,240 --> 01:26:11,040 Speaker 1: They've seen what's happened. So when people step out of 1155 01:26:11,080 --> 01:26:15,040 Speaker 1: the shorting, UH, that means that you've got this asymmetry 1156 01:26:15,120 --> 01:26:19,360 Speaker 1: and it's just more likely that you've got misvaluation. So 1157 01:26:19,520 --> 01:26:23,599 Speaker 1: in my opinion, given what's happened, I think that the 1158 01:26:23,640 --> 01:26:27,639 Speaker 1: market will become less efficient in the short term short 1159 01:26:27,720 --> 01:26:33,160 Speaker 1: term and UH that provides some opportunities, of course, but 1160 01:26:33,479 --> 01:26:40,080 Speaker 1: eventually I think that the information gathering will become cheaper, uh, 1161 01:26:40,200 --> 01:26:42,559 Speaker 1: more efficient, will kind of return to where we were. 1162 01:26:42,880 --> 01:26:46,760 Speaker 1: But in the short term, UH, we get situations like 1163 01:26:46,840 --> 01:26:51,720 Speaker 1: game stop and MC quite fascinating we're down to our 1164 01:26:51,760 --> 01:26:56,840 Speaker 1: favorite last two questions. What sort of advice would you 1165 01:26:56,880 --> 01:26:59,680 Speaker 1: give to a recent college grad who was interested in 1166 01:26:59,680 --> 01:27:03,560 Speaker 1: the crew year in either UM investment management or finance 1167 01:27:03,840 --> 01:27:10,120 Speaker 1: or crypto and defy. So the key thing to realize, 1168 01:27:10,439 --> 01:27:15,160 Speaker 1: and I give this advice to my students. Uh, the 1169 01:27:15,240 --> 01:27:19,479 Speaker 1: key thing to realize, in my opinion, is that finance 1170 01:27:19,520 --> 01:27:23,040 Speaker 1: will not look like it has in the past in 1171 01:27:23,080 --> 01:27:27,120 Speaker 1: the future. So we are in the midst of a 1172 01:27:27,200 --> 01:27:32,719 Speaker 1: structural change. So it's really important to have a vision 1173 01:27:33,160 --> 01:27:36,800 Speaker 1: of the future, and just a naive extrapolation from the 1174 01:27:36,840 --> 01:27:42,240 Speaker 1: past is not good enough. So I many of my 1175 01:27:42,280 --> 01:27:51,479 Speaker 1: students take the job at the traditional bank or investment bank, 1176 01:27:52,080 --> 01:27:57,400 Speaker 1: and my advice to them is, after graduating, that doesn't 1177 01:27:57,439 --> 01:28:01,519 Speaker 1: mean that you're finished your learning. You need to know 1178 01:28:01,840 --> 01:28:05,559 Speaker 1: what you don't know. And my course and my book 1179 01:28:06,080 --> 01:28:09,000 Speaker 1: is maybe a good example. After you read that book, 1180 01:28:09,479 --> 01:28:12,479 Speaker 1: you will know what you don't know, and you will 1181 01:28:12,479 --> 01:28:15,679 Speaker 1: know that there's not a lot more learning that has 1182 01:28:15,720 --> 01:28:20,080 Speaker 1: to happen. So those students that go into the traditional sector, 1183 01:28:20,120 --> 01:28:23,479 Speaker 1: I said, that's fine, you're gonna learn something. You need 1184 01:28:23,520 --> 01:28:27,400 Speaker 1: to continue. Uh, the quest of knowledge in this difficult 1185 01:28:27,400 --> 01:28:31,880 Speaker 1: space and the first day that you arrive, you need 1186 01:28:31,920 --> 01:28:36,000 Speaker 1: to be thinking about the next stop, and hopefully that 1187 01:28:36,080 --> 01:28:40,800 Speaker 1: stop is somewhere in the DeFi space. Pay down your 1188 01:28:40,800 --> 01:28:44,200 Speaker 1: student loan, and then take some risk to go to 1189 01:28:44,240 --> 01:28:47,599 Speaker 1: a venture. You're gonna learn a lot. The venture probably fail, 1190 01:28:47,760 --> 01:28:50,599 Speaker 1: but it doesn't matter. You're going to learn a lot 1191 01:28:50,840 --> 01:28:54,559 Speaker 1: and you'll be able to go to another venture very quickly. 1192 01:28:55,360 --> 01:29:00,000 Speaker 1: So it's not as risky as you think. But again, 1193 01:29:00,000 --> 01:29:03,080 Speaker 1: and it's way better to be at the vanguard of 1194 01:29:03,160 --> 01:29:09,040 Speaker 1: disruption rather than at an institution that is doing everything 1195 01:29:09,080 --> 01:29:13,639 Speaker 1: possible to hang on to extend that one way, fully 1196 01:29:13,760 --> 01:29:19,920 Speaker 1: knowing that they will be eventually replaced by algorithms. H 1197 01:29:20,400 --> 01:29:23,400 Speaker 1: really interesting in our final question, what do you know 1198 01:29:23,479 --> 01:29:27,080 Speaker 1: about the world of finance today that you wish you 1199 01:29:27,160 --> 01:29:30,200 Speaker 1: knew thirty years ago or so when you were first 1200 01:29:30,240 --> 01:29:35,600 Speaker 1: starting out. So I guess what I didn't fully appreciate. 1201 01:29:35,720 --> 01:29:39,160 Speaker 1: And it's kind of embarrassing because when you do economics 1202 01:29:39,200 --> 01:29:43,120 Speaker 1: at the University of Chicago, it's it's all about economic 1203 01:29:43,160 --> 01:29:48,880 Speaker 1: incentives and and how that shape's behavior. And we've talked 1204 01:29:48,880 --> 01:29:52,200 Speaker 1: about this a little bit that I've really realized that 1205 01:29:52,520 --> 01:29:59,320 Speaker 1: the research in my field is is shaped by Economic 1206 01:29:59,360 --> 01:30:05,040 Speaker 1: Guy and say atoms. So at most schools in the world, 1207 01:30:05,680 --> 01:30:09,679 Speaker 1: well maybe ninety percent or more schools, just a single 1208 01:30:10,040 --> 01:30:15,559 Speaker 1: publication in a very top journal is a job for life. 1209 01:30:16,640 --> 01:30:19,080 Speaker 1: You've done it right. So the Journal of Finance publishes 1210 01:30:19,320 --> 01:30:23,120 Speaker 1: seventy seven zero articles a year, so it's very difficult 1211 01:30:23,520 --> 01:30:27,760 Speaker 1: to get in to a journal like that. So to 1212 01:30:27,960 --> 01:30:33,519 Speaker 1: get promoted, UM, you've got to hit this top journal. 1213 01:30:33,920 --> 01:30:40,479 Speaker 1: And that causes UM data mining, UM and and and 1214 01:30:40,640 --> 01:30:44,720 Speaker 1: some of it might even be unconscious where you're you're 1215 01:30:44,760 --> 01:30:49,440 Speaker 1: trying to to look at various different techniques of estimation 1216 01:30:50,160 --> 01:30:52,679 Speaker 1: and you just happened to pick the one that works 1217 01:30:52,760 --> 01:30:57,840 Speaker 1: the best. So these incentives are really think of influenced 1218 01:30:58,760 --> 01:31:03,879 Speaker 1: research and has led to a problem with our research, 1219 01:31:04,360 --> 01:31:08,879 Speaker 1: and that when you take that research into live trading, 1220 01:31:09,560 --> 01:31:13,599 Speaker 1: it doesn't do as well as what was published. And 1221 01:31:13,680 --> 01:31:17,640 Speaker 1: I think it's purely the result of these incentives. I 1222 01:31:17,880 --> 01:31:23,200 Speaker 1: was naive UM graduating and thought that well, this is 1223 01:31:23,240 --> 01:31:27,240 Speaker 1: just about the pursuit of truth. Well that's part of it, 1224 01:31:27,880 --> 01:31:31,680 Speaker 1: but for many people it's about the pursuit of a 1225 01:31:31,800 --> 01:31:36,599 Speaker 1: job for life. That's quite quite fascinating. Professor cam Harvey, 1226 01:31:36,640 --> 01:31:40,960 Speaker 1: thank you for being so generous with your time. You 1227 01:31:40,960 --> 01:31:43,679 Speaker 1: can pick up his new book, Defy in the Future 1228 01:31:43,680 --> 01:31:49,240 Speaker 1: of Finance wherever you get your usual book purchases. If 1229 01:31:49,280 --> 01:31:51,439 Speaker 1: you enjoy this conversation, we'll be sure to check you 1230 01:31:51,479 --> 01:31:56,240 Speaker 1: out any of our previous three and seventy six podcasts 1231 01:31:56,320 --> 01:31:59,439 Speaker 1: we've done over the past seven years. You can find 1232 01:31:59,479 --> 01:32:05,120 Speaker 1: that iTunes, Spotify, wherever finer podcasts are sold. We love 1233 01:32:05,160 --> 01:32:08,760 Speaker 1: your comments, feedback and suggestions right to us at m 1234 01:32:08,800 --> 01:32:12,000 Speaker 1: IB podcast at Bloomberg dot net. Sign up for my 1235 01:32:12,080 --> 01:32:14,839 Speaker 1: daily reads at Riholts dot com. Check out my weekly 1236 01:32:14,920 --> 01:32:18,880 Speaker 1: column at Bloomberg dot com slash Opinion. Follow me on 1237 01:32:18,920 --> 01:32:22,000 Speaker 1: Twitter at Riolts. I would be remiss if I did 1238 01:32:22,000 --> 01:32:24,920 Speaker 1: not thank the Cracks staff who helps put these conversations 1239 01:32:24,960 --> 01:32:28,880 Speaker 1: together each week. Nick Falco is my audio engineer. Michael 1240 01:32:28,920 --> 01:32:31,880 Speaker 1: Batnick is my head of research. Paris Wald is my 1241 01:32:32,000 --> 01:32:36,160 Speaker 1: producer slash booker. Latico val Bron is our project manager. 1242 01:32:36,840 --> 01:32:40,880 Speaker 1: I'm Barry Riholtz, upens and two master's in business on 1243 01:32:41,080 --> 01:32:42,040 Speaker 1: Bloomberg Radio