1 00:00:02,720 --> 00:00:13,960 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. 2 00:00:18,560 --> 00:00:21,720 Speaker 2: Hello and welcome to another episode of the All Thoughts podcast. 3 00:00:21,880 --> 00:00:23,240 Speaker 2: I'm Tracy Alloway. 4 00:00:22,960 --> 00:00:24,200 Speaker 3: And I'm Joe. Why isn't thal. 5 00:00:24,400 --> 00:00:27,560 Speaker 2: Joe, what's your favorite financial movie? I don't think I've 6 00:00:27,600 --> 00:00:28,800 Speaker 2: ever asked you that question? 7 00:00:29,360 --> 00:00:31,240 Speaker 3: Really, I mean Trading Places. 8 00:00:31,360 --> 00:00:33,680 Speaker 2: Oh, that's funny. That's mine too. 9 00:00:34,240 --> 00:00:35,640 Speaker 3: Yeah, and not only. 10 00:00:35,440 --> 00:00:37,880 Speaker 2: Because it's funny, but because it led to a real 11 00:00:37,960 --> 00:00:40,960 Speaker 2: life development which I don't think a lot of people know. 12 00:00:41,000 --> 00:00:44,440 Speaker 2: But the CFTC set up something called the Eddie Murphy Rule. 13 00:00:44,880 --> 00:00:46,479 Speaker 2: I didn't know because of trading places. 14 00:00:46,560 --> 00:00:48,320 Speaker 3: I have no idea where you're going with, and I think. 15 00:00:48,240 --> 00:00:50,960 Speaker 2: There has been an enforcement action. Well, what I was 16 00:00:51,000 --> 00:00:52,720 Speaker 2: going to say is I think there is actually a 17 00:00:52,800 --> 00:00:55,400 Speaker 2: lack of really good financial movies. 18 00:00:55,520 --> 00:00:56,520 Speaker 3: Okay, here you go. 19 00:00:56,640 --> 00:01:01,280 Speaker 2: Trading Places aside, Yes, I would agree. Yeah, I know 20 00:01:01,320 --> 00:01:03,640 Speaker 2: we have the Big Shore and Margin Call was a 21 00:01:03,720 --> 00:01:06,480 Speaker 2: very realistic description of what it's like to work at 22 00:01:06,520 --> 00:01:09,440 Speaker 2: a bank. But I think we need more in our lives, 23 00:01:09,520 --> 00:01:12,200 Speaker 2: and I think we also need financial movies that sort 24 00:01:12,200 --> 00:01:16,480 Speaker 2: of delve into some of the theories of financial markets. 25 00:01:16,520 --> 00:01:19,360 Speaker 2: And I get why we don't. Those are really difficult 26 00:01:19,400 --> 00:01:22,920 Speaker 2: to illustrate in a visual way, but I still want them. 27 00:01:23,040 --> 00:01:26,639 Speaker 3: Me too, all right, keep going crazy? 28 00:01:26,720 --> 00:01:29,640 Speaker 2: Okay, Well, the good news is I just watched one 29 00:01:29,840 --> 00:01:34,080 Speaker 2: that fits into that category. So there's a new documentary 30 00:01:34,120 --> 00:01:37,759 Speaker 2: out called Tune Out the Noise, and it's all about 31 00:01:37,800 --> 00:01:43,120 Speaker 2: the birth of modern finance and it features an absolutely 32 00:01:43,440 --> 00:01:46,800 Speaker 2: all star cast of financial luminaries. So you know, there 33 00:01:46,800 --> 00:01:51,680 Speaker 2: are people like Martin Miller, Myron Scholes, Ken, French, Markowitz, 34 00:01:52,080 --> 00:01:55,360 Speaker 2: like the list goes on and on and on, and 35 00:01:55,400 --> 00:01:56,919 Speaker 2: we're going to talk to two of them today. 36 00:01:57,520 --> 00:02:00,320 Speaker 3: I'm really excited because I'm finally going to have as 37 00:02:00,360 --> 00:02:03,360 Speaker 3: to ask is it all priced in? Because this is 38 00:02:03,440 --> 00:02:06,200 Speaker 3: my core belief about markets, that is, like, no, it's 39 00:02:06,240 --> 00:02:09,760 Speaker 3: all priced in, and yet there appears to be a 40 00:02:09,800 --> 00:02:13,040 Speaker 3: financial industry that must on some level be premised on 41 00:02:13,120 --> 00:02:15,320 Speaker 3: the idea that it's not priced in. But I always 42 00:02:15,360 --> 00:02:17,799 Speaker 3: assume that it's all priced in, and so maybe we'll 43 00:02:17,840 --> 00:02:19,480 Speaker 3: finally get an answer to this question. 44 00:02:19,880 --> 00:02:22,440 Speaker 2: I suspect the way you feel about the term premium 45 00:02:22,480 --> 00:02:25,079 Speaker 2: is the way I feel about the efficient markets hypothesis. 46 00:02:25,080 --> 00:02:28,079 Speaker 2: But let's get into it. We are speaking with David Booth, 47 00:02:28,120 --> 00:02:31,799 Speaker 2: the founder and chairman of Dimensional fund advisors and professor 48 00:02:31,840 --> 00:02:34,840 Speaker 2: Eugene Fauma, who is of course a Nobel laureate. He 49 00:02:34,919 --> 00:02:37,560 Speaker 2: is also a director at Dimensional has had a long 50 00:02:37,639 --> 00:02:41,880 Speaker 2: running intellectual partnership with the firm. He's also sometimes called 51 00:02:42,200 --> 00:02:45,520 Speaker 2: the father of modern finance. I could keep going on 52 00:02:45,600 --> 00:02:48,840 Speaker 2: with the honorifics here, but you get the idea I 53 00:02:48,880 --> 00:02:51,600 Speaker 2: think so, David and Gene, welcome to the show. 54 00:02:51,960 --> 00:02:54,720 Speaker 4: Thank you well, thanks for having us. I'm looking forward 55 00:02:54,760 --> 00:02:55,040 Speaker 4: to it. 56 00:02:55,919 --> 00:02:59,080 Speaker 2: I guess I'll start with the obvious question, but why 57 00:02:59,200 --> 00:03:03,680 Speaker 2: a documentary movie about modern finance? It is, as I 58 00:03:03,760 --> 00:03:08,160 Speaker 2: mentioned earlier, not exactly an easy story to tell visually. 59 00:03:08,600 --> 00:03:10,520 Speaker 4: Well, it didn't start out to be a documentary. What 60 00:03:10,600 --> 00:03:14,080 Speaker 4: happened was we started working with Errol Morris. You know 61 00:03:14,160 --> 00:03:17,760 Speaker 4: he won the Academy Award for his film Fog of 62 00:03:17,800 --> 00:03:22,120 Speaker 4: Warren Unknown documentarian, and now we're talking to him about 63 00:03:22,120 --> 00:03:25,639 Speaker 4: how we could use some of his expertise for our firm. 64 00:03:26,160 --> 00:03:28,639 Speaker 4: He got really into it. He had no not much 65 00:03:28,680 --> 00:03:32,200 Speaker 4: background in finance and just got so fired up. He 66 00:03:32,280 --> 00:03:35,320 Speaker 4: wanted to make it his film rather than our film, 67 00:03:35,560 --> 00:03:37,040 Speaker 4: which I found to be very exciting. 68 00:03:37,160 --> 00:03:41,680 Speaker 3: That's cool. We've done an episode with Dimensional's co CEO, 69 00:03:41,800 --> 00:03:44,680 Speaker 3: George O'Reilly, why don't you talk to us a little 70 00:03:44,720 --> 00:03:47,080 Speaker 3: bit about the partnership of the two of you for 71 00:03:47,160 --> 00:03:49,200 Speaker 3: people who are not familiar, for people who are going 72 00:03:49,240 --> 00:03:52,000 Speaker 3: to be watching the film for the first time. The 73 00:03:52,040 --> 00:03:55,600 Speaker 3: two of you have been working together for literally decades 74 00:03:55,800 --> 00:03:59,360 Speaker 3: and really two of the biggest names truly in the 75 00:03:59,400 --> 00:04:03,520 Speaker 3: history of finance. What is the sort of short version 76 00:04:03,960 --> 00:04:07,320 Speaker 3: of the sort of intellectual partnership and how this firm 77 00:04:07,360 --> 00:04:08,720 Speaker 3: Dimensional came about. 78 00:04:09,320 --> 00:04:14,560 Speaker 5: Well, David was my research assistant fifty five years ago. 79 00:04:14,640 --> 00:04:16,000 Speaker 4: David, Yeah. 80 00:04:16,560 --> 00:04:19,560 Speaker 5: Anyway, it actually worked with me for several years at 81 00:04:19,600 --> 00:04:22,359 Speaker 5: the University of Chicago, and finally he came to me 82 00:04:22,400 --> 00:04:23,839 Speaker 5: and said, I see what you do, and I don't 83 00:04:23,839 --> 00:04:28,160 Speaker 5: want to do it. So he said he wanted to 84 00:04:28,200 --> 00:04:31,120 Speaker 5: go off and work in the financial industries. So I 85 00:04:31,200 --> 00:04:35,080 Speaker 5: called mac McCown and got David a job that way 86 00:04:35,320 --> 00:04:38,280 Speaker 5: with the Wells figu I us. It wasn't the time, David. 87 00:04:38,080 --> 00:04:40,760 Speaker 4: Right, right, nineteen seventy one. 88 00:04:40,800 --> 00:04:43,480 Speaker 6: Then eventually he went off on his own, found a 89 00:04:43,560 --> 00:04:45,440 Speaker 6: Dimensional and came back to me and asked me if 90 00:04:45,440 --> 00:04:47,520 Speaker 6: I wanted to be somehow involved. 91 00:04:48,000 --> 00:04:49,479 Speaker 5: We've been going in it ever since. 92 00:04:50,160 --> 00:04:52,159 Speaker 2: Oh yeah, this was in the movie. So I think 93 00:04:52,240 --> 00:04:55,400 Speaker 2: Wells Fargo basically just decided to share some of its 94 00:04:55,520 --> 00:04:59,640 Speaker 2: data and analysis with Vanguard, like at the very beginning 95 00:04:59,760 --> 00:05:03,080 Speaker 2: of Jack Bogel's career. And everyone was sort of scratching 96 00:05:03,120 --> 00:05:05,720 Speaker 2: their heads about why that happened. But do we have 97 00:05:05,760 --> 00:05:08,440 Speaker 2: any sense of why that happened. Was there just a 98 00:05:08,480 --> 00:05:13,599 Speaker 2: spirit of research or academic camaraderie that made private organizations 99 00:05:13,640 --> 00:05:14,920 Speaker 2: share things with each other? 100 00:05:15,560 --> 00:05:17,839 Speaker 4: Well, one of the things I've always admired about Gene 101 00:05:17,920 --> 00:05:23,839 Speaker 4: is his research, which we use extensively. He's always insisted 102 00:05:24,320 --> 00:05:27,400 Speaker 4: that his research be in the public domain. We're not 103 00:05:27,480 --> 00:05:31,000 Speaker 4: in the business of creating black box that nobody understands. 104 00:05:31,560 --> 00:05:35,400 Speaker 4: So it's so critically important to have an open air 105 00:05:35,920 --> 00:05:41,920 Speaker 4: philosophy about sharing research. And so Wells got off to 106 00:05:41,960 --> 00:05:45,440 Speaker 4: a slow start in some ways, but it was a 107 00:05:45,480 --> 00:05:47,720 Speaker 4: fund little question. You can even track the performance of 108 00:05:47,760 --> 00:05:50,039 Speaker 4: an index, and so Wells had done a lot of 109 00:05:50,040 --> 00:05:53,600 Speaker 4: simulations and stuff, and when the group I was working 110 00:05:53,640 --> 00:05:58,080 Speaker 4: on the walls got shut down, Mac just volunteered to 111 00:05:58,839 --> 00:06:02,560 Speaker 4: Bogel to share all of his NATA with him. 112 00:06:02,760 --> 00:06:06,880 Speaker 3: Gine, I'm curious, from your perspective, how did this interest 113 00:06:06,960 --> 00:06:10,400 Speaker 3: you as a intellectual field of study, and we'll get 114 00:06:10,400 --> 00:06:13,080 Speaker 3: into some of the specific and a sort of groundbreaking 115 00:06:13,160 --> 00:06:17,320 Speaker 3: contributions to what many people now consider absolute truths to 116 00:06:17,440 --> 00:06:21,400 Speaker 3: how the market worked. But this idea some of your ideas, 117 00:06:21,400 --> 00:06:25,839 Speaker 3: like why what attracted you to the study of markets 118 00:06:25,880 --> 00:06:28,360 Speaker 3: and some of your early research, well. 119 00:06:28,520 --> 00:06:31,440 Speaker 5: As I stand on it. In college, actually I worked 120 00:06:31,440 --> 00:06:34,719 Speaker 5: for a professor at TUFFS that had a stock market 121 00:06:34,760 --> 00:06:38,080 Speaker 5: forecasting service, and my job was to come up with 122 00:06:38,200 --> 00:06:39,400 Speaker 5: new ways to beat the market. 123 00:06:40,120 --> 00:06:40,680 Speaker 3: How'd that go? 124 00:06:40,960 --> 00:06:43,159 Speaker 5: It didn't go very well, but in the following sense, 125 00:06:43,600 --> 00:06:46,600 Speaker 5: he was very good statistician, so we always kept a 126 00:06:47,040 --> 00:06:50,280 Speaker 5: hold out sample and my ideas always worked in sample, 127 00:06:50,279 --> 00:06:53,359 Speaker 5: but they never worked out of sample. So that was 128 00:06:53,400 --> 00:06:56,599 Speaker 5: my first lesson on what do you can expect by 129 00:06:56,680 --> 00:06:59,520 Speaker 5: trying to beat the market. And after that I went 130 00:06:59,560 --> 00:07:03,200 Speaker 5: off to Sego, took my data with me from Tefts, 131 00:07:03,720 --> 00:07:04,880 Speaker 5: and eventually wrote. 132 00:07:04,600 --> 00:07:09,560 Speaker 7: My thesis using that data, which was kind of the 133 00:07:10,480 --> 00:07:13,560 Speaker 7: the first that maybe one of the bigger trumpeting of 134 00:07:13,880 --> 00:07:15,640 Speaker 7: fishing markets the term went. 135 00:07:15,680 --> 00:07:17,960 Speaker 6: It wasn't even wasn't even called that at the time, 136 00:07:18,040 --> 00:07:20,960 Speaker 6: but eventually that term came around as well. 137 00:07:21,560 --> 00:07:24,280 Speaker 4: One of the things is interesting about that observed he 138 00:07:24,320 --> 00:07:27,560 Speaker 4: did a study based on data collected by hand, and 139 00:07:27,600 --> 00:07:29,520 Speaker 4: that was kind of the state of the world. When 140 00:07:29,560 --> 00:07:33,600 Speaker 4: I went to Chicago to do a research project, frequently 141 00:07:33,720 --> 00:07:36,280 Speaker 4: had to hand collect the data. You know, these new 142 00:07:36,360 --> 00:07:40,000 Speaker 4: kids today wouldn't be aghast have if they knew how 143 00:07:40,000 --> 00:07:41,920 Speaker 4: we did things in the old days. 144 00:07:42,760 --> 00:07:45,120 Speaker 2: Well, I remember, in the old days of Bloomberg, we 145 00:07:45,240 --> 00:07:47,640 Speaker 2: often input it a lot of financially, if you're working 146 00:07:47,640 --> 00:07:50,080 Speaker 2: in the global data department, and you certainly input it 147 00:07:50,160 --> 00:07:53,080 Speaker 2: a lot of things by hand as well. This leads 148 00:07:53,120 --> 00:07:54,560 Speaker 2: to a question I want to ask you. So a 149 00:07:54,560 --> 00:07:57,280 Speaker 2: big chunk of the documentary is about all these different 150 00:07:57,280 --> 00:08:01,440 Speaker 2: people who spent time at the University of Chicago. What 151 00:08:01,600 --> 00:08:05,520 Speaker 2: was in the water at the university that it attracted 152 00:08:05,680 --> 00:08:08,840 Speaker 2: all these names that went on to do big things 153 00:08:08,880 --> 00:08:09,560 Speaker 2: in finance. 154 00:08:09,960 --> 00:08:15,560 Speaker 5: Well, Marton Miller was an important person. He was deeply 155 00:08:15,640 --> 00:08:19,200 Speaker 5: interested in this stuff. And Harry Arms was another important 156 00:08:19,240 --> 00:08:23,640 Speaker 5: person who had written on something resembling what would be 157 00:08:23,680 --> 00:08:26,480 Speaker 5: now called the fishing markets way back in the fifties. 158 00:08:27,040 --> 00:08:29,360 Speaker 5: So he was very much interested in it. And they 159 00:08:29,400 --> 00:08:32,800 Speaker 5: were kind of the two shining lights in this area. 160 00:08:33,320 --> 00:08:36,080 Speaker 5: And plus then there were a lot of PhD students, 161 00:08:36,400 --> 00:08:41,440 Speaker 5: including me, these is topics. So having faculty interested in 162 00:08:41,440 --> 00:08:43,719 Speaker 5: the topic was a good way of having researched them 163 00:08:43,760 --> 00:08:46,200 Speaker 5: by students in that type, because that was the way 164 00:08:46,200 --> 00:08:50,240 Speaker 5: to graduate. And at the time I had two kids 165 00:08:50,240 --> 00:08:52,280 Speaker 5: with another one on the way, so it was very 166 00:08:52,600 --> 00:08:54,240 Speaker 5: very keen on getting out quickly. 167 00:08:55,280 --> 00:08:57,640 Speaker 4: Well, I would also add, you know, Jim Laurie, I 168 00:08:57,640 --> 00:09:02,839 Speaker 4: mean gentleman Larry Fisher. They persuaded Barrel Lynch to fund 169 00:09:02,840 --> 00:09:08,800 Speaker 4: a study to collect a survivorship bias free database which 170 00:09:08,920 --> 00:09:12,680 Speaker 4: enabled all these new young hotshots to do their research. 171 00:09:13,559 --> 00:09:18,080 Speaker 4: Until that point to the data had never been collected 172 00:09:18,320 --> 00:09:21,560 Speaker 4: correctly and so he couldn't really do the research. 173 00:09:21,960 --> 00:09:25,760 Speaker 5: So when Larry started out to Larry's Fish started out 174 00:09:25,840 --> 00:09:28,640 Speaker 5: to collect that data and put it together. A computer 175 00:09:28,679 --> 00:09:32,040 Speaker 5: didn't exist it could handle it, but he said, well, 176 00:09:32,400 --> 00:09:34,040 Speaker 5: it's going to come along by the time me finish 177 00:09:34,080 --> 00:09:37,160 Speaker 5: this to be computer you can handle it. And he 178 00:09:37,280 --> 00:09:37,920 Speaker 5: took out to be. 179 00:09:37,960 --> 00:09:41,160 Speaker 3: Raised, well, actually, this is exactly what I wanted to ask, 180 00:09:41,200 --> 00:09:42,920 Speaker 3: and I think it sort of speaks to like a 181 00:09:42,920 --> 00:09:47,360 Speaker 3: big theoretical question. Let's say, part of good investing is 182 00:09:47,640 --> 00:09:51,160 Speaker 3: having good data, Like if you have to collect the 183 00:09:51,240 --> 00:09:54,600 Speaker 3: data by hand, You're already going to probably knock out 184 00:09:54,720 --> 00:09:57,240 Speaker 3: ninety nine point nine percent of the people who have interest, 185 00:09:57,320 --> 00:10:00,240 Speaker 3: because I wouldn't do it because my risk get really tired, 186 00:10:00,320 --> 00:10:03,880 Speaker 3: really fast, and my handwriting is garbage, so I wouldn't 187 00:10:03,880 --> 00:10:06,320 Speaker 3: even be able to read what I had written in 188 00:10:06,360 --> 00:10:09,640 Speaker 3: the graph paper, et cetera. A lot of things that 189 00:10:09,679 --> 00:10:14,760 Speaker 3: we take for granted about investing today, including measuring the 190 00:10:14,800 --> 00:10:17,680 Speaker 3: performance of an index, are things that literally take a 191 00:10:17,679 --> 00:10:21,600 Speaker 3: few keystrokes or less on a Bloomberg terminal today. And 192 00:10:21,679 --> 00:10:25,520 Speaker 3: I'm curious, like, when you think about, like generating superior 193 00:10:25,840 --> 00:10:30,760 Speaker 3: returns over time, how much of an edge was that 194 00:10:31,440 --> 00:10:34,440 Speaker 3: to just be willing to do the hard work of 195 00:10:34,520 --> 00:10:35,280 Speaker 3: collecting data. 196 00:10:35,920 --> 00:10:38,760 Speaker 4: Look, all these tests and market efficiency, which started in 197 00:10:38,800 --> 00:10:42,120 Speaker 4: the sixties, you know, and have keep showing the same 198 00:10:42,520 --> 00:10:47,360 Speaker 4: result every sense, even though with increasing levels of sophistication 199 00:10:47,440 --> 00:10:50,640 Speaker 4: of researchers and people having access to more and more 200 00:10:51,040 --> 00:10:54,959 Speaker 4: more data, better data, faster data, all of that, this 201 00:10:55,080 --> 00:10:59,400 Speaker 4: still shows the same outcome of it doesn't look like 202 00:11:00,040 --> 00:11:01,760 Speaker 4: find how guess the market is a winning game. 203 00:11:03,160 --> 00:11:06,719 Speaker 2: So, since we're on the subject of the efficient markets hypothesis, 204 00:11:06,880 --> 00:11:09,880 Speaker 2: one of your former students who also went on to 205 00:11:10,120 --> 00:11:13,439 Speaker 2: a great fame. Cliff asnas He published his own paper 206 00:11:13,520 --> 00:11:17,320 Speaker 2: called the less Efficient Markets Hypothesis, and it argues that 207 00:11:17,400 --> 00:11:20,439 Speaker 2: markets are less efficient than they once were, in part 208 00:11:20,559 --> 00:11:24,280 Speaker 2: because social media has basically turned us all into trend 209 00:11:24,320 --> 00:11:27,199 Speaker 2: following idiots. I guess, and this is something that I've 210 00:11:27,200 --> 00:11:31,680 Speaker 2: occasionally wondered. If the efficient markets hypothesis is reliant on 211 00:11:31,840 --> 00:11:36,079 Speaker 2: people making the right decisions with the information that they 212 00:11:36,120 --> 00:11:38,800 Speaker 2: have or the data they have, what happens if we 213 00:11:38,840 --> 00:11:43,920 Speaker 2: all get collectively more stupid? And I guess A different 214 00:11:43,960 --> 00:11:48,120 Speaker 2: way of asking this is, has your view of the 215 00:11:48,120 --> 00:11:51,320 Speaker 2: efficient markets hypothesis changed at all over time? 216 00:11:52,520 --> 00:11:58,040 Speaker 5: No, it hasn't really changed. It's adaptive in the sense 217 00:11:58,080 --> 00:12:01,760 Speaker 5: that I never said that the market was efficient for everybody. 218 00:12:02,200 --> 00:12:04,559 Speaker 5: There are for example, there's lots of evidence, for example, 219 00:12:04,600 --> 00:12:08,600 Speaker 5: that company insiders have information that isn't already in prices, 220 00:12:09,000 --> 00:12:11,760 Speaker 5: so as far as they're concerned, the stock of their 221 00:12:11,800 --> 00:12:16,280 Speaker 5: company is not priced efficiently. That's one instance of it. 222 00:12:16,320 --> 00:12:21,040 Speaker 5: But as far as professional managers are concerned, there is 223 00:12:21,120 --> 00:12:23,400 Speaker 5: evidence that if you give them back all their fees 224 00:12:23,440 --> 00:12:27,080 Speaker 5: and expenses, there are some who do have enough information 225 00:12:27,200 --> 00:12:28,000 Speaker 5: to beat the market. 226 00:12:28,480 --> 00:12:30,439 Speaker 6: But if you don't take out the fees and expensive 227 00:12:30,640 --> 00:12:34,040 Speaker 6: then the active managers look terrible relative to. 228 00:12:34,720 --> 00:12:39,080 Speaker 5: The passive managers. So that's the kind of data and 229 00:12:39,200 --> 00:12:42,200 Speaker 5: results that makes market efficiency look pretty good. 230 00:12:42,640 --> 00:12:43,040 Speaker 4: But it's not. 231 00:12:43,720 --> 00:12:48,040 Speaker 5: It's just a hypothesis. It's not a literal truth. It's 232 00:12:48,120 --> 00:12:51,040 Speaker 5: just an approximation to the world. But it worked really 233 00:12:51,080 --> 00:12:52,199 Speaker 5: well for almost everybody. 234 00:12:55,240 --> 00:12:55,600 Speaker 8: M hm. 235 00:13:08,040 --> 00:13:10,640 Speaker 3: So this gets to like a question that I've asked 236 00:13:10,679 --> 00:13:14,440 Speaker 3: before and I'm now thrilled to get to ask it 237 00:13:14,480 --> 00:13:19,200 Speaker 3: to you, which is why does the financial industry exist? 238 00:13:19,440 --> 00:13:22,000 Speaker 3: If markets are efficient, because there are a lot of 239 00:13:22,120 --> 00:13:28,320 Speaker 3: people that collect very big paychecks from some notion that 240 00:13:28,360 --> 00:13:32,640 Speaker 3: they can deliver better returns than someone else to their clients. 241 00:13:33,160 --> 00:13:36,160 Speaker 3: If markets are efficient, at least to most people in 242 00:13:36,200 --> 00:13:38,760 Speaker 3: the industry, why do we have this industry? 243 00:13:39,600 --> 00:13:42,200 Speaker 5: Because there are people who think they can pick the 244 00:13:42,559 --> 00:13:45,960 Speaker 5: managers that have special information. That's what keeps it going. 245 00:13:46,400 --> 00:13:50,000 Speaker 5: That's what keeps the active manages going. Individuals who make 246 00:13:51,360 --> 00:13:54,600 Speaker 5: who don't think the passive investing is for them, and 247 00:13:54,800 --> 00:13:57,600 Speaker 5: they invest they go with the active people, so that 248 00:13:58,000 --> 00:14:02,320 Speaker 5: markets are always about competition among different kinds of players. 249 00:14:02,320 --> 00:14:04,040 Speaker 5: And then we see who comes out on. 250 00:14:04,080 --> 00:14:07,320 Speaker 2: Top, Geene, how serious are you when you say stuff 251 00:14:07,400 --> 00:14:09,480 Speaker 2: like there's no such thing as a bubble, or that 252 00:14:09,520 --> 00:14:13,599 Speaker 2: bubbles are only identifiable after they burst, so it's pointless 253 00:14:13,640 --> 00:14:19,160 Speaker 2: to talk about them. Very serious, explain it more, because 254 00:14:19,240 --> 00:14:21,280 Speaker 2: Joe and I have lots of episodes where we talk 255 00:14:21,280 --> 00:14:23,960 Speaker 2: about either past bubbles or overvaluations. 256 00:14:24,320 --> 00:14:28,120 Speaker 5: Yeah, so with twenty twenty, I didn't say, as you know, 257 00:14:28,240 --> 00:14:32,360 Speaker 5: it's explain why prices won't happen, why why they way 258 00:14:32,400 --> 00:14:35,920 Speaker 5: they went down. But in my view, what a bubble 259 00:14:36,000 --> 00:14:40,040 Speaker 5: means is price has gone up and you can predict 260 00:14:40,120 --> 00:14:43,320 Speaker 5: when it's going to go down, when when that hope 261 00:14:43,640 --> 00:14:46,040 Speaker 5: phenomen it's going to that hope price movement is going 262 00:14:46,120 --> 00:14:50,120 Speaker 5: to go away. And that's what's just proving really difficult 263 00:14:50,160 --> 00:14:53,560 Speaker 5: to do. So lots of people use the word bubble 264 00:14:53,960 --> 00:14:57,760 Speaker 5: very loosely. I can't sell my subscription to the economists 265 00:14:57,760 --> 00:14:59,480 Speaker 5: because you're using the word. 266 00:15:01,120 --> 00:15:04,320 Speaker 3: Journalists are terrible about overusing bubble. I will cop to 267 00:15:04,400 --> 00:15:07,760 Speaker 3: that on the behalf of the entire profession, right. 268 00:15:08,080 --> 00:15:11,280 Speaker 5: So I need to know what the definition is before 269 00:15:11,280 --> 00:15:14,200 Speaker 5: I can respond to it, and in that case that's 270 00:15:14,240 --> 00:15:16,920 Speaker 5: much more difficult. Most people are willing to do that. 271 00:15:17,200 --> 00:15:19,520 Speaker 5: There are econs that are willing to do it, and 272 00:15:19,600 --> 00:15:22,400 Speaker 5: I can deal with that. There has to be some predictability, 273 00:15:22,480 --> 00:15:24,760 Speaker 5: but when it's going to end, and that's what proven 274 00:15:25,240 --> 00:15:27,160 Speaker 5: really difficult to establish. 275 00:15:27,280 --> 00:15:29,680 Speaker 3: Right, it seems fairly clear that you could sort of 276 00:15:29,760 --> 00:15:32,440 Speaker 3: sense like we're in some sort of mania, and even 277 00:15:32,720 --> 00:15:37,080 Speaker 3: knowing that fact and everyone agreeing on that fact. In fact, 278 00:15:37,080 --> 00:15:39,400 Speaker 3: to try to establish that fact is often a good 279 00:15:39,440 --> 00:15:43,200 Speaker 3: recipe for losing all your money if you're short at 280 00:15:43,240 --> 00:15:45,720 Speaker 3: or losing all your clients if you're avoiding it. So 281 00:15:46,200 --> 00:15:49,120 Speaker 3: I certainly take that point. Let me press further though, 282 00:15:49,440 --> 00:15:52,440 Speaker 3: So a lot of your research and this idea of 283 00:15:52,520 --> 00:15:57,640 Speaker 3: market efficiency, but you've also worked on factors that seem 284 00:15:57,880 --> 00:16:01,840 Speaker 3: over time historically to outperform. And so the idea of 285 00:16:02,200 --> 00:16:07,120 Speaker 3: small companies outperforming big companies or value companies outperforming over 286 00:16:07,320 --> 00:16:13,400 Speaker 3: time dimensional has funds that aren't just the pure market portfolio. 287 00:16:13,880 --> 00:16:18,680 Speaker 3: Reconcile the existence of that with the idea of efficient marketing. 288 00:16:18,680 --> 00:16:22,800 Speaker 5: Okay, that's that's a good question. So everybody has this confusion. 289 00:16:22,800 --> 00:16:25,880 Speaker 5: The confusion is mixing together market. 290 00:16:25,640 --> 00:16:30,920 Speaker 6: Efficiency and the dimensions of risk and portfolio selection. 291 00:16:31,160 --> 00:16:35,080 Speaker 5: So going back all the way to Macrowitz. We've a 292 00:16:35,160 --> 00:16:38,040 Speaker 5: long known for example, the people don't like variants, they 293 00:16:38,040 --> 00:16:42,440 Speaker 5: don't like uncertainty about future liters, and they're willing to 294 00:16:42,520 --> 00:16:45,280 Speaker 5: pay something to avoid it. So they gave rise to 295 00:16:46,040 --> 00:16:49,040 Speaker 5: the chaplain and their capital so called capital asset pricing 296 00:16:49,080 --> 00:16:53,000 Speaker 5: model in which sensitivity to the market was the measure 297 00:16:53,080 --> 00:16:57,000 Speaker 5: of it was the measure of risk. So basically into 298 00:16:57,000 --> 00:17:02,960 Speaker 5: confusion of prices being reflect value in the study about 299 00:17:03,200 --> 00:17:06,160 Speaker 5: what are the dimensions of risk in the market. So 300 00:17:06,200 --> 00:17:10,080 Speaker 5: that's a confusion that almost everybody seems to have. So 301 00:17:10,680 --> 00:17:13,720 Speaker 5: Marcus doesn't say there aren't risk premeans in the market, 302 00:17:13,960 --> 00:17:15,040 Speaker 5: does not say that at all. 303 00:17:16,200 --> 00:17:18,679 Speaker 4: One way to think about it is, you know, define 304 00:17:18,720 --> 00:17:20,920 Speaker 4: the market to be all the stocks and bonds that 305 00:17:20,920 --> 00:17:23,240 Speaker 4: are out there. Most of us believes talks are with 306 00:17:23,240 --> 00:17:27,240 Speaker 4: a long haul level higher return than bonds. A few 307 00:17:27,280 --> 00:17:30,440 Speaker 4: people invest all their money in stockses and doesn't mean 308 00:17:30,440 --> 00:17:35,320 Speaker 4: stocks are inefficient and efficiently priced, and just those are 309 00:17:35,359 --> 00:17:39,080 Speaker 4: the market prices. And you look at different combinations of 310 00:17:39,119 --> 00:17:42,719 Speaker 4: the two and they provide different distributions of outcomes, and 311 00:17:43,280 --> 00:17:46,119 Speaker 4: just find that distribution that works best for you. 312 00:17:47,440 --> 00:17:50,119 Speaker 2: So a big chunk of The documentary is about the 313 00:17:50,160 --> 00:17:53,719 Speaker 2: birth of passive investing and its connection with the efficient 314 00:17:53,800 --> 00:17:57,960 Speaker 2: markets hypothesis. What's been the impact of the growth of 315 00:17:58,040 --> 00:18:01,800 Speaker 2: passive investing on the market it because we often hear that, 316 00:18:02,000 --> 00:18:05,600 Speaker 2: you know, markets are reflexive, moves can end up impacting 317 00:18:05,640 --> 00:18:08,480 Speaker 2: the market itself. And David, I think you yourself have 318 00:18:08,640 --> 00:18:12,320 Speaker 2: argued that one of passive investing's biggest flaws is still 319 00:18:12,480 --> 00:18:16,679 Speaker 2: very much alive, the index effect, where stock prices go 320 00:18:16,800 --> 00:18:18,879 Speaker 2: up a lot when a company is added to an index, 321 00:18:18,960 --> 00:18:21,600 Speaker 2: even though everyone in the theory should know that this 322 00:18:21,680 --> 00:18:24,359 Speaker 2: is going to happen and so it should already be 323 00:18:24,480 --> 00:18:28,000 Speaker 2: priced in. How has passive actually changed the market? 324 00:18:28,400 --> 00:18:31,760 Speaker 4: Well, that's an interesting question. First off, the kind of 325 00:18:31,800 --> 00:18:35,280 Speaker 4: the impact of an index adding a new name, you know, 326 00:18:35,760 --> 00:18:39,080 Speaker 4: causing temporary prices to go up. That's a temporary effect. 327 00:18:39,119 --> 00:18:42,720 Speaker 4: It doesn't really impact the long term investor very much. 328 00:18:43,440 --> 00:18:47,399 Speaker 4: And one question that comes up a lot is, you know, 329 00:18:47,400 --> 00:18:49,560 Speaker 4: if everybody indexed, you know, then there would be no 330 00:18:49,600 --> 00:18:52,560 Speaker 4: price discovery. Wouldn't markets become inefficient? 331 00:18:52,840 --> 00:18:53,040 Speaker 5: You know? 332 00:18:53,080 --> 00:18:56,280 Speaker 4: That's kind of And my answer to that is, well, 333 00:18:56,400 --> 00:18:59,560 Speaker 4: let's take a look at it. The behavior of the 334 00:18:59,600 --> 00:19:03,200 Speaker 4: market over the last twenty years. There's been an incredible 335 00:19:03,280 --> 00:19:06,480 Speaker 4: movement to indexing over that time period, and yet there's 336 00:19:06,480 --> 00:19:10,920 Speaker 4: been an incredible increase in trading volume. You know, I 337 00:19:10,960 --> 00:19:14,280 Speaker 4: don't think of price discovery has been related to trading volume. 338 00:19:14,359 --> 00:19:18,200 Speaker 4: So just because there's a big movement to indexing doesn't 339 00:19:18,200 --> 00:19:23,280 Speaker 4: mean trading volume multi climb. What's happened, unfortunately, is it 340 00:19:23,280 --> 00:19:25,879 Speaker 4: turns out, like a lot of things that can be 341 00:19:25,960 --> 00:19:28,440 Speaker 4: used for good, they can also be used for bad. 342 00:19:29,119 --> 00:19:33,600 Speaker 4: And you know, index funds are the ideal market timing vehicle. 343 00:19:33,920 --> 00:19:38,840 Speaker 4: I'll buy this healthcare index fund and sell my technology 344 00:19:38,880 --> 00:19:41,200 Speaker 4: for or whatever it is. And I think that really 345 00:19:41,200 --> 00:19:44,480 Speaker 4: comes to what happened to the marketplace is it's kind 346 00:19:44,480 --> 00:19:48,000 Speaker 4: of to an individual instead of individual stock selection, it's 347 00:19:48,080 --> 00:19:51,600 Speaker 4: kind of like a big gambling casino where you have 348 00:19:51,640 --> 00:19:53,280 Speaker 4: a lot of different ways you can make your bets. 349 00:19:53,760 --> 00:19:57,040 Speaker 4: So it doesn't look like in terms of the basic 350 00:19:57,119 --> 00:20:00,600 Speaker 4: notion of market efficiency, it doesn't appear to have had 351 00:20:00,880 --> 00:20:01,880 Speaker 4: much impact on that. 352 00:20:02,960 --> 00:20:06,679 Speaker 5: So let me just take different direction. And people worry 353 00:20:06,680 --> 00:20:10,560 Speaker 5: that if everybody goes assive, how will prices get formed? 354 00:20:10,800 --> 00:20:13,760 Speaker 5: And that's a legitimate concern, But then the issue is 355 00:20:14,000 --> 00:20:17,880 Speaker 5: who drops out, who doesn't go active anymore. If it's 356 00:20:17,960 --> 00:20:21,280 Speaker 5: bad active man, just people who have no special information. 357 00:20:21,520 --> 00:20:25,040 Speaker 5: If they drop out, then you need few good active 358 00:20:25,359 --> 00:20:29,520 Speaker 5: people to keep prices inline. So it depends on who 359 00:20:29,600 --> 00:20:33,880 Speaker 5: drops out as to whether has any effect at all 360 00:20:33,920 --> 00:20:37,280 Speaker 5: on market efficiency. And we haven't been able to discern 361 00:20:37,359 --> 00:20:41,119 Speaker 5: anything like that in the behavior of prices, But that 362 00:20:41,359 --> 00:20:42,280 Speaker 5: is the question. 363 00:20:43,880 --> 00:20:46,840 Speaker 2: Since we're on the topic of indexing. You know, the 364 00:20:46,880 --> 00:20:50,560 Speaker 2: market nowadays, as you mentioned, is basically defined by benchmark indexes, 365 00:20:50,720 --> 00:20:52,600 Speaker 2: things like the S and P five hundred or the 366 00:20:52,760 --> 00:20:57,840 Speaker 2: MSCI World Index. And the benchmark index providers will often 367 00:20:57,880 --> 00:21:00,240 Speaker 2: say that they're just holding up a mirror to the 368 00:21:00,280 --> 00:21:04,480 Speaker 2: market as it exists. They're neutral, but it seems kind 369 00:21:04,520 --> 00:21:09,199 Speaker 2: of obvious to me that their decisions do impact the market, 370 00:21:09,280 --> 00:21:12,760 Speaker 2: and some of those decisions can be subjective, you know, 371 00:21:12,800 --> 00:21:15,880 Speaker 2: when it comes to measuring things like liquidity or how 372 00:21:15,960 --> 00:21:19,879 Speaker 2: developed a particular bond market is or whatever. Are we 373 00:21:20,000 --> 00:21:24,200 Speaker 2: just outsourcing investment decisions to index providers. 374 00:21:25,359 --> 00:21:28,600 Speaker 5: To choose the one you want. So my own tastes 375 00:21:28,800 --> 00:21:31,800 Speaker 5: run in the direction of a total market index being 376 00:21:31,840 --> 00:21:37,080 Speaker 5: a good choice for almost everybody. So I don't go from. 377 00:21:36,960 --> 00:21:40,560 Speaker 6: The subset things that thirty thirty down Jones that was 378 00:21:40,600 --> 00:21:41,720 Speaker 6: always kind of dumb. 379 00:21:42,800 --> 00:21:46,440 Speaker 5: But or even five hundred, that's only five hundred. There's 380 00:21:46,440 --> 00:21:48,040 Speaker 5: a loves stucks out there. 381 00:21:48,080 --> 00:21:52,640 Speaker 4: Then than that, let me just recall against the term passive. 382 00:21:53,000 --> 00:21:55,520 Speaker 4: You know, in my view, there's no such thing as 383 00:21:55,560 --> 00:22:00,199 Speaker 4: passive management. And you're you're touching on something right there. 384 00:22:00,280 --> 00:22:04,000 Speaker 4: You know the different index providers and how they do it, 385 00:22:04,040 --> 00:22:07,159 Speaker 4: and they'll do it differently and so forth. And you 386 00:22:07,200 --> 00:22:10,439 Speaker 4: know Standard and Poors when it wants to add stock 387 00:22:10,480 --> 00:22:13,560 Speaker 4: to its sm P five hundred, you know, the investment 388 00:22:13,560 --> 00:22:16,200 Speaker 4: committee sits around and talks about you know, what do 389 00:22:16,280 --> 00:22:18,480 Speaker 4: you like? You know, it's the S and P five 390 00:22:18,600 --> 00:22:21,280 Speaker 4: hundred is five hundred of the largest companies, but it's 391 00:22:21,320 --> 00:22:25,240 Speaker 4: not the five hundred largest companies. And there's quite a 392 00:22:25,240 --> 00:22:30,240 Speaker 4: bit of subjective judgment goes into deciding what stock goes 393 00:22:30,280 --> 00:22:33,879 Speaker 4: into the index. Which if you're going to an index 394 00:22:33,920 --> 00:22:36,359 Speaker 4: fund because you don't like stock selection, that's not the 395 00:22:36,440 --> 00:22:38,280 Speaker 4: kind of activity you want to you want to see. 396 00:22:39,080 --> 00:22:41,400 Speaker 3: I want to go back to this idea of even 397 00:22:41,440 --> 00:22:45,080 Speaker 3: if markets are efficient, there still are risk premia and 398 00:22:45,200 --> 00:22:48,040 Speaker 3: certain asset classes are expected to go up more than 399 00:22:48,119 --> 00:22:51,680 Speaker 3: others due to people's wanting to avoid drawdowns, et cetera. 400 00:22:52,040 --> 00:22:54,880 Speaker 3: You know, like I don't make many active decisions. I'm 401 00:22:54,960 --> 00:22:56,840 Speaker 3: like a good like I follow what I read in 402 00:22:56,880 --> 00:23:00,800 Speaker 3: the news, and I like, have some stocks and you 403 00:23:00,800 --> 00:23:04,000 Speaker 3: know it, probably have some treasuries and some fund or 404 00:23:04,000 --> 00:23:05,919 Speaker 3: something like that, and I don't like pay attention to 405 00:23:05,960 --> 00:23:11,359 Speaker 3: it much. Looking back though, at historical trends in portfolio construction, 406 00:23:11,600 --> 00:23:16,600 Speaker 3: I sometimes wonder why should anyone own bonds? Because you say, 407 00:23:16,760 --> 00:23:19,560 Speaker 3: hardly anyone just own stocks, and that seems to be 408 00:23:19,600 --> 00:23:22,720 Speaker 3: objectively true. But I wonder if, like, is there reason 409 00:23:22,760 --> 00:23:26,119 Speaker 3: to question some of this dogma of like why, like, 410 00:23:26,200 --> 00:23:29,440 Speaker 3: if I'm not going to retire in thirty years, do 411 00:23:29,480 --> 00:23:32,520 Speaker 3: I care about You know, I'm already diversifying over time 412 00:23:32,600 --> 00:23:35,760 Speaker 3: because I make an allocation to my retirement funds with 413 00:23:36,000 --> 00:23:40,400 Speaker 3: every paycheck, so I'm already getting time diversification. Are there 414 00:23:40,400 --> 00:23:44,480 Speaker 3: fundamental questions in portfolio construction that you think need to 415 00:23:44,520 --> 00:23:49,199 Speaker 3: be rethought if over the next thirty years before I 416 00:23:49,240 --> 00:23:53,520 Speaker 3: can retire twenty five years, maybe, like, if almost everyone 417 00:23:53,640 --> 00:23:57,640 Speaker 3: thinks it's certain that stocks will outperform bonds, why am 418 00:23:57,640 --> 00:24:00,240 Speaker 3: I holding bonds. 419 00:23:58,960 --> 00:24:03,160 Speaker 5: That sense that if almost every but he thinks that's true, 420 00:24:03,520 --> 00:24:07,439 Speaker 5: But it's not true. Stucks don't get less risk. In 421 00:24:07,440 --> 00:24:10,240 Speaker 5: the long term, risk accumulates, So. 422 00:24:11,800 --> 00:24:14,120 Speaker 3: I don't understand that. I don't understand how. 423 00:24:14,960 --> 00:24:18,600 Speaker 5: When you retire, when you retire a period when stocks 424 00:24:18,640 --> 00:24:22,800 Speaker 5: have been particularly poorly and you will get hurt, that's 425 00:24:22,840 --> 00:24:25,680 Speaker 5: always a possibility, doesn't go away with the time. 426 00:24:26,800 --> 00:24:30,840 Speaker 6: So the presumption is is what's incorrect? The risk is 427 00:24:30,880 --> 00:24:32,359 Speaker 6: always there, you don't get rid of it. 428 00:24:33,640 --> 00:24:36,520 Speaker 2: What do you think about the term smart beta? And 429 00:24:37,200 --> 00:24:40,000 Speaker 2: is dimensional doing smart beta? 430 00:24:41,200 --> 00:24:47,560 Speaker 5: Yeah, smart is a marketing term. Show me a dumb beta. 431 00:24:48,119 --> 00:24:50,359 Speaker 2: I'm sure I could find some examples, but they certainly 432 00:24:50,359 --> 00:24:52,800 Speaker 2: wouldn't have set out to create dumb beata. 433 00:24:53,359 --> 00:24:55,600 Speaker 5: There's a lot of Mike, there's a lot of marketing 434 00:24:56,000 --> 00:24:59,360 Speaker 5: in the financial business. That's one of them. That's one 435 00:24:59,359 --> 00:24:59,960 Speaker 5: of the big ones. 436 00:25:00,000 --> 00:25:01,920 Speaker 3: Well, what does it mean to you? So like when 437 00:25:01,960 --> 00:25:04,520 Speaker 3: you hear that term, like, what is the person trying 438 00:25:04,560 --> 00:25:05,040 Speaker 3: to sell to me? 439 00:25:05,160 --> 00:25:06,720 Speaker 5: Well, that have to give me an example because I 440 00:25:06,760 --> 00:25:10,360 Speaker 5: don't take it seriously. Obviously you can tell me checking here. 441 00:25:10,800 --> 00:25:13,920 Speaker 4: Well, I think it's a Jeans research that he did 442 00:25:13,960 --> 00:25:17,359 Speaker 4: with Ken French. You know, his landmark ninety two paper 443 00:25:17,440 --> 00:25:22,639 Speaker 4: on called cross section of expected returns anyway that you know, 444 00:25:22,720 --> 00:25:26,200 Speaker 4: kind of gave empirical support to the idea that there 445 00:25:26,240 --> 00:25:29,680 Speaker 4: can be many dimensions of returns. So if you focus 446 00:25:29,720 --> 00:25:33,600 Speaker 4: on a certain dimension. Some people came over the term 447 00:25:33,680 --> 00:25:37,399 Speaker 4: smart data. It's not smart, I mean, just it's just, 448 00:25:37,600 --> 00:25:41,480 Speaker 4: you know, a reflection of the research and the dimensions 449 00:25:41,480 --> 00:25:42,000 Speaker 4: of returns. 450 00:25:42,000 --> 00:26:00,359 Speaker 3: You know, something that I'm really interested in when it 451 00:26:00,520 --> 00:26:03,679 Speaker 3: comes to markets particularly, I would say over the last 452 00:26:04,000 --> 00:26:08,600 Speaker 3: fifteen years since the Great Financial Crisis, small caps have 453 00:26:08,760 --> 00:26:13,520 Speaker 3: certainly not provided any sort of superior risk adjusted returns 454 00:26:13,560 --> 00:26:16,200 Speaker 3: to large caps, and you can see that on basically 455 00:26:16,240 --> 00:26:21,359 Speaker 3: any chart. And growth companies year after year, you know, 456 00:26:21,400 --> 00:26:24,560 Speaker 3: by the traditional metrics of what we call growth and value, 457 00:26:24,560 --> 00:26:27,000 Speaker 3: and I know people sometimes try to redefine these to 458 00:26:27,760 --> 00:26:31,080 Speaker 3: allow them to put in VideA in their value fund. Clearly, 459 00:26:31,160 --> 00:26:34,560 Speaker 3: growth has been outperforming for a long time, and part 460 00:26:34,560 --> 00:26:36,720 Speaker 3: of the reason it seems very obvious to me that 461 00:26:36,800 --> 00:26:40,640 Speaker 3: these big tech stocks have done so well is because 462 00:26:40,920 --> 00:26:44,120 Speaker 3: the companies have all done extraordinarily well and beating earnings 463 00:26:44,160 --> 00:26:47,560 Speaker 3: expectations year after year after year. Does this pose a 464 00:26:47,640 --> 00:26:52,399 Speaker 3: problem for a sort of factor oriented investor. When the 465 00:26:52,480 --> 00:26:57,720 Speaker 3: fundamentals of one sector, the real fundamentals, not the stock performance, 466 00:26:58,640 --> 00:27:04,400 Speaker 3: produced these abnormal periods of profitability growth. 467 00:27:04,640 --> 00:27:06,760 Speaker 5: Well, I don't know how I abnormal they are. So 468 00:27:07,480 --> 00:27:11,560 Speaker 5: the instance of all these dimensions of returns is that 469 00:27:11,600 --> 00:27:15,480 Speaker 5: they're risky. There is, the results are highly uncertain over 470 00:27:15,520 --> 00:27:19,520 Speaker 5: any finite period of any period of time, so they 471 00:27:19,520 --> 00:27:21,800 Speaker 5: can do poorly for long periods of time. They can 472 00:27:21,840 --> 00:27:25,280 Speaker 5: also go away. If there's too many people jump on things, 473 00:27:25,480 --> 00:27:28,240 Speaker 5: it can cause them to go away. So it's possible, 474 00:27:28,320 --> 00:27:31,800 Speaker 5: for example, then interest in small stocks and interest in 475 00:27:31,920 --> 00:27:35,680 Speaker 5: value stocks killd thes size and the value premiums that 476 00:27:35,760 --> 00:27:40,040 Speaker 5: existed in the historical data. That's quite possible. Pricing of 477 00:27:40,080 --> 00:27:43,359 Speaker 5: securities is no more than supply and demand, So if 478 00:27:43,359 --> 00:27:46,000 Speaker 5: the demand goes up and the price goes up with it, 479 00:27:46,520 --> 00:27:50,800 Speaker 5: then you can see these premiums disappear. It's very difficult 480 00:27:50,840 --> 00:27:53,920 Speaker 5: to unravel the story in the data because there's. 481 00:27:53,720 --> 00:27:58,520 Speaker 6: So much ensutancy associated, so much volatility associated with prices 482 00:27:58,920 --> 00:28:04,120 Speaker 6: and returns. But these are always possibilities that these dimensions 483 00:28:04,160 --> 00:28:07,520 Speaker 6: of risk are no longer compensated because people don't feel 484 00:28:07,560 --> 00:28:08,320 Speaker 6: them anymore. 485 00:28:08,720 --> 00:28:11,239 Speaker 5: They jump into them if they think the returns out 486 00:28:12,320 --> 00:28:16,000 Speaker 5: are better. That's always been a possibility, Conferntion, and I 487 00:28:16,000 --> 00:28:18,440 Speaker 5: pointed that out in the initial papers we wrote on 488 00:28:18,840 --> 00:28:20,000 Speaker 5: the dimensions of risk. 489 00:28:20,720 --> 00:28:24,600 Speaker 3: So, just to press on this point further, small companies 490 00:28:24,640 --> 00:28:28,560 Speaker 3: are always going to have certain types of risks. Low 491 00:28:28,600 --> 00:28:31,239 Speaker 3: liquidity stocks are always going to have certain types of 492 00:28:31,320 --> 00:28:34,880 Speaker 3: risks that don't exist in high liquidity stocks. But when 493 00:28:34,880 --> 00:28:38,720 Speaker 3: you think about these factors, these do not strike you 494 00:28:38,840 --> 00:28:42,600 Speaker 3: as iron laws of how markets work that you will 495 00:28:42,640 --> 00:28:47,120 Speaker 3: at some point get compensated for taking on these risks 496 00:28:47,120 --> 00:28:48,040 Speaker 3: into your portfolio. 497 00:28:48,640 --> 00:28:51,800 Speaker 5: Well listen. And then the mixing and trading costs there, 498 00:28:51,880 --> 00:28:55,960 Speaker 5: So there are differential trading costs and different kinds of assets, 499 00:28:55,960 --> 00:28:59,280 Speaker 5: different transactions costs. Those are part of what you may 500 00:28:59,720 --> 00:29:03,080 Speaker 5: played play the game. In principle, it tract from the price. 501 00:29:02,880 --> 00:29:06,760 Speaker 6: Of the prices of the stocks. But I'm not sure 502 00:29:06,880 --> 00:29:09,200 Speaker 6: about what your question was actually. 503 00:29:10,160 --> 00:29:14,840 Speaker 3: Basically the idea that at any given point you will 504 00:29:14,880 --> 00:29:19,120 Speaker 3: be compensated for the risks of smaller, less liquid stocks. 505 00:29:19,680 --> 00:29:23,040 Speaker 3: That's not a necessarily a permanent characteristic of the market. 506 00:29:23,360 --> 00:29:25,440 Speaker 5: Well, it was, it was always there was always a 507 00:29:25,440 --> 00:29:29,080 Speaker 5: dimension of risk, which means this volatility associated with it. 508 00:29:29,200 --> 00:29:33,360 Speaker 5: So through the historically, during the periods when on the 509 00:29:33,480 --> 00:29:36,600 Speaker 5: over the long term small stocks did very well, there 510 00:29:36,600 --> 00:29:40,280 Speaker 5: were always periods when they didn't within those periods, within 511 00:29:40,320 --> 00:29:43,960 Speaker 5: the periods of good, good, good return. So that's always true. 512 00:29:44,000 --> 00:29:46,920 Speaker 5: So there always been periods when stocks did worse than 513 00:29:47,640 --> 00:29:51,480 Speaker 5: bills through a long period of that in the thirties, 514 00:29:51,520 --> 00:29:54,280 Speaker 5: forties all the way up to the fifties. So these 515 00:29:54,320 --> 00:29:57,520 Speaker 5: are just dimensions of risk and return basically, and risk 516 00:29:57,600 --> 00:29:58,120 Speaker 5: means you. 517 00:29:58,080 --> 00:30:01,400 Speaker 4: Can mose will point out a kind of the direction 518 00:30:01,400 --> 00:30:03,800 Speaker 4: in your head. It is what we believe is at 519 00:30:03,840 --> 00:30:05,120 Speaker 4: the end of the day, you need to come up 520 00:30:05,120 --> 00:30:09,720 Speaker 4: with sensible portfolios and well diversified, low cost and so forth. 521 00:30:10,200 --> 00:30:12,600 Speaker 4: And when we started the firm, you know, we built 522 00:30:12,600 --> 00:30:14,120 Speaker 4: it on the idea that you ought to have large 523 00:30:14,120 --> 00:30:17,640 Speaker 4: and small cap stocks in your portfolio, not just large cap. 524 00:30:18,280 --> 00:30:22,600 Speaker 4: Our first clients were large institutional clients and they were 525 00:30:22,640 --> 00:30:26,360 Speaker 4: only holding the stocks of bigger companies because they were 526 00:30:26,400 --> 00:30:29,160 Speaker 4: trying to the hired managers to how guests the market. 527 00:30:29,240 --> 00:30:32,040 Speaker 4: And you can't build a business, much of a business 528 00:30:32,480 --> 00:30:36,240 Speaker 4: trying to pick the winners of the small caps because 529 00:30:36,280 --> 00:30:40,480 Speaker 4: you can't buy enough of them to create a profitable 530 00:30:40,480 --> 00:30:43,840 Speaker 4: business or it's hard to anyway. So the thrust wasn't 531 00:30:43,880 --> 00:30:47,080 Speaker 4: so much that we guarantee your higher returns. The thrust 532 00:30:47,200 --> 00:30:50,080 Speaker 4: is you ought to have a well diversified portfolio, and 533 00:30:50,640 --> 00:30:54,760 Speaker 4: our view how to include a significant chunk of small cap. 534 00:30:56,040 --> 00:30:59,680 Speaker 2: David you highlighted earlier the importance of data in modern 535 00:30:59,720 --> 00:31:02,960 Speaker 2: final and that definitely comes through in the documentary. The 536 00:31:03,040 --> 00:31:06,400 Speaker 2: idea that a lot of these studies and theories went 537 00:31:06,560 --> 00:31:09,720 Speaker 2: hand in hand with the development of to Gene's point, 538 00:31:09,840 --> 00:31:13,040 Speaker 2: you know, computers and the ability to actually track more 539 00:31:13,080 --> 00:31:18,160 Speaker 2: information and crunch it more efficiently. Nowadays, it kind of 540 00:31:18,200 --> 00:31:22,080 Speaker 2: feels like we're drowning in data. Almost everything is tracked. 541 00:31:22,600 --> 00:31:27,960 Speaker 2: There's artificial intelligence generative AI, all this stuff we could use. 542 00:31:28,840 --> 00:31:32,520 Speaker 2: Do you see any new interesting ways of using that 543 00:31:32,720 --> 00:31:37,120 Speaker 2: data or any interesting ways that data is being translated 544 00:31:37,240 --> 00:31:41,400 Speaker 2: into either new financial theories or investment strategies. 545 00:31:41,720 --> 00:31:45,479 Speaker 4: Well, you know, Jeans you is the market reflects all 546 00:31:45,480 --> 00:31:49,720 Speaker 4: available information. That's kind of the implication of efficient markets, 547 00:31:51,040 --> 00:31:54,040 Speaker 4: and it was these AI programs so forth. I mean, 548 00:31:54,080 --> 00:31:58,360 Speaker 4: they have vast amounts of data, but no AI algorithm 549 00:31:58,760 --> 00:32:02,960 Speaker 4: can reflect all available information. So even though they have 550 00:32:03,000 --> 00:32:06,520 Speaker 4: lots of information, there's still lots to get reflected, seemingly 551 00:32:06,600 --> 00:32:08,160 Speaker 4: in stocking bond prices. 552 00:32:08,640 --> 00:32:12,080 Speaker 5: Looking at it from the academic side, what's happened with 553 00:32:12,200 --> 00:32:16,040 Speaker 5: the coming up so many big databases that people do 554 00:32:16,120 --> 00:32:20,040 Speaker 5: lots of research, is that research and finances expanded. There 555 00:32:20,120 --> 00:32:22,040 Speaker 5: used to be just a few of us still doing 556 00:32:22,080 --> 00:32:25,480 Speaker 5: it in the sixties and seventies. Now we have big 557 00:32:25,920 --> 00:32:30,880 Speaker 5: finance departments and almost every school all with people who 558 00:32:30,920 --> 00:32:33,400 Speaker 5: want to do work. Most of it are work on 559 00:32:33,680 --> 00:32:37,640 Speaker 5: lots of it work on market. So where there was 560 00:32:38,520 --> 00:32:42,000 Speaker 5: well basically one journal in this in the sixties, there 561 00:32:42,080 --> 00:32:44,560 Speaker 5: was all open to this kind of stuff. Now you 562 00:32:44,600 --> 00:32:46,440 Speaker 5: have four or five of them that are all all 563 00:32:46,520 --> 00:32:49,920 Speaker 5: pretty good. No coming up with no stuff, publishing three 564 00:32:50,000 --> 00:32:52,720 Speaker 5: or four times a year. So there's been an explosion 565 00:32:52,880 --> 00:32:56,640 Speaker 5: of research and uses all these new data, and that's 566 00:32:56,640 --> 00:32:59,920 Speaker 5: been to the plus. I think, I really when I 567 00:33:00,320 --> 00:33:03,400 Speaker 5: and my young people, I say, boy, in the old days, 568 00:33:03,440 --> 00:33:05,360 Speaker 5: it was easy. When I was coming up, it was 569 00:33:05,400 --> 00:33:08,240 Speaker 5: like shooting fishing in barrow. Nobody was doing anything, so 570 00:33:08,280 --> 00:33:11,240 Speaker 5: everything he did was new. Now it's much more difficult, 571 00:33:11,400 --> 00:33:14,160 Speaker 5: that much more precedent about what's been done and what 572 00:33:14,280 --> 00:33:15,200 Speaker 5: hasn't been done. 573 00:33:15,640 --> 00:33:20,520 Speaker 3: You started this conversation by talking about your initial problems, 574 00:33:20,560 --> 00:33:24,440 Speaker 3: which is that when you're identifying historical patterns, it's easy 575 00:33:24,480 --> 00:33:27,479 Speaker 3: to find something that works in the sample, and then 576 00:33:27,520 --> 00:33:29,560 Speaker 3: it doesn't work out of sample. So I could probably 577 00:33:29,640 --> 00:33:33,040 Speaker 3: come up with some story that tickers that start with 578 00:33:33,080 --> 00:33:36,400 Speaker 3: the letter P tend to outperform on Tuesdays, and I 579 00:33:36,400 --> 00:33:41,360 Speaker 3: could find some chart that shows that absolutely for years 580 00:33:41,400 --> 00:33:43,720 Speaker 3: and years and years is the case. And then of 581 00:33:43,760 --> 00:33:46,240 Speaker 3: course you know that's totally made up, and so then 582 00:33:46,960 --> 00:33:49,880 Speaker 3: it doesn't work. And we've seen this explosion of other factors. 583 00:33:49,960 --> 00:33:52,200 Speaker 3: You have your three factors, but people are coming up 584 00:33:52,200 --> 00:33:55,320 Speaker 3: with all kinds of factors, and you've added factors, et cetera. 585 00:33:55,800 --> 00:33:59,080 Speaker 3: When do you say, like a factor loses legitimacy. It's like, 586 00:33:59,160 --> 00:34:02,200 Speaker 3: you know what, this was p hacked. This turned out 587 00:34:02,240 --> 00:34:05,760 Speaker 3: to be. It turned out that actually it doesn't really 588 00:34:05,800 --> 00:34:08,120 Speaker 3: work out of sample after a long enough time. And 589 00:34:08,160 --> 00:34:10,800 Speaker 3: in my mind, I am going back to say value 590 00:34:10,880 --> 00:34:14,680 Speaker 3: versus growth or small versus big. Here is there a 591 00:34:14,760 --> 00:34:20,000 Speaker 3: period at which if growth keeps out performing value, you say, actually, 592 00:34:20,680 --> 00:34:24,400 Speaker 3: that's not a real sustainable factor. It's not mean reverting, 593 00:34:24,520 --> 00:34:28,400 Speaker 3: and this was a the appearance of these excess returns 594 00:34:28,880 --> 00:34:31,040 Speaker 3: was a function of limited sample size. 595 00:34:32,120 --> 00:34:35,000 Speaker 5: Okay, So Kim French and I have always been very 596 00:34:35,040 --> 00:34:38,759 Speaker 5: sensitive so exactly this problem. So every time we did 597 00:34:38,800 --> 00:34:42,239 Speaker 5: a paper that seemed to have a new result discovering 598 00:34:42,239 --> 00:34:45,719 Speaker 5: in it, we would consciously extend the data backward in 599 00:34:45,760 --> 00:34:48,920 Speaker 5: time and see if the same pattern were observed, And 600 00:34:48,960 --> 00:34:51,720 Speaker 5: then we'd go international and see if the same pattern 601 00:34:51,840 --> 00:34:55,000 Speaker 5: was observed in the market. So we were very sensitive 602 00:34:55,040 --> 00:34:58,640 Speaker 5: to the precisely issue they're raising. It's a very important issue. 603 00:34:58,840 --> 00:35:01,560 Speaker 5: Not many people do that. They don't look at out 604 00:35:01,560 --> 00:35:04,640 Speaker 5: of sample data to see if it worked there. Now, 605 00:35:05,040 --> 00:35:07,640 Speaker 5: we only went forward when we found things that seemed 606 00:35:07,640 --> 00:35:10,799 Speaker 5: to work back looking backward in the time, which is 607 00:35:10,880 --> 00:35:13,760 Speaker 5: one way of going out of sample, and looking across markets, 608 00:35:14,040 --> 00:35:17,600 Speaker 5: which is another way of going out of sample. But 609 00:35:17,680 --> 00:35:22,840 Speaker 5: still it's possible that the discovery of the effect causes 610 00:35:22,880 --> 00:35:27,280 Speaker 5: people to move through it to do stuff that basically 611 00:35:27,320 --> 00:35:29,959 Speaker 5: makes it go away. And it takes a long time 612 00:35:30,000 --> 00:35:30,920 Speaker 5: before you can tell. 613 00:35:30,800 --> 00:35:33,160 Speaker 6: That that's true because of the basic nature of the 614 00:35:33,480 --> 00:35:36,600 Speaker 6: uncertainty of the whole process, the amount of uncertainty there 615 00:35:36,640 --> 00:35:39,440 Speaker 6: is about the evolution of prices. 616 00:35:39,880 --> 00:35:41,320 Speaker 5: There's really no way to get around that. 617 00:35:41,480 --> 00:35:43,719 Speaker 8: So we won't know what our life and my life 618 00:35:44,080 --> 00:35:46,759 Speaker 8: my life time anyway, but I meany six years old, 619 00:35:47,400 --> 00:35:49,960 Speaker 8: we won't know my lifetime whether the value bringium of 620 00:35:50,040 --> 00:35:53,439 Speaker 8: the size meanium have actually gone away, because you still 621 00:35:53,440 --> 00:35:55,839 Speaker 8: don't have enough data to come to that, to come 622 00:35:55,880 --> 00:35:56,799 Speaker 8: to that conclusion. 623 00:35:57,560 --> 00:36:01,160 Speaker 4: Well, also, let me add one additional When the Gene 624 00:36:01,200 --> 00:36:04,840 Speaker 4: and Ken did did all his great research, they have 625 00:36:04,960 --> 00:36:08,239 Speaker 4: the data there that jumps out of here, and one 626 00:36:08,239 --> 00:36:10,840 Speaker 4: of the questions was always why would it be there? 627 00:36:11,520 --> 00:36:15,040 Speaker 4: And you can go through the algebra why low price 628 00:36:15,080 --> 00:36:18,880 Speaker 4: talks have higher average returns than high price talks. It 629 00:36:18,880 --> 00:36:22,399 Speaker 4: seems sensible that there would be that low price talks 630 00:36:22,480 --> 00:36:26,320 Speaker 4: might have higher expector returns because maybe because they're riskier. 631 00:36:28,120 --> 00:36:31,200 Speaker 2: Gene, towards the end of the documentary, just on the 632 00:36:31,239 --> 00:36:35,600 Speaker 2: notion of going forward, you kind of talk about what's 633 00:36:35,719 --> 00:36:39,680 Speaker 2: next in modern finance, and you make the point that 634 00:36:39,800 --> 00:36:43,920 Speaker 2: we are not making these sort of quantum academic jumps 635 00:36:44,080 --> 00:36:47,480 Speaker 2: as we did in the nineteen seventies, and that someone 636 00:36:47,560 --> 00:36:51,279 Speaker 2: needs to come up with a new innovation, a new 637 00:36:51,320 --> 00:36:55,640 Speaker 2: burst forward. But you don't really know who that might be. 638 00:36:56,920 --> 00:36:59,640 Speaker 2: Do you have any sense of where people should be 639 00:36:59,760 --> 00:37:03,400 Speaker 2: look looking for the next big thing in modern finance 640 00:37:03,520 --> 00:37:05,200 Speaker 2: or modern financial theory. 641 00:37:05,960 --> 00:37:10,239 Speaker 5: That's again excellent question. But I think the answer is 642 00:37:10,520 --> 00:37:13,319 Speaker 5: all that stuff is basically unpredictable. You don't know where 643 00:37:13,360 --> 00:37:18,719 Speaker 5: the new direction is until somebody discovers it, and where 644 00:37:18,800 --> 00:37:22,160 Speaker 5: people think it might be almost always turns out to 645 00:37:22,160 --> 00:37:25,160 Speaker 5: be the wrong, wrong, wrong place. Not that you shouldn't 646 00:37:25,160 --> 00:37:28,080 Speaker 5: do it, but simply this is a very difficult task. 647 00:37:28,800 --> 00:37:34,439 Speaker 5: So the question is excellent. The answer, it's unavoidably vague. 648 00:37:35,000 --> 00:37:39,000 Speaker 3: Fair enough answer, there's nothing. If if a young student 649 00:37:39,080 --> 00:37:40,960 Speaker 3: came to you and said, hey, i'm looking you know 650 00:37:41,160 --> 00:37:43,360 Speaker 3: at eighty six, you might not want to dive into 651 00:37:43,400 --> 00:37:45,279 Speaker 3: something new, but there's nothing. He's like, oh, yeah, I'm 652 00:37:45,280 --> 00:37:47,880 Speaker 3: sort of curious about that. You should try to pursue 653 00:37:47,920 --> 00:37:51,160 Speaker 3: a write of paper. There's nothing that comes to mind 654 00:37:51,320 --> 00:37:54,839 Speaker 3: that sort of you would suggest a young researcher make 655 00:37:54,880 --> 00:37:56,000 Speaker 3: a stab at Well. 656 00:37:56,600 --> 00:37:59,840 Speaker 5: The question we've started with was what's the next. 657 00:37:59,640 --> 00:38:01,360 Speaker 3: Big Yeah, right, right, Okay. 658 00:38:01,480 --> 00:38:04,400 Speaker 5: It changes the world. That's much more diffing. 659 00:38:05,040 --> 00:38:06,480 Speaker 4: Sure, it's the next. 660 00:38:06,440 --> 00:38:09,600 Speaker 5: Research wrinkle that we can do to extend that extends 661 00:38:09,640 --> 00:38:10,200 Speaker 5: the world. 662 00:38:10,000 --> 00:38:11,120 Speaker 4: A little bit fair enough. 663 00:38:11,160 --> 00:38:15,000 Speaker 5: That's mostly what goes on research, the small little steps 664 00:38:15,040 --> 00:38:19,120 Speaker 5: forward and sometimes little steps backwards. Stuff doesn't work out. 665 00:38:19,960 --> 00:38:22,920 Speaker 2: Since we have gene fauma here, I cannot resist asking 666 00:38:23,000 --> 00:38:27,319 Speaker 2: a sort of thought experiment question, But what would be 667 00:38:27,440 --> 00:38:32,719 Speaker 2: an EMH interpretation of the cryptocurrency market? Can you look 668 00:38:32,719 --> 00:38:34,880 Speaker 2: at it through an EMH lens? 669 00:38:35,520 --> 00:38:39,880 Speaker 5: I was wondering when you're come to that. But cryptocurrency 670 00:38:39,880 --> 00:38:43,520 Speaker 5: gives me all kinds of problems because like bitcoin is 671 00:38:43,560 --> 00:38:47,799 Speaker 5: the only one I'm roughly familiar with, but nobody can 672 00:38:47,880 --> 00:38:52,840 Speaker 5: explain why it survives because basically it's the old monetary 673 00:38:52,880 --> 00:38:56,439 Speaker 5: theory says that something that has a highly variable real 674 00:38:56,560 --> 00:39:01,120 Speaker 5: value can't be used as the medium of of exchange 675 00:39:01,360 --> 00:39:04,240 Speaker 5: because people won't want to deal with it. So, for example, 676 00:39:04,239 --> 00:39:07,280 Speaker 5: of business that doesn't want to do business in terms 677 00:39:07,280 --> 00:39:10,720 Speaker 5: of bitcoin because the variation in the price of bitcoin 678 00:39:10,760 --> 00:39:15,000 Speaker 5: itself can knot the company out of business. So then 679 00:39:15,040 --> 00:39:19,360 Speaker 5: the question becomes, who does want to use bitcoin? Historical 680 00:39:19,400 --> 00:39:22,760 Speaker 5: monetary theories I learned it it's not capable of answering 681 00:39:23,120 --> 00:39:26,200 Speaker 5: that question, so it would have predicted and I'm still 682 00:39:26,239 --> 00:39:29,239 Speaker 5: predicting that it'll bust. It it'll bust. At some point 683 00:39:29,280 --> 00:39:32,560 Speaker 5: people will say no, that's it, and they'll stop piling 684 00:39:32,760 --> 00:39:35,640 Speaker 5: piling into it, and then the market that marcro will 685 00:39:35,680 --> 00:39:39,600 Speaker 5: just disappear. But we'll see if it survives. We need 686 00:39:39,640 --> 00:39:42,760 Speaker 5: a whole theory to explain how and why. 687 00:39:43,320 --> 00:39:45,920 Speaker 2: That sounds suspiciously like you're saying it's in a bubble. 688 00:39:47,080 --> 00:39:52,440 Speaker 5: Oh I'm hoping it's in what I'm saying. 689 00:39:53,560 --> 00:39:57,480 Speaker 4: Well, I think maybe that he's also saying that if 690 00:39:57,520 --> 00:40:01,200 Speaker 4: crypto is going to survive, because it has value right 691 00:40:01,239 --> 00:40:07,919 Speaker 4: now and it could maybe someday, you can do transactions 692 00:40:08,000 --> 00:40:10,560 Speaker 4: cheaper than they can with master cards. 693 00:40:10,640 --> 00:40:13,880 Speaker 5: So that's that's that's a good, good point, dude. Because 694 00:40:13,960 --> 00:40:18,040 Speaker 5: there's the difference between the medium of exchange and the 695 00:40:18,080 --> 00:40:20,960 Speaker 5: method of exchange. So the method of exchange is how 696 00:40:21,000 --> 00:40:23,880 Speaker 5: do you carry out the transactions? The medium of exchange 697 00:40:23,920 --> 00:40:26,120 Speaker 5: is what do you put into it in order to 698 00:40:26,160 --> 00:40:30,240 Speaker 5: carry out the transactions. So the question is about the methods. 699 00:40:30,400 --> 00:40:31,920 Speaker 5: The methods evolve all the time. 700 00:40:32,080 --> 00:40:35,080 Speaker 6: So we have a central bank method now that we 701 00:40:35,520 --> 00:40:39,160 Speaker 6: use pretty much for every everything in the US, But 702 00:40:39,440 --> 00:40:42,680 Speaker 6: the blockchain is an alternative kind of mechanism. 703 00:40:43,000 --> 00:40:45,480 Speaker 5: What you put into it can be anything it can 704 00:40:45,520 --> 00:40:49,960 Speaker 5: be can be bitcoin, or it can be dollars. Does 705 00:40:50,000 --> 00:40:52,960 Speaker 5: it didn't really matter? So those are two different things. 706 00:40:53,239 --> 00:40:58,680 Speaker 5: So people worry that a system where a central bank 707 00:40:59,360 --> 00:41:02,880 Speaker 5: manages the into transactions, which is the system we have, 708 00:41:03,680 --> 00:41:07,239 Speaker 5: is too open to manipulation by the government, and that 709 00:41:07,360 --> 00:41:09,680 Speaker 5: the blockchain avoids it. But then it turns out that 710 00:41:09,680 --> 00:41:14,719 Speaker 5: the blockchain is not scalable intent its complication goes up 711 00:41:14,800 --> 00:41:19,560 Speaker 5: basically exponentially as you as it handles more transactions, so 712 00:41:19,600 --> 00:41:23,480 Speaker 5: that that's not the answer to the method of exchange problem. 713 00:41:23,719 --> 00:41:25,880 Speaker 5: I mean, that's something people are struggling with. 714 00:41:27,040 --> 00:41:29,200 Speaker 2: All Right, David and Gene, we're going to have to 715 00:41:29,400 --> 00:41:31,399 Speaker 2: leave it there, But thank you so much for coming 716 00:41:31,440 --> 00:41:33,760 Speaker 2: on odd Lots. It was a real pleasure to speak 717 00:41:33,800 --> 00:41:35,960 Speaker 2: with you both. And congrats on the movie. 718 00:41:36,160 --> 00:41:37,120 Speaker 4: Oh great, great, Thanks. 719 00:41:37,640 --> 00:41:52,000 Speaker 9: It was really a lot of fun, Joe. 720 00:41:52,000 --> 00:41:54,840 Speaker 2: That was really fun, Fama, especially with someone I always 721 00:41:54,840 --> 00:41:57,560 Speaker 2: wanted to speak to. I do have to say, you know, 722 00:41:57,600 --> 00:41:59,719 Speaker 2: I mentioned earlier, the way you feel about the term 723 00:41:59,719 --> 00:42:02,360 Speaker 2: prem is probably the way I feel about the efficient 724 00:42:02,400 --> 00:42:06,880 Speaker 2: markets hypothesis. And I recognize it's a theory that exists, 725 00:42:06,920 --> 00:42:10,080 Speaker 2: but I guess I'm not sure how useful. It is 726 00:42:10,120 --> 00:42:13,880 Speaker 2: to basically say that the average investor can match the 727 00:42:13,920 --> 00:42:17,040 Speaker 2: average return of the market. Like, does that lead anywhere? 728 00:42:17,120 --> 00:42:21,200 Speaker 3: Yeah, yeah, it absolutely leads somewhere. It means that you 729 00:42:21,719 --> 00:42:24,799 Speaker 3: almost certainly shouldn't try, and that if you try, you 730 00:42:24,840 --> 00:42:29,040 Speaker 3: will probably end up making mistakes. I mean, no, it's 731 00:42:29,080 --> 00:42:30,360 Speaker 3: such a depressing no. 732 00:42:30,440 --> 00:42:32,799 Speaker 2: I think the view of human capability, I. 733 00:42:32,719 --> 00:42:35,880 Speaker 3: Think this is one of the most useful maxims in 734 00:42:35,960 --> 00:42:40,479 Speaker 3: finance because even if it's not formally true, right, even 735 00:42:40,480 --> 00:42:43,960 Speaker 3: if there are slight variabilities, et cetera, I do think 736 00:42:44,000 --> 00:42:47,800 Speaker 3: it seems very clear that the vast majority of people, 737 00:42:47,880 --> 00:42:52,000 Speaker 3: including many professionals, as the statistics have borne out, like, 738 00:42:52,280 --> 00:42:56,440 Speaker 3: can't actually generate superior returns. And so if the only 739 00:42:56,600 --> 00:42:59,120 Speaker 3: thing that we like, if the only use we get 740 00:42:59,160 --> 00:43:03,160 Speaker 3: out of the efficient markets hypothesis is like do something 741 00:43:03,200 --> 00:43:05,920 Speaker 3: else with your life than trying to beat the market. 742 00:43:06,239 --> 00:43:08,800 Speaker 3: That sounds like wonderful advice that I think most people 743 00:43:08,800 --> 00:43:09,319 Speaker 3: should heed. 744 00:43:09,560 --> 00:43:11,640 Speaker 2: Should you say that on the All Thoughts podcast? 745 00:43:11,640 --> 00:43:13,200 Speaker 3: Well, that's the funny thing. It's like, why are we 746 00:43:13,280 --> 00:43:16,880 Speaker 3: all here? I mean, this is like the existential question 747 00:43:17,000 --> 00:43:22,319 Speaker 3: of everything, because, like my interpretation of Jane's answers is 748 00:43:22,400 --> 00:43:25,680 Speaker 3: basically a recurring series of yes, it's priced in, Yes 749 00:43:25,719 --> 00:43:28,120 Speaker 3: it's priced in, and yes it's priced in. Yes it's priced in. 750 00:43:28,760 --> 00:43:32,520 Speaker 3: And so I do have this existential question about we 751 00:43:32,680 --> 00:43:36,600 Speaker 3: support this news organization that supports an industry, and I 752 00:43:36,680 --> 00:43:39,200 Speaker 3: talk about this stuff all the time, and then it's like. 753 00:43:39,920 --> 00:43:43,759 Speaker 2: Why I think I'm closer to David's position on this, 754 00:43:44,000 --> 00:43:48,520 Speaker 2: where you know, true passive doesn't necessarily exist. There's sort 755 00:43:48,560 --> 00:43:51,759 Speaker 2: of a middle ground where you can have systematic approaches 756 00:43:52,280 --> 00:43:55,960 Speaker 2: but you're still making active decisions in the way you 757 00:43:56,040 --> 00:43:59,359 Speaker 2: either execute trades or you know, in the cost of 758 00:43:59,400 --> 00:44:02,319 Speaker 2: your investment and things like that. I think that's a 759 00:44:02,400 --> 00:44:05,799 Speaker 2: reasonable middle ground. I am not sure I am an 760 00:44:05,880 --> 00:44:10,200 Speaker 2: EMH fundamentalist camp just yet, but maybe you can convince me. 761 00:44:10,520 --> 00:44:13,799 Speaker 3: Yeah, you know, here's my This is not the weak form. 762 00:44:14,080 --> 00:44:17,600 Speaker 3: There's a definition of the weak form efficient market hypothesis. 763 00:44:17,719 --> 00:44:20,680 Speaker 3: What I would say is this, and I've actually given 764 00:44:20,719 --> 00:44:24,120 Speaker 3: this advice to other journalists, and I think this is 765 00:44:24,560 --> 00:44:27,800 Speaker 3: something that I could try to convince people of, which 766 00:44:27,840 --> 00:44:30,120 Speaker 3: is that if you look at the market and you 767 00:44:30,320 --> 00:44:35,160 Speaker 3: think that you identify some security or anything that seems 768 00:44:35,200 --> 00:44:38,760 Speaker 3: to you obviously mispriced. You should start with the presumption 769 00:44:38,800 --> 00:44:42,720 Speaker 3: you're missing something. It's very unlikely that you've just seen 770 00:44:42,840 --> 00:44:46,839 Speaker 3: something in the market that obviously you could profit from. 771 00:44:47,040 --> 00:44:50,399 Speaker 3: Occasionally happens in people have a thesis and something looks 772 00:44:50,400 --> 00:44:52,120 Speaker 3: clear and they make a lot of money. But I 773 00:44:52,160 --> 00:44:53,879 Speaker 3: think most of the time, if you see a line, 774 00:44:53,880 --> 00:44:56,440 Speaker 3: you're like, it shouldn't be there. You should start with 775 00:44:56,480 --> 00:45:00,160 Speaker 3: the assumption that the billions of dollars flowing through the 776 00:45:00,200 --> 00:45:03,080 Speaker 3: market didn't all miss something that you see as obvious. 777 00:45:03,200 --> 00:45:06,200 Speaker 2: Yeah, but there are people who outperform the market, and 778 00:45:06,239 --> 00:45:10,360 Speaker 2: it's a little bit like again tautological, I guess just 779 00:45:10,440 --> 00:45:12,600 Speaker 2: to hand wave it away and be like, oh, they 780 00:45:12,600 --> 00:45:13,040 Speaker 2: got lucky. 781 00:45:13,160 --> 00:45:16,719 Speaker 3: Yeah, right, but can you identify the people who right, 782 00:45:16,800 --> 00:45:19,040 Speaker 3: this is the problem? Like right, because yeah, and this 783 00:45:19,120 --> 00:45:22,560 Speaker 3: is why, this is why it's all these Maybe they're lucky. 784 00:45:22,320 --> 00:45:24,360 Speaker 2: In choosing the lucky investment managers. 785 00:45:24,440 --> 00:45:24,960 Speaker 4: How about that? 786 00:45:25,400 --> 00:45:27,440 Speaker 3: I mean, that's right, that's like, I mean, that's like, 787 00:45:27,600 --> 00:45:30,600 Speaker 3: you know, manager selection suffers from the exact same problem 788 00:45:30,640 --> 00:45:34,240 Speaker 3: with stock selection, the out of sample in sample bias. 789 00:45:34,560 --> 00:45:37,279 Speaker 3: This is why. But one thing I am curious about, 790 00:45:37,320 --> 00:45:40,319 Speaker 3: like when we are long dead and maybe the odd 791 00:45:40,360 --> 00:45:43,640 Speaker 3: lots franchise is so valuable that there's like, you know, 792 00:45:43,680 --> 00:45:46,120 Speaker 3: there's like new hosts of the podcast, right because they 793 00:45:46,120 --> 00:45:50,680 Speaker 3: want to continue it. Maybe they'll be alive long enough 794 00:45:50,719 --> 00:45:53,160 Speaker 3: to say, like, oh, turns out there's no small cat 795 00:45:53,200 --> 00:45:57,279 Speaker 3: premium after all. Because Jane opened up the possibility that, yeah, 796 00:45:57,560 --> 00:46:00,440 Speaker 3: we all of finance and economics suffer is from the 797 00:46:00,480 --> 00:46:04,160 Speaker 3: tragedy of small sample sizes. Like it's like this known phenomenon, 798 00:46:04,239 --> 00:46:07,080 Speaker 3: like the world is just getting started. Maybe one day 799 00:46:07,120 --> 00:46:09,759 Speaker 3: it'll be like, actually, turned out that wasn't really a thing, 800 00:46:09,800 --> 00:46:12,120 Speaker 3: but they'll probably be after all of our lifetimes. 801 00:46:12,400 --> 00:46:15,120 Speaker 2: In the long run, we're all dead. Since you mentioned it. 802 00:46:15,239 --> 00:46:19,640 Speaker 3: In the long run, all factors, all factors are suffer 803 00:46:19,719 --> 00:46:21,560 Speaker 3: from sample bias. 804 00:46:22,280 --> 00:46:24,920 Speaker 2: Since you mentioned the small cap stocks, there was this 805 00:46:24,960 --> 00:46:29,200 Speaker 2: little visual in the documentary where they showed a headline 806 00:46:29,280 --> 00:46:32,359 Speaker 2: from I think it was the early nineteen nineties, and 807 00:46:32,960 --> 00:46:37,360 Speaker 2: the headline was mutual funds offbeat theory by stock in 808 00:46:37,480 --> 00:46:40,719 Speaker 2: smaller firms, And I thought that was so funny and 809 00:46:40,880 --> 00:46:44,000 Speaker 2: kind of quaint because they're basically talking about gross stocks. 810 00:46:44,120 --> 00:46:46,960 Speaker 2: And you know, nowadays growth stocks are sort of an 811 00:46:46,960 --> 00:46:51,000 Speaker 2: accepted idea, but back then it was off beat and 812 00:46:51,120 --> 00:46:54,160 Speaker 2: offbeat theory, and it kind of shows just how much 813 00:46:54,239 --> 00:46:56,799 Speaker 2: financial theory is embedded in the market now that we 814 00:46:56,920 --> 00:46:59,920 Speaker 2: take for granted. But you know, a decade ago, or 815 00:47:00,040 --> 00:47:03,120 Speaker 2: two decades ago or five decades ago, people didn't know 816 00:47:03,160 --> 00:47:03,799 Speaker 2: it well. 817 00:47:03,840 --> 00:47:07,080 Speaker 3: And just on this one point, it is interesting too 818 00:47:07,880 --> 00:47:11,160 Speaker 3: that now if someone says growth stocks, you think really 819 00:47:11,200 --> 00:47:13,640 Speaker 3: big companies. Yeah, And there was a time when if 820 00:47:13,640 --> 00:47:16,200 Speaker 3: someone said growth stocks, you'd think about really small companies 821 00:47:16,400 --> 00:47:19,399 Speaker 3: and that big companies were supposed to grow slowly. And 822 00:47:19,480 --> 00:47:21,120 Speaker 3: so this is kind of what I wonder about, like 823 00:47:21,160 --> 00:47:25,200 Speaker 3: these like our fundamental realities of business changing, and could 824 00:47:25,200 --> 00:47:30,239 Speaker 3: those fundamental realities of business changing change fundamental aspects of 825 00:47:30,280 --> 00:47:34,439 Speaker 3: the stock market because we now have this era where 826 00:47:34,480 --> 00:47:37,840 Speaker 3: you have gigantic companies still putting up growth numbers that 827 00:47:38,080 --> 00:47:39,680 Speaker 3: in any time would be incredible. 828 00:47:40,239 --> 00:47:41,360 Speaker 2: All right, shall we leave it there. 829 00:47:41,560 --> 00:47:42,200 Speaker 3: Let's leave it there. 830 00:47:42,320 --> 00:47:44,880 Speaker 2: This has been another episode of the All Thoughts podcast. 831 00:47:44,960 --> 00:47:48,480 Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway and. 832 00:47:48,440 --> 00:47:51,160 Speaker 3: I'm Joe Wisenthal. You can follow me at The Stalwart. 833 00:47:51,560 --> 00:47:55,560 Speaker 3: Check out the new Errol Morris documentary Tune Out The 834 00:47:55,600 --> 00:47:57,920 Speaker 3: Noise That Talks about all of these things and the 835 00:47:57,960 --> 00:48:02,480 Speaker 3: beginnings of modern fire finance. Follow our producers Kerman Rodriguez 836 00:48:02,520 --> 00:48:05,279 Speaker 3: at Kerman armand dash Ol Bennett at Dashbot and kill 837 00:48:05,360 --> 00:48:08,600 Speaker 3: Brooks at Killebrooks. From our odd Lots content, go to 838 00:48:08,600 --> 00:48:11,719 Speaker 3: Bloomberg dot com slash odd lots, where we have a newsletter, 839 00:48:11,920 --> 00:48:14,680 Speaker 3: our episodes, and a blog and you can chat about 840 00:48:14,719 --> 00:48:19,680 Speaker 3: all of these topics, including endless circular discussions about market efficiency, 841 00:48:19,960 --> 00:48:23,759 Speaker 3: in our discord discord dot gg slash od lots. 842 00:48:23,680 --> 00:48:25,920 Speaker 2: And if you enjoy odd Lots, if you like it 843 00:48:25,960 --> 00:48:29,160 Speaker 2: when we in fact have an endless discussion about the 844 00:48:29,200 --> 00:48:32,600 Speaker 2: efficient markets hypothesis, then please leave us a positive review 845 00:48:32,680 --> 00:48:36,040 Speaker 2: on your favorite podcast platform. And remember, if you are 846 00:48:36,080 --> 00:48:38,839 Speaker 2: a Bloomberg subscriber, you can listen to all of our 847 00:48:38,880 --> 00:48:41,960 Speaker 2: episodes absolutely add free. All you need to do is 848 00:48:42,000 --> 00:48:45,120 Speaker 2: find the Bloomberg channel on Apple Podcasts and follow the 849 00:48:45,160 --> 00:49:04,040 Speaker 2: instructions there. Thanks for listening in