1 00:00:09,080 --> 00:00:12,440 Speaker 1: Hello, and welcome to another episode of the Odd Thoughts Podcast. 2 00:00:12,520 --> 00:00:16,640 Speaker 1: I'm Tracy Allaway and I'm Joe. Joe, what did you 3 00:00:16,680 --> 00:00:21,720 Speaker 1: study at college? Mmm? I'm already nervous about answering this 4 00:00:21,800 --> 00:00:24,599 Speaker 1: question because I don't I actually genuinely don't know where 5 00:00:24,600 --> 00:00:26,599 Speaker 1: you're going with it. Well, I also don't know what 6 00:00:26,640 --> 00:00:32,199 Speaker 1: you studied, so I'm genuinely curious. I studied international relations. 7 00:00:32,240 --> 00:00:35,440 Speaker 1: Actually I went at University of Texas. They called it government, 8 00:00:35,760 --> 00:00:38,400 Speaker 1: which is not really a thing anywhere else, but it 9 00:00:38,520 --> 00:00:40,479 Speaker 1: was kind of like their political science department. But I 10 00:00:40,520 --> 00:00:44,080 Speaker 1: focused on international relations. Okay, I swear this is a 11 00:00:44,159 --> 00:00:49,000 Speaker 1: complete coincidence, but I also studied international relations. Really, it's 12 00:00:49,040 --> 00:00:51,159 Speaker 1: funny that, like, of all this time I've known you, 13 00:00:51,240 --> 00:00:53,920 Speaker 1: this has never come up. No seriously, like for people 14 00:00:53,960 --> 00:00:56,040 Speaker 1: like who think who are listening, I think maybe we're 15 00:00:56,080 --> 00:00:59,160 Speaker 1: faking this or something. It's actually I don't. I genuinely 16 00:00:59,200 --> 00:01:01,320 Speaker 1: did not know that. About now people are thinking that 17 00:01:01,360 --> 00:01:03,880 Speaker 1: we just never talked to each other outside of this podcast. 18 00:01:03,960 --> 00:01:07,600 Speaker 1: We just we just only talk markets, no personal stuff. 19 00:01:07,800 --> 00:01:10,120 Speaker 1: The reason I was bringing it up was because I 20 00:01:10,160 --> 00:01:12,479 Speaker 1: was trying to think of a parallel with what we're 21 00:01:12,480 --> 00:01:15,160 Speaker 1: going to speak about in just a few minutes. Um, 22 00:01:15,160 --> 00:01:17,800 Speaker 1: And I was thinking, you know, in international relations, there 23 00:01:17,800 --> 00:01:22,360 Speaker 1: are these two dominant theories that govern how you think 24 00:01:22,400 --> 00:01:26,600 Speaker 1: about the world. Their realism and liberalism. Do you remember that. 25 00:01:28,160 --> 00:01:29,920 Speaker 1: I'm glad you didn't ask me to name them. I 26 00:01:29,920 --> 00:01:32,760 Speaker 1: would have remembered realism and I would have blanked on 27 00:01:32,800 --> 00:01:35,160 Speaker 1: the other one. But yes, that sounds right. Okay. So 28 00:01:35,240 --> 00:01:38,880 Speaker 1: realism is this theory that states and governments and people 29 00:01:38,920 --> 00:01:41,920 Speaker 1: are essentially self interested and you know, everyone's out to 30 00:01:41,959 --> 00:01:44,360 Speaker 1: get each other, and liberalism is, oh, actually we can 31 00:01:44,400 --> 00:01:48,840 Speaker 1: all get along and there's scope for cooperation to diametrically 32 00:01:48,960 --> 00:01:54,840 Speaker 1: opposed theories that completely govern that particular study. Um. Now, 33 00:01:54,960 --> 00:01:57,720 Speaker 1: the reason I'm bringing it up, it's because we are 34 00:01:57,760 --> 00:02:01,800 Speaker 1: going to talk about a similar parallel in economics. Can 35 00:02:01,840 --> 00:02:05,560 Speaker 1: you guess what it is? Uh? Why don't you just 36 00:02:05,600 --> 00:02:08,280 Speaker 1: tell me? I mean, I think, I think I know 37 00:02:08,280 --> 00:02:10,359 Speaker 1: where it's going. But I really like the way you're 38 00:02:10,360 --> 00:02:14,440 Speaker 1: taking this. So alright, So it's the efficient market hypothesis 39 00:02:14,639 --> 00:02:21,880 Speaker 1: versus behavioral economics. Yes, okay, so most people probably know this, 40 00:02:21,960 --> 00:02:26,080 Speaker 1: but the efficient market hypothesis basically says that you can't 41 00:02:26,200 --> 00:02:30,239 Speaker 1: beat the market, that it's a perfect reflection of the 42 00:02:30,280 --> 00:02:34,040 Speaker 1: information currently out there, in a perfect reflection of the 43 00:02:34,040 --> 00:02:37,399 Speaker 1: price that you should be paying for that information. Meanwhile, 44 00:02:37,720 --> 00:02:43,040 Speaker 1: behavioral economics basically suggests that human beings can be irrational 45 00:02:43,160 --> 00:02:45,040 Speaker 1: and we can get stuff wrong, and that means that 46 00:02:45,200 --> 00:02:48,200 Speaker 1: markets also can be irrational and can get stuff wrong. 47 00:02:48,560 --> 00:02:52,880 Speaker 1: So to pretty much diametrically opposed schools of thought. So 48 00:02:52,919 --> 00:02:56,320 Speaker 1: are we going to find out which one is correct today? No, 49 00:02:58,760 --> 00:03:01,119 Speaker 1: We're actually going to talk to someone who thinks they've 50 00:03:01,120 --> 00:03:07,840 Speaker 1: found a middle path between those two seemingly opposed schools 51 00:03:07,840 --> 00:03:11,000 Speaker 1: of thought. All right, I'm intrigued to who are we 52 00:03:11,040 --> 00:03:13,919 Speaker 1: talking to and what's their theory? Okay, I'm really excited 53 00:03:13,960 --> 00:03:16,680 Speaker 1: to bring on Andrew Low. He's an economist, he's a 54 00:03:16,680 --> 00:03:20,400 Speaker 1: long time m I T. Professor, and he's written well, 55 00:03:20,480 --> 00:03:23,720 Speaker 1: he's written several books, but most recently he has written 56 00:03:23,720 --> 00:03:37,040 Speaker 1: a book on exactly this topic. Andrew, thank you so 57 00:03:37,120 --> 00:03:41,040 Speaker 1: much for joining us. It's a pleasure, thanks for having me. So, 58 00:03:41,520 --> 00:03:44,040 Speaker 1: just going back to the efficient market hypothesis. I gave 59 00:03:44,080 --> 00:03:47,480 Speaker 1: a little snapshot of it, but maybe you could describe 60 00:03:47,480 --> 00:03:51,720 Speaker 1: it a little bit more and also perhaps explain how 61 00:03:51,840 --> 00:03:57,080 Speaker 1: it came to be a fundamental tenet of modern financial 62 00:03:57,600 --> 00:04:01,040 Speaker 1: uh theory, when everyone and seems to beat up on 63 00:04:01,080 --> 00:04:04,320 Speaker 1: it nowadays. Sure, well, you know, it's a really interesting 64 00:04:04,360 --> 00:04:09,080 Speaker 1: idea and it's the brainchild of two economists. Gene Fama 65 00:04:09,200 --> 00:04:12,040 Speaker 1: at the University of Chicago coined the term and came 66 00:04:12,120 --> 00:04:15,520 Speaker 1: up with the basic idea that in an efficient market, 67 00:04:15,920 --> 00:04:20,719 Speaker 1: prices fully reflect all available information. And so that's the case, 68 00:04:20,920 --> 00:04:24,240 Speaker 1: then you really can't beat the markets by using information 69 00:04:24,279 --> 00:04:27,560 Speaker 1: because it's already in the price and M. Paul Samuelson 70 00:04:27,640 --> 00:04:30,840 Speaker 1: was the other economist who contributed to this theory, and 71 00:04:31,040 --> 00:04:36,440 Speaker 1: his paper was titled proof that properly anticipated prices fluctuate randomly, 72 00:04:36,839 --> 00:04:39,960 Speaker 1: which is a very fancy way of saying that once 73 00:04:40,040 --> 00:04:43,960 Speaker 1: you incorporate all available information into prices, you don't know 74 00:04:43,960 --> 00:04:46,040 Speaker 1: where it's going to go, so you can't predict future 75 00:04:46,080 --> 00:04:49,599 Speaker 1: prices based upon where it is today. It seems to 76 00:04:49,640 --> 00:04:52,360 Speaker 1: me the efficient market hypothesis has come under a lot 77 00:04:52,360 --> 00:04:56,520 Speaker 1: of criticism in recent years. We've seen Nobel Prize winners 78 00:04:56,800 --> 00:04:59,560 Speaker 1: who have won for their work and sort of talking 79 00:04:59,560 --> 00:05:03,080 Speaker 1: about this more. The behavioral approach, which is very as 80 00:05:03,120 --> 00:05:06,360 Speaker 1: Tracy explained at the beginning, is sort of this opposite view, 81 00:05:06,920 --> 00:05:10,320 Speaker 1: But it still seems for all the criticism that efficient 82 00:05:10,360 --> 00:05:13,760 Speaker 1: markets has come under, it's still pretty hard to beat 83 00:05:13,800 --> 00:05:16,159 Speaker 1: the market. Like, it still seems like more or less 84 00:05:16,480 --> 00:05:19,800 Speaker 1: it's a pretty difficult task. Well, that was exactly the 85 00:05:19,839 --> 00:05:22,480 Speaker 1: conundrum that I was trying to figure out when trying 86 00:05:22,480 --> 00:05:25,240 Speaker 1: to sort through this particular theory versus all of the 87 00:05:25,320 --> 00:05:30,119 Speaker 1: various different critiques. The efficient market hypothesis actually works pretty well. 88 00:05:30,880 --> 00:05:33,680 Speaker 1: It is really hard to beat the market, and prices 89 00:05:33,720 --> 00:05:36,600 Speaker 1: do actually reflect a lot of information that's out there, 90 00:05:37,279 --> 00:05:41,000 Speaker 1: and so it really it's hard to reconcile the basic 91 00:05:41,160 --> 00:05:44,680 Speaker 1: ideas about efficient markets with all of the psychological and 92 00:05:44,720 --> 00:05:50,479 Speaker 1: behavioral anomalies that people like conoman diversity failure, and UH 93 00:05:50,600 --> 00:05:53,600 Speaker 1: and others have come up with to try to counteract 94 00:05:53,640 --> 00:05:57,600 Speaker 1: these various different ideas of efficiency. So walk us through 95 00:05:57,920 --> 00:06:00,480 Speaker 1: how you tackle that problem then, and the theory that 96 00:06:00,520 --> 00:06:04,360 Speaker 1: you came up with you call it adaptive markets. Right. 97 00:06:04,680 --> 00:06:09,159 Speaker 1: The basic idea is that there are elements of both 98 00:06:09,160 --> 00:06:13,000 Speaker 1: of these schools of thought that work well, but neither 99 00:06:13,440 --> 00:06:15,880 Speaker 1: is the complete picture. You really need both of them. 100 00:06:15,920 --> 00:06:22,000 Speaker 1: They're both important aspects of the same phenomenon, and the 101 00:06:22,279 --> 00:06:27,280 Speaker 1: idea behind adaptive markets is fairly straightforward. It basically says 102 00:06:27,360 --> 00:06:33,320 Speaker 1: that investors are highly competitive and adaptive, and therefore it 103 00:06:33,400 --> 00:06:35,400 Speaker 1: is tough to beat the market because lots of other 104 00:06:35,400 --> 00:06:38,520 Speaker 1: people are trying to do that. But it's not impossible 105 00:06:39,080 --> 00:06:42,000 Speaker 1: because every once in a while, markets aren't driven just 106 00:06:42,120 --> 00:06:47,120 Speaker 1: by logic and analysis, but they're also driven by human emotion. So, 107 00:06:47,200 --> 00:06:50,040 Speaker 1: for example, when the stock market goes down by ten 108 00:06:50,120 --> 00:06:53,479 Speaker 1: or a lot of people are going to start heading 109 00:06:53,520 --> 00:06:56,839 Speaker 1: for the exits. They're going to start unwinding their portfolios, 110 00:06:56,880 --> 00:06:59,960 Speaker 1: and that kind of a herd mentality can actually lead 111 00:07:00,160 --> 00:07:04,279 Speaker 1: two prices that don't fully reflect the information that's available 112 00:07:04,320 --> 00:07:06,640 Speaker 1: at that point in time, So, in other words, it 113 00:07:06,680 --> 00:07:11,080 Speaker 1: reflects emotion as opposed to fundamental valuations. The efficient market 114 00:07:11,160 --> 00:07:14,560 Speaker 1: hypothesis is a great way to explain market dynamics when 115 00:07:14,600 --> 00:07:17,840 Speaker 1: people are acting logically, but every once in a while 116 00:07:18,080 --> 00:07:21,280 Speaker 1: we freak out, and the freakout factor is where the 117 00:07:21,320 --> 00:07:25,040 Speaker 1: behavioral economists have their day. Both of these are important 118 00:07:25,080 --> 00:07:29,920 Speaker 1: aspects of market dynamics, but they don't always operate at 119 00:07:29,960 --> 00:07:33,960 Speaker 1: the same time, and it's really trying to understand which 120 00:07:34,040 --> 00:07:37,679 Speaker 1: part of these different phases are relevant at a given 121 00:07:37,720 --> 00:07:41,040 Speaker 1: point in time that the adaptive markets is focused on. 122 00:07:41,800 --> 00:07:45,280 Speaker 1: So I think that like anyone who looks at markets 123 00:07:45,720 --> 00:07:49,440 Speaker 1: can appreciate that there are times when sort of pure 124 00:07:49,440 --> 00:07:53,320 Speaker 1: emotion and animal spirits really take over, whether it's a panic, 125 00:07:53,520 --> 00:07:56,600 Speaker 1: whether it's in the stage of a bubble. But one 126 00:07:56,640 --> 00:07:58,920 Speaker 1: of the things that we've talked about a lot on 127 00:07:59,000 --> 00:08:01,800 Speaker 1: this podcast, as said, factors that even if you know 128 00:08:02,000 --> 00:08:04,480 Speaker 1: something as a bubble, or even if you know something's 129 00:08:04,480 --> 00:08:08,160 Speaker 1: a panic, it's really hard to know what stage you're 130 00:08:08,160 --> 00:08:11,000 Speaker 1: in and whether you're near a bottom or whether you're 131 00:08:11,040 --> 00:08:14,360 Speaker 1: you're near a top. So my question is, if you 132 00:08:14,440 --> 00:08:17,160 Speaker 1: know you know, you sort of thread this middle ground 133 00:08:17,240 --> 00:08:21,240 Speaker 1: where sometimes behavioral take takes over. Sometimes markets are based 134 00:08:21,280 --> 00:08:25,920 Speaker 1: on pure information. Does your theory help one get any 135 00:08:26,000 --> 00:08:31,000 Speaker 1: closer to actually, you know, maybe beating the market. Well, 136 00:08:31,040 --> 00:08:34,480 Speaker 1: it does, and I argue that those who do beat 137 00:08:34,480 --> 00:08:37,680 Speaker 1: the market today are using some form of this theory. 138 00:08:37,840 --> 00:08:43,240 Speaker 1: For example, hedge fund managers understand instinctively that market dynamics 139 00:08:43,360 --> 00:08:46,320 Speaker 1: change as a function of the flora and fauna of 140 00:08:46,360 --> 00:08:49,080 Speaker 1: the market ecology. In other words, they look at who 141 00:08:49,080 --> 00:08:51,600 Speaker 1: are the participants in any given market at a point 142 00:08:51,600 --> 00:08:56,199 Speaker 1: in time and they feel the the market dynamics as 143 00:08:56,240 --> 00:09:00,720 Speaker 1: a function of those various different participants. It really is 144 00:09:00,920 --> 00:09:03,560 Speaker 1: trying to understand markets from a more of a biological 145 00:09:03,600 --> 00:09:07,839 Speaker 1: perspective than a physical perspective. And uh, I think that 146 00:09:07,840 --> 00:09:10,959 Speaker 1: that kind of approach will requires us to collect very 147 00:09:11,000 --> 00:09:13,480 Speaker 1: different kinds of data from the ones that we're doing 148 00:09:13,559 --> 00:09:16,400 Speaker 1: right now, and if we had that data, we can 149 00:09:16,440 --> 00:09:19,080 Speaker 1: make much better predictions about where the market is going. 150 00:09:19,960 --> 00:09:22,360 Speaker 1: So what sort of data are you talking about? What 151 00:09:22,400 --> 00:09:25,280 Speaker 1: would be helpful just knowing who is and who isn't 152 00:09:25,320 --> 00:09:29,040 Speaker 1: participating in a particular market. Well, let me start by 153 00:09:29,160 --> 00:09:33,280 Speaker 1: giving you a different perspective. Imagine if you're an ecologist 154 00:09:33,440 --> 00:09:39,400 Speaker 1: being asked to study particular ecological niche say, the Amazon rainforest, 155 00:09:39,960 --> 00:09:42,680 Speaker 1: and let's suppose that you would like to save a 156 00:09:42,720 --> 00:09:46,719 Speaker 1: particular species in that ecology. How would you go about it. Well, 157 00:09:46,760 --> 00:09:50,040 Speaker 1: as an ecologist, you'd probably start by taking an inventory 158 00:09:50,080 --> 00:09:52,520 Speaker 1: of all of the different species, how they relate to 159 00:09:52,559 --> 00:09:55,720 Speaker 1: each other, what they eat, who they prey on, what 160 00:09:55,840 --> 00:09:59,040 Speaker 1: the various different food chain relationships are, what the environment 161 00:09:59,080 --> 00:10:01,720 Speaker 1: looks like and how it's changing over time. Once you 162 00:10:01,800 --> 00:10:05,160 Speaker 1: study all of those aspects of the environment and the 163 00:10:05,160 --> 00:10:08,400 Speaker 1: flora and the fauna. You can then start get identifying 164 00:10:08,920 --> 00:10:13,360 Speaker 1: key aspects of that system that require management in order 165 00:10:13,360 --> 00:10:17,160 Speaker 1: to preserve a given species or in order to highlight 166 00:10:17,200 --> 00:10:21,200 Speaker 1: a particular species. If you now take that same analogy 167 00:10:21,240 --> 00:10:24,880 Speaker 1: and apply it to the financial markets, you'd see that 168 00:10:25,080 --> 00:10:27,520 Speaker 1: what you want to start with is not just looking 169 00:10:27,559 --> 00:10:30,959 Speaker 1: at prices, but to understand who the buyers are, who 170 00:10:31,040 --> 00:10:34,280 Speaker 1: the sellers are, and not just that, but the nature 171 00:10:34,559 --> 00:10:37,840 Speaker 1: of the buying and the selling pension funds, broker dealers, 172 00:10:38,040 --> 00:10:41,560 Speaker 1: hedge fund managers, who the investors are, who the ultimate 173 00:10:41,640 --> 00:10:44,680 Speaker 1: buyers and sellers aren't, and what motivates them. Once you 174 00:10:44,800 --> 00:10:47,559 Speaker 1: understand the nature of the flora and fauna of the 175 00:10:47,600 --> 00:10:51,240 Speaker 1: financial markets, you can then start making predictions like, well, 176 00:10:51,280 --> 00:10:53,000 Speaker 1: if it turns out that pension funds are going to 177 00:10:53,080 --> 00:10:56,160 Speaker 1: be indexing and sticking to a particular asset allocation over 178 00:10:56,200 --> 00:10:58,320 Speaker 1: a period of time, then that means that they're going 179 00:10:58,400 --> 00:11:00,559 Speaker 1: to be submitting by orders when the market goes down 180 00:11:00,600 --> 00:11:02,880 Speaker 1: and submitting cell orders when the market goes up in 181 00:11:02,960 --> 00:11:06,480 Speaker 1: order to maintain that strategic asset allocation. You'd understand the 182 00:11:06,559 --> 00:11:10,680 Speaker 1: motivation for the various different species in that marketplace and 183 00:11:10,800 --> 00:11:13,120 Speaker 1: be able to make better predictions about how they would 184 00:11:13,120 --> 00:11:16,080 Speaker 1: react to certain kinds of market events. That that's the 185 00:11:16,120 --> 00:11:18,240 Speaker 1: kind of data that I think we need in order 186 00:11:18,280 --> 00:11:22,440 Speaker 1: to be able to analyze market dynamics. Now your book 187 00:11:22,480 --> 00:11:25,800 Speaker 1: and your theory is called adaptive market. If that data 188 00:11:25,840 --> 00:11:29,640 Speaker 1: were to be made available, presumably all of that would 189 00:11:29,640 --> 00:11:33,440 Speaker 1: then be incorporated back into price because people adapt would 190 00:11:33,480 --> 00:11:37,119 Speaker 1: that then require some sort of further metadata for investors 191 00:11:37,120 --> 00:11:41,520 Speaker 1: wanting to stay ahead of the trend? Absolutely, In other words, 192 00:11:41,679 --> 00:11:44,640 Speaker 1: you really have to take into account the impact of 193 00:11:44,760 --> 00:11:48,120 Speaker 1: behavior on those dynamics. And that's the same thing in 194 00:11:48,240 --> 00:11:51,440 Speaker 1: other kind of biological settings. You know, for example, if 195 00:11:51,480 --> 00:11:55,080 Speaker 1: it turns out that one species begins to grow, that 196 00:11:55,200 --> 00:11:57,440 Speaker 1: growth is going to mean that it's gonna be going 197 00:11:57,480 --> 00:12:01,720 Speaker 1: to be plentiful in terms of its numbers, and therefore 198 00:12:01,720 --> 00:12:04,880 Speaker 1: it's going to require more food. Whatever it preys on 199 00:12:05,160 --> 00:12:08,800 Speaker 1: is going to end up being selected out, and ultimately 200 00:12:08,840 --> 00:12:11,439 Speaker 1: that means it's going to have less food per individual, 201 00:12:11,559 --> 00:12:14,720 Speaker 1: which means that eventually the population is going to decline. 202 00:12:15,080 --> 00:12:17,680 Speaker 1: So in other ways, their feedback loops in the system 203 00:12:17,720 --> 00:12:21,080 Speaker 1: that have to be incorporated in terms of predicting how 204 00:12:21,120 --> 00:12:24,200 Speaker 1: one species will do relative to another. The case of 205 00:12:24,520 --> 00:12:28,080 Speaker 1: human beings interacting with each other's more complicated because we 206 00:12:28,120 --> 00:12:31,840 Speaker 1: can think farther ahead and plan and predict in much 207 00:12:31,840 --> 00:12:35,760 Speaker 1: more sophisticated ways. So once we see these kinds of 208 00:12:35,800 --> 00:12:39,400 Speaker 1: changing dynamics, we're going to alter our behavior, and that 209 00:12:39,559 --> 00:12:43,679 Speaker 1: change in behavior will then have an impact on those dynamics. 210 00:12:43,720 --> 00:12:46,679 Speaker 1: So the system tends to be more complicated, but nonetheless 211 00:12:46,679 --> 00:12:49,200 Speaker 1: it is a system that can be modeled, and with 212 00:12:49,280 --> 00:12:52,400 Speaker 1: the right kinds of mathematics and statistics, we can actually 213 00:12:52,440 --> 00:12:55,079 Speaker 1: do a better job of modeling that system than using 214 00:12:55,559 --> 00:12:58,160 Speaker 1: kind of static physical laws that we're trying to apply 215 00:12:58,360 --> 00:13:12,280 Speaker 1: right now to market dynamics. So this is what I'm 216 00:13:12,280 --> 00:13:15,400 Speaker 1: really curious about, because one of the attractions of the 217 00:13:15,440 --> 00:13:20,040 Speaker 1: efficient market hypothesis is its relative simplicity as a model. 218 00:13:20,640 --> 00:13:23,640 Speaker 1: What you're saying definitely makes sense, but I can only 219 00:13:23,679 --> 00:13:29,040 Speaker 1: imagine that, you know, identifying and figuring out how a 220 00:13:29,120 --> 00:13:33,040 Speaker 1: complete ecosystem of a particular market works. Are you actually 221 00:13:33,080 --> 00:13:37,600 Speaker 1: simplifying anything there? How useful is it as an actual model? Well, 222 00:13:37,640 --> 00:13:41,200 Speaker 1: all I can say is what Albert Einstein said when 223 00:13:41,240 --> 00:13:45,079 Speaker 1: he was accused of developing theories that were so complicated 224 00:13:45,160 --> 00:13:47,520 Speaker 1: and by the way. I'm no Albert Einstein, so I'm 225 00:13:47,520 --> 00:13:50,800 Speaker 1: not comparing myself to the great physicist. But when Einstein 226 00:13:51,040 --> 00:13:54,760 Speaker 1: was criticized for the complexity of his special theory of relativity, 227 00:13:55,520 --> 00:13:58,600 Speaker 1: he responded that a theory should be as simple as 228 00:13:58,640 --> 00:14:02,960 Speaker 1: possible and no simpler. And I think that the financial 229 00:14:03,040 --> 00:14:06,559 Speaker 1: theories that we're using are actually simpler than they should be. 230 00:14:07,120 --> 00:14:10,280 Speaker 1: So there's no doubt that the efficient markets hypothesis cuts 231 00:14:10,360 --> 00:14:15,600 Speaker 1: through a lot of really complicated and unnecessarily involved types 232 00:14:15,640 --> 00:14:18,320 Speaker 1: of theories that really don't make any sense. And so 233 00:14:18,559 --> 00:14:21,720 Speaker 1: that's one of the reasons why Fama, Samuelson and others 234 00:14:22,200 --> 00:14:26,280 Speaker 1: u had such an impact on both academia and industry. 235 00:14:27,120 --> 00:14:29,360 Speaker 1: But what we're seeing over the course of the last 236 00:14:29,520 --> 00:14:33,520 Speaker 1: couple of decades is much more complicated financial dynamics. It's 237 00:14:33,560 --> 00:14:36,640 Speaker 1: not the case anymore that a buy and hold strategy 238 00:14:36,680 --> 00:14:39,520 Speaker 1: of a sixty forty portfolio is good enough for retirement, 239 00:14:39,640 --> 00:14:42,240 Speaker 1: because well, we see markets going up and down in 240 00:14:42,280 --> 00:14:45,920 Speaker 1: some very dramatic ways over short periods of time, and 241 00:14:46,360 --> 00:14:48,760 Speaker 1: if we ignore those dynamics, we could actually get into 242 00:14:48,800 --> 00:14:50,840 Speaker 1: a fair bit of trouble, especially those of us who 243 00:14:50,840 --> 00:14:53,480 Speaker 1: are thinking about retiring within the next ten or twenty 244 00:14:53,520 --> 00:14:57,080 Speaker 1: years versus thirty or forty years. So horizon matters, the 245 00:14:57,160 --> 00:14:59,320 Speaker 1: nature of the buyers and sellers matter, the fact that 246 00:14:59,360 --> 00:15:02,600 Speaker 1: we have an inner, nationally integrated financial system that's different 247 00:15:02,640 --> 00:15:05,640 Speaker 1: than it was thirty or forty years ago. So I 248 00:15:05,680 --> 00:15:08,520 Speaker 1: think that we do need to have more complex theories 249 00:15:08,840 --> 00:15:11,840 Speaker 1: to match the complexity of the financial system as it 250 00:15:11,920 --> 00:15:14,600 Speaker 1: is today. But it doesn't mean that that we can't 251 00:15:14,720 --> 00:15:17,680 Speaker 1: simplify that kind of complexity. In other words, the theory 252 00:15:17,680 --> 00:15:21,800 Speaker 1: of evolution is a great simplification of what happens in nature, 253 00:15:22,320 --> 00:15:26,400 Speaker 1: and it is more complicated than the earlier stories about 254 00:15:26,440 --> 00:15:29,360 Speaker 1: how we evolve and how we change, but I think 255 00:15:29,400 --> 00:15:32,760 Speaker 1: that it does capture a very important set of of 256 00:15:32,840 --> 00:15:36,560 Speaker 1: differences from those earlier theories. So what I'm hoping is 257 00:15:36,560 --> 00:15:39,440 Speaker 1: that the adaptive market hypothesis, while it is somewhat more 258 00:15:39,480 --> 00:15:44,000 Speaker 1: complicated because it contains both human behavior as well as 259 00:15:44,040 --> 00:15:50,280 Speaker 1: efficient markets as uh sub subsets or subcases, it nevertheless 260 00:15:50,320 --> 00:15:54,240 Speaker 1: provides a unifying framework that allows both of those theories 261 00:15:54,280 --> 00:15:57,680 Speaker 1: to live happily under one roof. So I'd love to 262 00:15:58,200 --> 00:16:01,160 Speaker 1: spin it forward and talk about this market today. Because 263 00:16:01,160 --> 00:16:04,200 Speaker 1: there are all sorts of interesting debates going on right now. 264 00:16:04,240 --> 00:16:07,600 Speaker 1: People say, is there a bubble going on? Has the 265 00:16:07,640 --> 00:16:13,480 Speaker 1: Federal Reserve created some sort of unusual stability? What explains 266 00:16:13,840 --> 00:16:18,520 Speaker 1: the lack of market volatility despite seeming you headlines that 267 00:16:18,560 --> 00:16:24,120 Speaker 1: are extraordinary when you look at this current market from 268 00:16:24,160 --> 00:16:28,160 Speaker 1: the sort of ecological standpoint that you describe, what are 269 00:16:28,160 --> 00:16:30,840 Speaker 1: the what are some interesting things that you're seeing or 270 00:16:30,880 --> 00:16:35,360 Speaker 1: that you're just sort of exploring in today's flora and fauna. Well, 271 00:16:35,400 --> 00:16:38,600 Speaker 1: it's interesting that you mentioned those various different aspects of 272 00:16:38,640 --> 00:16:41,000 Speaker 1: what's going on in the financial system, because they're actually 273 00:16:41,080 --> 00:16:44,040 Speaker 1: quite closely related, but in ways that I don't think 274 00:16:44,040 --> 00:16:46,080 Speaker 1: you would have been able to see if you're focusing 275 00:16:46,120 --> 00:16:50,080 Speaker 1: on markets from the efficiency perspective. So take the example 276 00:16:50,320 --> 00:16:53,000 Speaker 1: of the Fed. Well, we know that the FED engaged 277 00:16:53,080 --> 00:16:56,480 Speaker 1: in some very significant quantitative easing in the aftermath of 278 00:16:56,520 --> 00:16:59,960 Speaker 1: the financial crisis. Now why is that important? Well, quantity 279 00:17:00,000 --> 00:17:02,880 Speaker 1: It of easing is a direct way of trying to 280 00:17:03,080 --> 00:17:08,640 Speaker 1: stabilize markets and increase employment by taking on certain kinds 281 00:17:08,640 --> 00:17:13,560 Speaker 1: of assets and managing the liquidity of the Federal reserve system. 282 00:17:13,600 --> 00:17:17,120 Speaker 1: That involved reducing interest rates to a certain level and 283 00:17:18,040 --> 00:17:22,320 Speaker 1: encouraging investors to put money in riskier assets. So that's 284 00:17:22,320 --> 00:17:24,560 Speaker 1: what we've seen. We've seen in a low yield environment, 285 00:17:24,960 --> 00:17:29,480 Speaker 1: investors have flocked to a variety of risky investments, but 286 00:17:29,600 --> 00:17:32,680 Speaker 1: the vast majority of the funds have gone into stable, 287 00:17:32,840 --> 00:17:38,639 Speaker 1: passive index products, and that in turn has actually caused 288 00:17:38,640 --> 00:17:42,120 Speaker 1: equity prices to rise over the course of the last decade. 289 00:17:42,960 --> 00:17:47,680 Speaker 1: And that increase in equity prices, particularly in passive vehicles, 290 00:17:48,160 --> 00:17:51,240 Speaker 1: definitely contributes to the fact that we have lower volatility 291 00:17:51,280 --> 00:17:56,159 Speaker 1: today than we had in probably twenty years. That decrease 292 00:17:56,200 --> 00:18:00,760 Speaker 1: in average volatility, in turn has caused as investors to 293 00:18:00,800 --> 00:18:03,720 Speaker 1: put more money in equities because of risk parity strategies 294 00:18:03,960 --> 00:18:08,159 Speaker 1: and other volatility linked investments. So the action of the 295 00:18:08,160 --> 00:18:11,439 Speaker 1: FED which was in response to this financial crisis, and 296 00:18:11,480 --> 00:18:15,080 Speaker 1: it was an emotional reaction in a way, because one 297 00:18:15,119 --> 00:18:17,480 Speaker 1: could argue that prices go up and down all the time, 298 00:18:17,480 --> 00:18:19,840 Speaker 1: you should just let the chips fall where they may. 299 00:18:19,880 --> 00:18:22,720 Speaker 1: But because we care about people who are out of work, 300 00:18:23,240 --> 00:18:25,879 Speaker 1: we want to make sure that financial stability is a 301 00:18:25,960 --> 00:18:30,359 Speaker 1: high priority among regulators and policymakers. So that kind of 302 00:18:30,400 --> 00:18:35,240 Speaker 1: reaction has repercussions that have an effect on market dynamics. 303 00:18:35,320 --> 00:18:39,679 Speaker 1: And we're working through those effects today. So when people 304 00:18:39,760 --> 00:18:42,280 Speaker 1: hear the word adaptation, or at least when I hear 305 00:18:42,320 --> 00:18:44,639 Speaker 1: the word adaptation, I also, you know, I think a 306 00:18:44,640 --> 00:18:48,720 Speaker 1: little bit about resiliency and you know, again the ability 307 00:18:48,760 --> 00:18:50,639 Speaker 1: to adapt to new situations. So when you look at 308 00:18:50,640 --> 00:18:54,640 Speaker 1: the market nowadays, lots of people are thinking about valuations 309 00:18:54,680 --> 00:18:57,840 Speaker 1: being sky high, the possibility of things may be beginning 310 00:18:57,920 --> 00:19:02,160 Speaker 1: to pop as central banks withdraw their quidity. What's what's 311 00:19:02,200 --> 00:19:05,199 Speaker 1: the fragility that you see in the ecosystem, What's the 312 00:19:05,320 --> 00:19:08,359 Speaker 1: thing that could topple over the dynamic that we've been 313 00:19:08,400 --> 00:19:11,880 Speaker 1: seeing for the past five or six years. Well that's 314 00:19:11,880 --> 00:19:16,199 Speaker 1: a great point, because fragility is something that biologists and 315 00:19:16,280 --> 00:19:20,359 Speaker 1: particularly ecologists study all the time. And one of the 316 00:19:20,359 --> 00:19:23,959 Speaker 1: things that they tell us about fragility is that we 317 00:19:24,080 --> 00:19:27,560 Speaker 1: need to have a certain amount of biodiversity in order 318 00:19:27,600 --> 00:19:31,280 Speaker 1: to create a more robust ecology. The basic idea being 319 00:19:31,320 --> 00:19:34,040 Speaker 1: that certain species can get wiped out because of an 320 00:19:34,119 --> 00:19:37,840 Speaker 1: environmental change, but if we have a variety of different species, 321 00:19:38,080 --> 00:19:40,399 Speaker 1: the likelihood that one or two of them will be 322 00:19:40,480 --> 00:19:44,960 Speaker 1: able to survive will allow the ecology to maintain some 323 00:19:45,040 --> 00:19:50,000 Speaker 1: semblance of its prior existence. Even before that big evolutionary shock, 324 00:19:50,880 --> 00:19:54,600 Speaker 1: we don't have that same kind of resiliency concept in economics. 325 00:19:55,119 --> 00:19:57,560 Speaker 1: I think that certain economists, over the course of the 326 00:19:57,640 --> 00:20:00,800 Speaker 1: last several decades have tried to focus on that by 327 00:20:00,840 --> 00:20:04,679 Speaker 1: looking at things like concentration in the industries and various 328 00:20:04,720 --> 00:20:07,119 Speaker 1: different types of industries that are starting and those that 329 00:20:07,160 --> 00:20:11,600 Speaker 1: are declining. But the idea of measuring resiliency in the 330 00:20:11,600 --> 00:20:16,040 Speaker 1: economy is really pretty far behind what the biologists are doing. 331 00:20:16,720 --> 00:20:19,040 Speaker 1: So from my point of view, I think that resiliency 332 00:20:19,080 --> 00:20:21,119 Speaker 1: is really a key issue, and that's one of the 333 00:20:21,160 --> 00:20:23,840 Speaker 1: reasons why I focus in some of my research on 334 00:20:24,000 --> 00:20:27,840 Speaker 1: hedge funds. The hedge fund industry is actually a source 335 00:20:27,960 --> 00:20:31,159 Speaker 1: of all sorts of new species. If you think about, 336 00:20:31,720 --> 00:20:34,919 Speaker 1: you know, various different kinds of investment vehicles that are 337 00:20:34,960 --> 00:20:38,639 Speaker 1: now widely available. A lot of those investment vehicles first 338 00:20:38,680 --> 00:20:42,959 Speaker 1: began in the hedge fund industry, and so it's important 339 00:20:43,119 --> 00:20:46,520 Speaker 1: if you want to maintain resiliency to have a vibrant 340 00:20:46,520 --> 00:20:49,479 Speaker 1: hedge fund sector where all sorts of new ideas can 341 00:20:49,520 --> 00:20:51,760 Speaker 1: get tried out, and the ones that work well will 342 00:20:51,880 --> 00:20:54,680 Speaker 1: progress and grow, and the ones that don't will basically 343 00:20:54,680 --> 00:20:57,520 Speaker 1: get wiped out. You want to have that kind of 344 00:20:57,600 --> 00:21:02,400 Speaker 1: turnover in ideas and and financial products and services so 345 00:21:02,440 --> 00:21:04,560 Speaker 1: that we don't ever get into a situation where we're 346 00:21:04,560 --> 00:21:07,639 Speaker 1: getting locked into something. The one concern that I have 347 00:21:07,800 --> 00:21:11,320 Speaker 1: about resiliency right now is that we have a huge 348 00:21:11,359 --> 00:21:15,960 Speaker 1: amount of assets flowing into passive index strategies, and obviously 349 00:21:16,000 --> 00:21:19,359 Speaker 1: that's been a very important source of investment return for 350 00:21:19,400 --> 00:21:23,280 Speaker 1: a large majority of investors who don't have the skills 351 00:21:23,320 --> 00:21:27,720 Speaker 1: to manage their portfolio actively. So active versus passive is 352 00:21:27,720 --> 00:21:31,760 Speaker 1: a debate that I think has long been settled. Passive 353 00:21:31,880 --> 00:21:34,480 Speaker 1: is definitely here to stay, and it's an incredibly important 354 00:21:34,520 --> 00:21:38,119 Speaker 1: component of the flora and fauna of the investors that 355 00:21:38,520 --> 00:21:41,880 Speaker 1: are looking for opportunities. The problem is that if we 356 00:21:41,960 --> 00:21:46,360 Speaker 1: now are all investing in these passive vehicles, what happens 357 00:21:46,720 --> 00:21:50,080 Speaker 1: when there's a stock market correction that inevitably there will be, 358 00:21:50,720 --> 00:21:54,320 Speaker 1: and we see these passive investments under performing, Well, we're 359 00:21:54,359 --> 00:21:58,399 Speaker 1: gonna get a massive exit from that particular set of vehicles. 360 00:21:58,520 --> 00:22:01,240 Speaker 1: And like any kind of a situation where you've got 361 00:22:01,240 --> 00:22:05,000 Speaker 1: a crowded trade and a massive unwinding, you can see 362 00:22:05,040 --> 00:22:10,480 Speaker 1: a much bigger drop in these market levels. So crashes 363 00:22:11,080 --> 00:22:14,040 Speaker 1: are now more likely. In fact, we see flash crashes 364 00:22:14,080 --> 00:22:17,840 Speaker 1: happening all the time, which is a technological example of 365 00:22:17,880 --> 00:22:20,560 Speaker 1: these kinds of phenomenon happening in very very short term. 366 00:22:21,280 --> 00:22:23,240 Speaker 1: But I think that this is a concern that I 367 00:22:23,320 --> 00:22:28,719 Speaker 1: have about resiliency. We're creating opportunities for financial panics that 368 00:22:29,119 --> 00:22:31,399 Speaker 1: didn't exist ten years ago or didn't exist to the 369 00:22:31,440 --> 00:22:34,080 Speaker 1: same degree. So we just need to be wary of 370 00:22:34,119 --> 00:22:38,120 Speaker 1: that and be prepared for those kinds of shocks. Very 371 00:22:38,359 --> 00:22:42,639 Speaker 1: bleak answer, but obviously, you know, it's definitely capturing an 372 00:22:42,680 --> 00:22:45,280 Speaker 1: anxiety that I think a lot of people feel right 373 00:22:45,320 --> 00:22:47,520 Speaker 1: now about the markets. We've talked about this a lot, 374 00:22:47,600 --> 00:22:50,440 Speaker 1: that sort of where is this sort of endless boom 375 00:22:50,440 --> 00:22:53,920 Speaker 1: and E T f S and passive actually go. But 376 00:22:54,040 --> 00:22:57,040 Speaker 1: you know, there's debate about how big passive could get. 377 00:22:57,119 --> 00:23:02,160 Speaker 1: There's the study of ecology. Give us any clues into 378 00:23:02,400 --> 00:23:05,439 Speaker 1: when tipping points could happen or anything like that, or 379 00:23:05,480 --> 00:23:07,879 Speaker 1: do we just sort of have do you know it'll 380 00:23:07,960 --> 00:23:10,400 Speaker 1: just happen one day and it will be all over Well, 381 00:23:10,440 --> 00:23:12,960 Speaker 1: I think it does give us a clue. Rather, it 382 00:23:13,000 --> 00:23:16,240 Speaker 1: gives us a way of trying to understand where those 383 00:23:16,280 --> 00:23:20,439 Speaker 1: tipping points might arise, and once again, the way to 384 00:23:20,480 --> 00:23:24,640 Speaker 1: do that is to measure the biomass of the various 385 00:23:24,640 --> 00:23:29,159 Speaker 1: different species and ask what they're driven by and ultimately 386 00:23:29,520 --> 00:23:34,360 Speaker 1: what will cause them to change their direction. I think 387 00:23:34,359 --> 00:23:37,240 Speaker 1: that in the case of passive investing, it's pretty clear 388 00:23:37,560 --> 00:23:41,880 Speaker 1: that it offers tremendous benefits to a large number of investors. 389 00:23:41,880 --> 00:23:44,080 Speaker 1: So we're not going to see any kind of a 390 00:23:44,119 --> 00:23:48,640 Speaker 1: decline unless and until there are some kind of widespread 391 00:23:48,800 --> 00:23:51,920 Speaker 1: market decline. If the stock market goes down by ten 392 00:23:52,040 --> 00:23:57,080 Speaker 1: or that might be enough to cause a retreat into 393 00:23:57,359 --> 00:24:00,879 Speaker 1: fixed income assets or cash for a period of time. 394 00:24:01,520 --> 00:24:03,760 Speaker 1: And so I think that's really the kind of tipping 395 00:24:03,800 --> 00:24:07,920 Speaker 1: point for passive investments because right now, given the low 396 00:24:08,000 --> 00:24:12,399 Speaker 1: yield environment, investors are really continuing to pour money into 397 00:24:12,400 --> 00:24:16,280 Speaker 1: that sector. But eventually nothing lasts forever. We're going to 398 00:24:16,359 --> 00:24:20,280 Speaker 1: see reversals in every kind of asset class. And in 399 00:24:20,320 --> 00:24:22,600 Speaker 1: this case, if we take a look at the nature 400 00:24:22,720 --> 00:24:25,280 Speaker 1: of the investors who are going into the market versus 401 00:24:25,320 --> 00:24:28,080 Speaker 1: those who are willing to take money out of the market, 402 00:24:28,400 --> 00:24:30,600 Speaker 1: will get a better idea of when that kind of 403 00:24:30,600 --> 00:24:32,960 Speaker 1: a tipping point might be and and what kind of 404 00:24:32,960 --> 00:24:36,200 Speaker 1: triggers might cause that tipping point to happen. I'm trying 405 00:24:36,240 --> 00:24:38,960 Speaker 1: to think if passive funds are the eight hundred pound 406 00:24:39,080 --> 00:24:44,959 Speaker 1: guerrillas or the excitable antelopes in the market ecosystem. All right, 407 00:24:45,080 --> 00:24:49,400 Speaker 1: Andrew low, m i T Professor and author of Adaptive Markets, 408 00:24:49,440 --> 00:24:52,239 Speaker 1: Financial Evolution at the Speed of Thought, Thank you so 409 00:24:52,320 --> 00:25:07,520 Speaker 1: much for joining us. Thank you, it's been a pleasure. So, Joe, 410 00:25:07,600 --> 00:25:10,240 Speaker 1: what did you think of the you know, the ecosystem 411 00:25:10,280 --> 00:25:13,760 Speaker 1: analogy was strong in that conversation. Yeah, I really like 412 00:25:13,880 --> 00:25:17,840 Speaker 1: that conversation, and I really like that framework for thinking 413 00:25:17,880 --> 00:25:20,520 Speaker 1: about it. You know, it's funny thinking about what we 414 00:25:20,600 --> 00:25:24,760 Speaker 1: do all day, writing about markets and what people think 415 00:25:24,960 --> 00:25:26,520 Speaker 1: is going to go up or what people think are 416 00:25:26,520 --> 00:25:30,600 Speaker 1: good investments. Are not even a pure emage world. We'd 417 00:25:30,640 --> 00:25:34,160 Speaker 1: kind of have to admit that our jobs are sort 418 00:25:34,160 --> 00:25:36,560 Speaker 1: of stupid in a way, like why even bother writing 419 00:25:36,640 --> 00:25:40,119 Speaker 1: about this? Why bother saying? Why bother? Why bother bringing 420 00:25:40,160 --> 00:25:43,359 Speaker 1: people's opinions if there's no way for anyone to just 421 00:25:43,400 --> 00:25:45,520 Speaker 1: sort of get a pure edge. And what I like 422 00:25:45,600 --> 00:25:49,600 Speaker 1: about Andrew's view is the idea that it's really tough, 423 00:25:50,200 --> 00:25:53,199 Speaker 1: but it's not impossible and that if you explore the 424 00:25:53,280 --> 00:25:56,760 Speaker 1: right facet there is value in sort of in at 425 00:25:56,800 --> 00:26:01,040 Speaker 1: least trying. I agree all the I'm not sure. I 426 00:26:01,080 --> 00:26:03,440 Speaker 1: like the notion that our jobs are meaningless. Well. One 427 00:26:03,480 --> 00:26:05,919 Speaker 1: thing I really liked about his framing, though, is the 428 00:26:06,000 --> 00:26:10,199 Speaker 1: emphasis on market structure, because this is something that you know, 429 00:26:10,280 --> 00:26:12,520 Speaker 1: you and I bang on and on about, but in 430 00:26:12,600 --> 00:26:15,320 Speaker 1: order to understand the market, you really need to understand 431 00:26:15,720 --> 00:26:18,119 Speaker 1: the structure of it and the various players and the 432 00:26:18,160 --> 00:26:20,919 Speaker 1: motivation at play. And I really think that's the point 433 00:26:21,160 --> 00:26:25,399 Speaker 1: he's making about his theory. That said, you know, I 434 00:26:25,680 --> 00:26:29,080 Speaker 1: can imagine that that does get quite complex when you're 435 00:26:29,320 --> 00:26:33,640 Speaker 1: an economist trying to publish a you know, paper for instance. 436 00:26:33,760 --> 00:26:37,680 Speaker 1: That's that's a lot to model totally. But this idea 437 00:26:37,760 --> 00:26:39,600 Speaker 1: that you know, there's sort of two different ways of 438 00:26:39,640 --> 00:26:42,199 Speaker 1: thinking about the market. So one is you might have 439 00:26:42,240 --> 00:26:45,680 Speaker 1: a stock and you might look at its income statement 440 00:26:45,760 --> 00:26:48,200 Speaker 1: and it's balance sheet and sort of what we're talking 441 00:26:48,200 --> 00:26:52,840 Speaker 1: about with Ozwa Dalmadaran recently. But then the other aspect 442 00:26:52,880 --> 00:26:54,679 Speaker 1: is this where it's like you look at the overall 443 00:26:54,720 --> 00:26:57,000 Speaker 1: market and you try to figure out who the gazelles 444 00:26:57,040 --> 00:27:00,359 Speaker 1: are and who the hyenas are, and who the eight 445 00:27:00,960 --> 00:27:04,560 Speaker 1: hundred pound gorillas are and figure out, Okay, what is 446 00:27:04,600 --> 00:27:06,879 Speaker 1: the motivation of each of these And I think that 447 00:27:07,040 --> 00:27:10,840 Speaker 1: also is a very interesting way of thinking about what's 448 00:27:10,880 --> 00:27:13,600 Speaker 1: what in the market. Yeah, agreed, I really want to 449 00:27:13,600 --> 00:27:16,040 Speaker 1: go to the zoo. Now I have this urge to 450 00:27:16,040 --> 00:27:18,360 Speaker 1: go to the zoo. Okay, let's leave it there. That 451 00:27:18,480 --> 00:27:21,879 Speaker 1: was another episode of the Odd Thoughts podcast. I'm Tracy Alloway. 452 00:27:21,960 --> 00:27:24,960 Speaker 1: You can follow me on Twitter at Tracy Alloway. And 453 00:27:25,040 --> 00:27:28,360 Speaker 1: I'm Joel Wisnthal. You can follow me on Twitter at 454 00:27:28,400 --> 00:27:32,080 Speaker 1: the Stalwart. And you can follow Andrew Low on Twitter 455 00:27:32,400 --> 00:27:37,560 Speaker 1: at Andrew w. Low and follow our producer Sarah Patterson 456 00:27:37,720 --> 00:27:41,040 Speaker 1: at Sarah pet With two Teas. Thanks for listening.