WEBVTT - An MIT Professor Explains His Original Theory For How Markets Really Work 0:00:09.080 --> 0:00:12.440 Hello, and welcome to another episode of the Odd Thoughts Podcast. 0:00:12.520 --> 0:00:16.640 I'm Tracy Allaway and I'm Joe. Joe, what did you 0:00:16.680 --> 0:00:21.720 study at college? Mmm? I'm already nervous about answering this 0:00:21.800 --> 0:00:24.599 question because I don't I actually genuinely don't know where 0:00:24.600 --> 0:00:26.599 you're going with it. Well, I also don't know what 0:00:26.640 --> 0:00:32.199 you studied, so I'm genuinely curious. I studied international relations. 0:00:32.240 --> 0:00:35.440 Actually I went at University of Texas. They called it government, 0:00:35.760 --> 0:00:38.400 which is not really a thing anywhere else, but it 0:00:38.520 --> 0:00:40.479 was kind of like their political science department. But I 0:00:40.520 --> 0:00:44.080 focused on international relations. Okay, I swear this is a 0:00:44.159 --> 0:00:49.000 complete coincidence, but I also studied international relations. Really, it's 0:00:49.040 --> 0:00:51.159 funny that, like, of all this time I've known you, 0:00:51.240 --> 0:00:53.920 this has never come up. No seriously, like for people 0:00:53.960 --> 0:00:56.040 like who think who are listening, I think maybe we're 0:00:56.080 --> 0:00:59.160 faking this or something. It's actually I don't. I genuinely 0:00:59.200 --> 0:01:01.320 did not know that. About now people are thinking that 0:01:01.360 --> 0:01:03.880 we just never talked to each other outside of this podcast. 0:01:03.960 --> 0:01:07.600 We just we just only talk markets, no personal stuff. 0:01:07.800 --> 0:01:10.120 The reason I was bringing it up was because I 0:01:10.160 --> 0:01:12.479 was trying to think of a parallel with what we're 0:01:12.480 --> 0:01:15.160 going to speak about in just a few minutes. Um, 0:01:15.160 --> 0:01:17.800 And I was thinking, you know, in international relations, there 0:01:17.800 --> 0:01:22.360 are these two dominant theories that govern how you think 0:01:22.400 --> 0:01:26.600 about the world. Their realism and liberalism. Do you remember that. 0:01:28.160 --> 0:01:29.920 I'm glad you didn't ask me to name them. I 0:01:29.920 --> 0:01:32.760 would have remembered realism and I would have blanked on 0:01:32.800 --> 0:01:35.160 the other one. But yes, that sounds right. Okay. So 0:01:35.240 --> 0:01:38.880 realism is this theory that states and governments and people 0:01:38.920 --> 0:01:41.920 are essentially self interested and you know, everyone's out to 0:01:41.959 --> 0:01:44.360 get each other, and liberalism is, oh, actually we can 0:01:44.400 --> 0:01:48.840 all get along and there's scope for cooperation to diametrically 0:01:48.960 --> 0:01:54.840 opposed theories that completely govern that particular study. Um. Now, 0:01:54.960 --> 0:01:57.720 the reason I'm bringing it up, it's because we are 0:01:57.760 --> 0:02:01.800 going to talk about a similar parallel in economics. Can 0:02:01.840 --> 0:02:05.560 you guess what it is? Uh? Why don't you just 0:02:05.600 --> 0:02:08.280 tell me? I mean, I think, I think I know 0:02:08.280 --> 0:02:10.359 where it's going. But I really like the way you're 0:02:10.360 --> 0:02:14.440 taking this. So alright, So it's the efficient market hypothesis 0:02:14.639 --> 0:02:21.880 versus behavioral economics. Yes, okay, so most people probably know this, 0:02:21.960 --> 0:02:26.080 but the efficient market hypothesis basically says that you can't 0:02:26.200 --> 0:02:30.239 beat the market, that it's a perfect reflection of the 0:02:30.280 --> 0:02:34.040 information currently out there, in a perfect reflection of the 0:02:34.040 --> 0:02:37.399 price that you should be paying for that information. Meanwhile, 0:02:37.720 --> 0:02:43.040 behavioral economics basically suggests that human beings can be irrational 0:02:43.160 --> 0:02:45.040 and we can get stuff wrong, and that means that 0:02:45.200 --> 0:02:48.200 markets also can be irrational and can get stuff wrong. 0:02:48.560 --> 0:02:52.880 So to pretty much diametrically opposed schools of thought. So 0:02:52.919 --> 0:02:56.320 are we going to find out which one is correct today? No, 0:02:58.760 --> 0:03:01.119 We're actually going to talk to someone who thinks they've 0:03:01.120 --> 0:03:07.840 found a middle path between those two seemingly opposed schools 0:03:07.840 --> 0:03:11.000 of thought. All right, I'm intrigued to who are we 0:03:11.040 --> 0:03:13.919 talking to and what's their theory? Okay, I'm really excited 0:03:13.960 --> 0:03:16.680 to bring on Andrew Low. He's an economist, he's a 0:03:16.680 --> 0:03:20.400 long time m I T. Professor, and he's written well, 0:03:20.480 --> 0:03:23.720 he's written several books, but most recently he has written 0:03:23.720 --> 0:03:37.040 a book on exactly this topic. Andrew, thank you so 0:03:37.120 --> 0:03:41.040 much for joining us. It's a pleasure, thanks for having me. So, 0:03:41.520 --> 0:03:44.040 just going back to the efficient market hypothesis. I gave 0:03:44.080 --> 0:03:47.480 a little snapshot of it, but maybe you could describe 0:03:47.480 --> 0:03:51.720 it a little bit more and also perhaps explain how 0:03:51.840 --> 0:03:57.080 it came to be a fundamental tenet of modern financial 0:03:57.600 --> 0:04:01.040 uh theory, when everyone and seems to beat up on 0:04:01.080 --> 0:04:04.320 it nowadays. Sure, well, you know, it's a really interesting 0:04:04.360 --> 0:04:09.080 idea and it's the brainchild of two economists. Gene Fama 0:04:09.200 --> 0:04:12.040 at the University of Chicago coined the term and came 0:04:12.120 --> 0:04:15.520 up with the basic idea that in an efficient market, 0:04:15.920 --> 0:04:20.719 prices fully reflect all available information. And so that's the case, 0:04:20.920 --> 0:04:24.240 then you really can't beat the markets by using information 0:04:24.279 --> 0:04:27.560 because it's already in the price and M. Paul Samuelson 0:04:27.640 --> 0:04:30.840 was the other economist who contributed to this theory, and 0:04:31.040 --> 0:04:36.440 his paper was titled proof that properly anticipated prices fluctuate randomly, 0:04:36.839 --> 0:04:39.960 which is a very fancy way of saying that once 0:04:40.040 --> 0:04:43.960 you incorporate all available information into prices, you don't know 0:04:43.960 --> 0:04:46.040 where it's going to go, so you can't predict future 0:04:46.080 --> 0:04:49.599 prices based upon where it is today. It seems to 0:04:49.640 --> 0:04:52.360 me the efficient market hypothesis has come under a lot 0:04:52.360 --> 0:04:56.520 of criticism in recent years. We've seen Nobel Prize winners 0:04:56.800 --> 0:04:59.560 who have won for their work and sort of talking 0:04:59.560 --> 0:05:03.080 about this more. The behavioral approach, which is very as 0:05:03.120 --> 0:05:06.360 Tracy explained at the beginning, is sort of this opposite view, 0:05:06.920 --> 0:05:10.320 But it still seems for all the criticism that efficient 0:05:10.360 --> 0:05:13.760 markets has come under, it's still pretty hard to beat 0:05:13.800 --> 0:05:16.159 the market. Like, it still seems like more or less 0:05:16.480 --> 0:05:19.800 it's a pretty difficult task. Well, that was exactly the 0:05:19.839 --> 0:05:22.480 conundrum that I was trying to figure out when trying 0:05:22.480 --> 0:05:25.240 to sort through this particular theory versus all of the 0:05:25.320 --> 0:05:30.119 various different critiques. The efficient market hypothesis actually works pretty well. 0:05:30.880 --> 0:05:33.680 It is really hard to beat the market, and prices 0:05:33.720 --> 0:05:36.600 do actually reflect a lot of information that's out there, 0:05:37.279 --> 0:05:41.000 and so it really it's hard to reconcile the basic 0:05:41.160 --> 0:05:44.680 ideas about efficient markets with all of the psychological and 0:05:44.720 --> 0:05:50.479 behavioral anomalies that people like conoman diversity failure, and UH 0:05:50.600 --> 0:05:53.600 and others have come up with to try to counteract 0:05:53.640 --> 0:05:57.600 these various different ideas of efficiency. So walk us through 0:05:57.920 --> 0:06:00.480 how you tackle that problem then, and the theory that 0:06:00.520 --> 0:06:04.360 you came up with you call it adaptive markets. Right. 0:06:04.680 --> 0:06:09.159 The basic idea is that there are elements of both 0:06:09.160 --> 0:06:13.000 of these schools of thought that work well, but neither 0:06:13.440 --> 0:06:15.880 is the complete picture. You really need both of them. 0:06:15.920 --> 0:06:22.000 They're both important aspects of the same phenomenon, and the 0:06:22.279 --> 0:06:27.280 idea behind adaptive markets is fairly straightforward. It basically says 0:06:27.360 --> 0:06:33.320 that investors are highly competitive and adaptive, and therefore it 0:06:33.400 --> 0:06:35.400 is tough to beat the market because lots of other 0:06:35.400 --> 0:06:38.520 people are trying to do that. But it's not impossible 0:06:39.080 --> 0:06:42.000 because every once in a while, markets aren't driven just 0:06:42.120 --> 0:06:47.120 by logic and analysis, but they're also driven by human emotion. So, 0:06:47.200 --> 0:06:50.040 for example, when the stock market goes down by ten 0:06:50.120 --> 0:06:53.479 or a lot of people are going to start heading 0:06:53.520 --> 0:06:56.839 for the exits. They're going to start unwinding their portfolios, 0:06:56.880 --> 0:06:59.960 and that kind of a herd mentality can actually lead 0:07:00.160 --> 0:07:04.279 two prices that don't fully reflect the information that's available 0:07:04.320 --> 0:07:06.640 at that point in time, So, in other words, it 0:07:06.680 --> 0:07:11.080 reflects emotion as opposed to fundamental valuations. The efficient market 0:07:11.160 --> 0:07:14.560 hypothesis is a great way to explain market dynamics when 0:07:14.600 --> 0:07:17.840 people are acting logically, but every once in a while 0:07:18.080 --> 0:07:21.280 we freak out, and the freakout factor is where the 0:07:21.320 --> 0:07:25.040 behavioral economists have their day. Both of these are important 0:07:25.080 --> 0:07:29.920 aspects of market dynamics, but they don't always operate at 0:07:29.960 --> 0:07:33.960 the same time, and it's really trying to understand which 0:07:34.040 --> 0:07:37.679 part of these different phases are relevant at a given 0:07:37.720 --> 0:07:41.040 point in time that the adaptive markets is focused on. 0:07:41.800 --> 0:07:45.280 So I think that like anyone who looks at markets 0:07:45.720 --> 0:07:49.440 can appreciate that there are times when sort of pure 0:07:49.440 --> 0:07:53.320 emotion and animal spirits really take over, whether it's a panic, 0:07:53.520 --> 0:07:56.600 whether it's in the stage of a bubble. But one 0:07:56.640 --> 0:07:58.920 of the things that we've talked about a lot on 0:07:59.000 --> 0:08:01.800 this podcast, as said, factors that even if you know 0:08:02.000 --> 0:08:04.480 something as a bubble, or even if you know something's 0:08:04.480 --> 0:08:08.160 a panic, it's really hard to know what stage you're 0:08:08.160 --> 0:08:11.000 in and whether you're near a bottom or whether you're 0:08:11.040 --> 0:08:14.360 you're near a top. So my question is, if you 0:08:14.440 --> 0:08:17.160 know you know, you sort of thread this middle ground 0:08:17.240 --> 0:08:21.240 where sometimes behavioral take takes over. Sometimes markets are based 0:08:21.280 --> 0:08:25.920 on pure information. Does your theory help one get any 0:08:26.000 --> 0:08:31.000 closer to actually, you know, maybe beating the market. Well, 0:08:31.040 --> 0:08:34.480 it does, and I argue that those who do beat 0:08:34.480 --> 0:08:37.680 the market today are using some form of this theory. 0:08:37.840 --> 0:08:43.240 For example, hedge fund managers understand instinctively that market dynamics 0:08:43.360 --> 0:08:46.320 change as a function of the flora and fauna of 0:08:46.360 --> 0:08:49.080 the market ecology. In other words, they look at who 0:08:49.080 --> 0:08:51.600 are the participants in any given market at a point 0:08:51.600 --> 0:08:56.199 in time and they feel the the market dynamics as 0:08:56.240 --> 0:09:00.720 a function of those various different participants. It really is 0:09:00.920 --> 0:09:03.560 trying to understand markets from a more of a biological 0:09:03.600 --> 0:09:07.839 perspective than a physical perspective. And uh, I think that 0:09:07.840 --> 0:09:10.959 that kind of approach will requires us to collect very 0:09:11.000 --> 0:09:13.480 different kinds of data from the ones that we're doing 0:09:13.559 --> 0:09:16.400 right now, and if we had that data, we can 0:09:16.440 --> 0:09:19.080 make much better predictions about where the market is going. 0:09:19.960 --> 0:09:22.360 So what sort of data are you talking about? What 0:09:22.400 --> 0:09:25.280 would be helpful just knowing who is and who isn't 0:09:25.320 --> 0:09:29.040 participating in a particular market. Well, let me start by 0:09:29.160 --> 0:09:33.280 giving you a different perspective. Imagine if you're an ecologist 0:09:33.440 --> 0:09:39.400 being asked to study particular ecological niche say, the Amazon rainforest, 0:09:39.960 --> 0:09:42.680 and let's suppose that you would like to save a 0:09:42.720 --> 0:09:46.719 particular species in that ecology. How would you go about it. Well, 0:09:46.760 --> 0:09:50.040 as an ecologist, you'd probably start by taking an inventory 0:09:50.080 --> 0:09:52.520 of all of the different species, how they relate to 0:09:52.559 --> 0:09:55.720 each other, what they eat, who they prey on, what 0:09:55.840 --> 0:09:59.040 the various different food chain relationships are, what the environment 0:09:59.080 --> 0:10:01.720 looks like and how it's changing over time. Once you 0:10:01.800 --> 0:10:05.160 study all of those aspects of the environment and the 0:10:05.160 --> 0:10:08.400 flora and the fauna. You can then start get identifying 0:10:08.920 --> 0:10:13.360 key aspects of that system that require management in order 0:10:13.360 --> 0:10:17.160 to preserve a given species or in order to highlight 0:10:17.200 --> 0:10:21.200 a particular species. If you now take that same analogy 0:10:21.240 --> 0:10:24.880 and apply it to the financial markets, you'd see that 0:10:25.080 --> 0:10:27.520 what you want to start with is not just looking 0:10:27.559 --> 0:10:30.959 at prices, but to understand who the buyers are, who 0:10:31.040 --> 0:10:34.280 the sellers are, and not just that, but the nature 0:10:34.559 --> 0:10:37.840 of the buying and the selling pension funds, broker dealers, 0:10:38.040 --> 0:10:41.560 hedge fund managers, who the investors are, who the ultimate 0:10:41.640 --> 0:10:44.680 buyers and sellers aren't, and what motivates them. Once you 0:10:44.800 --> 0:10:47.559 understand the nature of the flora and fauna of the 0:10:47.600 --> 0:10:51.240 financial markets, you can then start making predictions like, well, 0:10:51.280 --> 0:10:53.000 if it turns out that pension funds are going to 0:10:53.080 --> 0:10:56.160 be indexing and sticking to a particular asset allocation over 0:10:56.200 --> 0:10:58.320 a period of time, then that means that they're going 0:10:58.400 --> 0:11:00.559 to be submitting by orders when the market goes down 0:11:00.600 --> 0:11:02.880 and submitting cell orders when the market goes up in 0:11:02.960 --> 0:11:06.480 order to maintain that strategic asset allocation. You'd understand the 0:11:06.559 --> 0:11:10.680 motivation for the various different species in that marketplace and 0:11:10.800 --> 0:11:13.120 be able to make better predictions about how they would 0:11:13.120 --> 0:11:16.080 react to certain kinds of market events. That that's the 0:11:16.120 --> 0:11:18.240 kind of data that I think we need in order 0:11:18.280 --> 0:11:22.440 to be able to analyze market dynamics. Now your book 0:11:22.480 --> 0:11:25.800 and your theory is called adaptive market. If that data 0:11:25.840 --> 0:11:29.640 were to be made available, presumably all of that would 0:11:29.640 --> 0:11:33.440 then be incorporated back into price because people adapt would 0:11:33.480 --> 0:11:37.119 that then require some sort of further metadata for investors 0:11:37.120 --> 0:11:41.520 wanting to stay ahead of the trend? Absolutely, In other words, 0:11:41.679 --> 0:11:44.640 you really have to take into account the impact of 0:11:44.760 --> 0:11:48.120 behavior on those dynamics. And that's the same thing in 0:11:48.240 --> 0:11:51.440 other kind of biological settings. You know, for example, if 0:11:51.480 --> 0:11:55.080 it turns out that one species begins to grow, that 0:11:55.200 --> 0:11:57.440 growth is going to mean that it's gonna be going 0:11:57.480 --> 0:12:01.720 to be plentiful in terms of its numbers, and therefore 0:12:01.720 --> 0:12:04.880 it's going to require more food. Whatever it preys on 0:12:05.160 --> 0:12:08.800 is going to end up being selected out, and ultimately 0:12:08.840 --> 0:12:11.439 that means it's going to have less food per individual, 0:12:11.559 --> 0:12:14.720 which means that eventually the population is going to decline. 0:12:15.080 --> 0:12:17.680 So in other ways, their feedback loops in the system 0:12:17.720 --> 0:12:21.080 that have to be incorporated in terms of predicting how 0:12:21.120 --> 0:12:24.200 one species will do relative to another. The case of 0:12:24.520 --> 0:12:28.080 human beings interacting with each other's more complicated because we 0:12:28.120 --> 0:12:31.840 can think farther ahead and plan and predict in much 0:12:31.840 --> 0:12:35.760 more sophisticated ways. So once we see these kinds of 0:12:35.800 --> 0:12:39.400 changing dynamics, we're going to alter our behavior, and that 0:12:39.559 --> 0:12:43.679 change in behavior will then have an impact on those dynamics. 0:12:43.720 --> 0:12:46.679 So the system tends to be more complicated, but nonetheless 0:12:46.679 --> 0:12:49.200 it is a system that can be modeled, and with 0:12:49.280 --> 0:12:52.400 the right kinds of mathematics and statistics, we can actually 0:12:52.440 --> 0:12:55.079 do a better job of modeling that system than using 0:12:55.559 --> 0:12:58.160 kind of static physical laws that we're trying to apply 0:12:58.360 --> 0:13:12.280 right now to market dynamics. So this is what I'm 0:13:12.280 --> 0:13:15.400 really curious about, because one of the attractions of the 0:13:15.440 --> 0:13:20.040 efficient market hypothesis is its relative simplicity as a model. 0:13:20.640 --> 0:13:23.640 What you're saying definitely makes sense, but I can only 0:13:23.679 --> 0:13:29.040 imagine that, you know, identifying and figuring out how a 0:13:29.120 --> 0:13:33.040 complete ecosystem of a particular market works. Are you actually 0:13:33.080 --> 0:13:37.600 simplifying anything there? How useful is it as an actual model? Well, 0:13:37.640 --> 0:13:41.200 all I can say is what Albert Einstein said when 0:13:41.240 --> 0:13:45.079 he was accused of developing theories that were so complicated 0:13:45.160 --> 0:13:47.520 and by the way. I'm no Albert Einstein, so I'm 0:13:47.520 --> 0:13:50.800 not comparing myself to the great physicist. But when Einstein 0:13:51.040 --> 0:13:54.760 was criticized for the complexity of his special theory of relativity, 0:13:55.520 --> 0:13:58.600 he responded that a theory should be as simple as 0:13:58.640 --> 0:14:02.960 possible and no simpler. And I think that the financial 0:14:03.040 --> 0:14:06.559 theories that we're using are actually simpler than they should be. 0:14:07.120 --> 0:14:10.280 So there's no doubt that the efficient markets hypothesis cuts 0:14:10.360 --> 0:14:15.600 through a lot of really complicated and unnecessarily involved types 0:14:15.640 --> 0:14:18.320 of theories that really don't make any sense. And so 0:14:18.559 --> 0:14:21.720 that's one of the reasons why Fama, Samuelson and others 0:14:22.200 --> 0:14:26.280 u had such an impact on both academia and industry. 0:14:27.120 --> 0:14:29.360 But what we're seeing over the course of the last 0:14:29.520 --> 0:14:33.520 couple of decades is much more complicated financial dynamics. It's 0:14:33.560 --> 0:14:36.640 not the case anymore that a buy and hold strategy 0:14:36.680 --> 0:14:39.520 of a sixty forty portfolio is good enough for retirement, 0:14:39.640 --> 0:14:42.240 because well, we see markets going up and down in 0:14:42.280 --> 0:14:45.920 some very dramatic ways over short periods of time, and 0:14:46.360 --> 0:14:48.760 if we ignore those dynamics, we could actually get into 0:14:48.800 --> 0:14:50.840 a fair bit of trouble, especially those of us who 0:14:50.840 --> 0:14:53.480 are thinking about retiring within the next ten or twenty 0:14:53.520 --> 0:14:57.080 years versus thirty or forty years. So horizon matters, the 0:14:57.160 --> 0:14:59.320 nature of the buyers and sellers matter, the fact that 0:14:59.360 --> 0:15:02.600 we have an inner, nationally integrated financial system that's different 0:15:02.640 --> 0:15:05.640 than it was thirty or forty years ago. So I 0:15:05.680 --> 0:15:08.520 think that we do need to have more complex theories 0:15:08.840 --> 0:15:11.840 to match the complexity of the financial system as it 0:15:11.920 --> 0:15:14.600 is today. But it doesn't mean that that we can't 0:15:14.720 --> 0:15:17.680 simplify that kind of complexity. In other words, the theory 0:15:17.680 --> 0:15:21.800 of evolution is a great simplification of what happens in nature, 0:15:22.320 --> 0:15:26.400 and it is more complicated than the earlier stories about 0:15:26.440 --> 0:15:29.360 how we evolve and how we change, but I think 0:15:29.400 --> 0:15:32.760 that it does capture a very important set of of 0:15:32.840 --> 0:15:36.560 differences from those earlier theories. So what I'm hoping is 0:15:36.560 --> 0:15:39.440 that the adaptive market hypothesis, while it is somewhat more 0:15:39.480 --> 0:15:44.000 complicated because it contains both human behavior as well as 0:15:44.040 --> 0:15:50.280 efficient markets as uh sub subsets or subcases, it nevertheless 0:15:50.320 --> 0:15:54.240 provides a unifying framework that allows both of those theories 0:15:54.280 --> 0:15:57.680 to live happily under one roof. So I'd love to 0:15:58.200 --> 0:16:01.160 spin it forward and talk about this market today. Because 0:16:01.160 --> 0:16:04.200 there are all sorts of interesting debates going on right now. 0:16:04.240 --> 0:16:07.600 People say, is there a bubble going on? Has the 0:16:07.640 --> 0:16:13.480 Federal Reserve created some sort of unusual stability? What explains 0:16:13.840 --> 0:16:18.520 the lack of market volatility despite seeming you headlines that 0:16:18.560 --> 0:16:24.120 are extraordinary when you look at this current market from 0:16:24.160 --> 0:16:28.160 the sort of ecological standpoint that you describe, what are 0:16:28.160 --> 0:16:30.840 the what are some interesting things that you're seeing or 0:16:30.880 --> 0:16:35.360 that you're just sort of exploring in today's flora and fauna. Well, 0:16:35.400 --> 0:16:38.600 it's interesting that you mentioned those various different aspects of 0:16:38.640 --> 0:16:41.000 what's going on in the financial system, because they're actually 0:16:41.080 --> 0:16:44.040 quite closely related, but in ways that I don't think 0:16:44.040 --> 0:16:46.080 you would have been able to see if you're focusing 0:16:46.120 --> 0:16:50.080 on markets from the efficiency perspective. So take the example 0:16:50.320 --> 0:16:53.000 of the Fed. Well, we know that the FED engaged 0:16:53.080 --> 0:16:56.480 in some very significant quantitative easing in the aftermath of 0:16:56.520 --> 0:16:59.960 the financial crisis. Now why is that important? Well, quantity 0:17:00.000 --> 0:17:02.880 It of easing is a direct way of trying to 0:17:03.080 --> 0:17:08.640 stabilize markets and increase employment by taking on certain kinds 0:17:08.640 --> 0:17:13.560 of assets and managing the liquidity of the Federal reserve system. 0:17:13.600 --> 0:17:17.120 That involved reducing interest rates to a certain level and 0:17:18.040 --> 0:17:22.320 encouraging investors to put money in riskier assets. So that's 0:17:22.320 --> 0:17:24.560 what we've seen. We've seen in a low yield environment, 0:17:24.960 --> 0:17:29.480 investors have flocked to a variety of risky investments, but 0:17:29.600 --> 0:17:32.680 the vast majority of the funds have gone into stable, 0:17:32.840 --> 0:17:38.639 passive index products, and that in turn has actually caused 0:17:38.640 --> 0:17:42.120 equity prices to rise over the course of the last decade. 0:17:42.960 --> 0:17:47.680 And that increase in equity prices, particularly in passive vehicles, 0:17:48.160 --> 0:17:51.240 definitely contributes to the fact that we have lower volatility 0:17:51.280 --> 0:17:56.159 today than we had in probably twenty years. That decrease 0:17:56.200 --> 0:18:00.760 in average volatility, in turn has caused as investors to 0:18:00.800 --> 0:18:03.720 put more money in equities because of risk parity strategies 0:18:03.960 --> 0:18:08.159 and other volatility linked investments. So the action of the 0:18:08.160 --> 0:18:11.439 FED which was in response to this financial crisis, and 0:18:11.480 --> 0:18:15.080 it was an emotional reaction in a way, because one 0:18:15.119 --> 0:18:17.480 could argue that prices go up and down all the time, 0:18:17.480 --> 0:18:19.840 you should just let the chips fall where they may. 0:18:19.880 --> 0:18:22.720 But because we care about people who are out of work, 0:18:23.240 --> 0:18:25.879 we want to make sure that financial stability is a 0:18:25.960 --> 0:18:30.359 high priority among regulators and policymakers. So that kind of 0:18:30.400 --> 0:18:35.240 reaction has repercussions that have an effect on market dynamics. 0:18:35.320 --> 0:18:39.679 And we're working through those effects today. So when people 0:18:39.760 --> 0:18:42.280 hear the word adaptation, or at least when I hear 0:18:42.320 --> 0:18:44.639 the word adaptation, I also, you know, I think a 0:18:44.640 --> 0:18:48.720 little bit about resiliency and you know, again the ability 0:18:48.760 --> 0:18:50.639 to adapt to new situations. So when you look at 0:18:50.640 --> 0:18:54.640 the market nowadays, lots of people are thinking about valuations 0:18:54.680 --> 0:18:57.840 being sky high, the possibility of things may be beginning 0:18:57.920 --> 0:19:02.160 to pop as central banks withdraw their quidity. What's what's 0:19:02.200 --> 0:19:05.199 the fragility that you see in the ecosystem, What's the 0:19:05.320 --> 0:19:08.359 thing that could topple over the dynamic that we've been 0:19:08.400 --> 0:19:11.880 seeing for the past five or six years. Well that's 0:19:11.880 --> 0:19:16.199 a great point, because fragility is something that biologists and 0:19:16.280 --> 0:19:20.359 particularly ecologists study all the time. And one of the 0:19:20.359 --> 0:19:23.959 things that they tell us about fragility is that we 0:19:24.080 --> 0:19:27.560 need to have a certain amount of biodiversity in order 0:19:27.600 --> 0:19:31.280 to create a more robust ecology. The basic idea being 0:19:31.320 --> 0:19:34.040 that certain species can get wiped out because of an 0:19:34.119 --> 0:19:37.840 environmental change, but if we have a variety of different species, 0:19:38.080 --> 0:19:40.399 the likelihood that one or two of them will be 0:19:40.480 --> 0:19:44.960 able to survive will allow the ecology to maintain some 0:19:45.040 --> 0:19:50.000 semblance of its prior existence. Even before that big evolutionary shock, 0:19:50.880 --> 0:19:54.600 we don't have that same kind of resiliency concept in economics. 0:19:55.119 --> 0:19:57.560 I think that certain economists, over the course of the 0:19:57.640 --> 0:20:00.800 last several decades have tried to focus on that by 0:20:00.840 --> 0:20:04.679 looking at things like concentration in the industries and various 0:20:04.720 --> 0:20:07.119 different types of industries that are starting and those that 0:20:07.160 --> 0:20:11.600 are declining. But the idea of measuring resiliency in the 0:20:11.600 --> 0:20:16.040 economy is really pretty far behind what the biologists are doing. 0:20:16.720 --> 0:20:19.040 So from my point of view, I think that resiliency 0:20:19.080 --> 0:20:21.119 is really a key issue, and that's one of the 0:20:21.160 --> 0:20:23.840 reasons why I focus in some of my research on 0:20:24.000 --> 0:20:27.840 hedge funds. The hedge fund industry is actually a source 0:20:27.960 --> 0:20:31.159 of all sorts of new species. If you think about, 0:20:31.720 --> 0:20:34.919 you know, various different kinds of investment vehicles that are 0:20:34.960 --> 0:20:38.639 now widely available. A lot of those investment vehicles first 0:20:38.680 --> 0:20:42.959 began in the hedge fund industry, and so it's important 0:20:43.119 --> 0:20:46.520 if you want to maintain resiliency to have a vibrant 0:20:46.520 --> 0:20:49.479 hedge fund sector where all sorts of new ideas can 0:20:49.520 --> 0:20:51.760 get tried out, and the ones that work well will 0:20:51.880 --> 0:20:54.680 progress and grow, and the ones that don't will basically 0:20:54.680 --> 0:20:57.520 get wiped out. You want to have that kind of 0:20:57.600 --> 0:21:02.400 turnover in ideas and and financial products and services so 0:21:02.440 --> 0:21:04.560 that we don't ever get into a situation where we're 0:21:04.560 --> 0:21:07.639 getting locked into something. The one concern that I have 0:21:07.800 --> 0:21:11.320 about resiliency right now is that we have a huge 0:21:11.359 --> 0:21:15.960 amount of assets flowing into passive index strategies, and obviously 0:21:16.000 --> 0:21:19.359 that's been a very important source of investment return for 0:21:19.400 --> 0:21:23.280 a large majority of investors who don't have the skills 0:21:23.320 --> 0:21:27.720 to manage their portfolio actively. So active versus passive is 0:21:27.720 --> 0:21:31.760 a debate that I think has long been settled. Passive 0:21:31.880 --> 0:21:34.480 is definitely here to stay, and it's an incredibly important 0:21:34.520 --> 0:21:38.119 component of the flora and fauna of the investors that 0:21:38.520 --> 0:21:41.880 are looking for opportunities. The problem is that if we 0:21:41.960 --> 0:21:46.360 now are all investing in these passive vehicles, what happens 0:21:46.720 --> 0:21:50.080 when there's a stock market correction that inevitably there will be, 0:21:50.720 --> 0:21:54.320 and we see these passive investments under performing, Well, we're 0:21:54.359 --> 0:21:58.399 gonna get a massive exit from that particular set of vehicles. 0:21:58.520 --> 0:22:01.240 And like any kind of a situation where you've got 0:22:01.240 --> 0:22:05.000 a crowded trade and a massive unwinding, you can see 0:22:05.040 --> 0:22:10.480 a much bigger drop in these market levels. So crashes 0:22:11.080 --> 0:22:14.040 are now more likely. In fact, we see flash crashes 0:22:14.080 --> 0:22:17.840 happening all the time, which is a technological example of 0:22:17.880 --> 0:22:20.560 these kinds of phenomenon happening in very very short term. 0:22:21.280 --> 0:22:23.240 But I think that this is a concern that I 0:22:23.320 --> 0:22:28.719 have about resiliency. We're creating opportunities for financial panics that 0:22:29.119 --> 0:22:31.399 didn't exist ten years ago or didn't exist to the 0:22:31.440 --> 0:22:34.080 same degree. So we just need to be wary of 0:22:34.119 --> 0:22:38.120 that and be prepared for those kinds of shocks. Very 0:22:38.359 --> 0:22:42.639 bleak answer, but obviously, you know, it's definitely capturing an 0:22:42.680 --> 0:22:45.280 anxiety that I think a lot of people feel right 0:22:45.320 --> 0:22:47.520 now about the markets. We've talked about this a lot, 0:22:47.600 --> 0:22:50.440 that sort of where is this sort of endless boom 0:22:50.440 --> 0:22:53.920 and E T f S and passive actually go. But 0:22:54.040 --> 0:22:57.040 you know, there's debate about how big passive could get. 0:22:57.119 --> 0:23:02.160 There's the study of ecology. Give us any clues into 0:23:02.400 --> 0:23:05.439 when tipping points could happen or anything like that, or 0:23:05.480 --> 0:23:07.879 do we just sort of have do you know it'll 0:23:07.960 --> 0:23:10.400 just happen one day and it will be all over Well, 0:23:10.440 --> 0:23:12.960 I think it does give us a clue. Rather, it 0:23:13.000 --> 0:23:16.240 gives us a way of trying to understand where those 0:23:16.280 --> 0:23:20.439 tipping points might arise, and once again, the way to 0:23:20.480 --> 0:23:24.640 do that is to measure the biomass of the various 0:23:24.640 --> 0:23:29.159 different species and ask what they're driven by and ultimately 0:23:29.520 --> 0:23:34.360 what will cause them to change their direction. I think 0:23:34.359 --> 0:23:37.240 that in the case of passive investing, it's pretty clear 0:23:37.560 --> 0:23:41.880 that it offers tremendous benefits to a large number of investors. 0:23:41.880 --> 0:23:44.080 So we're not going to see any kind of a 0:23:44.119 --> 0:23:48.640 decline unless and until there are some kind of widespread 0:23:48.800 --> 0:23:51.920 market decline. If the stock market goes down by ten 0:23:52.040 --> 0:23:57.080 or that might be enough to cause a retreat into 0:23:57.359 --> 0:24:00.879 fixed income assets or cash for a period of time. 0:24:01.520 --> 0:24:03.760 And so I think that's really the kind of tipping 0:24:03.800 --> 0:24:07.920 point for passive investments because right now, given the low 0:24:08.000 --> 0:24:12.399 yield environment, investors are really continuing to pour money into 0:24:12.400 --> 0:24:16.280 that sector. But eventually nothing lasts forever. We're going to 0:24:16.359 --> 0:24:20.280 see reversals in every kind of asset class. And in 0:24:20.320 --> 0:24:22.600 this case, if we take a look at the nature 0:24:22.720 --> 0:24:25.280 of the investors who are going into the market versus 0:24:25.320 --> 0:24:28.080