Odd Lots - An MIT Professor Explains His Original Theory For How Markets Really Work

Episode Date: December 4, 2017

There are two popular schools of thought with regards to how markets work. There's the efficient markets hypothesis (EMH) which says that it's basically impossible to beat the market, because all information is completely priced in at all times (more or less). On the other side is an increasingly popular behavioral view which argues that various human emotions and biases are always creating situations that aren't justified by the data. On this week's episode of the Odd Lots podcast, we speak to Andrew Lo, a professor of finance at the MIT Sloan School of Management about his own theory, which he calls Adaptive Markets. The theory attempts to bridge the behavioral approach with the efficient markets view. He argues that the proper way to view the market is through an ecological lens, examining the players as flora and fauna of a complicated system, to help determine who's thriving, who's dying, and where asset prices will go.See omnystudio.com/listener for privacy information.

I'm June Grasso, inviting you to join me for the Bloomberg Law podcast. Every weekday, we help you make sense of the legal stories that shape the nation and the world. Listen for complete analysis of the biggest court cases, the latest actions from Congress and regulators, and the legal moves driving the markets, from corporate law to constitutional law, and from state courts to the Supreme Court. At Bloomberg Law, we go beyond the day's headlines. We speak with top attorneys, judges, scholars and policy experts to break down what the rulings really mean. We do this every weekday,

then bring you the best conversations in our daily podcast. Search for Bloomberg Law on YouTube, Apple, Spotify, or anywhere else you listen. On the East Coast, listen as you start your day, and on the West Coast, catch up in the evening. That's the Bloomberg Law podcast with me, June Grosso. Subscribe today wherever you get your podcast. Hello and welcome to another episode of the Odd Lots Podcast. I'm Tracy Alloway. And I'm Joe Weisandthal. Joe, what did you study at college?

Hmm. I'm already nervous about answering this question because I actually genuinely don't know where you're going with it. Well, I also don't know what you studied, so I'm genuinely curious. I studied international relations. Actually, I went at University of Texas. They called it government. which is not really a thing anywhere else. Right.

It was kind of like their political science department, but I focused on international relations. Okay. I swear this is a complete coincidence, but I also studied international relations. Really? That's funny that, like, of all this time I've known you, this has never come up.

No, seriously, like for people who think, who are listening, who think maybe we're faking this or something, it's actually, I genuinely did not know that about you. Now people are thinking that we just never talk to each other outside of this podcast. We just only talk, pockets. No personal stuff. The reason I was bringing it up was because I was trying to think of a

parallel with what we're going to speak about in just a few minutes. And I was thinking, you know, in international relations, there are these two dominant theories that govern how you think about the world. They're realism and liberalism. Do you remember that? I'm glad you didn't ask me to name them. I would have remembered realism and I would have blanked on the other one. But yes, that sounds right. Okay, so realism is this theory that states and governments and people are essentially self-interested and, you know, everyone's out to get each other. And liberalism is, oh, actually, we can all get along and there's scope for cooperation. Two diametrically opposed theories that completely govern that particular study.

Now, the reason I'm bringing it up is because we are going to talk about a similar parallel in economics. Can you guess what it is? Why don't you just tell me? I mean, I think I know where it's going, but I really like the way you're taking this. All right. So it's the efficient market hypothesis versus behavioral economics. Ah, yes. Yes.

Okay. So most people probably know this, but the efficient market hypothesis basically says that you can't beat the market that it's a perfect reflection of the information currently out there in a perfect reflection of the price that you should be paying for that information. Meanwhile, behavioral economics basically suggests that human beings can be irrational and we can get stuff wrong and that means that markets also can be irrational and can get stuff wrong. So two pretty much diametrically opposed schools of thought. So are we going to find out which one is correct today? No. We're actually going to talk to someone who thinks they've found a middle path between those two seemingly opposed schools of thought. All right. I'm intrigued. So who are we talking to and what's their theory?

Okay. I'm really excited to bring on Andrew Lowe. He's an economist. He's a long-time MIT professor. And he's written, well, he's written several books. But most recently, he has written a book on exactly this topic. Andrew, thank you so much for joining us. It's a pleasure. Thanks for having me. So just going back to the efficient market hypothesis, I gave a little snapshot of it, but maybe you could describe it a little bit more. And also perhaps explain how it came to be a fundamental tenet of modern financial theory when everyone seems to beat up on it nowadays. Sure. Well, you know, it's a really interesting idea. And it's the brainchild of two economists. Gene Fama at the University of Chicago coined the term and came up with the basic idea that in an efficient market, prices fully reflect all available information.

And so if that's the case, then you really can't beat the markets by using information because it's already in the price. And Paul Samuelson was the other economist who contributed to this theory. And his paper was titled, Proof, that properly anticipated prices fluctuate randomly, which is a very fancy way of sense. saying that once you incorporate all available information into prices, you don't know where it's going to go. So you can't predict future prices based upon where it is today. It seems to me the efficient market's hypothesis has come under a lot of criticism in recent years. We've seen Nobel Prize winners who have won for their work and sort of talking about this more the behavioral approach, which is very, as Tracy explained in the beginning, is sort of this

opposite view, but it still seems for all the criticism that efficient markets has come under, it's still pretty hard to beat the market. Like it still seems like more or less it's a pretty difficult task. Well, that was exactly the conundrum that I was trying to figure out when trying to sort through this particular theory versus all of the various different critiques. The efficient markets hypothesis actually works pretty well. It is really hard to beat the market and prices do actually reflect a lot of information that's out there. And so it really is hard to reconcile the basic ideas about efficient markets with all of the psychological and behavioral anomalies that people like Kahneman, Tversky, Thaler,

and others have come up with to try to counteract these various different ideas of efficiency. So walk us through how you tackled that problem then and the theory that you came up with. you call it adaptive markets? Right. The basic idea is that there are elements of both of these schools of thought that work well, but neither is the complete picture. You really need both of them. They're both important aspects of the same phenomenon.

And the idea behind adaptive markets is fairly straightforward. It basically says that investors are highly competitive and adaptive. and therefore it is tough to beat the market because lots of other people are trying to do that. But it's not impossible because every once in a while, markets aren't driven just by logic and analysis, but they're also driven by human emotion. So for example, when the stock market goes down by 10 or 20 percent, a lot of people are going to start heading for the exits. They're going to start unwinding their portfolios. And that kind of a herd mentality can actually lead to prices that don't fully reflect the information that's available at that point in time. So in other words,

it reflects emotion as opposed to fundamental valuations. The efficient market's hypothesis is a great way to explain market dynamics when people are acting logically. But every once in a while, we freak out. And the freak out factor is where the behavioral economists have their day. Both of these are important aspects of market dynamics, but they don't always operate at the same time. And it's really trying to understand which part of these different phases are relevant at a given point in time that the adaptive markets is focused on. So I think that like anyone who looks at markets can appreciate that there are times when sort of pure emotion and animal spirits really take over, whether it's a panic,

whether it's in the stage of a bubble. But one of the things that we've talked about a lot on this podcast, in fact, is that even if you know something is a bubble or even if you know something is a panic, it's really hard to know what stage you're in and whether you're near a bottom or whether you're near a top. So my question is, if you know, you sort of thread this middle ground where sometimes behavioral takes over, sometimes markets are based on pure information, does your theory help one get any closer to actually, you know, maybe beating the market? Well, it does. And I argue that those who do beat the market today are using some form of this theory. For example, hedge fund managers understand instinctively that market dynamics change

as a function of the flora and fauna of the market ecology. In other words, they look at who are the participants in any given market at a point in time. And they, they, feel the market dynamics as a function of those various different participants. It really is trying to understand markets from a more of a biological perspective than a physical perspective. And I think that that kind of approach requires us to collect very different kinds of data from the ones that we're doing right now. And if we had that data, we can make much better predictions about where the market is going. So what sort of data are you talking about? What would be helpful just knowing who is and who isn't participating in a particular market?

Well, let me start by giving you a different perspective. Imagine if you're an ecologist being asked to study a particular ecological niche, say the Amazon rainforest. And let's suppose that you would like to save a particular species in that ecology. How would you go about it? Well, as an ecologist, you'd probably start by taking an inventory of all of the different species, how they relate to each other, what they eat, who they prey on, what the various different food chain relationships are, what the environment looks like, and how it's changing over time.

Once you study all of those aspects of the environment and the flora and the fauna, you can then start identifying key aspects of that system that require management in order to preserve a given species or in order to highlight a particular species. If you now take that same analogy and apply it to the financial markets, you'd see that what you'd want to start with is not just looking at prices, but to understand who the buyers are, who the sellers are. And not just that, but the nature of the buying and the selling, pension funds, broker dealers, hedge fund managers, who are the investors are, who are the ultimate buyers and sellers are, and what motivates them. Once you understand the nature of the flora and fauna of the financial markets, you can then start making predictions like, well, if it turns out that pension funds are going to be indexing and sticking to a particular asset allocation over a period of time,

then that means that they're going to be submitting buy orders when the market goes down and submitting sell orders when the market goes up in order to maintain that strategic asset allocation. You'd understand the motivation for the various different species in that marketplace and be able to make better predictions about how they would react to certain kinds of market events. That's the kind of data that I think we need in order to be able to analyze market dynamics. Now, your book and your theory is called Adaptive Markets, if that data were to be made available, presumably all of that would then be incorporated back into price because people adapt. Would that then require some sort of further metadata for investors wanting to stay ahead of the trend?

Absolutely. In other words, you really have to take into account the impact of behavior on those dynamics. And that's the same thing in other kind of biological settings. You know, for example, if it turns out that one species begins to grow, that growth is going to mean that it's going to be more plentiful in terms of its numbers, and therefore it's going to require more food. Whatever it preys on is going to end up being selected out, and ultimately that means it's going to have less. food per individual, which means that eventually the population is going to decline. So in other words, there are feedback loops in the system that have to be incorporated in terms of predicting how one species will do relative to another. The case of human beings interacting with each other is more complicated because we can think farther ahead and plan and predict

in much more sophisticated ways. So once we see these kinds of changing dynamics, we're going to alter our behavior, and that change in behavior will then have an impact on those dynamics. So the system tends to be more complicated, but nonetheless, it is a system that can be modeled, and with the right kinds of mathematics and statistics, we can actually do a better job of modeling that system than using static physical laws that we're trying to apply right now to market dynamics. So this is what I'm really curious about, because one of the attractions of the efficient market hypothesis is its relative simplicity as a model. What you're saying definitely makes sense,

but I can only imagine that, you know, identifying and figuring out how a complete ecosystem of a particular market works, are you actually simplifying anything there? How useful is it as an actual model? Well, all I can say is what Albert Einstein said when he was accused of developing theories that were so complicated. And by the way, I'm no Albert Einstein, so I'm not comparing myself to the great physicist. But when Einstein was criticized for the complexity of his special theory of relativity, he responded that a theory should be as simple as possible and no simpler. And I think that the financial theories that we're using are actually simpler than they should be.

So there's no doubt that the efficient markets hypothesis cuts through a lot of really complicated and unnecessarily involved types of theories that really don't make any sense. And so that's one of the reasons why Fama, Samuelson, and others had such an impact on both academia and industry. But what we're seeing over the course of the last couple of decades is much more complicated financial dynamics. It's not the case anymore that a buy-and-hold strategy of a 60-40 portfolio is good enough for retirement because, well, we see markets going up and down in some very dry.

dramatic ways over short periods of time. And if we ignore those dynamics, we could actually get into a fair bit of trouble, especially those of us who are thinking about retiring within the next 10 or 20 years versus 30 or 40 years. So horizon matters, the nature of the buyers and sellers matter, the fact that we have an internationally integrated financial system. That's different than it was 30 or 40 years ago. So I think that we do need to have more complex theories to match the complexity of the financial system as it is today. But it doesn't mean that we can't simplify that kind of complexity. In other words, the theory of evolution is a great simplification of what happens in nature. And it is more complicated than the earlier stories about how we evolve and

how we change. But I think that it does capture a very important set of differences from those earlier theories. So what I'm hoping is that the adaptive market hypothesis, while it is somewhat more complicated because it contains both human behavior as well as efficient markets as subsets or subcases. It nevertheless provides a unifying framework that allows both of those theories to live happily under one roof. So I'd love to like spin it forward and talk about this market today because there are all sorts of interesting debates going on right now. People say, is there a bubble going on? Has the Federal Reserve created some sort of unusual stability, what explains the lack of market volatility despite seeming, you know,

headlines that are extraordinary. When you look at this current market from the sort of ecological standpoint that you describe, what are the, what are some interesting things that you're seeing or that you're just sort of exploring in today's flora and fauna? Well, it's interesting that you mentioned those various different aspects of what's going on in the financial system, because they're actually quite closely related, but in ways that I don't think you would have been able to see if you're focusing on markets from the efficiency perspective. So take the example of the Fed. Well, we know that the Fed engaged in some very significant quantitative easing in the aftermath of the financial crisis. Now, why is that important? Well, quantitative

easing is a direct way of trying to stabilize markets and increase employment. by taking on certain kinds of assets and managing the liquidity of the Federal Reserve system. That involved reducing interest rates to a certain level and encouraging investors to put money in riskier assets. So that's what we've seen. We've seen in a low-yield environment, investors have flocked to a variety of risky investments, but the vast majority of the funds have gone into stable, passive index products. and that in turn has actually caused equity prices to rise over the course of the last decade. And that increase in equity prices, particularly in passive vehicles, definitely contributes to the fact that we have lower volatility today than we had in probably 20 years.

That decrease in average volatility, in turn, has caused investors to put more money in equities because of risk parity strategies and other volatility. linked investments. So the action of the Fed, which was in response to this financial crisis, and it was an emotional reaction in a way because one could argue that prices go up and down all the time. You should just let the chips fall where they may. But because we care about people who are out of work, we want to make sure that financial stability is a high priority among regulators and policymakers. So that kind of reaction has repercussions that have an effect on market dynamics and we're working through those effects today. So when people hear the word adaptation, or at least when I hear the word adaptation, I also, you know, I think a little bit about

resiliency and, you know, again, the ability to adapt to new situations. So when you look at the market nowadays, lots of people are thinking about valuations being sky high, the possibility of things maybe beginning to pop as central banks withdraw their liquidity. What's the fragility that you see in the ecosystem? What's the thing that could topple over the dynamic that we've been seeing for the past five or six years? Well, that's a great point, because fragility is something that biologists and particularly ecologists study all the time. And one of the things that they tell us about fragility is that we need to have a certain amount of biodiversity in order to create a more robust ecology. The basic idea being that certain species can get wiped out.

out because of an environmental change, but if we have a variety of different species, the likelihood that one or two of them will be able to survive will allow the ecology to maintain some semblance of its prior existence, even before that big evolutionary shock. We don't have that same kind of resiliency concept in economics. I think that certain economists over the course of the last several decades have tried to focus on that by looking at things like concentration in the industries and various different types of industries that are starting and those that are declining. But the idea of measuring resiliency in the economy is really pretty far behind what the biologists are doing. So from my point of view, I think that resiliency is really a key issue. And that's

one of the reasons why I focus in some of my research on hedge funds. The hedge fund industry is actually a source of all sorts of new species. If you think about various different kinds of investment vehicles that are now widely available, a lot of those investment vehicles first began in the hedge fund industry. And so it's important if you want to maintain resiliency to have a vibrant hedge fund sector where all sorts of new ideas can get tried out

and the ones that work well will progress and grow and the ones that don't will basically get wiped out. you want to have that kind of turnover in ideas and financial products and services so that we don't ever get into a situation where we're getting locked into something. The one concern that I have about resiliency right now is that we have a huge amount of assets flowing into passive index strategies. And obviously, that's been a very important source of investment return for a large majority of investors who don't have the skills to manage their portfolio actively.

So active versus passive is a debate that I think has long been settled. Passive is definitely here to stay, and it's an incredibly important component of the flora and fauna of the investors that are looking for opportunities. The problem is that if we now are all investing in these passive vehicles, what happens when there's a stock market correction that inevitably there will be? And we see these passive investments underperforming. well, we're going to get a massive exit from that particular set of vehicles. And like any kind of a situation where you've got a crowded trade and a massive unwinding, you can see a much bigger drop in these market levels. So crashes are now more likely.

In fact, we see flash crashes happening all the time, which is a technological example of these kinds of phenomenon happening in very, very short term. But I think that this is a concern that I have. about resiliency. We're creating opportunities for financial panics that didn't exist 10 years ago or didn't exist to the same degree. So we just need to be wary of that and be prepared for those kinds of shocks. Very bleak answer. But obviously, it's definitely capturing an anxiety that I think a lot of people feel right now about the markets. We've talked about this a lot. the sort of where does this sort of endless boom in ETFs and passive actually go?

But, you know, there's debate about how big passive could get. Does the study of ecology give us any clues into when tipping points could happen or anything like that? Or do we just sort of have to, you know, it'll just happen one day and it'll be all over? Well, I think it does give us a clue. Rather, it gives us a way of trying to understand where those tipping points might arise. And once again, the way to do that is to measure the biomass of the various different species and ask what they're driven by and ultimately what will cause them to change their direction. I think that in the case of passive investing, it's pretty clear that it offers tremendous benefits

to a large number of investors. So we're not going to see any kind of a decline unless and until there is some kind of widespread market decline. If the stock market goes down by 10 or 20 percent, that might be enough to cause a retreat into fixed income assets or cash for a period of time. And so I think that's really the kind of tipping point for passive investments, because right now, given the low-yield environment, investors are really continuing to pour money into that sector. But eventually, nothing lasts forever. We're going to say, see reversals in every kind of asset class. And in this case, if we take a look at the nature of the investors who are going into the market versus those who are willing to take money

out of the market, we'll get a better idea of when that kind of a tipping point might be and what kind of triggers might cause that tipping point to happen. I'm trying to think if passive funds are the 800-pound gorillas or the excitable antelopes in the market ecosystem. All right, Andrew Lowe, MIT professor and author of Adaptive Markets Financial Evolution at the Speed of Thought. Thank you so much for joining us. Thank you. It's been a pleasure. So, Joe, what did you think of the, you know, the ecosystem analogy was strong in that conversation. Yeah, I really like that conversation. And I really like that framework for thinking about it.

You know, it's funny thinking about what we do all day writing about markets and what people think is going to go up or what people think are good investments or not. Even a pure EMH world, we'd kind of have to admit that our jobs are sort of stupid in a way. Like, why even bother writing about this? Why bother saying, why bother bringing people's opinions if there's no way for anyone to just sort of get a pure edge? And what I like about Andrew's view is the idea that it's really tough, but it's not impossible. And that if you explore the right facets, there is value in. sort of in at least trying. I agree, although I'm not sure I like the notion that our jobs are meaningless. Well, one thing I really liked about his framing, though, is the emphasis on market

structure, because this is something that, you know, you and I bang on and on about. But in order to understand the market, you really need to understand the structure of it and the various players and the motivation at play. And I really think that's the point he's making about his theory. That said, And, you know, I can imagine that that does get quite complex when you're an economist trying to publish a, you know, paper, for instance. That's a lot to model. Totally. But this idea that, you know, there's sort of two different ways of thinking about the market. So one is you might have a stock and you might look at its income statement and its balance sheet and sort of what we were talking about with Azwath Damadaran recently.

But then the other aspect is this where it's like you look at the old. overall market and you try to figure out who the gazelles are and who the 800 pound gorillas are and figure out, okay, what is the motivation of each of these? And I think that also is a very interesting way of thinking about what's what in the market. Yeah, agreed. I really want to go to the zoo now. I have this like urge to go to the zoo. Okay, let's leave it there. That was another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Aller. with. And I'm Jill Wisenthall. You can follow me on Twitter at the stalwart. And you can follow Andrew Lowe on Twitter at Andrew W. Lowe and follow our producer Sarah Patterson at Sarah Pat with

two teas. Thanks for listening.