The Joe Walker Podcast - Eugene Fama — For Whom Is The Market Efficient?

Episode Date: December 31, 2024

Eugene Fama is a 2013 Nobel laureate in economic sciences, and is widely recognised as the "father of modern finance." He is currently the Robert R. McCormick Distinguished Service Professor of Finance at the University of Chicago. Full transcript available at: https://josephnoelwalker.com/eugene-fama-156/See omnystudio.com/listener for privacy information.

Hi everyone, this is a conversation with the economist Eugene Farmer. On one of my trips to the US, an incredible opportunity came up to chat with Gene in Los Angeles just before I returned to Sydney. It was a lot of fun. Gene of course won the Nobel Prize in Economic Sciences in 2013. He's widely recognized as the father of modern finance and is currently a professor of finance at the University of Chicago. As of 2024, based on his academic work, he's ranked as the 10th most influential economist of all time. This is a fairly lighthearted and relatively short chat, a little different to

my usual episodes. Enjoy. Eugene Farmer, welcome to the podcast. Thank you. Eugene, I was talking with a few friends who work in high finance in preparation for this conversation. And one of my impressions is that a lot of people think of you as holding this extreme position that markets are perfectly rational. But I know that you don't believe that. And I've also heard people who've taken your classes at chicago say that you repeat ad nauseum that models aren't real and the question is really how efficient are markets and so it's a different way of putting it actually who is it efficient for oh interesting another way to put it can you elaborate on that well i mean for almost everybody the market is

efficient in the sense that they don't have information that's not already built into prices. So people who have special information, the market's not efficient for them. So let's say insiders, for example, typically have special information. So as far as they're concerned, their stock is not priced totally efficiently because they have information they know will change the price. But for everybody else, assuming it's efficient, maybe a really good approximation. So does that mean you think that the semi-strong version of the efficient markets hypothesis is the most plausible version?

No, I don't think those words really make any sense anymore. Oh, interesting. I invented those words 100 years ago. Right, right. But that was describing the nature of the tests that people were doing. Not the reality of what the market is like. It's just what kind of tests are likely to expose whatever shortcomings the efficient market hypothesis has. I see.

And there are some that are not strong enough to expose so that would i used to call weak form tests yeah and semi-strong would be a little bit better and then strong form would be the way i describe it and you find people who can beat the market i say so so let me ask you then if you had to quantify in some very crude way where you sit on the continuum between a market that's perfectly efficient for everyone and a market that's perfectly inefficient for everyone um how close are you to the perfectly efficient for everyone end of the spectrum like 95 percent of the way there well i can't put a number on it because that would be i'm a data person so that

would require data that is not sufficient to answer that question. So if you give me a group of people, I'll have a guess. So if you say, tell me about professional investors, and I'll say a very small fraction of them show evidence of having information that isn't already built into the price. So that's going to the top of the food chain. Among the professionals, there are very few that have information that isn't already in the price. If I go out to the public, all right, everybody. The market's efficient for everybody out there. So rather than asking you to define the efficient markets hypothesis

for probably the umpteenth time in your life, perhaps I could give a four-point summary, not just of it, but its implications, and then you can grade me on it if you like. All right. So number one, the efficient markets hypothesis is simply the claim that prices fully reflect available information. Correct. Number two, that also means that prices should roughly follow a random walk.

False. So the problem is, this is what I call the joint hypothesis problem. Yeah. You can't tell me that prices reflect all available information unless you take a stance on what the price should be. So you have to have some model that tells me, for example, what is risk and what's the relation between risk and expected return. And then we can look at deviations from that and see if the market is efficient. So there is what I call this joint hypothesis problem.

You need a model that tells you how prices get formed. So, you know, in the jargon, that's called a model of market equilibrium. You need to join that tells you how prices get formed. So, you know, in the jargon, that's called the model of market equilibrium. You need to join that with efficiency. Then I can test it in the context of whatever you tell me is that model determining prices. I feel like that's perhaps the deepest insight of your work, the joint hypothesis problem.

I do want to come back to it because I want to talk about asset pricing models. Right. But, but i mean that was actually going to be my third and fourth points in my summary so the the two key implications of the efficient markets hypothesis are to borrow dick thaler's um summary that the price is right and that there's no free lunch. And then I guess relatedly and finally. You have to tell me what that means. That's the problem, right? Yeah, exactly, exactly. That's where the joint hypothesis problem comes in.

Yeah. So, okay, anything else you would add or change about that summary? No. Okay. So I'd like to talk about some specific anecdotes and then just get your interpretation of them. And of course, these are just anecdotes, but it still might be fun to hear how you think about them.

So first is GameStop. I didn't follow that very carefully, so I'll tell you what happened. Yeah, just in brief, at one point the stock price was about $3. About a week later, it was $100. One of those prices was probably massively wrong, and I think it's almost certainly the high one. Where is it now? Good question.

Maybe I should check, but I think it's come right back down. Okay. There's no doubt that the price can get out of line, that the market for that stock can become inefficient if enough people pile in on it. So, finance is just a branch of economics. Every branch of economics says supply and demand determine prices. So if the demand gets high, the price is going to go up. And maybe that will last, maybe it won't. But in this case, if people are just doing it because other people are doing it,

then it's going to bail out eventually. So those things happen, but they're exceptions. They're not the rule. It's not everybody's investing that we're talking about there. It's not big things either. You know, you're dealing with a little company in that case. So you can distort prices with enough demand, or you can distort them the other way by not having enough demand.

I'd like to talk about some potentially bigger things okay a little bit later such as the u.s housing market but we can we can come to that yeah i'm working on that right now actually oh fascinating okay all right well i'd definitely like to hear about that but a few more anecdotes first so how do you interpret the success of outlier investors or firms, people with incredible track records like, for example, Renaissance and Jim Simons? Are they examples of survivorship bias or are they exceptions to the rule of the efficient markets hypothesis? Suppose we take 10,000 tosses of a coin and I'm telling you we're going to do it 10,000 tosses of a coin,

and I'm telling you we're going to do it 10,000 times, and the probability of a head is 0.5, and I'm going to say, how many heads can you get in a row? Well, if you do it 10,000 times, you're going to get a lot of runs of heads and tails. So you're going to get a lot of big winners and a lot of big losers. So my message is, be careful.

After the fact, what looks like good performance could just be luck. So when people have studied this, what they've found is, if you look at the winners of the past and then you follow them in the future, they don't look like winners anymore. Most of them just look random after you anoint them.

That's pretty typical. But, of course, even some fraction of those will continue to do well solely by chance. So the problem is 20-20 hindsight. It doesn't work. You have to identify before the fact. Or you can do as Ken French and I did in that paper. We said, well, given the game that's played, what fraction of people would you expect to win by chance?

And if you look at it, I always chuckle when there's bad news coming. So if you look at the cast of mutual fund managers, what you find is before fees and expenses, in other words, not returns to investors, but just returns on their portfolio before you take out the expenses that they take back themselves. Well, then what you see is there's a very small fraction

that you can't explain by chance. So there are some people out there that do have special information. If you take away fees and expenses though, oh, but it's a terrible game for investors. They lose. So it looks like now even in that game, there are winners. There are people that do better than their fees and expenses. But you expect lots of those by chance, and there are fewer of them than you expect. Well, not fewer than you expect by chance, but a much smaller number than you get before fees and expenses. But chance alone will produce such results.

That's the problem. So when we anoint people, most of the time we're anointing them based on chance. They were just lucky. Is it less likely that they were just lucky if they also have a compelling causal theory as to how they were successful? So say someone like George Soros comes in with reflexivity or or Michael Burry has his kind of theory of what's going to happen to the U.S. housing market and and and all that before it actually happens if there's a compelling causal

theory does that increase the likelihood that it's actually due to skill rather than love? You have to do the test right if you if you do the test after the fact there's always a causal theory that somebody will come up with but you have to do it you have to do the test. Right. If you do the test after the fact, there's always a causal theory that somebody will come up with. But you have to do it looking forward. You have to tell me your causal theory, and then we'll follow it. And we'll see how it does. And if it works on a better than chance basis, fine. I'm not one that says these things can't happen. They can happen.

But that's the way you have to test them. You have to test them going forward. You can't test them looking backward. Yeah. Or otherwise the causal theory is just like an adornment. Otherwise it's just rationalization. Post hoc. Right.

Post hoc. What do you, I'm curious, what do you make of George Soros' theory of reflexivity? Just intuitively. I have no idea what do you make of George Soros' theory of reflexivity? Just intuitively. I have no idea what it is. Oh, really? Why would I know what that is? The idea that investors react to price increases and it's like a self-fulfilling. So he thinks it's momentum, basically.

Exactly. Well, there is, in stocks, there is a little bit of momentum. Very short-lived. And I've never seen anybody, I mean, I've not seen evidence of professional managers that can't effectively gain from it. Everybody knows it's in the data. That's well-documented, but it's very short-term. Notically, you can capitalize on it. It's not something that I look now and then two weeks later, I can capitalize on it. It's not something that I look now and then two weeks later I can capitalize on it.

It's not. It's very short term. I see. So, but that is one of the, on a statistical basis, that's one of the embarrassments of market efficiency is the existence of this momentum that doesn't seem to be tied to risk in any sense because momentum changes so much over short periods of time and moves across stocks so much in short periods of time that you can't attribute it to risk it's too short term so that no i have no problem i mean

it was one of my phd students that discoveredums. And when he came to me and thought I was going to be mad at him, I said, no, it's in the data. It's in the data. That's it. That was Cliff Asnos. Yeah, right. So this next question is high variance. It could either be very dumb or very interesting,

but I'll give it a try. So I guess I'm trying to gesture at how solid the assumptions like information theory are underpinning the efficient markets hypothesis. So in a million years, if human civilization and stock markets still exist, do you predict that? Will markets be more or less efficient? Yeah, let me put it that way. This is like usually the way it's asked, we've gotten so much better at collecting

information, has the market become more efficient? Well, the problem is you can't, that's so hard to test in the data. You don't really know what the answer is. So the way I answer it is, the market has always looked pretty efficient. When I did my thesis in 1963, we didn't have all of the you know the high the high speed stuff that we have now but getting information but it still looked very efficient at that point i'm not sure there's any evidence that it's more or less efficient now got it got it we discussed the joint hypothesis problem perhaps you could just elaborate on that a little further. Okay, so you cannot test market efficiency without a story

about risk and return, which is a market equilibrium issue. And the reverse is also true. You can't test models of market equilibrium without market efficiency. So these two things are like joined at the hip. They can't be separated. People who do market efficiency, I don't,

they almost don't exist anymore. Everybody takes it for granted in the academic sphere. It's considered uninteresting to test. But, everybody that does market efficiency understands the giant hypothesis problem, but it's not that widely recognized

among the people who do asset risk and return models. So they just, it's not that widely recognized among people who do asset risk and return models. So they just implicitly assume, but they never make it explicit. I see. So they're not so interested in the efficiency questions. No, they take it for granted. So there are a few asset pricing models. Obviously, the capital asset pricing model, or CAPM,

then there was the three-factor model that you and ken french created to extend the cap m and then after that more recently the five-factor model um there are also models that incorporate momentum as a factor i have some questions about the cap m perhaps we could just begin if you could just very briefly outline what the CAPM actually is. Well, the CAPM was a brilliant insight of Bill Sharp. It was his, I don't think it was his PhD thesis, but it was the next paper that he wrote. It was published in 1963, I think. And it was the first asset pricing model. So it was the first formal story about what is risk and what's the relation between risk and expected return.

And the model is really simple. So it basically says, in a simple world, everybody would hold a combination of risk-free security and the market portfolio. And you would vary a risk by how much you put in the risk-free security and how much you put in it by varying the proportions in the two. In that model, if everybody followed it and they all had the same information, in other words, the market was efficient, it would say that the measure of risk is your sensitivity to the market portfolio, the sensitivity of a security's return to the market return. That was all you would have to know in order to describe the expected return on the security.

So that was a powerful idea. And it was tested up and down. It looked very good for the way these models go. They look very good for 10 years. And then so-called anomalies come along that say, well, they can't explain this, can't explain that, can't explain the other thing. That's what happened to that one.

That's what happens to every asset pricing model basically. Enough anomalies accrue that it starts to look pretty bad. People look beyond it, right? Yeah. So that's why we came up with the three-factor model and then the five-factor model. Yeah. And then I'm not sure whether you saw this new, there's a new paper by Nicholas Hommel

and a couple of other authors where they compared different discounting approaches on their ability to predict actual market prices. And they found that the discounting based on expected returns, such as variance on the CAPM or multi-factor model actually performs very poorly and i know that you've you and and ken french have have questioned the cap m for a few decades now i guess my question is is there anything left of it? Is it just utterly useless now at this point? It's not utterly useless. I would never use it.

So people who don't understand asset pricing use that model in their classes, for example. So corporate finance people, when they teach capital budgeting, will tell you to use the CAP M to calculate your cost of capital. The problem is that's terrible in practice. Basically, what the evidence says is you can't use this market sensitivity as a measure of differential risk. You do that, it looks like everything has the same expected return.

It just doesn't work. So its applicability is basically gone. that, it looks like everything is the same expected return. It just doesn't work. So its applicability is basically gone. But the insight of the model was incredible. So I never take that away from Bill Sharpe. As models go, this one really opened the field up. Yeah. There's no way around that. The field of asset pricing basically starts with that model. And it evolved. Bob Merton made a huge contribution to it.

I don't know, three-factor and five-factor model. Those are kind of ad hoc. Those are trying to pick up things that we observed in the data. They're not the same. No. It's not something we came up with without looking at the data. So it's been suspicious from that perspective. But people have kind of lost interest in asset pricing

because stuff we had that looked good doesn't look that good. It's easy to find stuff that doesn't work for us. So asset pricing is kind of at a slow point right now. The young people in finance are doing things that really don't look like asset pricing. They're kind of branching off into other areas. Otherwise, they won't get tenure, I guess. What are the current fashionable areas? Behavioral finance?

Well, that's had its time, but everything is behavioral after all. All of economics is behavioral. So I would say that what is called behavioral finance or behavioral economics is really irrational finance, irrational accounts. What's the irrational behavior of people? What's the effect of that on prices? Not just of stocks, but of everything. That's what that stuff is about. Now, the problem is that behavioral finance, behavioral economics doesn't have any models. They're wrong.

It's just a criticism of other models. So I've always chided Dick Thaler and told him, hey, it's easy to criticize my models if that's what you guys do. Give me a model of yours that I can criticize. Never done it so i don't i don't i really get under his skin when i say there's no real behavioral economics is just a branch of efficient markets you don't have a model of your own you just have a criticism for efficient markets so they're really just my cousin i heard a debate between you and thaler where you said that you were the most important person in behavioral finance that's what i said that's another one

of my lines without efficient markets i'd have nothing to criticize yeah yeah do you think um do you think eventually the anomalies will kind of coalesce into a theory that is the hope but doesn't happen so far are there any good efforts that you've noticed well stuff maybe by andre schleifer or no um andre is trying to develop behavioral models so he's trying he's trying to give content to the what i would call plus content to the behavioral aspect but But I haven't seen anything from that school yet. In your opinion, what's the current best asset pricing model? Is it the five-factor model? I don't know.

I wouldn't claim that. I mean, that does well on the things it was designed to explain, both nationally and internationally. But there are contradictions of it. So it's like every other model. There are things that it can't explain. So I would say it explains the things it was designed to explain, and they're really important. A lot of money is managed based on those things.

But is it the best model? I hope not. I would like to see – I don't want more factors. I want less. I want simpler models that work, not more complicated models. So I'm still hoping that it'll last. I will last to the point where something good comes along that says, I don't need five.

Here are two that will do the trick. Yeah. More parsimonious. Yeah, right. Exactly. Because the models with more factors feel like you're just kind of like overfitting to the data. Right.

You're just data judging, right? Data judging, yeah. Have you developed any theories behind any of the factors that you added to the cap amp? So the three-factor model basically added a size factor, small stocks versus big stocks, and a value growth factor. Value versus growth being the second factor. And there was a little bit of intuition in those in a sense that everybody would think that small stocks are more risky than big stocks. Everybody would kind of agree that value stocks tend to be poorly performing companies.

Maybe the market requires higher expected returns for those. But multi-factor asset pricing requires something in people's tastes that make them have negative attitudes that will persist. So if you tell me that after this discovery of these things, value factor, small stock factor, people pile into them because they're really nearly right. They're really not concerned that the stocks are small or that they're poorly performing companies.

They only care about the expected return. Well, then I get a problem because I think that will erase it. I think that'll nullify the model on its own. The problem is you won't know if that happened or not. So those models have not done as well in the last 15 to 20 years of data. Yeah. But that's a drop in the bucket as far as model testing goes. That's the reality of it. You basically need a lifetime of data to test an asset pricing model.

A whole lifetime is like the minimum. Right. Yeah. So obviously these pricing models are about relating risk and return, as you've said. How do you think about black swan events in the context of pricing models? Well, I wrote my thesis on those. So it is the case that it is the case that outliers are much more frequent than would be expected if returns were normally distributed. They aren't. They're far from normally distributed.

They have fat tails in both directions. Now, I wrote, I did a, one of my first papers was a version of the capital asset pricing model that took account of these outliers. But the problem was, if the distributions are symmetric, the cap-m works. And that was my basic point. You really didn't have to do much to accommodate these fat tails. So there's no specific model that addresses that. Yeah.

Are there specific tools or approaches that help deal with the existence of black swan events? Yeah. Don't invest in stocks. That's what it comes down to right yeah if you you don't like the fact that um there's been several days in history when prices have gone down by more than 15 you can't live with that it shouldn't be there let's talk about housing so there's good empirical evidence that housing markets are relatively less efficient than

stock markets. What do you mean by that though? So, for example, I think there's a paper by Case and Schiller where they find enormous inertia in momentum in house prices. So, I guess firstly, do you agree with that claim that housing markets are relatively less efficient? It's very difficult to tell because the data are not that good. I don't think you can really test.

I'd love to do it. I don't think you can really test efficiency in the housing market. So they constructed these industries, which they're very good. They're the best housing industries available. But they basically are moving averages. So you're not going to test market efficiency with moving averages. I see.

You're building legs into the data. I see. So I think that's a really difficult question. Okay. So it's hard to test. But I mean- It's hard to test in that market. The housing market is very difficult to do those kinds of tests.

Yeah. But aren't there good reasons to think a priori that housing markets would be less efficient? So, for example, very high transactions costs. They're less liquid. You can't short sell houses. You kind of have. So they're simultaneously investment and consumption goods. So you have a lot of amateur houses. You kind of have – so they're simultaneously investment and consumption goods.

So you have a lot of amateur investors. You have homeowners. I don't know. Some of those things are common to lots of markets, you know, and they don't seem to destroy market efficiency. I don't know why they wouldn't in this one. Common stocks are very expensive to short. So I'm not sure that it could make it more difficult.

I'm not sure they should destroy efficiency in that market. So the issue is, doesn't everybody that buys a house want to get the best possible price? As well, the buyer and the seller both get the best possible price, as well as the buyer and the seller. Both want the best possible price. So they have all kinds of incentives to investigate whether they're getting a good price or the right price. If that doesn't work, I don't know. I don't know how to test it unless you give me really good data on all the transactions that take place.

And even then, you get a quality problem so every house is different so it's not like they're all comparable then you can you have a price series on general motors or whatever you don't then that was that's the beauty of the case chile thing is it is we repeat sales of the same house But they still have the quality problem because they're looking across houses and constructing indices. Right, and people can modify their homes over time. Sure, right. Yeah. Right.

Yeah. It's a difficult issue, but I wouldn't say a priori that there are problems, something about that market that makes it less efficient automatically because other markets have problems too. But I guess it's a difference of degree. Maybe. Maybe.

But I don't think we have the data that allows us to tell how bad it really is if it is bad. Should we have futures markets for house prices? I think Bob Shiller tried to do that. And I think, I don't forget forget it was Merck or whatever, one of the Chicago exchanges tried to develop an index that people would trade on and there wasn't enough interest in it so they gave it up. Yeah, I mean that was my next question why haven't such markets taken off in the us well that's a good question um the the stock answer would be

there just isn't enough volatility so futures markets exist on volatility and there's just not enough volatility in house prices to keep them going, I guess. And should we be encouraging those markets? We should be encouraging markets. Shilla, who doesn't really believe in market efficiency, but who has done really good work, thinks you still want to develop markets and they'll make things better. So I would say the same thing really i mean you you do want to develop futures markets in these things if people want to trade in them but if they don't nobody's going to have an incentive to keep them going yeah so you mentioned that you're doing some work on housing

at the moment can you share a little bit about that okay well we're trying to not test efficiency because I think that's impossible. But one of the papers is trying to extract the information from house prices about expected future rents. And that's very difficult because what you find is what you also find in stock prices. That is, house prices vary much more than rents. So when we think that in terms of stocks, what we think is that the discount rate for expected future earnings and dividends is varying through time, and that's creating variation in addition

to the variation associated with dividends and earnings. Well, you get the same problem with houses. There's a discount rate for expected rents. That seems to vary a lot through time. Seems to be worse on, it's highly correlated across areas, West Coast, East Coast, Central areas.

It's much more extreme in the coast than it is in the central areas. Really interesting. Why do you think that is? I don't know. Any hunches? Yeah. Well, I,

a big ingredient in volatility is how restricted is the housing market? You know, so it's land very expensive because, you know, the rules about building houses are very restrictive, like right here. They're very restrictive. So the value of very restrictive, like right here. They're very restrictive. So the value of land here, it's incredible.

So there are those kinds of things. Maybe they are more extreme in the coast than they are in the central areas. But there are people who work on that, and I think that's one of the conclusions I come to. So we're looking at things that are very high level, not high level, but aggregate fuel. So we were looking at basically 11 metro areas and looking at prices and rents in those areas

and seeing if we can extract information and prices about expected rents. And I think we've done it. I think Synthetica have done it. Okay, so you famously cancelled your subscription to The Economist because they were throwing the B word, am I allowed to say it? Yeah, yeah. Bubble around too lightly.

Right. Can you explain your problem with the concept of bubbles? The concept of bubble, the way they're using the word, is something you identify with hindsight. That's something you identify going forward. So I think that in the actual empirical literature, there's no evidence of bubbles because there are huge price swings, but they're basically unpredictable.

If they're not predictable, that kind of violates the definition of a bubble. Yeah. And that was my problem with their sloppy use of the term. So when you're talking about huge price swings, I mean it's kind of reminiscent of a weak form efficient markets test, but what about a semi-strong form kind of test? No, that's fine. If you can find things that you can use to predict prices, good luck to you.

I mean, fine. That's a higher level test than just looking at statistical behavior of prices. That's fine. I mean, that was a popular area. I, along with some of my students, wrote the first paper testing it. And, you know, after that, hundreds of papers were written looking at different events and seeing how well prices adjusted to those events. Usually it was very good. So those events studies were among the best evidence on how efficient the market is.

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matched. Again, that's givewell.org to donate or find out more. Excluding you and David Booth, does Dimensional use any behavioral finance insights in its strategies? Not that I know of. You've expunged them. No. I mean, basically, they're an efficient markets shop. So they're creating products based on basically the three-factor model and the five-factor model, mostly the three-factor model. So they're assuming that that is a model for expected returns, and they'll give people mechanisms, products, to allow them to put their money

in the ones that seem to have higher expected returns and the ones that seem to have lower expected returns if you want to do that. With your experience with Dimensional, how easy did you find it translating academic theory into practice? Well, they were my former students, so David's one of the best students I've ever had. He has no problem grasping these things.

And the people on the line there, initially they had one Caltech guy who learned finance in about 12 minutes, and then they got another Caltech guy who learned finance in about 10 minutes so the stuff we were saying was not a problem for them to to grasp when they implemented it without a problem so it wasn't they were never in the stock picking game they were pure scientists yeah so i'm just curious generally how how easy or difficult it is to

yeah translate academic research into into practice oh well it used to be incredibly difficult why is that well go back to 1963 when i wrote my thesis i mean there was nobody doing passive investing at that point. And it took a long time before it cut on. And it took a long time before there was a substantial fraction of total investing done passively. And it's only recently, I think, that it's gotten around 50% in the stock market. And we're talking 70 years here, 65. So it takes a long time for this stuff to penetrate.

And there are always people who don't believe it, which is fine. Is there a way in which efficient market hypotheses and behavioral finance people converge on the same prescription for how average people should manage their money so absolutely so like efficient market purists would say that the market is efficient um so just you know invest in an index fund behavioral finance people would say people are irrational and dumb and it's nihilistic so just invest in an index fund so they come to the same same conclusion different reasons yeah but i guess those reasons could mutually coexist they could right yeah but how many how many people do you know that will volunteer that they're dumb

but according to the behaviorists everybody's dumb it's not just the the people you think are dumb but experts are also dumb. So they make consistent mistakes that should be easily avoidable. You know, doctors. It's not just finance people. So that's their problem, not mine. Yeah. Yeah, all of the experts are dumb except for the behavioral finance people

well that's a good point actually so why aren't they among the dumb maybe they are the dumb and the other people are the smarts have you heard of this idea of bias bias no good gigarenza has a has a paper i think with that in the title but it's about the i, the tendency to see bias everywhere. Do two negatives make a positive? Well, it's more about the tendency to see bias in places where it doesn't exist or be explained by something else. But I guess you can apply that to the behavioral finance people.

I'm curious about the link between libertarianism and the efficient markets hypothesis so i think you would correct me if i'm wrong but you would now you would describe yourself as a hardcore libertarian were you were you a hardcore libertarian before you started getting interested in the efficient markets hypothesis or was it the other way around uh i guess so in college i guess i would say that the professors were they weren't libertarians that's for sure sure, but they were more liberals than libertarians back in the 50s. So I would have been influenced by them. And then when I went to the University of Chicago, took Friedman's course, and listened to the goings-on of various workshops,

and started thinking about stuff, I became a libertarian. That was before I wrote my thesis. I think I turned my political code before actually dealing with efficient markets. Milton never believed markets were efficient. He didn't. He thought he could beat the market. He never started any evidence to that effect. Milton Friedman? Yeah. Yeah. Did he beat the market? No, I don't think so but he thought he could yeah did he accept the logic of the efficient markets like Bob this is or what wide accepted the logic but you just thought he was in that fraction yeah right everybody does

actually maybe that's a bias over confidence. Well, it is a bias. Yeah. I'd like to see his portfolio. I mean, you're free to reject that premise that I guess it was implied in my question that there's perhaps some kind of connection between a libertarian worldview and belief in the efficient markets hypothesis.

I don't necessarily like that word belief, but do you understand my point? Yeah, I do understand it. I'm thinking. So I don't know Thaler's politics, but it used to be easy. People's politics and their economics used to be easy to figure out. It isn't anymore. So Chicago is a free market school still. But one of my colleagues was Barack Obama's chief economics person

and is now going to the Fed. Who is that? Austin Goolsbee. Yeah. So my guess is Austin's a libertarian when you come down to it. He's not. He's a Democrat. But his ideas about economics are quite libertarian.

I don't think he likes a lot of government interference. I don't know anybody that does. Among economists, that's pretty general they're suspicious of what the government is likely to do given a free free hand that's so the way i classify libertarians is we don't trust republicans are democrats and we don't favor one over the other we think they both are self-seeking yeah i'm interested in talking about some applications of the efficient markets hypothesis generally yeah have there been any situations outside of your direct field of research where you've you've noticed that it was analogous to the efficient markets hypothesis

is it generalizable in any interesting ways? Well, basically, the presumption in all of economics until recently was that behavior is rational. The price is, in all contexts, not just financial markets, rational. So in that sense, the idea of efficient markets is ancient. It was the basis for all of economics. Now it's being questioned all over the place now, not just in France, but all kinds of markets. So it remains to be seen, I guess, how true it is in individual markets outside of markets outside of how many profit opportunities are out there that people have not yet exploited.

But that's the issue. It's the same across all areas, basically. And some of them, you know, you got to make a bigger bet and a more concentrated bet than you do buying a diversified portfolio in the market. But it's basically the same problem. Let me give another concrete example. So I guess like moving to labor markets, I look at the US labor market in particular and view it as quite inefficient, like inefficient in obviously a broader sense.

There's a lot of credentialism, employers obsess over pedigree rather than skills or more than skills. There are a lot of jobs that require four-year degrees for just inexplicable reasons. Why has someone not arbitraged that away? Like, could you use efficient markets thinking to explain why the- You could use empirical work for sure. Okay. To see if the presumptions that you just stated are actually true.

Yeah. Now, if I went and looked, would I find that people with four-year degrees are actually in the end more productive than people that don't have them in the same jobs? So I think there's a presumption that there are a lot of jobs where that isn't true but what's the evidence now that's always the bottom line question what's the evidence um so i don't think these questions have extant answers to them they require tests a couple of questions to finish on so as as I mentioned, I was interviewing Danny Kahneman in New York.

I'm curious what you make of, obviously, his research with Amos was the research that kind of kicked off the behavioral economics program, including, in many ways, behavioral finance. What do you make of their research generally, Dunny and Amos? It's, I don't know, it's, so it's had an impact, obviously, in the sense that people have become much more aware that there are pretty systematic biases that people have that you can avoid with simple cures. And Dick Thaler's a genius at that.

Coming up with how do you arrange the choices in your retirement plan to make people do things that they think they should do, but they don't get around to doing? So how do you set up the decision problem to make them do the things they want to do? But what an economist would say is it seems to them too costly to do it. He wants to lower those costs. So take the book, Thinking Fast and Thinking Slow. Okay? I think that's kind of his favorite. He's a big seller.

So I threw this one at Thaler, and he didn't have an answer to it. I said, Dick, that's not a scientific theory. What can't I explain with Thinking Fast and Thinking Slow? It's a tautology. So he thought about it, and I think he agreed. That was not, and that's an incredibly popular book that people think is full of insights, but the basic presumption is a tautology. Being dual process theory. Yeah, right.

If you tell me, okay, I'm going to explain what you did because you were thinking too fast. I'm going to explain what you did because you were thinking too slow. What don't want to explain what you did because you were thinking too slow. What can't I explain there? No? But shouldn't we think of that as the, I guess, like the kind of underlying conceptual framework? It's like evolution.

Like evolution by natural selection is a tautology as well. In a way, isn't the efficient markets hypothesis a tautology? No, because I can contradict it. I can get evidence that contradicts it. Evolution too, I mean, that could have gone a different way, right? You couldn't perfectly predict what's going to evolve from selection. But the concept of you've got variation and then the things that get selected for are the things that survive and reproduce the best. Yeah, there are probably exceptions to that too.

Okay so final question. I think the behavioral stuff and systematizing the mistakes that people make in different circumstances and how you can explain them, I mean, that doesn't have anything to do with Kahneman's book. I think that's very useful. I mean, there's just no way around it. What I object to among the behaviorists is that they go into a problem looking at those things, and they're not willing to go the other way. That, to me me is not scientific. So I would go in and say, you've got a problem. It could be because markets work or it could be because you've discovered

something that's inconsistent with rational behavior in markets, but you don't go in with a presumption about the answer to that. And I think most of them do. I don't go in with a presumption about the answer to that. And I think most of them do. I don't go in with a presumption, or at least I try not to. And I'm willing to be contradicted by evidence that tells me, like Cliff's momentum, for example. That's a big embarrassment to market efficiency, but it's there. So I'm not going to argue with it.

I mean, statistically, it's there so i'm not gonna argue with it i mean statistically it's it's not saleable uh and i think that's the way everybody should approach these approach these issues you shouldn't go in with uh a particular looking for something of a particular slant and then move on to something else if you don't find it. It's just data dredging. Right. How much does momentum undermine the efficient markets hypothesis? How much less of an efficient market hypothesis did you become after Cliff's discovery?

I mean, I think that's something that's so short-term that it doesn't seem like anybody can make any money off of it. So it's basically a curiosity item. But it is a violation of market efficiency, so no way around that. But if it's just in the realm of a curiosity item, I don't think it affects anything in the end. So there's also evidence of reversals. They're not reversals. It's just negative autocorrelation in the long term. But you expect that if expected returns are varying through time.

So that's not so embarrassing. There are explanations for that. But short-term momentum is kind of a of a killer at least logically mm-hmm final question apart from the apart from the housing stuff what are you working on at the moment and what what it what excites you or is it just mainly the housing stuff? At the moment, I'm chuckling because that's kind of the way I am. So you usually start with a small thing, write a paper on it, and then that suggests some extension that you want to do. And eventually, you do something that's, when you put it all together, all the papers that you write to do. Eventually, you do something that's... When you put it all

together, all the papers that you write in the same thing, it looks like something much bigger. That's the way I've always worked. I'm not the person that can jump ahead with my mind and say, here's where I want to be in 10 years.

I can't do that. I make little steps and try to build on them. So I don't know where this real estate stuff is going to go. And I'm hoping that I can find, I'm doing this with Ken French. So I'm hoping we can find data that will allow us to investigate more questions. But it remains to be seen. Yeah.

I mean, I guess that's the nature of your very empirical approach right kind of just follow things where they lead right well um it's been great chatting with you gene thank you so much for having me here today and it's been an honor my pleasure thanks for listening if you'd like to read a full transcript of this conversation you can find that on my website, jnwpod.com. Also, a reminder that in early 2025, I'll be hosting six live podcasts in Australia. If you'd like to get tickets to attend those events, you can also do that on my website, jnwpod.com. That's jnwpod.com.

Thanks. Until next time. Ciao.