Tuesday, December 17, 2013

Three Nobel Lectures, and the Rhetoric of Finance



It was my great pleasure -- and honor -- to attend this year's Nobel prize ceremonies. It started with the Nobel prize lectures, which I found very thought provoking.

Shiller 

I'll work backwards, as it was thinking about Bob Shiller's talk that taught me the biggest lesson. Preview: this will start pretty negative, but I learn a big lesson by the end. Hang in there, Shiller fans.

I thought I thought we had reached a consensus on volatility tests. Shiller (and others) brought us volatility tests, while Fama (and others), starting in 1975, showed that all sorts of returns are forecastable at long horizon. After sturm und drang, we -- including Campbell and Shiller, but also a wider literature (I wrote a few papers) -- realized that volatility tests are exactly, mathematically equivalent to return forecasting regressions. Expected returns (true measure) vary over time, a lot, and fully account for volatility tests.

The remaining question is whether time-varying expected returns are connected to macroeconomic quantities through marginal rates of transformation and substitution, or whether people misperceive probabilities and don't know about time-varying expected returns.

There is a joint hypothesis theorem -- probability and marginal utility always enter together in asset pricing formulas -- so no amount of staring at prices will ever solve this interpretation question. We need models.  Economic models (such as habit persistence) give a somewhat successful answer, but are also rejected. The great challenge for behavioral finance is to produce similar, scientific - looking models that tie irrational expectations to other data in a rejectable way, and thus rise above ex-post story telling.

Volatility tests were a deeply important, Nobel-worthy part of this story. They showed the economic importance of time-varying expected returns -- and the as yet incomplete effort to understand those returns -- in a way that t stats and R2 values did not.

Well, that's what I thought the consensus was. What I found remarkable is just how much of that consensus Bob completely abjured.

At 1:12 Bob starts right in:
What is a bubble? You [Gene Fama] said nobody defines it. So I will define it. A speculative bubble is a fad. People get excited sometimes. Too excited... Prices start going up, they start talking, the newspapers start writing about it, more and more people pile in to a market and they push prices up more and it goes on for a while. eventually it breaks and the bubble bursts.
That's not a "definition." That's an explanation, a theory. A definition tells you in an operational way what pattern in the data describes "bubble." An explanation is a theory that predicts the defined phenomenon.

That doesn't answer Gene at all. Gene asked Bob how to measure a price above "fundamentals." how to measure that a "fad" is underway? For example, in a previous podcast, Gene had offered to believe in bubbles if Bob could show a method that reliably forecast a negative market expected return.

Bob pointedly did not take even that olive branch, that chance to agree on a common language.  If we can't get straight what a definition is vs. an explanation, maybe the physicists are right that they shouldn't give out economics Nobels. We'll surely be at this another 35 years.

Next, Bob put up an update of the famous volatility graph, where he contrasts actual prices with ex-post dividends discounted at a constant rate. (1:15:45)



He called the dividend line "the actual market if everyone knew the future" and the "true value."

(A minor thought. Really? Would the world really be working right if that's what stock prices had all the return and no risk? If we have an equity premium puzzle now, imagine what it would look like with no risk! If prices have no risk so we should discount dividends with riskfree rates, the major failure of today's markets is not the volatility of the price-dividend ratio, it's the level, which should be many times higher?)

Admitting briefly that efficient markets allow some return forecastability, he showed us some graphs discounting dividends with interest rates and consumption growth raised to a power.

On this evidence,  he concluded that we are  "seeing repeated fads and fashions" though they are "integrated with the economy" in a  way that is "difficult to understand." Nonetheless, we can conclude that "The market is too volatile, people are a little crazy, there is a social psychological component."

How do we we get from the failure of one model (constant expected returns, or power utility) to the failure of any possible model, to "people are a little crazy?"

More deeply, in the face of the joint hypothesis theorem, how do you get to claim victory for any view without a model at all?

More deeply, we've all been over and over this.  The subsequent literature answered all this years ago. How could Bob not know that or even mention it?

At 1:23, he described the Campbell-Ammer variance decomposition, concluding "only about a half or a third of the fluctuations in the stock market could be explained by evidence about future dividends," and concluding, "so most of the market doesn’t make sense"



This was really revealing. Bob's Campbell-Ammer slide says "excess [expected] return variation two to three times that of [expected] dividend innovation" His words were "most of the market doesn’t make sense!"

Add this up and it's all eye-popping. Bob is basically denying the 20 year old theorem that volatility tests are equivalent to time-varying expected returns. I listened to the lecture and carefully to the video. You won't find an admission of that theorem, or that mechanically time varying expected returns account for these plots. That's especially astonishing given that the Nobel committee cited him for discovering long-run return forecastability, ignoring Fama's role! For example the Nobel poster said
"Beginning in the 1960s Eugne Fama demonstrated that stock prices are extremely difficult to predict in the short run. .. If Fama's results are right, then shouldn't it be even harder to make predictions over several years? The answer is no, as Robert Shiller discovered in the early 1980s."
Bob is denying the joint-hypothesis theorem that probability and marginal utility always enter together, so we need a model of either to say anything. And Bob is denying the essence of what it means to supply a definition.    

Bob closed with an overview of psychology and sociology concepts that inspire his views,

He urged economists to incorporate more ideas from psychology, sociology and other fields, "I think that in understanding speculative bubbles we have to be eclectic. .. population biology… epidemiology, neuro economics.. To understand complex phenomenal we need to take account of every kind of expertise."

OK,  "listen to psychologists" is good advice. Economics has benefitted from intellectual arbitrage many times in the past. But Nobel prizes are supposed to be given for past successes (typically, long-past!) not "maybe you can do something with this in the future."

In an entire lecture, Bob did not give a single concrete example of how "listening to psychologists" produces one concrete positive step to understanding "bubbles."

(There was a lot more in Bob's speech, including description of his innovative work with Case in  constructing a real estate price index. Curiously, he showed how today's forward prices are forecasting another "bubble" -- this market price correctly forecasts "fundamentals," unlike all the others? And he closed,  advocating more markets, such as GDP futures, admitting they will have bubbles and fads too, but that they are useful anyway. "What I’ve done is present imperfect evidence…with the conclusion that’s maybe radically different about bubbles, but not about the general importance of our financial markets.")

Deep Breath. Another view

It slowly dawned on me though, that this is much too harsh an evaluation and an unsatisfactory theory. Bob is a smart and thoughtful guy.  The theory that he doesn't know the difference between a definition and an explanation, hasn't read Fama's 1970 definition of "efficiency" or "joint hypothesis," doesn't understand that volatility is exactly the same as return forecastability, and so on, just doesn't make sense. I remembered my Kuhn (Structure of Scientific Revolutions) and McCloskey (Rhetoric of Economics). (If you're an economist and haven't read these, do so now.)

I realized just how deep and audacious  Bob's project is. He is telling us to abandon the "scientific" pretense. He wants us to adopt a literary style, where we look at the world, are inspired by psychology, and write interpretive prose as he has done.  When he says that the definition of a a bubble is a fad, he isn't being sneaky and avoiding the argument. He means exactly what he says and wants us to think and write this way too. A bubble, to Bob, is defined as any time a time that he, writing about it, informed by psychology, and reading newspapers, thinks a "fad" is going on. And he invites us to think and write like that too. A model is, to Bob, wrapped up in one person's judgement and not an objective machine. If I complain that this is ex-post story telling, he might say sure, stop pretending to be physics, write ex-post stories. If I complain that there are no rules and that this is no better than "the gods are angry," he might say, no, read psychology not ancient theology, and the rules are you have to couch your story telling in their terms. He does not want us to try to construct models, either psychological or rational, that make quantitative predictions.

He wants to fundamentally remake how we do finance, how we talk about finance, how we write about finance. He wants to define a new rhetoric of finance. When he says we should read psychology and social psychology -- and, implicitly, not physics or economics -- he means exactly what he says. He (obviously) isn't going to fall in the trap of writing rejectable models, making predictions and so forth. That's like speaking Greek, and at his party, we speak Latin.

I am by nature a listener, an integrator. I wrote a paper on how volatility tests are the same as Fama French regressions. Bob has no interest at all in listening or integrating. He wants to redefine how we do things in his own style, as pure and simple as possible.

This is what scientific revolutions are all about. This is what Nobel Prizes are all about.  They give them to people who strike out, write a novel language and methodology for conducting research, and convince others to follow and do it their way and talk their language. All previous revolutions -- successful or not -- have had these interminable debates where we can't even seem to agree on the meaning of simple words ("efficiency," "definition", "model") and talk past each other. The salient facts and classic tests are only written ex post by the winners. Bob wants a revolution of that sort, and listening to economists is the last way to accomplish it.

Now that is an audacious project! And Bob has collected a lot of people who talk and write his way.  Not me, so far -- only one in ten attempted scientific revolutions catch on, and I'm placing my bets elsewhere. I still like to talk like a physicist. But I think I understand the audacity of the project, and why it is we seem to talk to cross purposes and not even agree on basic questions like what constitutes a definition, what's a theorem, and whether the absence of quantitative rejectable behavioral models that tie expected returns to other data matters or not. And why trying to debate -- to ask for a definition of bubble, for a quantifiable measure of "fundamentals", to ask for a quantiative model of distorted expectations -- will get nowhere.

Hansen

With that thought in mind, I came to a similar different view of Lars Hansen's talk. Lars isn't in the middle of Gene and Bob;  Lars is way off on the other end of Bob.

Lars chose to talk more about his current research and less about the research that got him the prize, a good technique for these lectures. He's working on "ambiguity," how to handle the fact that we don't really know what the right model is, and, even more interestingly, how to construct models in which the people in the models don't really know what the right model is. Typically for Lars, this is a very deep research program, which may lead to a fundamental difference in how we think about risk and information in economics.

At one point he described which he described models with  "twisted expectations."  Here's the slide


In the first equation S with a tilde on it represents marginal utility, consumption to the gamma power in the usual formulation, X represents an asset payoff, and Q is then the price. This is the standard present value formula -- except Lars wants to think about E as a "distorted" expectation. Following the usual theorems, in the bottom equation we can represent the same idea with the real expectation and an extra M term multiplying the stochastic discount factor. (Yes, everyone else uses M for Lars' S, and P for his Q.) This is essentially the risk neutral valuation trick, that we can introduce a new "discount factor" M to represent the probability "twist."

Seeing this, I would have been tempted to position it between Gene and Bob. Gene thinks of "efficiency" with true or rational expectations E. Bob thinks of inefficiency as "fads" meaning irrationally optimistic and pessimistic expectations. But Bob doesn't show us how to link those irrational expectations to data. So I would have said this M, which Lars' models do link to data, is a structured way to incorporate the non-rational distorted expectations that Bob thinks he sees into models, but in a disciplined, rejectable way.

Lars didn't do that. In fact, when I suggested he position the talk as halfway between the "rational" and "behavioral" debate in this way, he said something deep, to the effect of he wished the whole rational-behavioral debate would just go away. Since it hasn't gotten far in 35 years, he has a point.

But with Shiller behind me, I now understand Lars' goal better. Lars, just like Bob, is setting forth a pure rhetoric, a pure language, a pure methodology for how we should think about finance and do finance. As Bob wants it to look like social psychology or maybe literary criticism, Lars wants it to look like physics. We write down the model, formally, and carefully. We test the model. We do not spend any time on loosely written ideas, either "rational" or "behavioral." We don't spend time on "alternative explanations" as is common in empirical finance.  We don't pretend that empirical work can say anything useful about whole classes of models, like "economic" or "rational" or "psychological." In Lars' world, the whole rational-irrational debate is a waste of time. Show us your models, or be quiet. A test can tell you something about this model, period. At best a summary statistic like the Hansen-Jagannathan bound can tell you "this is what discount factors produced by any model must behave," but that's it.

This too is how Nobel Prizes are won. And looked at empirically -- how many followers he has collected who write in his style -- this is a successful language too.

Fama

Which brings me at last to Gene Fama, who came first. Gene gave a straightforward talk on efficient markets, long run forecastability  and empirical finance. The one slight zinger was putting down some equations and citations to remind the world that indeed he started documenting long-run return forecasts in 1975. He apparently had some behavioral finance zingers in reserve, but didn't get time to give them. The written version will be interesting.

Looked at in this rhetorical light, Gene can afford to be gracious. Gene also invented a language, a methodology, for empirical fiance. And his language and methodology did not just attract a small band of followers, but took over the finance profession, so thoroughly and completely that it's easy to forget his influence. When Gene runs Fama MacBeth regressions, we run Fama MacBeth regressions -- even if GLS might be more efficient, even if time series variation might be informative. When Gene sorts stocks into 10 portfolios, we sort stocks into 10 portfolios -- even if 20 or smooth kernels might make sense. When Gene uses monthly returns, we use monthly returns. Gene writes beautiful paragraphs of prose to describe his theories, (no criticism, it's just comparative advantage) so do we. When Gene defines terms like "efficiency" and "joint hypothesis" the rest of us use those definitions.  When Gene points out differences between empirical finance and empirical economics, perhaps there you can see just how strong the Fama language effect has been.





43 comments:

  1. I think Shiller's point might be that the fads is often WHY the expected returns are time varying.
    for example, http://www.federalreserve.gov/pubs/feds/2008/200817/200817abs.html

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  2. There was a perfectly good definition of a bubble in the Aug. 1980 JPE.

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  3. The beauty contest example seems much like a game scenario, where one’s payoff depends on other’s action. Instead of irrational exuberance, could game theory be used to explain “bubbles”?

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    1. https://www.princeton.edu/~smorris/Published/paper_49_Beauty_Contests.pdf

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  4. Thank you for a very detailed post! I've been thinking about the Fama / Shiller debate, and I've reached the conclusion that they are both right. The part that Shiller is missing is that asset valuations reflect not only expectations for future returns but also current preferences for allocation into money in relation to other assets. Since money is denominated in itself, such preferences affect the prices of other assets. At the peak of a bubble, as defined by Shiller, asset prices simply reflect the relative preference for cash at the the time. In this post (http://tinyurl.com/md5pf22), I have a more detailed explanation of why both Fama and Shiller are correct, and also I refer to historical evidence that changes in money demand largely explain stock price movement over the last 25 years.

    I am very interested in your thoughts on how I derive changes in the demand for money as explained here ( http://tinyurl.com/q8pmmb2). There is a very strong negative correlation between that measure and the S&P 500 Index starting in the late 1980's. Interestingly, there seems to be a strong positive correlation in the prior decades. I suppose people began to perceive money as an asset only after Paul Volker defeated inflation.

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  5. Here's a definition of bubble: When informatoin assymitries and limits to arbitrage interact, leading to an statistically-expected mispricing.

    With this definition, people with an information advantage (think insider information) can expect the market price to be wrong. Limits to arbitrage (like it's illegal to trade on isider information) will prevent the price from gravitating toward equilibrium.

    The magnitude of the mispricing and popularity should really play a role here. We could test this idea by somehow polling those with insider information, and seeing if on average, they are able to spot mispricings. Bubbles with no insider trading are harder/impossible to spot because of the expert problem.

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    1. Bubbles are funny. They can inhabit Fama's and Hansen's Euler equatiins with ease. At issue is the market;s perception of the appropriate terminal condition. For bonds the terminal is clear - for stocks less so. Sometimes I think the efficient markets statement is completely empty. Sometimes I think it is a combination of the Euler and the terminal condition. I can follow what Hansen says, but Shiller baffles me and really so does Fama.

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  6. I was a fan of Bob's behavioural theory UNTIL I read his research seriously, did a lot of empirical tests and realized it's nothing more than a story telling.

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  7. Doesn't Shiller use the cyclically adjusted price to earnings ratio as his bubble metric?

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    1. Exactly the same statistic that Fama uses as his time-varying risk premium metric. The point of my "I thought we had a consensus" was that both sides need to bring forth models to avoid that empty naming exercise, and others on both sides have done so. Bob is obviously not going to play that game.

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    2. Shiller may not be playing the game at the Nobel lecture, but he sure seems to advocate a portfolio shift towards bonds when the CAPE goes above 26x!

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  8. Thanks John for providing an informative and thought-provoking blog post. I wonder if this difference in paradigms that you described in the field of finance reflects more broadly the message that behavioral economists have been sending to neoclassical economists for the past 10 to 15 years?

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    1. This isn't about behavioral economics more generally. There is a lot of interesting research on microeconomics, marketing, and individual portfolio formation that this set of comments has nothing to do with. Actually, there is a lot of interesting behavioral finance that this set of comments has nothing to do with.

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  9. So , individual people overreact or underreact all the time, not just in their personal lives, but in public sphere - think Germans voting for Hitler for example. So, Fama claims that all the overreactions perfectly cancel out all the underreactions ALL the time and therefore, the market is efficient. This is truly an astonishing claim to make.

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    1. Fama claimed nothing of the sort.

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    2. So if overreactions do not always cancel out underreactions then at those moments in time markets are not priced according to all available information. Doesn't that follow ? This is what Fama said about crashes:

      http://www.dfaus.com/2009/05/an-interview-with-eugene-fama.html

      But if '87 was a mistake, doesn't that suggest that there are moments in time when markets are not efficiently priced?
      Well, no. Take the previous crash in 1929. That one wasn't big enough. So you have two crashes. One was too big [1987] and one was too small [1929]!

      But in an efficient market context, how are these crashes accounted for in terms of "correct pricing"? I mean, if the market was correctly priced on Friday, why did we need a crash on Monday?
      That's why I gave the example of two crashes. Half the time, the crashes should be too little, and half the time they should be too big.

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    3. Anonymous,

      Has it occurred to you that crashes may occur because some information has a bigger impact on asset prices than others? Whether or not crashes occur has little to do with efficiency. An efficient market IS NOT a market with perfect foresight.

      I think you are combining two widely held beliefs and reaching an illegitimate conclusion:

      1. Markets are forward looking
      2. Markets are informationally efficient

      Markets are forward looking only in the sense that returns on investment are realized after the investment is made. Markets are informationally efficient only in the sense that prices reflect all previously obtained information about the asset - and I would argue that because a lot of information is compressed - market pricing is not very efficient at all.

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    4. My thoughts on this: When people make asset decisions they do act rationally and consider all the available information in regards to their individual preferences and expectations for return, risk, liquidity and carrying costs. There is a tremendous amount of uncertainty associated with each of those expectations, and individual decisions are not immune to error. However, for each buyer there is a seller, which means that in total someone's errors will be offset by someone's gains.

      If we stopped the analysis here, markets indeed would be perfectly efficient and would not be subject to booms and busts. However, markets suffer from a particular flaw - imperfect information. Specifically, market participants have no way of projecting the impact an individual decision can have on the market in total, which will ultimately exert an influence back on them. Basically, there is a feedback loop between the decision to take a risk and the return associated with such risk. From information standpoint, this feedback loop is unknowable to individual market participants. Accordingly, risks in the economy and particular markets do not offset but rather tend to compound. When you take such market tendencies for risks to compound and add the pro-cyclical influence of money, you end up with markets subject to booms and busts.

      Booms and busts are not proof that markets are inefficient, but rather that there is unknowable information to market participants.

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    5. "However, for each buyer there is a seller, which means that in total someone's errors will be offset by someone's gains. "

      This sounds like a fallacy of composition.

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  10. The changes that Shiller is calling for are long overdue. Economics has been an odd social science in taking the trajectory it took. The key is to open it up to expertise and knowledge from outside. It has also got to ask questions about its micro-foundations and why it took the path it did. Assumptions that people are basically greedy (unlimited wants, limited resources, "shown" with budget lines and indifference curves originating from peculiar nineteenth century British Empire political economy) are controversial to people who have actually studied humans and humanity and societies literally on the field; and we need to ask why in such highly political interpretations about human behaviour have been taken as baseline and presented as "scientific.

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    1. Is Shiller not assuming "greedy" agents in the normal economic sense? My take is that he's not arguing about what people want, but how they go about it based on their expectations of the future. It's Fama who's making an argument that people's utility functions (risk premia) explains behavior that Shiller thinks is irrational.

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  11. John, this is the best post that you have had all year. It is refreshing to see a blogger take Shiller at the face value of his argument rather than assume ulterior motives. What I find hilarious is that practitioners are emotionally Shiller (harping on about "irrationality") but functionally Fama (heavily using betas, rapidly discarding prior's, and treating asset pricing cycles as the unwieldy beasts that they are). They ultimately understand that while Shiller provides no systematic way to make money, Fama provides a way not to lose it.

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    1. yes, of course. But practitioners, such as quant traders, also know that it is possible to identify situations in the market when it is not efficiently priced on some time scale. Shiller doesn't tell them how to run their regressions, but clearly they don't believe that Fama is right.

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    2. The same story is repeated again and again. There are always many practitioners who think that Fama is not right and yet still losing money without realizing they are doing less well than if they adopted a buy and hold strategy.

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  12. Your interpretation of Shiller's language makes me think George Soros's book "The Alchemy of Finance" is a much more conceptually well fleshed out version of a similar argument. He argues not only that finance should work this way, but there are basic reasons why all social sciences have to look this way.

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  13. I will define a bubble ( inefficiency ) for you: a bubble ( inefficiency ) is a state of the market in which the price of the asset in question cannot be justified with any reasonable probability by all available information regarding the cashflows necessary to replicate this asset. Successfull quant traders build models to do this all the time - but if the models work, they don't go around publicizing the results. This is the main problem with the "show me the models" argument.

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    1. "Successfull quant traders build models to do this all the time".

      Where are these models?

      "but if the models work, they don't go around publicizing the results"

      So, we will never know!

      Science requires evidence! Otherwise, these are only assumptions.

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    2. Are there strategies to exploit these inefficiencies, to the point of offsetting the costs of their implementation and beating a simple buy-and-hold strategy?

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    3. Of course there are. There is a number of successful quant trading firms and hedge funds out there that have been in existence for a very long time. Chicago, where John lives, is one of the major centers of high frequency trading, for example. Then there's Buffett and his famous lecture on a number of Graham's disciples, including himself.

      There is a convenient "hidden risk factor" explanation that efficient markets theorists resort to, which is fine, but the problem is, if it's truly hidden, then we don't know that it is there.

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    4. 1/ "Successful quant trading firms": to what extent? Where are the empirical studies that show that these funds consistently beat the market? HFT firms I know are far from beating the market. Take a look at the track record of Quantam Group for example (http://www.quantam.net/home.php?language=en).
      Anyway, prior to 2008, many people also told me that Madoff consistently beat the market.

      2/ Buffet is not a simple fund manager who seeks to predict the stock market prices. He is an entrepreneur. When people say Buffett has generated 23% annual returns over a 40 year period, what they are really saying is that Berkshire Hathaway’s (BRK) book value has grown at a 23% annual rate over that period of time, which is not even close to the same as saying Buffett’s stock-picking prowess returned 23% per year. Berkhshire Hathaway participates in the management of more than 70 different companies it owns. Opposing Buffet and EMH is quite irrelevant.

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    5. read this on buffett
      http://www.bloomberg.com/news/2013-12-02/you-can-invest-just-like-warren-buffett-if-you-re-a-quant-hedge-fund.html

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    6. Berkshire Hathaway has realized a Sharpe ratio of 0.76, higher than any other stock or mutual fund with a history of more than 30 years, and Berkshire has a significant alpha to traditional risk factors. However, we find that the alpha becomes insignificant when controlling for exposures to Betting-Against-Beta and Quality-Minus-Junk factors. Further, we estimate that Buffett’s leverage is about 1.6-to-1 on average. Buffett’s returns appear to be neither luck nor magic, but, rather, reward for the use of leverage combined with a focus on cheap, safe, quality stocks. Decomposing Berkshires’ portfolio into ownership in publicly traded stocks versus wholly-owned private companies, we find that the former performs the best, suggesting that Buffett’s returns are more due to stock selection than to his effect on management. These results have broad implications for market efficiency and the implementability of academic factors.

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    7. You give high frequency traders way too much credit in the context of this discussion of market efficiency. These HFT "quant firms" are simply collecting the bid/ask spread, the same way NYSE specialists and floor traders on every exchange did for decades. They have no need for any special information or foresight--it's simply computing power to make a faster and tighter market than other participants. Hence the need to maintain computers as physically close the the exchange servers as possible. There is no market efficiency magic--just nanoseconds.

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  14. As Binmore points out in his book (referring to a Greek philosopher), "it is easy to win a debate when you're debating yourself". Similarly, it is easy for Shiller to win a debate when he refuses to speak the language used by most of the economics/finance profession.

    Binmore also writes in another book that if you're going to trust someone's intuition, that person better be someone like von Neumann. Clearly, Bob Shiller is no von Neumann, so I'll take his claims of bubbles, fads, and tautologies with a grain of salt.

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  15. I don't think this is a fair way to try to win an argument. Indeed, I think you misrepresent what Shiller is saying. As you noted:

    "That doesn't answer Gene at all. Gene asked Bob how to measure a price above "fundamentals." how to measure that a "fad" is underway? For example, in a previous podcast, Gene had offered to believe in bubbles if Bob could show a method that reliably forecast a negative market expected return."

    You can see from what Shiller said -- as you quoted him -- that the dynamics of a fad or bubble depend on How people are behaving, and WHY they are making the decisions they are making... as he said, they get excited, too excited, etc. i.e. social influence begins to play a major role in undermining independent decision making and carrying people along to views and decisions they might not otherwise have or make. I certainly had friends during the housing bubble who bought properties because house prices "never fall." Why did they believe that? See Solomon Asch and the long literature of social psychology; it would be astonishing if such dynamics DID NOT play a big role in finance (for a recent example, see http://www.pnas.org/content/early/2011/05/10/1008636108).

    But the most important point, implicit in what Shiller said, is that a bubble is not necessarily evident JUST in the time series of prices. You have to look to the actors themselves, through surveys, recordings, sampling testosterone (see Coates' book, http://www.amazon.com/The-Hour-Between-Dog-Wolf/dp/1594203385), or whatever other means you might invent, to find out if social influence and other factors grounded in biology are playing a role. You can't just sit in your office and do maths. Finance is a part of social science and depends on the full spectrum of human behaviors. Shiller is not saying give up maths. He's saying use your quantitative methods to study more than the narrow movements of prices. Why not try to quantify how and why and when strong correlations can get created in the behavior of large groups of people? Indeed, part of the Case-Shiller Index does try to find out WHY people are buying properties. What fraction are buying because they see prices rising and want to make a speculative profit? How does this fraction change over time? This is how you might get evidence of a bubble, or a definition of one, if you like.

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  16. "Similarly, it is easy for Shiller to win a debate when he refuses to speak the language used by most of the economics/finance profession."

    The problem is, as a philosopher would say, the object is determined by the subject. That is the modeller determines the language which determines the outcome. To get a different outcome, you need a different framework. The only way we can progress in economics is to start again.

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  17. You sound as if Shiller doesn't present evidence. But what about this paper on housing where people were surveyed etc, about what they actually think being downright irrational?
    http://www.econ.upf.edu/~montalvo/burbuja/case_shiller_bpea.pdf

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  18. Per bringing in psychology, it's naive to think this is a novel approach. Way back in 1951 George Stigler noted "each decade, for the past nine or ten decades[!], economists have read widely in the then-current psychological literature. These explorers have published their findings, and others in the field have found them wanting—wanting in useful hypotheses about economic behavior." And so it goes.

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    1. Do you have the source for this lovely quote? I found your book online, but google books blocked the page with the citation.

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    2. It's in an essay in a collection. As a grad student I saw him at a cocktails after some speech, he was standing alone, and was going to say hi, but I figured he's too famous for me. He died like a month later. Always regret that, he was such a mensch.
      Stigler, George. 1951. Specialism: A dissenting opinion. in The Intellectual and the Market Place. 1984. Harvard University Press: Cambridge, Massachusetts.

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  19. "... No amount of staring at prices will ever solve this interpretation question. We need models."

    I love that.

    I wish we could dispense with so much of the statistics we do teach economics and business majors at the undergraduate (and even MA/MBA level), and rapidly jump to the most primitive ways to identify and estimate supply and demand. For so much of what we do, the models are essential ... but they're firewalled off from our principles/intermediate/theory classes.

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  20. I think it's obvious that in the short run asset prices don't reflect any expected return, but are just driven by supply and demand. All the wealthy tech guys here in the Bay Are buying Twitters etc don't even look at the fundamentals, market caps, whatever. They just buy the stock because it's sexy, it's $20 and Google is $1000, so someday X will be at least $200. It's amazing but I think most of the "ordinary" people just buy stocks based on the name, brand and nominal stock price, without paying any attention to the actual fundamentals. So Schiller is exactly right when saying that sometimes people are just bit crazy. And you cannot model that.

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  21. Iyou are combining two widely held beliefs and reaching an illegitimate conclusion:

    1. Markets are forward looking
    2. Markets are informationally efficient

    Markets are forward looking only in the sense that returns on investment are realized after the investment is made. Markets are informationally efficient only in the sense that prices reflect all previously obtained information about the asset - and I would argue that because a lot of information is compressed - market pricing is not very efficient at all.

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