It takes a certain amount of audacity to appeal to cognitive illusions in defense of a hypothesis that denies any role for human psychology in the determination of asset prices. But this is precisely what Scott Sumner has done:
Now let’s ask why people have this mistaken notion that bubbles are easy to spot, and that Fama is deluded. I believe it is a cognitive illusion. People think they see lots of bubbles. Future price changes seem to confirm their views. This reinforces their perception that they were right all along. Sometimes they were right, as when The Economist predicted the NASDAQ bubble, or the US housing bubble. But far more often people are wrong, but think they were right.
He then goes on to argue that anyone with the ability to identify bubbles should be able to make significant sums of money:
So let’s say The Economist magazine really knows the fundamental value of assets in the various countries it covers. It does cover a lot of countries, and probably knows more about those countries than almost any other magazine. Also suppose The Economist started a mutual fund that invested based on its ability to spot fundamental values and deviations from those values. That mutual fund should outperform other funds. And not just by a little bit, but massively outperform them.
There are really two separate questions here: can bubbles be reliably identified in real time, while they are in the process of inflating, and if so, does this present opportunities for making abnormally high risk-adjusted returns? It is possible to answer the first question in the affirmative but not the second, for the simple reason that the eventual size of the bubble and the timing of the crash are unpredictable. Selling short too soon can result in huge losses if one is unable to continue meeting margin calls as the bubble expands. Trying to ride the bubble for a while can be disastrous if one doesn't get out of the market soon enough. And avoiding the market altogether can also be risky, if one's returns as a fund manager are compared with those of one's peers.
Each of these risks may be illustrated with some vivid examples from the bubble in technology stocks that eventually burst in April 2000. Many of those who sold these assets short could not profit from the decline because they were forced to liquidate their positions too soon:
Pity the short-sellers. Practically driven to extinction by a bull market run, they should be reveling now that many of the stocks they long considered overvalued have fallen sharply. But many of them have been left out of this market move, too.
The meteoric rise of technology stocks over the last few years forced many short-sellers to abandon positions, shut their operations or liquidate their portfolios and go into cash. So when the technology sector and the market over all finally had a bracing retreat in April, some of the investment funds that have specialized in selling stocks short, or betting that stock prices will drop, were not positioned to profit...
Many highflying stocks, including PMC-Sierra, MicroStrategy and Echelon, soared in February and March only to plummet in April. As the stocks soared, short-sellers began unwinding their positions because of mounting losses. By the time the stock of MicroStrategy, a Virginia software company, fell precipitously on reports of accounting problems, the shorts had largely given up. Its short interest declined to 724,630 shares in mid-March from 3.8 million shares in mid-December. The stock peaked in March and then fell 94 percent to its April trough.
A particularly interesting case is that of the Quantum fund, which suffered significant losses from short positions in 1999:
Quantum, the flagship fund of the world's biggest hedge fund investment group, is suffering its worst ever year after a wrong call that the "internet bubble" was about to burst... Quantum bet heavily that shares in internet companies would fall. Instead, companies such as Amazon.com, the online retailer, and Yahoo, the website search group, rose to all-time highs in April. Although these shares have fallen recently, it was too late for Quantum, which was down by almost 20%, or $1.5bn (£937m), before making up some ground in the past month. Shawn Pattison, a group spokesman, said yesterday: "We called the bursting of the internet bubble too early."
This caused the fund managers to reverse course and buy technology stocks, resulting in a rebound in late 1999. But they held on to these positions too long:
Stanley Druckenmiller knew technology stocks were overvalued, but he didn't think the party was going to end so rapidly.
''We thought it was the eighth inning, and it was the ninth,'' he said, explaining how the $8.2 billion Quantum Fund, which he managed for Soros Fund Management, wound up down 22 percent this year before he announced yesterday that he was calling it quits after a phenomenal record at Soros over the last 12 years. ''I overplayed my hand.''
Given the risks involved in taking positions on either side of the market during a bubble, one might be tempted to simply avoid the affected assets altogether. But this carries a different kind of risk:
After Julian Robertson, Mr. Druckenmiller is the second legendary hedge fund manager to walk away from the business in the last month after suffering reverses. Mr. Robertson's fund had performed poorly because he thought technology stocks were way overvalued, and he refused to play.
''The moral of this story is that irrational markets can kill you,'' said one Wall Street analyst who has dealt with both men. ''Julian said, 'This is irrational and I won't play,' and they carried him out feet first. Druckenmiller said, 'This is irrational and I will play,' and they carried him out feet first.''
The last two examples are mentioned by Abreu and Brunnermeier in their 2003 Econometrica paper on bubbles and crashes. One of the key points made in that paper is that even sophisticated, forward looking investors face a dilemma when they become aware of a bubble, because they know that it will continue to expand unless there is coordinated selling by enough of them. And such coordination is not easily achieved, resulting in the possibility of prolonged departures of prices from fundamental values.
As a result, identifying bubbles as they occur is a lot easier than cashing in on this knowledge. Free Exchange (via Brad DeLong) sums up this position neatly in a direct response to Sumner:
Markets are efficient in the sense that it's hard to make an easy buck off of them, particularly when they're rushing maniacally up the skin of an inflating bubble. But are they efficient in the sense that prices are right? Tens of thousands of empty homes say no. And despite the great extent to which markets depart from the theoretician's ideal, people did manage to put together models predicting the fall, bet on those models, and make a great deal of money off of those bets.
The same point is made by Richard Thaler in his recent interview with John Cassidy (via Mark Thoma). Here's Thaler's response to a question about what remains of the efficient markets hypothesis:
I always stress that there are two components to the theory. One, the market price is always right. Two, there is no free lunch: you can’t beat the market without taking on more risk. The no-free-lunch component is still sturdy, and it was in no way shaken by recent events: in fact, it may have been strengthened. Some people thought that they could make a lot of money without taking more risk, and actually they couldn’t. So either you can’t beat the market, or beating the market is very difficult—everybody agrees with that. My own view is that you can [beat the market] but it is difficult.
The question of whether asset prices get things right is where there is a lot of dispute. Gene [Fama] doesn’t like to talk about that much, but it’s crucial from a policy point of view. We had two enormous bubbles in the last decade, with massive consequences for the allocation of resources.
This is why the separation of the prediction question from the profitability question is so important. If the Federal Reserve is to adopt policies that respond to asset price bubbles, it is necessary only that such phenomena be reliably diagnosed, not that the identification of bubbles be hugely profitable for private investors. And those who deny the possibility of predicting bubbles really ought to provide some direct evidence for this view, independently of the fact that the market is hard to beat. Consider, for instance, this excerpt from Cassidy's interview with Fama:
I guess most people would define a bubble as an extended period during which asset prices depart quite significantly from economic fundamentals.
That’s what I would think it is, but that means that somebody must have made a lot of money betting on that, if you could identify it. It’s easy to say prices went down, it must have been a bubble, after the fact. I think most bubbles are twenty-twenty hindsight. Now after the fact you always find people who said before the fact that prices are too high. People are always saying that prices are too high. When they turn out to be right, we anoint them. When they turn out to be wrong, we ignore them. They are typically right and wrong about half the time.
Like Sumner, Fama here is alleging that those who take bubbles seriously are suffering from a cognitive illusion. But it's the very last sentence that I find most troubling. How do we know that such individuals are typically right and wrong about half the time? This is an empirical question, and needs to be addressed with data. And studies showing that it is difficult if not impossible to beat the market are not helpful in answering it.
I agree it is worth empirically investigating the distinction between identifying bubbles and being able to profit from this knowledge but I'm not sure how to do this. Presumably we would ask large groups of investors, economists, policy-makers, etc. to make many predictions and then examine their track-record. What form should their predictions take?ReplyDelete
It is also worth noting a distinction parallel to the one you make: it is one thing for policy-makers to be able to, on average, identify a bubbles in real-time, it is another thing for policy-makers to implement good policy based on this information.
Michael, I'm working on a post that deals with exactly this question. Examining the track record of investors and policy makers is a clumsy way to proceed; I think that cleaner tests are possible. One can look at whether prices of certain derivative contracts (such as index straddles) that are used to hedge against volatility are leading indicators of crashes or bear markets. Or one can set up contracts in existing prediction markets that are linked to significant future price declines. I'll discuss this fully in my next post but it might take a few days to finish it.ReplyDelete
Great post. To assert that markets are "efficient" is very different from saying that it's extremely difficult to beat the market.ReplyDelete
Shleifer and Vishny's seminal paper on the "Limits of Arbitrage" highlighted this a long time ago and I'm surprised so many people still conflate these two very different assertions.
You've highlighted two important reasons for these limits, the principal-agent problem in professional investing and the problem of margin calls. I'd just add that selling short is even riskier than going long because of the potential for unlimited losses. At least if one's not leveraged, a long position can be held onto for a much longer time.
I wrote a post on the difficulties of going short a while ago here:
John Hempton on Efficient Markets
I'd also add that given the complexity of markets, market timing is an almost impossible task but this does not mean that we cannot construct Hayekian "pattern predictions". I have another post here connecting Hayek's view on complexity and predictability to predictability in ecosystems.
Efficient Markets and Pattern Predictions
If ecologists were forced to predict the exact time of ecosystem collapse rather than predicting patterns, they'd all be unemployed!
Thanks, those are interesting posts, and the John Hempton piece you linked to is excellent. I think economics would do well to pay more attention to ecology. More on this here.ReplyDelete
Thanks Rajiv. I agree - an evolutionary/ecosystem viewpoint has much to offer economics, especially macroeconomics.ReplyDelete
Much of what gets interpreted as irrationality can be explained via agent adaptation/natural selection under uncertainty.
And Minsky's theory has many parallels in ecology, most strikingly in Buzz Holling's work on resilience which I've written a short note on here .
Just read your excellent post on Minsky and Holling. Some of the formal models of resilience in ecology could be very useful in thinking about systemic risk and financial fragility... I'll look into this some more when time permits.ReplyDelete
One of my favorite Keynes quotes summarizes the argument quite nicely--"The market can remain irrational longer than you can remain solvent".ReplyDelete