Identifying Bubbles
In response to the barrage of criticism that has been aimed at the efficient markets hypothesis recently, Robin Hanson makes a plea:
Look, everyone, this game should have rules. EMH (at least the interesting version) says prices are our best estimates, so to deny EMH is to assert that prices are predictably wrong. And for EHM violations to be relevant for regulatory policy, price errors must be so systematic as to allow a government agency to follow some bureaucratic process to identify when prices are too high, vs. too low, and act on that info.
The efficient markets hypothesis makes a stronger claim than just price unpredictability; it identifies prices with fundamental values. So one can indeed question the hypothesis without asserting that "prices are predictably wrong." But Hanson's broader point is surely correct: if the Federal Reserve is charged with reacting to asset price bubbles, then bubbles must be identifiable not just on the basis of hindsight, but in real time, as they occur. Can this be done?
For reasons discussed at length in a previous post, a belief that an asset is overpriced relative to fundamentals is consistent with a broad range of trading strategies, each of which carries significant risks. One cannot therefore deduce an individual's beliefs about the existence of a bubble simply by observing their trades or holdings of the asset in question. However, it might be possible to obtain information about the prevalence of beliefs about an asset bubble by looking at the prices of options.
Specifically, anyone who thinks that they have identified a bubble must also believe that the likelihood of a major correction (such as a crash or bear market) must be higher than would normally be the case. They may also believe that the likelihood of significant short term increases in price is higher than normal. If so, they are predicting greater volatility in the asset price than would arise in the absence of a bubble. And if such expectations are widely held, they should be reflected in the price of options strategies that are especially profitable in the face of major price movements.
In the case of a bubble involving a large class of securities (such as technology stocks) a widespread belief that prices exceed fundamental values should be reflected in higher prices for index straddles: a combination of put and call options with the same expiration date and strike price, written on a market index. The Chicago Board Options Exchange specifically recommends this strategy for investors who are convinced that "a particular index will make a major directional move" and those who anticipate "increased volatility." One possible approach to determining whether bubbles are identifiable as they occur is therefore to ask whether the price of an index straddle is a leading indicator of a crash or bear market.
This basic idea has been used previously in a number of event studies. David Bates, for instance, found that "out-of-the-money puts, which provide crash insurance, were unusually expensive relative to out-of-the-money calls" during the year preceding the 1987 stock market crash. He interprets this as reflecting "a strong perception of downside risk" over this period. Joseph Fung found that implied volatility deduced from the prices of index options rose sharply in May and June of 1997, predicting the Hong Kong stock market crash of October 1997. He concludes that "option implied volatility could be incorporated into an early warning system intended to indicate large market movements or crisis events." There were no index options traded at the time of the 1929 crash, but Rappoport and White used data on brokers' loans collateralized by stock (which they interpret as a option-like contract) to ask whether the crash was predicted. They found that:
During the stock-market boom, "the key attributes of brokers' loan contracts (the interest rate and the initial required margin) rose significantly, suggesting that lenders felt a need for protection from a sharp decline in the value of their collateral... The rise in the margin required and the interest rate charged suggest that those who lent money for investment in the stock market (bankers and brokers) radically revised their opinion of the risks inherent in making brokers' loans as the market climbed and once again when it collapsed.
Event studies such as these are not quite enough to address Hanson's concern, since they do not consider false alarms: situations in which the prices of options signaled an increase in volatility that did not eventually materialize. But it seems that the same approach could be used to determine whether or not bubbles are indeed identifiable: one simply needs to examine a long, uninterrupted time series to see if implied volatility (as reflected in the prices of options) is predictive of major market declines.
If it is, then perhaps the Federal Reserve should respond not only to the inflation rate, output gap, and system-wide leverage, but also to the implied volatility in index options. It is at least conceivable that such a policy might reduce the incidence and severity of asset price bubbles.
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Update (1/29). Even if it were possible to reliably identify bubbles, it is not obvious that the Fed should respond in any systematic way. Bernanke and Gertler (2001) argued firmly that the costs of doing so would outweigh any benefits:
even if the central bank is certain that a bubble is driving the market, once policy performance is averaged over all possible realizations of the bubble process, by any reasonable metric there is no consequential advantage of responding to stock prices.
It would be interesting to know whether Bernanke has softened his position on this. An intriguing possibility is that the willingness of the central bank to intervene could influence asset market behavior in such a manner as to make actual interventions largely unnecessary. As Lucas observed in a hugely influential paper, one cannot assume that structural patterns in the data will persist if policy responses to such patterns are altered.
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Update (1/31). In a comment on this post, Barkley Rosser points out that the clearest examples of bubbles may be found in closed-end funds that are trading at a significant premium over net asset value:
there is one category of assets where the fundamental is very well defined: closed-end funds, although one must account for the ability to buy and sell the underlying assets and must account for management fees and tax effect. Thus, most closed-end funds run single-digit discounts. But if one sees a closed-end fund with a soaring premium of the price over the net asset value, one can be about as sure as one can be that one is observing a bubble.
This is absolutely correct: a closed-end fund selling at a premium is overpriced by definition relative to the value of the underlying assets, and the premium can only be sustained if the overpricing is expected to become even larger at some point. But how often do such bubbles arise in practice? Barkley directs us to some evidence (links added):
There is an existing [literature] on this that arose in response to the "misspecified fundamentals" arguments about bubbles put forward by Garber and others about 20 years ago. One of those was [by DeLong and Shleifer] in the Journal of Economic History. They noted the 100% premia that appeared on closed-end funds in the US in 1929, arguing that one might not be able to prove that there was a bubble on the stock market, but there most definitely was one on the closed-end funds at that time.
Ahmed, Koppl, Rosser, and White document the bubble on closed-end country funds that hit in 1989-90 (100% premia on the Germany and Spain funds before the crash in Frb. 1990) in "Complex bubble persistence in closed-end country funds" in the Jan. 1997 issue of JEBO.