In a recent paper on financial innovation and fragility, Gennaioli, Shleifer and Vishny argue that investors (and often also financial intermediaries) are hobbled by certain systematic cognitive biases that cause them to neglect unlikely events when assessing asset values. They argue that such "local thinking" results in the creation and excessive issuance of engineered securities that are widely believed to be close substitutes for more traditional safe assets, but turn out to be much riskier than initially anticipated. This psychological regularity, they believe, accounts for a number of historical episodes of financial instability:
Many recent episodes of financial innovation share a common narrative. It begins with a strong demand from investors for a particular, often safe, pattern of cash flows. Some traditional securities available in the market offer this pattern, but investors demand more (so prices are high). In response to demand, financial intermediaries create new securities offering the sought after pattern of cash flows, usually by carving them out of existing projects or other securities that are more risky. By virtue of diversification, tranching, insurance, and other forms of financial engineering, the new securities are believed by the investors, and often by the intermediaries themselves, to be good substitutes for the traditional ones, and are consequently issued and bought in great volumes. At some point, news reveals that new securities are vulnerable to some unattended risks, and in particular are not good substitutes for the traditional securities. Both investors and intermediaries are surprised by the news, and investors sell these “false substitutes,” moving back to the traditional securities with the cash flows they seek. As investors fly for safety, financial institutions are stuck holding the supply of the new securities (or worse yet, having to dump them as well in a fire sale because they are leveraged). The prices of traditional securities rise while those of the new ones fall sharply.
The authors claim that this sequence of events describes not only the recent experience with collateralized debt obligations and money market funds, but also earlier episodes of financial innovation, including prepayment tranching of collateralized mortgage obligations in the 1980s.
In order to explore precisely the implications of local thinking in the context of financial innovation, the authors construct a model based on a number of stark, simplifying assumptions. There are two assets: a traditional safe security and a risky asset that has three possible terminal payoffs. The worst case outcome for the risky asset is also the least likely to occur (this is a crucial assumption). Investors are homogeneous and highly risk averse. Financial innovation takes the form of separating the cash flows from the risky asset into two components: a "safe" security that earns the the worst case payoff regardless of the actual outcome, and a risky residual claim. Under rational expectations this innovation is welfare improving, and the quantity of the substitute issued is precisely such that all such claims would be covered even if the worst case loss were to materialize. That is, the substitute security really is safe.
Under local thinking, the least likely event (which is also the worst case outcome) is simply neglected, and beliefs about the other two outcomes are correspondingly inflated. The intermediate outcome is now (mistakenly) perceived to be the worst, and a greater quantity of the substitute security is issued than could be honored if the actual worst case outcome were to be realized. Now suppose that some bad news arrives, conditional on which the objective probabilities of the three outcomes are altered in such a manner as to make the intermediate outcome the least likely. Local thinking then causes investors to become excessively pessimistic: the worst case outcome not only becomes suddenly salient, but the less disastrous intermediate outcome is neglected and the decline in the price of the asset previously thought to be safe is greater than it would be under rational expectations.
The development of a theoretical framework within which common elements of various historical episodes can be examined is clearly a worthwhile exercise. But what troubles me about this paper (and much of the behavioral finance literature) is that the rational expectations hypothesis of identical, accurate forecasts is replaced by an equally implausible hypothesis of identical, inaccurate forecasts. The underlying assumption is that financial market participants operating under competitive conditions will reliably express cognitive biases identified in controlled laboratory environments. And the implication is that financial instability could be avoided if only we were less cognitively constrained, or constrained in different ways -- endowed with a propensity to overestimate rather than discount the likelihood of unlikely events for example.
This narrowly psychological approach to financial fragility neglects two of the most analytically interesting aspects of market dynamics: belief heterogeneity and evolutionary selection. Even behavioral propensities that are psychologically rare in the general population can become widespread in financial markets if they result in the adoption of successful strategies. As a result, asset prices disproportionately reflect the beliefs of investors who have been most successful in the recent past. There is no reason why these beliefs should consistently conform to those in the general population.
I have argued previously for the further development of this ecological perspective on financial instability, and similar themes have been explored elsewhere; see especially Macroeconomic Resilience and David Murphy. As I said in an earlier post, a bit too much is being asked of behavioral economics at this time, more than it has the capacity to deliver.
Update (7/11). David Murphy follows up with characteristic clarity:
Update (7/11). David Murphy follows up with characteristic clarity:
I would even go further, because this argument neglects the explicitly reflexive nature of market participant’s thinking. (Call it social metacognition if you really want some high end jargon.) Traders can both absolutely understand that a behavioral propensity is rare and likely to lead to catastrophe and behave that way: they do this because they believe that other market participants will too, and behaving that way if others do will make money in the short term. Even if you think that it is crazy for (pick your favourite bubblicious asset) to trade that high, providing you also believe others will buy it, then it makes sense for you to buy it along with the crowd. Moreover, worse, you may well believe that they too think it is crazy: but all of you are in a self-sustaining system and the first one to get off looks the most foolish (for a while). Most people are capable of spotting a bubble if it lasts long enough: the hard part is timing your exit to account for the behaviour of all the other smart people trying to time their exit too.I agree completely. There are many examples of prominent fund managers trying to grapple with this problem during the bubble in technology stocks a decade ago. This is why markets can (approximately) satisfy what James Tobin called information arbitrage efficiency while failing to satisfy fundamental valuation efficiency.