Antonio Guarino

Herd Behavior and Contagion in Financial Markets

We study a sequential trading financial market where there are gains from trade, that is, where informed traders have heterogeneous private values. We show that an informational cascade (i.e., a complete blockage of information) arises and prices fail to aggregate information dispersed among traders. During an informational cascade, all traders with the same preferences choose the same action, following the market (herding) or going against it (contrarianism). We also study financial contagion by extending our model to a two-asset economy. We show that informational cascades in one market can be generated by informational spillovers from the other. Such spillovers have pathological consequences, generating long-lasting misalignments between prices and fundamentals.

Transaction Costs and Informational Cascades in Financial Markets: Theory and Experimental Evidence

We study the effect of transaction costs (e.g., a trading fee or a transaction tax, like the Tobin tax) on the aggregation of private information in financial markets. We analyze a financial market a la Glosten and Milgrom, in which informed and uninformed traders trade in sequence with a market maker. Traders have to pay a cost in order to trade. We show that, eventually, all informed traders decide not to trade, independently of their private information, i.e., an informational cascade occurs. We replicated our financial market in the laboratory. We found that, in the experiment, informational cascades occur when the theory suggests they should. Nevertheless, the ability of the price to aggregate private information is not significantly affected.

Aggregate information cascades

We introduce a new model of aggregate information cascades where only one of two possible actions is observable to others. Agents make a binary decision in sequence. The order is random and agents are not aware of their own position in the sequence. When called upon, they are only informed about the total number of others who have chosen the observable action before them. This informational structure arises naturally in many applications. Our most important result is that only one type of cascade arises in equilibrium, the aggregate cascade on the observable action. A cascade on the unobservable action never arises.

Averting economic collapse and the solipsism bias

We study the behavior of experimental subjects who have to make a sequence of risky investment decisions in the presence of network externalities. Subjects follow a simple heuristic—investing after positive experiences and reducing their propensity to invest after a failure. This result contrasts with the theoretical findings of Jeitschko and Taylor [Jeitschko, T.D., Taylor, C., 2001. Local discouragement and global collapse: A theory of coordination avalanches. Amer. Econ. Rev. 91 (1), 208–224] in which even agents who have only good experiences eventually stop investing because they account for the fact that others with worse experiences will quit. This can trigger sudden economic collapse—a coordination avalanche—even in the most efficient Bayesian equilibrium. In the experiment, subjects follow their own experiences and disregard the possible bad experiences of others—thus exhibiting behavior that we term “solipsism bias.” Solipsism results in sustained investment activity and thus averts complete collapse.

No-Trade in the Laboratory

We construct laboratory financial markets in which subjects can trade an asset whose value is unknown. Subjects receive private clues about the asset value and then set bid and ask prices at which they are willing to buy or to sell from the other participants. In some of our markets (experimental treatments), there are gains from trade, while in others there are no gains: trade is zero sum. Celebrated no-trade theorems state that differences in private information alone cannot explain trade in the zero sum case. We study whether purely informational trade is eliminated in our experimental markets with no gains. The comparison of our results for gains and no-gains treatments shows that subjects fail to reach the no-trade outcome by pure introspection, but they approach it over time through market feedback and learning. Furthermore, the less noisy the clue-asset relationship is, the closer trade comes to being eliminated entirely.

Bayesian Social Learning with Local Interactions

We study social learning in a large population of agents who only observe the actions taken by their neighbours. Agents have to choose one, out of two, reversible actions, each optimal in one, out of two, unknown states of the world. Each agent chooses rationally, on the basis of private information and of the observation of his neighbours’ actions. Agents can repeatedly update their choices at revision opportunities that they receive in a random sequential order. We show that if agents receive equally informative signals and observe both neighbours, then actions converge exponentially fast to a configuration where some agents are permanently wrong. In contrast, if agents are unequally informed (in that some agents receive a perfectly informative signal and others are uninformed) and observe one neighbour only, then everyone will eventually choose the correct action. Convergence, however, obtains very slowly, at rate √t.

Can Fear Cause Economic Collapse? Insights from an Experimental Study

We study the behavior of experimental subjects who have to make a sequence of risky investment decisions in the presence of network externalities. Subjects follow a simple heuristic – investing after positive experiences and reducing their propensity to invest after a failure. This result contrasts with the theoretical findings of Jeitschko and Taylor (2001) in which even agents who have only good experiences eventually stop investing because they are afraid that others with worse experiences will quit. In theory, this Bayesian fear can trigger sudden economic collapse – even in the most efficient Bayesian equilibrium. In the experiment, subjects are surprisingly fearless of others’ experiences, and simply follow their own experiences, thus averting a total collapse.

Informational Contagion in the Laboratory

We study the informational channel of financial contagion under laboratory conditions. In our experiment, two markets with correlated fundamentals open sequentially and in both of them subjects receive private information. Subjects in the market opening second also observe the history of trades and prices in the first market. We find that although in both markets private information is only imperfectly aggregated, subjects are able to make correct inferences based on the public information coming from the market that opens first. We thus observe financial contagion under laboratory conditions: the correlation between asset prices is very close to that predicted by the theory. Moreover, as the theory predicts, there is no contagion when asset fundamentals are independent: in other words, subjects only react to the history of prices and trades in the first market when it is rational to do so because they convey information.

Herd Behavior in Financial Markets

Over the last twenty-five years, there has been a lot of interest in herd behavior in financial markets?that is, a trader?s decision to disregard her private information to follow the behavior of the crowd. A large theoretical literature has identified abstract mechanisms through which herding can arise, even in a world where people are fully rational. Until now, however, the empirical work on herding has been completely disconnected from this theoretical analysis; it simply looked for statistical evidence of trade clustering and, when that evidence was present, interpreted the clustering as herd behavior. However, since decision clustering may be the result of something other than herding?such as the common reaction to public announcements?the existing empirical literature cannot distinguish ?spurious? herding from ?true? herd behavior.