Informational Cascades

‘The role of news events in affecting the market seems often to be delayed, and to have the effect of setting in motion a sequence of public attentions. These attentions may be to images or stories, or to facts that may already have been well known. The facts may previously have been ignored or judged inconsequential, but they can attain newfound prominence in the wake of breaking news. These sequences of attention may be called cascades, as one focus of attention leads to attention to another, and then another.’
Shiller (2000) [book]

‘There is now substantial evidence that financial markets do not react to information exactly as suggested by the efficient market hypothesis. Consequently, a number of papers have asked the question "how can this be explained?" Initially, one of the main explanations was that exogenous institutional imperfections, such as transactions costs, are the cause. This type of explanation is now being replaced by behavioural ones, which focus on exactly how agents process information. The idea in this paper is that agents respond not only to their own private information, but also to the information which they infer other agents have. The inference is made on the basis of the actions which other agents are seen to take.’
Skerratt (2000)

‘We offer a model to explain why groups of people sometimes converge upon poor decisions and are prone to fads, even though they can discuss the outcomes of their choices. Models of informational herding or cascades have examined how rational individuals learn by observing predecessors’ actions, and show that when individuals stop using their own private signals, improvements in decision quality cease. A literature on word-of-mouth learning shows how observation of outcomes as well as actions can cause convergence upon correct decisions. However, the assumptions of these models differ considerably from those of the cascades/herding literature. In a setting which adds ‘conversational’ learning about both the payoff outcomes of predecessors to a basic cascades model, we describe conditions under which (1) cascades/herding occurs with probability one; (2) once started there is a positive probability (generally less than one) that a cascade lasts forever; (3) cascades aggregate information inefficiently and are fragile; (4) the ability to observe past payoffs can reduce average decision accuracy and welfare; and (5) delay in observation of payoffs can improve average accuracy and welfare.’
Cao and Hirshleifer (2000)

‘We review theory and evidence relating to herd behavior, payoff and reputational interactions, social learning, and informational cascades in capital markets. We offer a simple taxonomy of effects, and evaluate how alternative theories may help explain evidence on the behavior of investors, firms, and analysts. We consider both incentives for parties to engage in herding or cascading, and the incentives for parties to protect against or take advantage of herding or cascading by others.’
Hirshleifer and Hong Teoh (2001)

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