Explain herding and how it links to market anomalies
The idea
Herding is following the crowd in place of independent analysis, and it is not always irrational at the individual level: a manager who is wrong alongside everyone else keeps their job, while one who is wrong alone does not. Aggregated, it produces momentum, bubbles and crashes, since prices move on flows rather than on information. Anomalies such as momentum and post-earnings drift are consistent with herding and underreaction, though a persistent anomaly is always open to the competing explanation that it is compensation for a risk not yet identified.
A practice question
When herding is widespread, prices tend to move mainly on which of the following?
- InformationWhy not: Prices moving on information is efficiency working. Herding is what happens when they move without it.
- Trading flows - correct
- Fundamental valueWhy not: Value is what prices are supposed to track. Herding is precisely the force that detaches them from it.
When many investors copy each other, prices move because of the volume of buying or selling, called trading flows, rather than because of news about the companies. For example, if holders pile into a rising stock, the price keeps rising on the buying alone. Once prices respond to flows instead of news or fundamental value, momentum (trends that continue) and bubbles can follow.
A harder one
Why can herding be individually rational for a professional manager?
- Because positions held by most managers earn higher returns for clientsWhy not: They do not, which is what makes the behaviour costly for clients.
- Because being wrong alone costs a career more than being wrong with peers - correct
- Because clients are legally entitled to demand that managers match peersWhy not: No such entitlement exists; managers are free to hold whatever positions they judge best.
A manager is judged and paid on results, so the payoff to the manager differs from the payoff to the client. If a manager is wrong alone, that stands out and may cost a job. If the manager is wrong along with everyone else, it is easier to excuse. So copying the consensus protects the manager's career, even though consensus positions do not always do well for clients. This conflict between the interests of the manager and the client is called a principal-agent problem.
The hardest tier
A documented anomaly persists for decades and survives out-of-sample tests. What are the two leading explanations?
- Either transaction costs have fallen, or the anomaly was never realWhy not: Falling costs would erode an anomaly rather than sustain it, and out-of-sample persistence argues against the anomaly never having been real.
- Either the market is fully efficient, or arbitrage is unconstrainedWhy not: If the market were fully efficient and arbitrage unconstrained, the anomaly would be traded away. It would not persist.
- Either compensation for an unmeasured risk, or limits to arbitrage - correct
An anomaly is a pattern in returns that a standard model cannot explain. If it lasts for decades and holds in new data, there are two leading explanations. One is that it pays for a risk the model leaves out, so it is fair compensation. The other is limits to arbitrage: investors who could profit by trading against the pattern are held back by costs, risk or short-selling limits, so behavioural biases persist. Example: a strategy beating the model by 3% a year either pays for hidden risk or survives because it is too costly to trade away.
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