Herding or wisdom of the crowd? Controlling efficiency in a partially rational financial market

Abstract

Herding has often been blamed as one of the possible causes of market instabilities, ultimately yielding to bubbles and crushes. On the other hand, researchers hypothesized that financial systems may benefit from the so-called wisdom of the crowd. To solve this apparent dichotomy, we leverage a novel financial market model, where the agents form their expectations by combining their individual return estimation with the expectations of their neighbors. By establishing a link between herding, sociality, and market instabilities, we point out that the emergence of collective decisions in the market is not necessarily detrimental. Indeed, when all the agents tend to conform their expectations to those of one or few leaders, herding might dramatically reduce market efficiency. However, when each agent accounts for a plurality of opinions, thus following the wisdom of the crowd, market dynamics become efficient. Following these observations, we propose two alternative control strategies to reduce market instability and enhance its efficiency.

Analyze the Behavioral Foundation of Stylized Facts Using Agent-Based Simulation and STGP Algorithm

“…Then, the presence of a chartist artificial agent is necessary to explain the market's anomalies. Rossa et al (2020) developed an artificial model and investigated the effect of herd behavior (collective wisdom) on market instability (or dynamics). The model links herding behavior with sociality and market instabilities and forms the agents' expectations based on their returns and the expectations of their neighbors.…”