Estimating a model of herding behavior on social networks

【Author】 Nicolas, Maxime L. D.

【Source】PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

【影响因子】3.778

【Abstract】In this paper, we estimate an agent-based model (ABM) to investigate herding behaviors in the formation of investor sentiment. We formalize a simple opinion dynamics model in a social network framework and rely on a numerical method to estimate its parameters. We derive a sentiment proxy from the weekly aggregation of online messages concerning 15 US stocks and 5 cryptocurrencies. Our empirical results suggest a strong impact of herding behavior on the formation of sentiment toward highly volatile assets. For such assets, we simultaneously find limited impacts of financial returns and investor attention on the opinion formation process, suggesting that investor sentiment is explained by social interactions. On the other hand, we find a limited influence of social interactions on sentiment regarding less volatile assets, whose formation process is instead explained by the strong influence of financial returns and investor attention. In particular, we find that herding behavior was significantly higher and played a major role in the sentiment formation process regarding cryptocurrencies when the bubble occurred. (C) 2022 Elsevier B.V. All rights reserved.

【Keywords】Agent -based model; Investor sentiment; Herding behavior; Social network

【发表时间】2022 15-Oct

【收录时间】2022-08-15

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-市场分析