Volatility clustering and herding agents: Does it matter what they observe?

Ryuichi Yamamoto*

*この研究の対応する著者

研究成果: Article査読

9 被引用数 (Scopus)

抄録

Recent agent-based models have demonstrated that agents' herding behavior causes volatility clustering in stock markets. We examine economies where agents herd on others, yet they have limited sets of information on other agents to imitate. In particular, we conduct experiments on economies with agents with different levels of information sharing where agents can imitate: (1) the strategies of others but with an error, (2) the strategies of only a fraction of agents, or (3) the strategies of others, but update their parameters only by a proportion. In each experiment we change the likelihood that agents make errors to copy the strategy of others, the fraction of agents to herd, or the proportion of the parameter that agents update, in order to examine the effect of the different degrees of information sharing on volatility clustering. We show that volatility clustering tends to disappear when agents have limited information on the strategies of others, and agents need to imitate the strategy details of others in order to generate the clustered volatility.

本文言語English
ページ(範囲)41-59
ページ数19
ジャーナルJournal of Economic Interaction and Coordination
6
1
DOI
出版ステータスPublished - 2011 5 1
外部発表はい

ASJC Scopus subject areas

  • ビジネスおよび国際経営
  • 経済学、計量経済学

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