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

研究成果: Article

7 引用 (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.

元の言語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
発行部数1
DOI
出版物ステータスPublished - 2011 5
外部発表Yes

Fingerprint

Volatility clustering
Herding
Information sharing
Experiment
Proportion
Limited information
Herding behavior
Stock market
Agent-based model

ASJC Scopus subject areas

  • Economics and Econometrics
  • Business and International Management

これを引用

@article{298ae99eb6f24760a8251cd7510a26b7,
title = "Volatility clustering and herding agents: Does it matter what they observe?",
abstract = "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.",
keywords = "Agent-based, Herding, Learning, Volatility clustering",
author = "Ryuichi Yamamoto",
year = "2011",
month = "5",
doi = "10.1007/s11403-010-0075-5",
language = "English",
volume = "6",
pages = "41--59",
journal = "Journal of Economic Interaction and Coordination",
issn = "1860-711X",
publisher = "Springer Verlag",
number = "1",

}

TY - JOUR

T1 - Volatility clustering and herding agents

T2 - Does it matter what they observe?

AU - Yamamoto, Ryuichi

PY - 2011/5

Y1 - 2011/5

N2 - 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.

AB - 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.

KW - Agent-based

KW - Herding

KW - Learning

KW - Volatility clustering

UR - http://www.scopus.com/inward/record.url?scp=79953163699&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79953163699&partnerID=8YFLogxK

U2 - 10.1007/s11403-010-0075-5

DO - 10.1007/s11403-010-0075-5

M3 - Article

AN - SCOPUS:79953163699

VL - 6

SP - 41

EP - 59

JO - Journal of Economic Interaction and Coordination

JF - Journal of Economic Interaction and Coordination

SN - 1860-711X

IS - 1

ER -