Analyzing the influence of overconfident investors on financial markets through agent-based model

Hiroshi Takahashi, Takao Terano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

In this research, we employ Agent-Based Model to analyze how asset prices are affected by investors' Behavior. This analysis places focus on the influence of overconfident investors on financial market. As a result of intensive analysis, we find that overconfident investors are generated in a bottom-up fashion in the market. Furthermore, it has also been found that overconfident investors have the ability to contribute to market efficiency.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2007 - 8th International Conference, Proceedings
Pages1042-1052
Number of pages11
Publication statusPublished - 2007 Dec 1
Event8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007 - Birmingham, United Kingdom
Duration: 2007 Dec 162007 Dec 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4881 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007
CountryUnited Kingdom
CityBirmingham
Period07/12/1607/12/19

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Keywords

  • Agent based-model
  • Asset pricing
  • Behavioral economics
  • Overconfidence

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Takahashi, H., & Terano, T. (2007). Analyzing the influence of overconfident investors on financial markets through agent-based model. In Intelligent Data Engineering and Automated Learning - IDEAL 2007 - 8th International Conference, Proceedings (pp. 1042-1052). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4881 LNCS).