The development of the financial learning tool through business game

Yasuo Yamashita, Hiroshi Takahashi, Takao Terano

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

3 Citations (Scopus)

Abstract

Recently financial education has become more important because financial technology is highly developing and financial market is growing in importance. In this research, we apply Business Game method to financial education. Especially we focused on learning of asset allocation. As a result of intensive experiments, we found that (1) players learned not to take excessive risk through business game and (2) they recognize the importance of risk control by our experiments. These findings indicate that our approach is valid for financial education.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
Pages986-993
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2008 Dec 24
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia
Duration: 2008 Sep 32008 Sep 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5178 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
CountryCroatia
CityZagreb
Period08/9/308/9/5

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Keywords

  • Business game
  • Investment decision making
  • WWW browser
  • WWW server

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Yamashita, Y., Takahashi, H., & Terano, T. (2008). The development of the financial learning tool through business game. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings (PART 2 ed., pp. 986-993). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5178 LNAI, No. PART 2). https://doi.org/10.1007/978-3-540-85565-1-123