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International Joint Conference on Rough Sets

IJCRS 2018: Rough Sets pp 1–12Cite as

Subjective Analysis of Price Herd Using Dominance Rough Set Induction: Case Study of Solar Companies

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11103))

Abstract

Herd behavior depends on subjectivity and objectivity combination. Usually the former over controls the latter and makes a special distinction from others. Especially, herd could regard itself as objective thus sacrificing all differences. Getting insight of the subjectivity appears more and more important in economics. However, the combination of subjectivity and objectivity varies with time evolution. To illustrate subjective analysis, we propose an inferential model to distinguish special enterprises from price herds. It assumes public finance as intrinsic self of subjectivity and the herding behavior as objective expectation of majority then identifies subjective actions.

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Author information

Authors and Affiliations

  1. Faculty of Software and Information Science, Iwate Prefectural University, Takizawa, 020-0693, Japan

    Hamido Fujita

  2. Department of Information Management, Chung Hua University, Hsinchu, 30012, Taiwan

    Yu-Chien Ko

Authors
  1. Hamido Fujita
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  2. Yu-Chien Ko
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Correspondence to Hamido Fujita .

Editor information

Editors and Affiliations

  1. University of Warsaw, Warsaw, Poland

    Hung Son Nguyen

  2. Faculty of Information Technology, Vietnam National University, Hanoi, Vietnam

    Quang-Thuy Ha

  3. School of Information Science, Southwest Jiaotong University, Chengdu, China

    Tianrui Li

  4. Institute of Computer Science, University of Silesia, Sosnowiec, Poland

    Małgorzata Przybyła-Kasperek

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Fujita, H., Ko, YC. (2018). Subjective Analysis of Price Herd Using Dominance Rough Set Induction: Case Study of Solar Companies. In: Nguyen, H., Ha, QT., Li, T., Przybyła-Kasperek, M. (eds) Rough Sets. IJCRS 2018. Lecture Notes in Computer Science(), vol 11103. Springer, Cham. https://doi.org/10.1007/978-3-319-99368-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-99368-3_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99367-6

  • Online ISBN: 978-3-319-99368-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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