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The Generalization of λ-Fuzzy Measures with Application to the Fuzzy Option

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Fuzzy Systems and Knowledge Discovery (FSKD 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4223))

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Abstract

In this paper, we present the definition of λ-fuzzy signed measure, its generalized transform function, and the distribution properties of λ-fuzzy measures. Then investors’ heterogeneity is revealed with a family of λ-fuzzy measures. The approach to asset pricing based on λ-fuzzy measures breaks through the traditional ”identical rationality” assumption, and provides an useful analytical tool for recent researches of behavioral economics and finance.

The research is supported by National Natural Science Foundation of China, titled as ”Research on the pricing methods of options based on the fuzzy measures” (70271010).

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Authors and Affiliations

  1. School of Economics and Management, Beihang University, Beijing, 100083, China

    Liyan Han & Wenli Chen

Authors
  1. Liyan Han
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  2. Wenli Chen
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Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University,, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Life Science Research Center, School of Electronic Engineering, Xidian University,, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  3. School of Electrical and Electronic Engineering, Xidian University, 710071, Xi’an, China

    Guanming Shi

  4. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, Brisbane, Queensland, Australia

    Xue Li

  5. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

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© 2006 Springer-Verlag Berlin Heidelberg

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Han, L., Chen, W. (2006). The Generalization of λ-Fuzzy Measures with Application to the Fuzzy Option. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_93

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  • DOI: https://doi.org/10.1007/11881599_93

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45916-3

  • Online ISBN: 978-3-540-45917-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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