Risk-Management Models Based on the Portfolio Theory Using Historical Data under Uncertainty

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Author(s): Takashi Hasuike (Osaka University, Japan)
Copyright: 2010
Pages: 24
Source title: Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies
Source Author(s)/Editor(s): Leon Shyue-Liang Wang (National University of Kaohsiung, Taiwan)and Tzung-Pei Hong (National University of Kaohsiung, Taiwan)
DOI: 10.4018/978-1-61520-757-2.ch007

Keywords: Data Mining / Data Mining and Databases / Information Science Reference / Library & Information Science

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Abstract

This chapter considers various types of risk-management models based on the portfolio theory under some social uncertainty that received historical data includes ambiguity, and that they are assumed not to be constant. These models with uncertainty are represented many social problems such as assets allocation, logistics, scheduling, urban project problems, etc.. However, since these problems with uncertainty are formulated as stochastic and fuzzy programming problems, it is difficult to solve them analytically in the sense of deterministic mathematical programming. Therefore, introducing possibility and necessity measures based on the fuzzy programming approach and considering the concept of risk-management based on the portfolio theory, main problems are transformed into the deterministic programming problems. Then, in order to solve the deterministic problems efficiently, the solution method is constructed.

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Risk-Management Models Based on the Portfolio Theory Using Historical Data under Uncertainty

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