A Dynamic Average Value-at-Risk Portfolio Model with Fuzzy Random Variables

A perception-based portfolio model under uncertainty is presented. In the proposed model, randomness and fuzziness are evaluated respectively by probabilistic expectation and the mean values with evaluation weights and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepacka...

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Bibliographic Details
Published inFuzzy Sets, Rough Sets, Multisets and Clustering Vol. 671; pp. 291 - 306
Main Author Yoshida, Yuji
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2017
Springer International Publishing
SeriesStudies in Computational Intelligence
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Summary:A perception-based portfolio model under uncertainty is presented. In the proposed model, randomness and fuzziness are evaluated respectively by probabilistic expectation and the mean values with evaluation weights and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document}-mean functions. Introducing average value-at-risks under conditions, this paper formulates average value-at-risks in dynamic stochastic environment. By dynamic programming approach, an optimality condition of the optimal portfolios for dynamic average value-at-risks is derived. It is shown that the optimal average value-at-risk is a solution of the optimality equation under a reasonable assumption, and an optimal portfolio weight is obtained from the equation.
ISBN:3319475568
9783319475561
ISSN:1860-949X
1860-9503
DOI:10.1007/978-3-319-47557-8_17