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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Published in | Fuzzy Sets, Rough Sets, Multisets and Clustering Vol. 671; pp. 291 - 306 |
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Main Author | |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2017
Springer International Publishing |
Series | Studies in Computational Intelligence |
Subjects | |
Online Access | Get full text |
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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}
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\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. |
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ISBN: | 3319475568 9783319475561 |
ISSN: | 1860-949X 1860-9503 |
DOI: | 10.1007/978-3-319-47557-8_17 |