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Granular Computing
Erschienen in: Granular Computing 4/2019

05.06.2018 | Original Paper

Portfolio optimization with perception-based risk measures in dynamic fuzzy asset management

verfasst von: Yuji Yoshida

Erschienen in: Granular Computing | Ausgabe 4/2019

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Abstract

In asset management with uncertainty, a dynamic portfolio allocation problem to minimize the average rates of falling is discussed. Introducing coherent risk measures and average value-at-risks, this paper deals with portfolio optimization to make the asset management stable for a long term. These criteria are applied to fuzzy random variables by perception-based extension. In this model, randomness is estimated stochastically and fuzziness is evaluated by \(\lambda\)-mean functions and evaluation weights. By mathematical programming and dynamic programming, dynamic optimality conditions with optimal portfolios are derived. A few numerical examples are given to compare the cases of coherent risk measures with other value-at-risks. It is observed that the presented portfolio optimization method with coherent risk measures gives stable asset management in a long term.
Nächster Artikel Type 1 fuzzy function approach based on ridge regression for forecasting

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Metadaten
Titel
Portfolio optimization with perception-based risk measures in dynamic fuzzy asset management
verfasst von
Yuji Yoshida
Publikationsdatum
05.06.2018
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 4/2019
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-018-0100-y

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Correction

Correction to: Interactive granular computing

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