Fuzzy portfolio diversification with ordered fuzzy numbers
Authors:
- Adam Marszałek,
- Tadeusz Burczyński
Abstract
In this paper, we consider a multi-objective portfolio diversification problem under real constraints in fuzzy environment, where the objective is to minimize the variance of portfolio and maximize expected return rate of portfolio. The return rates of assets are modeled using concept of Ordered Fuzzy Candlesticks, which are Ordered Fuzzy Numbers. The use of them allows modeling uncertainty associated with financial data based on high-frequency data. Thanks to well-defined arithmetic of Ordered Fuzzy Numbers, the estimators of fuzzy-valued expected value and covariance can be computed in the same way as for real random variables. In an empirical study, 20 assets included in the Warsaw Stock Exchange Top 20 Index are used to compare considered fuzzy model with crisp mean-variance model.
- Record ID
- CUTf2156f71753c4b83ac4487a46dafcba7
- Publication categories
- ; ;
- Author
- Pages
- 279-291
- Other elements of collation
- Bibliografia (liczba pozycji) - 27; Oznaczenie streszczenia - Abstr.
- Book
- Rutkowski Leszek, Leszek Rutkowski Korytkowski Marcin, Marcin Korytkowski Scherer Rafał Rafał Scherer [et al.] (eds.): Artificial Intelligence and Soft Computing : 16th International Conference, ICAISC 2017, Zakopane, Poland, June 11-15, 2017 : proceedings. Pt. 1, Lecture Notes in Artificial Intelligence, 2017, Cham, Springer, Springer, ISBN 978-3-319-59063-9 (eBook)
- Keywords in English
- ordered fuzzy number, Kosinski’s fuzzy number, ordered fuzzy candlestick, fuzzy portfolio diversification, fuzzy returns, multiobjective optimization, financial high-frequency data
- DOI
- DOI:10.1007/978-3-319-59063-9_25 Opening in a new tab
- URL
- https://link.springer.com/chapter/10.1007/978-3-319-59063-9_25 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 20
- Additional fields
- Indeksowana w: Web of Science, Scopus, CORE
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTf2156f71753c4b83ac4487a46dafcba7/
- URN
urn:pkr-prod:CUTf2156f71753c4b83ac4487a46dafcba7
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