Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Fuzzy optimization for portfolio selection based on Embedding Theorem in Fuzzy Normed Linear Spaces
Download
[15811832 - Organizacija] Fuzzy optimization for portfolio selection based on Embedding Theorem in Fuzzy Normed Linear Spaces.pdf
Date
2014-5-1
Author
Solatikia, Farnaz
Kiliç, Erdem
Weber, Gerhard Wilhelm
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
193
views
76
downloads
Cite This
<jats:title>Abstract</jats:title> <jats:p>Background: This paper generalizes the results of Embedding problem of Fuzzy Number Space and its extension into a Fuzzy Banach Space C(Ω) × C(Ω), where C(Ω) is the set of all real-valued continuous functions on an open set Ω. </jats:p> <jats:p>Objectives: The main idea behind our approach consists of taking advantage of interplays between fuzzy normed spaces and normed spaces in a way to get an equivalent stochastic program. This helps avoiding pitfalls due to severe oversimplification of the reality. </jats:p> <jats:p>Method: The embedding theorem shows that the set of all fuzzy numbers can be embedded into a Fuzzy Banach space. Inspired by this embedding theorem, we propose a solution concept of fuzzy optimization problem which is obtained by applying the embedding function to the original fuzzy optimization problem. </jats:p> <jats:p>Results: The proposed method is used to extend the classical Mean-Variance portfolio selection model into Mean Variance-Skewness model in fuzzy environment under the criteria on short and long term returns, liquidity and dividends. </jats:p> <jats:p>Conclusion: A fuzzy optimization problem can be transformed into a multiobjective optimization problem which can be solved by using interactive fuzzy decision making procedure. Investor preferences determine the optimal multiobjective solution according to alternative scenarios.</jats:p>
Subject Keywords
Embedding problem
,
Fuzzy optimization
,
Fuzzy Banach Space
,
Portfolio selection
URI
https://hdl.handle.net/11511/51456
Journal
Organizacija
DOI
https://doi.org/10.2478/orga-2014-0010
Collections
Graduate School of Applied Mathematics, Article
Suggestions
OpenMETU
Core
Some finite-dimensional backward shift-invariant subspaces in the ball and a related factorization problem
Alpay, D; Kaptanoglu, HT (2000-12-15)
Beurling's theorem characterizes subspaces of the Hardy space invariant under the forward-shift operator in terms of inner functions. In this Note we consider the case where the ball replaces the open unit desk and the reproducing kernel Hilbert space with reproducing kernel 1/(1-Sigma (N)(1) a(j)w(j)*) replaces the Hardy space. We give explicit formulas which generalize Blaschke products in the case of spaces of finite codimension. (C) 2000 Academie des sciences/Editions scientifiques et medicales Elsevier...
Linear Canonical Domains and Degrees of Freedom of Signals and Systems
Öktem, Sevinç Figen (2016-01-01)
We discuss the relationships between linear canonical transform (LCT) domains, fractional Fourier transform (FRT) domains, and the space-frequency plane. In particular, we show that LCT domains correspond to scaled fractional Fourier domains and thus to scaled oblique axes in the space-frequency plane. This allows LCT domains to be labeled and monotonically ordered by the corresponding fractional order parameter and provides a more transparent view of the evolution of light through an optical system modeled...
Temporal neuro-fuzzy MAR Algorithm for time series data in rule-based systems
Sisman, NA; Alpaslan, Ferda Nur (1998-04-23)
This paper introduces a new neuro-fuzzy model for constructing a knowledge-base of temporal fuzzy rules obtained by MAR (Multivariate Autoregressive) Algorithm. The model described contains two main parts which are fuzzy-rule extraction and storage of them. The fuzzy rules are obtained from time series data using MAR Algorithm. Fuzzy linear function with fuzzy number coefficients are used. The extracted rules are fed into the temporal fuzzy multilayer feedforward neural network.
Parallel Approximation, and Integer Programming Reformulation
Patakı, Gabor; Tural, Mustafa Kemal (null; 2008-03-14)
We show that in a knapsack feasibility problem an integral vectorp, which is short, and nearparallel to the constraint vector gives a branching direction with small integer width.We use this result to analyze two computationally efficient reformulation techniques on lowdensity knapsack problems. Both reformulations have a constraint matrix with columns reducedin the sense of Lenstra, Lenstra, and Lov ́asz. We prove an upper bound on the integer widthalong the last variable, which becomes 1,when the density ...
On endomorphisms of surface mapping class groups
Korkmaz, Mustafa (Elsevier BV, 2001-05-01)
In this paper, we prove that every endomorphism of the mapping class group of an orientable surface onto a subgroup of finite index is in fact an automorphism.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
F. Solatikia, E. Kiliç, and G. W. Weber, “Fuzzy optimization for portfolio selection based on Embedding Theorem in Fuzzy Normed Linear Spaces,”
Organizacija
, pp. 90–97, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51456.