Paper Info
Title
Fuzzy Chance-Constrained Multiobjective Portfolio Selection Model
Abstract
This paper addresses the problem of portfolio selection with fuzzy parameters from a perspective of chance-constrained multiobjective programming. The key financial criteria used here are conventional, namely, return, risk, and liquidity; however, we use short- and long-term variants of return rather than a single measure of an investor’s expectations in respect thereof. The proposed model aims to achieve the maximal return (short term as well as long term) and liquidity of the portfolio. It does so at a credibility, which is no less than the confidence levels defined by the investor. Further, to capture uncertain behavior of the financial markets more realistically, fuzzy parameters used here are such as those characterized by general functional forms. To solve the problem, we rely on a specially developed algorithm that hybridizes fuzzy simulation and real-coded genetic algorithm. Numerical experiments are included to showcase the applicability and efficiency of the model in a real investment environment.
Year
DOI
Venue
2014
10.1109/TFUZZ.2013.2272479
Fuzzy Systems, IEEE Transactions  
Keywords
Field
DocType
fuzzy set theory,genetic algorithms,investment,stock markets,chance-constrained multiobjective programming,financial markets,fuzzy chance-constrained multiobjective portfolio selection model,fuzzy parameters,general functional forms,portfolio liquidity,real-coded genetic algorithm,Chance-constrained programming,credibility measure,fuzzy portfolio selection,multiobjective optimization,real-coded genetic algorithm (RCGA)
Market liquidity,Mathematical optimization,Credibility,Fuzzy logic,Portfolio,Portfolio optimization,Linear programming,Financial market,Mathematics,Genetic algorithm
Journal
Volume
Issue
ISSN
22
3
1063-6706
Citations 
PageRank 
References 
16
0.62
35
Authors
2
Name
Order
Citations
PageRank
Mukesh Kumar Mehlawat127522.90
Pankaj Gupta21479133.85