Tuesday , October 23 2018

A New Portfolio Selection Method Based on Interval Data

Mădălina Ecaterina ANDREICA1, Ion DOBRE1, Mugurel Ionuţ ANDREICA2, Cornel RESTEANU3

1 Bucharest Academy of Economic Studies, 010552, Romania
madalina.andreica@gmail.com, dobrerio@ase.ro

2 Politehnica University of Bucharest, 060032, Romania
mugurel.andreica@cs.pub.ro

3 I C I Bucharest
(National Institute for R & D in Informatics)

8-10 Averescu Blvd.
011455 Bucharest 1, Romania
resteanu@ici.ro

Abstract: The aim of this paper is to extend a portfolio selection method based on MADM techniques for the case of interval data. In order to highlight the procedure of the proposed algorithm an example of product portfolio selection for a leasing company has been analyzed. Several numerical simulations have been performed in order to illustrate our interval data method.

Keywords: Multi-Attribute Decision Making, Imprecise Data, Shannon’s Entropy, Portfolio Selection, Leasing.

>>Full text
CITE THIS PAPER AS:
Mădălina Ecaterina ANDREICA, Ion DOBRE, Mugurel Ionuţ ANDREICA, Cornel RESTEANU, A New Portfolio Selection Method Based on Interval Data, Studies in Informatics and Control, ISSN 1220-1766, vol. 19 (3), pp. 253-262, 2010.

1. Introduction

The process of decision making is both a permanent necessity and a challenge in many fields, like risk management, banking, operational research and many others. The importance of the decision making process has been confirmed by the large number of publications which develop efficient decision making techniques. These techniques can be classified into several broad categories, such as those handling certain and complete information, those using uncertain data and objectives, and those based on risk assessment [3, 11]. Some of the best known decision making optimization methods are multi-attribute and multi-objective decision making [2, 7, 10], fuzzy decision rules [8] and dynamic programming.

Multi-Attribute Decision Making (MADM) refers to making preference decisions over the available alternatives that are characterized by multiple, generally conflicting attributes. In traditional MADM problems, most of the input variables are assumed to be crisp data. However, in most cases it is quite difficult to determine precisely the exact value of the attributes under incomplete information and uncertainty and as a result of this, their values are considered as intervals. Therefore, the aim of this paper is to extend a portfolio selection method based on MADM methods, for the case of interval data.

Finally, an example of product portfolio selection for a leasing company is shown in order to highlight the procedure of the proposed algorithm.

The paper is structured as follows. Section 2 presents the portfolio selection method for interval data, for which a numerical example is then given in Section 3, followed by some numerical simulations in Section 4, while Section 5 concludes.

REFERENCES

  1. AMIRI, M., N. E. NOSRATIAN, A. Jamshidi, A. Kazemi, Developing a New ELECTRE Method with Interval Data in Multiple Attribute Decision Making Problems, Journals of Applied Sciences, 8(22), 2008, pp. 4017-4028.
  2. ANDREICA, M. E., M. I. ANDREICA, N. CĂTĂNICIU, Multidimensional Data Structures and Techniques for Efficient Decision Making, Proc. of the 10th WSEAS International Conference MCBE’09, 2009, pp. 249-254.
  3. ANDREICA M. E., I. DOBRE, M. ANDREICA, B. NIŢU, R. ANDREICA, A New Approach of the Risk Project from Managerial Perspective, Ec. Computation and Ec. Cybernetics Studies and Research Journal, vol. 42, no. 1-2 / 2008, pp. 121-130.
  4. CHEN, C. T., W. Z.HUNG, A New Decision-Making Method for Stock Portfolio Selection Based on Computing with Linguistic Assessment, Journal of Applied Mathematics and Decision Sciences Volume, 2009.
  5. JAHANSHAHLOO, G. R., F. H. LOTFI, M. IZADIKHAH, An Algorithmic Method to Extend TOPSIS for Decision-making Problems with Interval Data, Applied Mathematics and Computation 175 – 2006, pp. 1375-1384.
  6. LOTFI, F. H., R. FALLAHNEJAD, Imprecise Shannon’s Entropy and Multi Attribute Decision Making, Entropy, 2010, 12, pp. 53-62.
  7. RESTEANU, C., M. SOMODI, M. ANDREICA, E. MITAN, Distributed and Parallel Computing in MADM Domain using the OPTCHOICE Software, Proc. of the 7th WSEAS Intl. Conf. on Applied Computer Science, 2007, pp. 376-384.
  8. STOICA, M., D. NICOLAE, M. A. UNGUREANU, A. ANDREICA, M. E. ANDREICA, Fuzzy Sets and Their Applications, Proc. WSEAS Intl. Conf. on Math. and Comp. in Business. and Econ., 2008, pp. 197-202.
  9. YE, F., Y. N. LI, Group Multi-attribute Decision Model to Partner Selection in the Formation of Virtual Enterprise under Incomplete Information, Expert Systems with Applications, 36, 2009, pp. 9350-9357.
  10. RESTEANU, C., F. G. FILIP, et al., On Optimal Choice Problem Solving, Proc. of IEEE International Conference on Systems, Man and Cybernetics – Information, Intelligence and Systems, vols 1-4, Oct 14-17, Beijing, China, 1996, pp. 1864-1869.
  11. RĂDULESCU M., C.-Z. RĂDULESCU, G. ZBĂGANU, Asset Allocation Models in Discrete Variable, Studies in Informatics and Control, vol 18 – 1, 2009, pp. 63-70.
  12. RESTEANU, C., F G. FILIP, C. IONESCU, et al., Knowledge-based Simulation in Multiattribute Decision Making, Proc. of. EUROSIM Conference, Vienna Austria, Sep 11-15, 1995, pp. 1271-12.

https://doi.org/10.24846/v19i3y201005