Optimization of Bank Portfolio Investment Decision Considering Resistive Economy

Roxana Fekri (), Maghsoud Amiri (), Rasoul Sajjad () and Ramin Golestaneh ()
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Roxana Fekri: Department of Industrial Engineering, Payamenoor University
Maghsoud Amiri: Faculty of Management & Accounting, Allameh Tabatabaei University
Rasoul Sajjad: Department of Financial Engineering, University of Science and Culture
Ramin Golestaneh: Department of Industrial Engineering, Payamenoor University

Journal of Money and Economy, 2016, vol. 11, issue 4, 375-400

Abstract: Increasing economy's resistance against the menace of sanctions, various risks, shocks, and internal and external threats are one of the main national policies which can be implemented through bank investments. Investment project selection is a complex and multi-criteria decision-making process that is influenced by multiple and often some conflicting objectives. This paper studies portfolio investment decisions in Iranian Banks. The main contribution of this paper is the creation of a project portfolio selection model that facilitates how Iranian banks would make investment decisions on proposed projects to satisfy bank profit maximization and risk minimization, while focus on national policies such as Resistance Economy Policies. The considered problem is formulated as a multi-objective integer programming model. A framework called Multi-Objective Electromagnetism-like (MOEM) algorithm, is developed to solve this NP-hard problem. To further enhance MOEM, a local search heuristic based on simulated annealing is incorporated in the algorithm. In order to demonstrate the efficiency and reliability of the proposed algorithm, a number of test are performed. The MOEM results are compared with two well-known multi-objective genetic algorithms in the literature, i.e. Non-dominated Sorting Genetic Algorithm (NSGA-II) and Strength Pareto Evolutionary Algorithm (SPEA-II) based on some comparison metrics. Also, these algorithms are compared with an integer linear programming formulation for small instances. Computational experiments indicate the superiority of the MOEM over existing algorithms.

Keywords: Project Portfolio Selection; Bank Investment; Resistive Economy; Multi-objective optimization; Electromagnetism-like algorithm; ɛ-constraint method. (search for similar items in EconPapers)
JEL-codes: C61 G11 (search for similar items in EconPapers)
Date: 2016
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