درخت حوزه‌های تخصصی

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.

The literature on Foreign Direct Investment (FDI) has advanced several explanations of the links between financial market developments and FDI inflows across developing as well as developed countries. Empirical literature show that financial market development reduces informational frictions and improves resource allocation more efficiently. Also, financial systems are important for both productivity and development, where a better developed financial systems can receive more benefit from FDI and its inflows depend on condition of host country and their characteristics. The paper tries to examine and compare the relationship between foreign direct investment and local financial market development across oil exporting and importing emerging market economies by using VAR panel model during 1970-2014. The results show that there is a relationship between financial market development and FDI and financial development indicators are causality for FDI, particularly banking system indicators. Moreover, banking system is more important and efficient in oil importing countries than oil exporting countries to attract FDI from abroad. JEL Classification: F21, P45, O16, G1.