الفهرس يوجد فقط 14 صفحة متاحة للعرض العام
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المستخلص
ABSTRACT Mainly, because of the limited successes of Operations Research’s Traditional Techniques in resolving Portfolio Selection Problem (PSP) with multiple reasoning financial goals and revolutionary ideas from the knowledge to construct a Decision Support System (DSS) for Decision Makers (DMs), this work has focus on how further the ability of implementing Knowledge based DSS for the portfolio problem. For this reason, there was a need of some effective portfolio mathematical model considering fuzzy returns of future scenarios has adopted different equity markets in a form of Fuzzy Multi-scenario Main-Variance (M-V) portfolio selection model and an interactive method have been developed for solving Fuzzy Non-Linear Multi-Scenario (FNLMS) Portfolio Problems. Portfolio Selection is how to configure a variety of equities positions to best meet the decision makers (DMs) risk and return trade-off. In 1952, Markowitz the founder of modern portfolio theory assumed DMs are risk averse, and variance is a measure for investment risk a Mean-Variance portfolio selection MV-Model was established by Markowitz who assumed it is necessary to calculate the covariance between the risky assets. However, when trying to resolve a real portfolio, a lot of computational difficulties had been found. DMs can efficiently allocate their capitals through potential portfolio diversification to
include a number of multi-national risky equities that have several fuzzy returns or shortterm holding periods. The fuzzy returns result in conflicting future alternatives. If equity returns related to one scenario are one of those conflicting alternatives, then a multi criteria mathematical portfolio program can be developed which considers different scenarios in order to maximize the portfolio future returns and arrive at the net capital gain. This is to be achieved through an equity portfolio aiming to reach ultimate goal of preserving and generating wealth from a number of equity markets that the DM selects from. In this research, we developed a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz’s M-V model we developed a Fuzzy Mixed Integer Multi-Scenario Nonlinear Programming Problem (FMIMSNLP) to maximize the investors’ future gains on equity markets, and optain the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.We focus on multi-scenario integer nonlinear programming portfolio problems having fuzzy parameters in the objective function and in the constraints. The set of α-Pareto optimal solutions is determined for the problem under consideration together with the corresponding stability set of the first kind (SSKl). In addition, an algorithm is described to solve the formulated model. Since we have developed a model that depends on fuzzy logic, DMs need to acquire the knowledge from expertise, and determine what kind of equities, industrial categories, and from which capital markets to invest in. However, for the purpose of downsizing the set of equities to use in the model, we are in need of developing a Knowledge base DSS that uses rule-based systems with expert explanation capabilities as the tool for decision support. The central part of the DSS is a model-base containing a comprehensive set of computational and analytical models that are managed by a Model-Base Management System. While the rule of the knowledge base is due to the equity selection.