Modeling Portfolio Optimization based on Fundamental Analysis using an Expert System in the Real Estate Industry

Abstract

Models of decision making optimization in the stock market have been challenged and evaluated by researchers in recent years. Financial and economic knowledge alone will not allow to analyze and facilitate decision making and to determine the appropriate strategy, and one of the most important obstacles in this regard is the complexity of tools and methods of analysis and modeling. The multiplicity of indicators and financial ratios on the one hand and the breadth of data on the other hand are the most important obstacles in the behavioral analysis of financial markets. Accordingly, the present study aims to model the decision-making process in financial markets. In this research, a different approach is presented in conceptual modeling by combining methods and tools of artificial intelligence with financial issues. Based on this, the portfolio will be optimized by extracting appropriate financial ratios considering the effect of time, and then modeling them in a technical expert system assuming a neutral risk investor. In addition to trying to conclude and analyze based on the realities of the stock market fundamental analysis, the system rules and the classification of companies are also distinguished from similar studies based on the dynamics of the stock market. The proposed model has been implemented using the data of companies in the real estate industry during 2007-2018. The results indicate the proper performance of the proposed model and that it has the appropriate flexibility to decide and select a portfolio.