FUZZY INFERENCE SYSTEM FOR INVESTMENT VALUE ASSESSMENT BASED ON HISTORICAL DATA
DOI:
https://doi.org/10.17770/etr2024vol2.8025Keywords:
fuzzy inference system, investment value, membership functionAbstract
The analysis of financial parameters is of fundamental importance when planning one or another investment in shares of a given company. It is important for such an analysis to consider some basic numerical parameters such as: annual revenue growth for the last few years, gross, operating, and net profit margins, price/earnings ratio, current price, average annual price, and other historical data for analysis. In this research, an investment decision-making approach based on fuzzy logic is proposed, which evaluates various aspects of a given company's activity. Mamdani method and the fuzzy logic toolset in MATLAB were used. A set of fuzzy rules forms the basis of the investment evaluation system and determines the investment type recommendation, depending on the financial data provided. Simulation experiments with different inputs prove the correct approach and the adequate solutions that can be obtained. The precise set of input variables and well-thought-out logical rules can achieve a reduction in risks for specific investment intentions.
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