A Mamdani Fuzzy System with Multivariate Analysis and Weighted Aggregation for Precision Stock Investments Decisions -An AI Approach
Nirmala M S , Lata Kulkarni , Jyothi N M
DOI: 10.5110/77. 1041 Page: 06-26 Vol: 18 Issue: 09 Year: 2023
This paper introduces a decision support system for stock trading, employing Fuzzy IF-THEN Rules. The system leverages three crucial linguistic variables as input parameters: Price-to-Earnings Ratio (PE), Earnings per Share (EPS), Price-to-Book Ratio (PB). Its primary objective is to aid investors in making rational decisions regarding their stock investments, with the goal of maximizing profits in the stock market—a notably intricate and challenging environment. To simplify and enhance decision-making for investors in this complex realm, this study harnesses Artificial Intelligence (AI) through the application of Fuzzy Logic (FL). The stock Investment decider is built by building Mamdani Type 2 Fuzzy Logic System using Mat Lab. Numerous prior research efforts have demonstrated the efficacy of FL in navigating the intricacies of stock trading environments. The study rigorously evaluates all the fuzzy rules through the utilization of a Fuzzy Inference System implemented in MATLAB. This comprehensive approach ensures that the proposed system’s effectiveness is thoroughly assessed and validated.
Fuzzy logic, Mamdani Fuzzy type -2, MATLAB, crisp values, stock investment decision
Received: 12 October 2023
Accepted: 23 October 2023
Published: 01 November 2023