Can fuzzy logic accurately predict stock market behavior? This paper explores the application of fuzzy logic engineering tools in finance, particularly in technical analysis. It presents a new method that translates technical analysis indicators used by experts into inputs for a fuzzy logic system. The study aims to create an optimized, computerized model for evaluating stock price movements. Central to the approach is the use of human psychology to forecast behavior when specific price patterns emerge. The system's performance is gauged by comparing its output with actual stock price movements. The research offers a compelling integration of human sentiment and technical indicators. Ultimately, the research demonstrates that this innovative stock evaluation method surpasses market performance, positioning it as a valuable tool in the technical analysis domain. Its flexibility further enhances its appeal, paving the way for more accurate and adaptable financial models. Keywords integrated include: fuzzy logic, stock evaluation, technical analysis, financial markets.
Published in the International Journal of Theoretical and Applied Finance, this paper fits squarely within the journal's focus on innovative financial methodologies. By applying fuzzy logic to stock evaluation, it aligns with the journal's emphasis on theoretical frameworks with practical applications, contributing to the broader understanding of market dynamics.