Exploring the Fuzzy Nature of Technical Patterns of U. S Stock Market

Technical analysis has been a part of financial practice for many decades. One of the most challenging areas in technical analysis is the automatic detection of technical patterns that are similar in the eyes of expert investors. In this paper, we propose a fuzzy logic based approach for technical analysis. By introducing the inter & intra fuzzification into an automatic pattern detection and analysis process, we incorporate human cognitive uncertainty into the technical analysis domain. Using a random sample of U. S. stocks, we find that our approach is able to detect subtle differences within a clearly defined pattern template. Our results suggest that such subtle differences could be a source of controversy surrounding technical analysis. Comparing with existing visual technical pattern analysis approaches, our fuzzy logic based approach offers superior precision in detecting and interpreting the technical patterns.