Chartists usually rely on technical indicators to predict trends in time series charts. Although the indicators are precise and most practitioners tend to concur to a large extent on the general meaning of the indicators, it is hard to specify precise thresholds as a basis for deciding on a particular course of action. Probabilistic based approaches do offer recourse for handling such kinds of uncertainty. However, a probabilistic mode of managing uncertainty lacks the flair for capturing the essence of subjectivity that unfortunately (or fortunately) is an inherent trait of human chartists. Fuzzy logic therefore offers a better alternative in this sense. It is further suggested that the fuzzy knowledge can be tuned by means of various existing learning algorithms to accommodate the needs of the chartists
Published in:
Computational Intelligence for Financial Engineering, 1999. (CIFEr) Proceedings of the IEEE/IAFE 1999 Conference on
Date of Conference: 1999