A novel, rule-based technical pattern identification mechanism: Identifying and evaluating saucers and resistant levels in the US stock market

摘要

This paper has two main purposes. The first one is the development of a rigorous rule-based mechanism for identifying the rounding bottoms (also known as saucers) pattern and resistant levels. The design of this model is based solely on principles of technical analysis, and thus making it a proper system for eval uating the efficacy of the aforementioned technical trading patterns. The second aim of this paper is mea suring the predictive power of buy-signals generated by these technical patterns. Empirical results obtained from seven US tech stocks indicate that simple resistant levels outperform saucers patterns. Fur thermore, positive statistical significant excess returns are being generated only in first sub-periods of examination. These returns decline or even vanish as the experiment proceeds to recent years. Our find ings are aligned with the results reported by various former studies. The proposed identification mech anism can be used as a component of an expert system to assist academic community in evaluating trading strategies where technical patterns are embedded.