Discovery of technical analysis patterns

In this paper our method of discovering data sequences in the time series is presented. Two major approaches to this topic are considered. The first one, when we need to judge whether a given a series is similar to any of the known patterns and the second one when there is a necessity to find how many times within a long series a defined pattern occurs. In both cases the main problem is to recognize pattern occurrence(s), but the distinction is essential because of the time frame within which identification process is carried on. The proposed method is based on the usage of multilayered feed-forward neural network. Effectiveness of the method is tested in the domain of financial analysis but its adaptation to almost any kind of sequences data can be done easily.