In this paper we introduce our method that is able to analyze and recognize Elliott waves in time series. Our method uses an artificial neural network that is adapted by backpropagation. Neural network uses Elliot wave’s patterns in order to extract them and recognize. Artificial neural networks are suitable for pattern recognition in time series mainly because of learning only from examples. There is no need to add additional information that could bring more confusion than recognition effect. Neural networks are able to generalize and are resistant to noise. On the other hand, it is generally not possible to determine exactly what a neural network learned and it is also hard to estimate possible recognition error. They are ideal especially when we do not have any other description of the observed series. This paper also includes experimental results of Elliott waves recognition carried out with our method.
Does anyone know if there is a formal mathematical proof for Elliott Wave Theory?
