Multi-classifier based on Elliott wave's recognition

Authors:
Eva Volna;Martin Kotyrba;Robert Jarusek
Affiliations:
-;-;-
Venue:
Computers & Mathematics with Applications
Year:
2013

Citing 7
Cited 0

Practical neural network recipes in C++

Practical neural network recipes in C++
Charting patterns on price history

Proceedings of the sixth ACM SIGPLAN international conference on Functional programming
Time Series Analysis: Forecasting and Control

Time Series Analysis: Forecasting and Control
Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach
A computational implementation of stock charting: abrupt volume increase as signal for movement in New York stock exchange composite index

Decision Support Systems - Special issue: Data mining for financial decision making
Time Series Pattern Recognition via SoftComputing

3PGCIC '11 Proceedings of the 2011 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
Classification with Pseudo Neural Networks Based on Evolutionary Symbolic Regression

3PGCIC '11 Proceedings of the 2011 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

Quantified Score

Hi-index	0.09

Visualization

Abstract

This article deals with prediction by means of Elliott wave recognition. Our goal is to find and recognize important Elliott wave patterns which repeatedly appear in the market history for the purpose of prediction of subsequent trader's action. The pattern recognition approach is based on neural networks. We focus on reliability of Elliott wave pattern recognition made by the developed algorithms which also causes the reduction of the calculation costs.