Paper Info
Title
Improving trading systems using the RSI financial indicator and neural networks
Abstract
Trading and Stock Behavioral Analysis Systems require efficient Artificial Intelligence techniques for analyzing Large Financial Datasets (LFD) and have become in the current economic landscape a significant challenge for multi-disciplinary research. Particularly, Trading-oriented Decision Support Systems based on the Chartist or Technical Analysis Relative Strength Indicator (RSI) have been published and used worldwide. However, its combination with Neural Networks as a branch of computational intelligence which can outperform previous results remain a relevant approach which has not deserved enough attention. In this paper, we present the Chartist Analysis Platform for Trading (CAST, in short) platform, a proof-of-concept architecture and implementation of a Trading Decision Support System based on the RSI and Feed-Forward Neural Networks (FFNN). CAST provides a set of relatively more accurate financial decisions yielded by the combination of Artificial Intelligence techniques to the RSI calculation and a more precise and improved upshot obtained from feed-forward algorithms application to stock value datasets.
Year
DOI
Venue
2010
10.1007/978-3-642-15037-1_3
PKAW
Keywords
Field
DocType
improving trading system,neural network,stock behavioral analysis systems,artificial intelligence technique,trading decision support system,feed-forward neural networks,chartist analysis platform,technical analysis relative strength,rsi financial indicator,neural networks,efficient artificial intelligence technique,trading-oriented decision support systems,rsi calculation,feed forward neural network,artificial intelligent,computational intelligence,technical analysis,feed forward,behavior analysis,proof of concept,decision support system
Data mining,Architecture,Computational intelligence,Computer science,Decision support system,Relative strength index,Artificial intelligence,Behavioral analysis,Finance,Artificial neural network,Machine learning,Technical analysis
Conference
Volume
ISSN
ISBN
6232
0302-9743
3-642-15036-5
Citations 
PageRank 
References 
0
0.34
13
Authors
8
Name
Order
Citations
PageRank
Alejandro Rodríguez-González1877.70
Fernando Guldrís-Iglesias200.34
Ricardo Colomo-Palacios361837.20
Juan Miguel Gomez-Berbis4133.96
Enrique Jimenez-Domingo500.68
Giner Alor-Hernandez6549.40
Ruben Posada-Gomez7449.21
Guillermo Cortes-Robles8154.02