Improving Trading Systems Using the RSI Financial Indicator and Neural Networks View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Alejandro Rodríguez-González , Fernando Guldrís-Iglesias , Ricardo Colomo-Palacios , Juan Miguel Gomez-Berbis , Enrique Jimenez-Domingo , Giner Alor-Hernandez , Rubén Posada-Gomez , Guillermo Cortes-Robles

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. More... »

PAGES

27-37

Book

TITLE

Knowledge Management and Acquisition for Smart Systems and Services

ISBN

978-3-642-15036-4
978-3-642-15037-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-15037-1_3

DOI

http://dx.doi.org/10.1007/978-3-642-15037-1_3

DIMENSIONS

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