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Improving N calculation of the RSI financial indicator using neural networks

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5 Author(s)
Alejandro Rodríguez-González ; Computer Science Department, Universidad Carlos III de Madrid Leganés, Spain ; Fernando Guldris-Iglesias ; Ricardo Colomo-Palacios ; Giner Alor-Hernandez
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Trading and Stock Behavioral Analysis Systems require efficient Artificial Intelligence techniques for analyzing large financial datasets 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 evolutionary computing 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 N value calculation 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 N calculation for RSI and a more precise and improved upshot obtained from feed-forward algorithms application to stock value datasets.

Published in:

Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on

Date of Conference:

17-19 Sept. 2010