Publication:
Improving trading saystems using the RSI financial indicator and neural networks.

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ISSN: 1611-3349 (Online)
ISSN: 0302-9743 (Print)
ISBN: 3-642-15036-5
ISBN: 978-3-642-15036-4
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2010-08-12
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Springer
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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.
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Proceedings of: 11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010), 20 August-3 September 2010, Daegu (Korea)
Keywords
Neural networks, RSI financial indicator
Bibliographic citation
Byeong-Ho Kang et al. (eds.), Knowledge management and acquisition for smart systems and services. 11th International Workshop, PKAW 2010, Daegu, Korea, August 20 - September 3, 2010 (pp. 27-37). Proceedings. Berlin: Springer, 2010