Improving N Calculation of the RSI Financial Indicator Using Neural Networks
Trading and Stock Behavioral Analysis Systems require efficient Artificial Intelligence techniques fur 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 ((AST,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.
neural networks RSI trading prediction
Alejandro Rodríguez-González Fernando Guldris-Iglesias Ricardo Colomo-Palacios Giner Alor-Hernandez Ruben Posada-Gomez
Computer Science Departmcnt Universidad Carlos Ⅲ de MadridLegancs.Spain Computer Science Department Instituto Tecnologico de Orizaba Orizaba.Mexico
国际会议
重庆
英文
49-53
2010-09-17（万方平台首次上网日期，不代表论文的发表时间）