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CAST: Using neural networks to improve trading systems based on technical analysis by means of the RSI financial indicator

Authors :
Rodríguez-González, Alejandro
García-Crespo, Ángel
Colomo-Palacios, Ricardo
Guldrís Iglesias, Fernando
Gómez-Berbís, Juan Miguel
Source :
Expert Systems with Applications. Sep2011, Vol. 38 Issue 9, p11489-11500. 12p.
Publication Year :
2011

Abstract

Abstract: Stock price predictions have been a field of study from several points of view including, among others, artificial intelligence and expert systems. For short-term predictions, the technical indicator relative strength indicator (RSI) has been published in many papers and used worldwide. CAST is presented in this paper. CAST can be seen as a set of solutions for calculating the RSI using artificial intelligence techniques. The improvement is based on the use of feedforward neural networks to calculate the RSI in a more accurate way, which we call the iRSI. This new tool will be used in two scenarios. In the first, it will predict a market – in our case, the Spanish IBEX 35 stock market. In the second, it will predict single-company values pertaining to the IBEX 35. The results are very encouraging and reveal that the CAST can predict the given market as a whole along with individual stock pertaining to the IBEX 35 index. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09574174
Volume :
38
Issue :
9
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
60379799
Full Text :
https://doi.org/10.1016/j.eswa.2011.03.023