Title of article :
CAST: Using neural networks to improve trading systems based on technical analysis by means of the RSI financial indicator
Author/Authors :
Rodrيguez-Gonzلlez، نويسنده , , Alejandro and Garcيa-Crespo، نويسنده , , ءngel and Colomo-Palacios، نويسنده , , Ricardo and Guldrيs Iglesias، نويسنده , , Fernando and Gَmez-Berbيs، نويسنده , , Juan Miguel، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
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.
s 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.
Keywords :
NEURAL NETWORKS , Generalized feedforward , Ibex 35 , Relative strength index , Technical analysis
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications