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

authors

  • RODRIGUEZ GONZALEZ, ALEJANDRO
  • GARCIA CRESPO, ANGEL
  • COLOMO PALACIOS, RICARDO
  • GULDRIS IGLESIAS, FERNANDO
  • GOMEZ BERBIS, JUAN MIGUEL

publication date

  • September 2011

start page

  • 11489

end page

  • 11500

issue

  • 9

volume

  • 38

International Standard Serial Number (ISSN)

  • 0957-4174

Electronic International Standard Serial Number (EISSN)

  • 1873-6793

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.