Title
CAST: Using neural networks to improve trading systems based on technical analysis by means of the RSI financial indicator
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.
Year
DOI
Venue
2011
10.1016/j.eswa.2011.03.023
Expert Syst. Appl.
Keywords
Field
DocType
relative strength indicator,feedforward neural network,neural networks,ibex 35,trading system,technical indicator,rsi financial indicator,artificial intelligence,expert system,technical analysis,generalized feedforward,stock price prediction,relative strength index,spanish ibex,individual stock,stock market,artificial intelligence technique,neural network,artificial intelligent,indexation
Feedforward neural network,Stock price,Computer science,Expert system,Relative strength index,Operations research,Technical indicator,Artificial neural network,Stock market,Technical analysis
Journal
Volume
Issue
ISSN
38
9
Expert Systems With Applications
Citations 
PageRank 
References 
16
0.79
50
Authors
5