Use of neural networks for improvement of the trade systems based on the technical analysis
Abstract
This article is considered as a set of decisions on improvement of the standard technical indicator CCI by use of neural networks. Enhancement is based on use of neural networks of direct distribution for calculation by the CCI more exact method which we called nCCI. This new tool will be used in two situations. First, it will allow to predict the market, in our case of the future for the RTS Index. Secondly, he will predict the value of one company which is included in calculation of this index. In results we will receive the indicator which will be able to predict as the future for the RTS Index, and separate shares which enter calculation of this future will behave.
References
1. C. J., Lee, T. S., & Chiu, C. C. (2009). Financial time series forecasting using independent component analysis and support vector regression. Decision Support Systems, 47(2), 115-125.
2. Majhi, R., Panda, G., & Sahoo, G. (2009). Development and performance evaluation of FLANN based model for forecasting ofstock markets. Expert Systems with Applications, 36(3 Part 2), 6800-6808.
Review
For citations:
Skryabin E.A. Use of neural networks for improvement of the trade systems based on the technical analysis. Entrepreneur’s Guide. 2016;(31):154-161. (In Russ.)
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