A Hybrid Fuzzy-Neural Model for Pattern Detection to Predict the Egyptian Stocks Price Movement Direction

• Main Author: Badr ElDin Abeer
• Format: Article
• Language: English
• Published: EDP Sciences 2019-01-01
• Series: MATEC Web of Conferences
• Online Access: https://www.matec-conferences.org/articles/matecconf/pdf/2019/41/matecconf_cscc2019_03015.pdf

In this paper, a hybrid fuzzy-neural system for Egyptian stocks price prediction is proposed. The model helps choosing the right stock mixture with the highest profit within a certain risk factor. A hybrid fuzzy-neural system is applied to significantly save effort and time of portfolio managers. The model increases the individual investors’ local market understanding by providing buy and sells signals that reflect market sentiments, breaking news and technical analysis expectations. An implemented system of the proposed model has demonstrated a promising performance of the applied test datasets containing 100 Stock Symbols over the past 9 years (January 2009-July 2018). The prediction accuracy of the model is computed by comparing the applied system predicted results against the actual results of the Egyptian stock market during the test period.