The Egyptian Stock Market Return Prediction: A Genetic Programming Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{El-Telbany:2004:ICEEC,

• author = "Mohammed E. El-Telbany",
• title = "The {Egyptian} Stock Market Return Prediction: A Genetic Programming Approach",
• booktitle = "International Conference on Electrical, Electronic and Computer Engineering, ICEEC-04",
• year = "2004",
• editor = "Abdel-Moniem Wahdan and Ahmed Amer and Hani Fikry and Ashraf Salem",
• pages = "161--164",
• address = "Ain Shams University, Cairo, Egypt",
• month = "5-7 " # sep,
• keywords = "genetic algorithms, genetic programming, Application software, Consumer electronics, Data mining, Economic forecasting, Electronic mail, Investments, Neural networks, Predictive models, Stock markets",
• DOI = "doi:10.1109/ICEEC.2004.1374410",
• size = "4 pages",
• abstract = "Applications of learning algorithms in knowledge discovery are promising and relevant area of research. It is offering new possibilities and benefits in real-world applications, helping us understand better mechanisms of our own methods of knowledge acquisition. Genetic programming as learning algorithm posses certain advantages that make it suitable for forecasting and mining the financial data. Especially the stock time series have a large number of specific properties that together makes the prediction task unusual. This paper presents the results of using genetic programming to forecast the Egyptian Sock Market return. Experiments results demonstrate the capability of genetic programming to predict accurate results, comparable to traditional machine learning algorithms i.e., neural networks.",
• notes = "details from ieee",

}

Genetic Programming entries for Mohammed E El-Telbany

Citations