Stock exchange prediction and portfolio administration by statistics and artificial neural networks

被引：0
|
作者：
Ortiz-Rossains, F [1 ]
Calderón-Aveitua, A [1 ]
Hernández-Gress, N [1 ]
机构：
[1] Inst Tecnoll Estudios Super Monterrey, Monterrey, Mexico
来源：
PROCEEDINGS OF THE 7TH JOINT CONFERENCE ON INFORMATION SCIENCES | 2003年
关键词：
stock exchange; prediction; portfolio administration; PCA; neural networks;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes the techniques used to develop a system capable of modeling the complex relations of the Mexican stock exchange by statistics methods as Principal Component Analysis (PCA) and Artificial Neural Networks (ANN). Finally, portfolio administration is performed via quadratic programming and genetic algorithms (GA). These methodologies constitute an alternative to classic statistical models of regression, variance and mean.
引用
收藏
页码：1157 / 1160
页数：4
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