The Portfolio Heuristic Optimisation System (PHOS)

被引:0
|
作者
N. Loukeris
I. Eleftheriadis
E. Livanis
机构
[1] University of Macedonia,Department of Business Administration
[2] University of Macedonia,Department of Accounting and Finance
来源
Computational Economics | 2016年 / 48卷
关键词
Support vector machines; Genetic algorithms; Portfolio selection; Bankruptcy;
D O I
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中图分类号
学科分类号
摘要
The efficient representation of the accurate corporate value on the stock price is vital to investors and fund managers that desire to optimise the net worth of the overall stock portfolio. Although the efficient market hypothesis sets limits, the practice of markets is an ideal place of manipulation, and corruption on prices. The accounting statements, evaluated by support vector machines and the SVM hybrids under genetic algorithms provide superiority in portfolio selection, on condition. A specific genetic hybrid SVM outperformed all examined SVM models being a powerful tool in financial analysis. We also offer the integrated model of portfolio selection, PHOS.
引用
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页码:627 / 648
页数:21
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