The Portfolio Heuristic Optimisation System (PHOS)
Authors: Loukeris, Nikolaos 
Eleftheriadis, Iordanis 
Livanis, Efstratios 
Issue Date: 1-Dec-2016
Journal: Computational Economics 
Volume: 48
Issue: 4
Keywords: Bankruptcy, Genetic algorithms, Portfolio selection, Support vector machines
Abstract: 
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.
ISSN: 1572-9974
0927-7099
DOI: 10.1007/s10614-015-9552-1
URI: https://uniwacris.uniwa.gr/handle/3000/2191
Type: Article
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
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