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) |
Appears in Collections: | Articles / Άρθρα |
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