Authors: | Loukeris, Nikolaos Eleftheriadis, Iordanis Livanis, Efstratios |
Issue Date: | 1-Dec-2013 |
Conference: | IEEE International Symposium on Signal Processing and Information Technology, 12-15 December 2013, Athens, Greece |
Book: | Proceedings of the IEEE International Symposium on Signal Processing and Information Technology |
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 optimize the net worth of the overall stock portfolio. Although 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 excellence in portfolio selection. A specific Neuro-genetic Hybrid SVM outperformed all examined SVM models being a powerful tool in financial analysis. |
ISBN: | 978-1-4799-4796-6 |
DOI: | 10.1109/ISSPIT.2013.6781852 |
URI: | https://uniwacris.uniwa.gr/handle/3000/2220 |
Type: | Conference Paper |
Department: | Department of Business Administration |
School: | School of Administrative, Economics and Social Sciences |
Affiliation: | University of West Attica (UNIWA) |
Appears in Collections: | Book Chapter / Κεφάλαιο Βιβλίου |
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