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Support Vector Machines Networks to Hybrid Neuro-Genetic SVMs in Portfolio Selection
Department of Business Administration, University of Macedonia, Thessaloniki, Greece
Department of Business Administration, University of Macedonia, Thessaloniki, Greece
- 1 Department of Business Administration, University of Macedonia, Thessaloniki, Greece
- 2 Department of Business Administration, University of Macedonia, Thessaloniki, Greece
Intelligent Information Management·Volume 07 (2015)·Pages 123–129·Published 28 April 2015·DOI10.4236/iim.2015.73011
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Abstract
Corporate net value is efficiently described on its stock price, offering investors a chance to include a potentially surplus value to the net worth of the overall investment portfolio. Financial analysis of corporations extracted from the accounting statements is constantly demanded to support decisions making of portfolio managers. Econometrics and Artificial Intelligence methods aim to extract hidden information from complex accounting and financial data. Support Vector Machines hybrids optimized in their components by Genetic Algorithms provide effective results in corporate financial analysis.
KeywordsSupport Vector MachinesGenetic AlgorithmsCorporate FinanceFinancial Markets
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