Corporate financial analysis with efficient logistic regressions and hybrids of neuro-genetic networks
Authors: Loukeris, Nikolaos 
Issue Date: 1-Jul-2007
Conference: 11th WSEAS International Conference on Computers, 26-28 July 2007, Crete Island, Greece 
Book: Proceedings of the 11th WSEAS International Conference on Computers 
Keywords: Logistic regressions, Hybrid systems, Neural networks, Genetic algorithms, Financial analysis
Abstract: 
Financial institutions, portfolio managers and investors demand strong analytical methods of corporate finance to maintain lucrative investment portfolios. The volatility of stock prices, affected partially by the vast accounting data and the level of efficiency in the financial market require support by accurate decision making to increase the value of investments. Logistic regressions in Econometrics achieve significant results in financial analysis of companies, whilst Artificial Intelligence-as nonlinear regression systems-provides efficient corporate financial evaluations in longer computation time.
ISBN: 978-960-8457-95-9
URI: https://uniwacris.uniwa.gr/handle/3000/2217
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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