The evolutional portfolio optimization system (EPOS)
Authors: Loukeris, Nikolaos 
Eleftheriadis, Iordanis 
Boutalis, Yannis 
Issue Date: 1-Jul-2017
Conference: World Congress in Computer Science, Computer Engineering and Applied Computing (CSCE 2017), 17 -20 July 2017, Las Vegas, Nevada 
Book: Proceedings of the 2017 International Conference on Artificial Intelligence : ICAI 2017 
Keywords: Higher moments, Hybrid networks, Isoelastic utility function, Jordan-Elman neural networks, Portfolio optimization, Recurrent neural networks, Time-lag recurrent neural networks
Abstract: 
We introduce a new methodology that incorporates advanced higher moments evaluation in a new approach of the Portfolio Selection problem, supported by effective Computational Intelligence models. The Evolutional Portfolio Optimization System (EPOS) extracts hidden patterns out of the numerous accounting data and financial statements filtering misguiding effects such as noise or fraud, offering an optimal portfolio selection method.
ISBN: 9781601324603
URI: https://uniwacris.uniwa.gr/handle/3000/2231
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

CORE Recommender
Show full item record

SCOPUSTM   
Citations

1
checked on Nov 15, 2024

Page view(s)

17
checked on Nov 21, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.