Optimizing Portfolio in the Evolutional Portfolio Optimization System (EPOS)

Nikolaos Loukeris (), Yiannis Boutalis, Iordanis Eleftheriadis and Gregorios Gikas
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Nikolaos Loukeris: Department of Business Administration, University of West Attica, Petrou Ralli & Thivon Avenue, 12241 Athens, Greece
Yiannis Boutalis: Department of Electrical and Computer Engineers, Democritus University of Thrace, 67100 Xanthi, Greece
Iordanis Eleftheriadis: Department of Business Administration, University of Macedonia, Egnatias 156, 54636 Thessaloniki, Greece
Gregorios Gikas: Department of Business Administration, University of West Attica, Petrou Ralli & Thivon Avenue, 12241 Athens, Greece

Mathematics, 2024, vol. 12, issue 17, 1-25

Abstract: A novel method of portfolio selection is provided with further higher moments, filtering with fundamentals in intelligent computing resources. The Evolutional Portfolio Optimization System (EPOS) evaluates unobtrusive relations from a vast amount of accounting and financial data, excluding hoax and noise, to select the optimal portfolio. The fundamental question of Free Will, limited in investment selection, is answered through a new philosophical approach.

Keywords: higher moments; Isoelastic Utility Function; Jordan–Elman networks; recurrent networks; time-lag recurrent networks; MLP; neural networks; genetic algorithms; hybrids; portfolio optimization; Epicurus; Aristotle; logic; Free Will; eudaimonia (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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