Optimal Investments in the Portfolio Yield Reactive (PYR) Model

Author:

Loukeris Nikolaos1ORCID,Eleftheriadis Iordanis2

Affiliation:

1. Department of Business Administration, University of West Attica, Petrou Ralli & Thivon 250 Avenue, 12241 Athens, Greece

2. Department of Business Administration, University of Macedonia, Egnatias 156, 54636 Thessaloniki, Greece

Abstract

We evolved our past Portfolio Yield Reactive (PYR) model to provide a competitive system with infiltration of categorical information and fundamentals into advanced higher-order moments that support more objective portfolio selection aided by intelligent computing. The system of the PYR model searches for hidden corporate performance prototypes in big data from accounting and financial statements. The PYR model restricts malicious patterns, such as hoaxes, noise, and manipulation, incorporated into a novel optimal portfolio selection method.

Funder

ELKE Fund of the Universities of Macedonia and West Attica

Publisher

MDPI AG

Reference31 articles.

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2. Sovereign bond yield spillovers in the Euro zone during the financial and debt crisis;Antonakakis;Journal of International Financial Markets, Institutions and Money,2013

3. Satchell, Stephen, and Scowcroft, Alan (2003). Incorporating skewness and Kurtosis in portfolio optimization: A multidimensional efficient set. Advances in Portfolio Construction and Implementation, Butterworth-Heinemann.

4. Bouzerdoum, Abdesselam (, January November). A new class of high-order neural networks with nonlinear decision boundaries. Paper presented at the Sixth International Conference on Neural Information Processing (ICONIP ‘99), Perth, Australia.

5. Bouzerdoum, Abdesselam (, January July). Classification and function approximation using feed-forward shunting inhibitory artificial neural networks. Paper presented at the International Joint Conference on Neural Networks (IJCNN 2000), Como, Italy.

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