Enhancing global portfolio optimization using Genetic Network Programming

Victor Parque*, Shingo Mabu, Kotaro Hirasawa

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Financial risk has evolved from simple variability of returns in stock trading activities toward interconnected uncertainty factors in our economic systems. In this context, building global portfolios provides a natural mechanism to manage diversified risk between asset classes. This paper proposes a novel framework for the asset selection and allocation under global diversification principles using Genetic Network Programming(GNP) and Genetic Relation Algorithm(GRA). Asset classes such as stocks, bonds and currencies listed in relevant developed financial markets in USA, Europe and Asia are used. The comparison with conventional schemes in finance literature shows competitive advantages of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
PublisherSociety of Instrument and Control Engineers (SICE)
Number of pages6
ISBN (Print)9784907764364
Publication statusPublished - 2010 Jan 1

Publication series

NameProceedings of the SICE Annual Conference


  • Asset allocation
  • Asset selection
  • Diversification
  • Genetic network programming
  • Global portfolio optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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