Evolving asset portfolios by genetic relation algorithm

Victor Parque*, Shingo Mabu, Kotaro Hirasawa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Global financial development have opened innumerable risks and opportunities for investments. A global view of the portfolio allocation through diversification brings advantages for the risk allocation in investments. In this paper, an asset allocation framework under the return, risk and liquidity considerations is proposed for short term investment using Genetic Relation Algorithm. Simulations using the stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show that the proposed framework is effective and robust. The efficacy of the proposed method is compared against the relevant constructs in finance and computational fields.

Original languageEnglish
Pages (from-to)464-474
Number of pages11
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Issue number5
Publication statusPublished - 2010 Jul


  • Asset allocation
  • Capital allocation
  • Computational finance
  • Portfolio optimization

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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