Evolving asset selection using genetic network programming

Victor Parque, Shingo Mabu, Kotaro Hirasawa

Research output: Contribution to journalArticle

Abstract

As global financial innovation opens innumerable risks and opportunities, a global view of the asset allocation brings advantages in risk diversification for investments. We propose a novel framework for asset selection under global diversification principles using genetic network programming. Simulations using the stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show that the proposed framework is effective and offers competitive advantages against the conventional methods in finance and computational fields.

Original languageEnglish
Pages (from-to)174-182
Number of pages9
JournalIEEJ Transactions on Electrical and Electronic Engineering
Volume7
Issue number2
DOIs
Publication statusPublished - 2012 Mar

Keywords

  • Asset selection
  • Evolutionary finance
  • Genetic network programming
  • Value and growth

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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