Robust genetic network programming on asset selection

Victor Parque, Shingo Mabu, Kotaro Hirasawa

研究成果: Conference contribution

抄録

Financial innovation is continuously testing the asset selection models, which are the key both for building robust portfolios and for managing diversified risk. This paper describes a novel evolutionary based scheme for the asset selection using Robust Genetic Network Programming(r-GNP). The distinctive feature of r-GNP lies in its generalization ability when building the optimal asset selection model, in which several training environments are used throughout the evolutionary approach to avoid the over-fitting problem to the training data. Simulation using stocks, bonds and currencies in developed financial markets show competitive advantages over conventional asset selection schemes.

本文言語English
ホスト出版物のタイトルTENCON 2010 - 2010 IEEE Region 10 Conference
ページ1021-1026
ページ数6
DOI
出版ステータスPublished - 2010 12 1
イベント2010 IEEE Region 10 Conference, TENCON 2010 - Fukuoka, Japan
継続期間: 2010 11 212010 11 24

出版物シリーズ

名前IEEE Region 10 Annual International Conference, Proceedings/TENCON

Other

Other2010 IEEE Region 10 Conference, TENCON 2010
国/地域Japan
CityFukuoka
Period10/11/2110/11/24

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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