Guided genetic relation algorithm on the adaptive asset allocation

Victor Parque, Shingo Mabu, Kotaro Hirasawa

研究成果: Conference contribution

抜粋

One important question in investment is how to build adaptive asset allocation strategies, i.e. portfolios which adjust to the changing conditions of the economic environments. This paper proposes an evolutionary approach for the adaptive asset allocation by using Guided Genetic Relation Algorithm(GRA-g), whose main role is to model and evolve the optimal adaptive portfolio structures. Simulations using asset classes in USA show that the proposed scheme offers competitive economic advantages. This paper suggests that the use of evolutionary computing techniques is an excellent tool to aid the asset allocation, whose advantages imply the usefulness to manage the exposure to risk.

元の言語English
ホスト出版物のタイトルSICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
出版者Society of Instrument and Control Engineers (SICE)
ページ173-178
ページ数6
ISBN(印刷物)9784907764395
出版物ステータスPublished - 2011 1 1
イベント50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
継続期間: 2011 9 132011 9 18

出版物シリーズ

名前Proceedings of the SICE Annual Conference

Other

Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011
Japan
Tokyo
期間11/9/1311/9/18

ASJC Scopus subject areas

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

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  • これを引用

    Parque, V., Mabu, S., & Hirasawa, K. (2011). Guided genetic relation algorithm on the adaptive asset allocation. : SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts (pp. 173-178). [6060597] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE).