JACIII Vol.14 No.5 pp. 464-474
doi: 10.20965/jaciii.2010.p0464


Evolving Asset Portfolios by Genetic Relation Algorithm

Victor Parque, Shingo Mabu, and Kotaro Hirasawa

Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 803-0135, Japan

December 3, 2009
March 24, 2010
July 20, 2010
capital allocation, portfolio optimization, asset allocation, computational finance

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.

Cite this article as:
Victor Parque, Shingo Mabu, and Kotaro Hirasawa, “Evolving Asset Portfolios by Genetic Relation Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.14, No.5, pp. 464-474, 2010.
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