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The Portfolio Risk Analysis Based on Dynamic Particle Swarm Optimization Algorithm

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Modeling Risk Management for Resources and Environment in China

Part of the book series: Computational Risk Management ((Comp. Risk Mgmt))

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Abstract

Risk prediction about investor portfolio holdings can provide powerful test of asset pricing theories. In this paper, we present dynamic Particle Swarm Optimization (PSO) algorithm to Markowitz portfolio selection problem, and improved the algorithm in pseudo code as well as implement in computer program. Furthermore in order to prevent blindness in operation and selection of investment, we tried to make risk least and seek revenue most in investment and so do in the program. As used in practice, it showed great application value.

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Authors and Affiliations

  1. Department of Information Management, ZheJiang University of Finance and Economics, TX, 310018, Hangzhou, China

    Qin Suntao

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  1. Qin Suntao
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Correspondence to Qin Suntao .

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Editors and Affiliations

  1. , Risklab, University of Toronto, Spadina Crescent 1, Toronto, M5S 3G3, Ontario, Canada

    Desheng Dash Wu

  2. , Academy of Mathematics and Systems Scien, Chinese Academy of Sciences, Beijing, 100190, China, People's Republic

    Yong Zhou

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© 2011 Springer-Verlag Berlin Heidelberg

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Suntao, Q. (2011). The Portfolio Risk Analysis Based on Dynamic Particle Swarm Optimization Algorithm. In: Wu, D., Zhou, Y. (eds) Modeling Risk Management for Resources and Environment in China. Computational Risk Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18387-4_55

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