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基于QPSO和MATLAB优化资金投资组合
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作者 李盘荣 《四川理工学院学报(自然科学版)》 CAS 2008年第5期118-120,共3页
量子粒子群优化算法(QPSO)是一种基于粒子群优化算法(PSO)的进化算法,它收敛速度快、规则简单、易于编程实现;Matlab是国际控制界公认的标准计算软件。采用QPSO对资金组合投资的多目标问题进行优化,使用Matlab编程,解决了传统方法难以... 量子粒子群优化算法(QPSO)是一种基于粒子群优化算法(PSO)的进化算法,它收敛速度快、规则简单、易于编程实现;Matlab是国际控制界公认的标准计算软件。采用QPSO对资金组合投资的多目标问题进行优化,使用Matlab编程,解决了传统方法难以解决的问题,仿真实验表明采用本方法能对资金投资组合问题提出较好的优化决策。 展开更多
关键词 粒子群优化算法 量子粒子群优化算法 资金投资组合 组合优化
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Investor's Portfolio Allocation by Financial Asset Classes Using Fuzzy Logic-Based Approach in Decision Support System 被引量:1
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作者 Andrius Jurgutis Rimvydas Simutis Ausrine Jurgutiene 《Computer Technology and Application》 2011年第10期757-764,共8页
The paper present the fuzzy logic expert system called MADSYS for an investor's portfolio allocation by financial asset classes. MADSYS system will be used in the interface agent (agents) of multi-agent investment ... The paper present the fuzzy logic expert system called MADSYS for an investor's portfolio allocation by financial asset classes. MADSYS system will be used in the interface agent (agents) of multi-agent investment management information system. One of the principal tasks of the multi-agent system is to help an investor to make investment decisions and to provide appropriate investment proposals according to the investor's profile. From MADSYS depends a lot of things, namely the multi-agent investment management information system accuracy, proposed investment decisions, the right portfolio allocation of financial assets, reliability and investor satisfaction. The usage of MADSYS system in the multi-agent system makes it more intellectual, i.e. the system will be able to adjust automatically to the changing of investor profile. The MADSYS system may be tried online at the following address:www.sprendimutechnologij os.lt/webapp. 展开更多
关键词 Fuzzy logic portfolio allocation multi-agents system.
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MAXIMUM PRINCIPLE FOR FORWARD-BACKWARD STOCHASTIC CONTROL SYSTEM WITH RANDOM JUMPS AND APPLICATIONS TO FINANCE 被引量:13
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作者 Jingtao SHI·Zhen WU School of Mathematics,Shandong University,Jinan 250100,China. 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2010年第2期219-231,共13页
Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both dif... Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form. 展开更多
关键词 Forward-backward stochastic control system maximum principle Poisson random measure recursive utility stochastic optimal control.
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