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作 者:肖莘玥 陈峙臻 XIAO Xinyue;CHEN Zhizhen(Business School,University of Greenwich,London SE109LS,UK)
出 处:《南昌工程学院学报》2024年第6期91-98,共8页Journal of Nanchang Institute of Technology
摘 要:本文旨在为投资组合理论中的智能金融优化研究提出一种基于背包模型的优化求解途径和总体框架。基于对投资组合理论研究的考察与分析,论证给出投资组合理论研究向智能金融优化方向发展的必要性,提出投资组合理论研究的整体架构和智能金融优化的新方向,进而围绕经典金融优化、智能金融优化和行为金融学进行对比分析和阐释说明。论述智能金融优化在整体层面上的优越性,即把基于优化求解的经典金融优化与基于协调求解的行为金融学结合起来,各取所长,形成综合优势。从资源分配的视角阐述投资组合理论研究向智能金融优化方向发展转向的可行性,借助资源分配视角的连接关系和纽带作用,建立起投资组合问题与背包问题数学模型之间的映射关系,使得投资组合问题可以转化为背包模型这样的组合优化模型进行求解。从操作实现层面阐述可用于解决投资组合问题的多种类型的背包模型,针对求解背包模型的元启发式算法进行分类说明,可为运用背包模型与算法解决投资组合问题提供有益的借鉴和有效的指导。This paper aims to propose a knapsack model based on optimization approach and overall framework for the new direction of intelligent financial optimization in portfolio theory.Based on the investigation and analysis of portfolio theory research,this paper demonstrates the necessity of portfolio theory research to develop in the direction of intelligent financial optimization,puts forward the overall framework of portfolio theory research and the new direction of intelligent financial optimization,and compares and explains the classical financial optimization,intelligent financial optimization and behavioral finance.It points out that intelligent financial optimization synthesizes the advantages of classical financial optimization based on optimal solution and behavioral finance based on coordinated solution.From the perspective of resource allocation,this paper expounds the feasibility of portfolio theory research to develop intelligent financial optimization.With the help of connection and linkage from the perspective of resource allocation,a mapping relationship between the mathematical model of portfolio problem and the knapsack problem is established,so that the former can be transformed into a combinatorial optimization model such as the knapsack model for solving.The knapsack model and the meta-heuristic algorithm for solving the portfolio problem are described from the operational implementation level,which can provide reference for solving the portfolio problem with knapsack model and algorithm.
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