投资组合选择的一种模糊决策方法

针对带有V-型交易费用的半绝对偏差风险函数投资组合问题,利用模糊决策理论,提出了一种新的投资收益目标水平和投资风险目标水平心理满意度的非线性隶属函数,并将满足非线性满意程度的投资组合选择模型转化为线性规划模型,证明了两者的等价性,最后通过实例说明了所建模型的可行性与有效性.     

基于偏好可能性均值的模糊投资组合模型及实证分析

本文通过客观模糊频数统计法,将证券投资的不确定收益用模糊数来表达,并利用模糊数的可能性均值将模糊收益清晰化,以及采用半绝对偏差函数来度量证券投资的风险,考虑证券换手率约束,构建基于偏好可能性均值—半绝对偏差投资组合模型,并对所建模型进行实证分析.     

离散线性投资组合模型的分枝定界算法

本文提出了一类新的带整数交易手数和凹型交易费用的均值绝对偏差模型(MAD)和极大极小投资组合模型(Minmax),并给出了离散模型的分枝定界算法.我们分别用随机产生的数据和Nasdaq股票市场的真实数据进行了数值实验,数值分析表明在一定的收益水平下均值绝对偏差离散模型风险控制上优于极大极小投资组合离散模型,而计算效率上极大极小投资组合离散模型优于期望绝对偏差离散模型.     

具有熵约束的多阶段均值—绝对偏差模糊投资组合决策

文章运用可能性绝对偏差和比例熵分别度量风险和分散化程度,提出了具有风险控制和线性交易成本的终期财富最大化的多阶段模糊投资组合模型。运用可能理论,将该模型转化为显示的非线性动态优化问题。由于投资过程存在交易成本,上述模型为具有路径依赖性的动态优化问题。文章提出了前向动态规划方法求解。最后, 通过实证研究比较了不同熵的取值投资组合最优投资比例和最终财富的变化。     

具有交易成本的多阶段M-AAD模糊投资组合优化

考虑交易成本、交易量的阀值约束和熵约束,提出均值-平均绝对偏差(M-AAD)多阶段的模糊投资组合模型。模型中的收益水平由模糊收益的均值确定,其风险水平由模糊收益的绝对偏差确定,熵度量投资组合的多样化程度。由于存在交易成本,该模型是一个具有路径依赖性的动态优化问题。提出离散近似迭代法求解。最后,以具体的算例比较不同熵约束下最优投资组合策略,并验证模型的算法和有效性。     

基于最小交易量和交易费用的多阶段模糊投资组合

考虑了在摩擦市场下的多阶段模糊投资组合模型,基于半绝对方差风险函数,建立了带有最小交易量和交易费用限制的收益最大化多阶段模糊投资组合模型.利用绝对值函数的性质,将模型转化为混合整数线性规划形式,并通过实例验证了模型的可行性,最后对模型与基于可能性均值和可能性方差的多阶段模糊投资组合模型进行了对比,分析了模型的优越性,并验证了模型的可行性.     

带有模糊系数的投资组合模型研究

在证券市场,由于各种不确定因素的存在,证券的预期收益率是难以精确估算的。本文采用模糊数来处理不确定性,提出了一种基于模糊收益率的投资组合模型。为度量投资组合的风险,将绝对偏差扩展到模糊情形。通过引入模糊数绝对值的概念和不等关系的两种占优准则,将该模型转化为相应的确定性线性规划问题,投资者可根据自己的主观态度选择参数和投资策略。最后用一个具体例子验证了模型的合理性和有效性。     

半绝对偏差投资组合模型构建及其应用

通过对模糊隶属函数以及基金投资组合基本模型的适当变形,构建了带交易费及流动性约束的极大极小-半绝对偏差投资组合模型.选取5支证券,依据2008年全年的数据作为样本数据,按投资者的不同偏好得出不同的最优投资策略,并对几种情形进行了对比,结果显示此模型能很好地反映出投资者的主观意愿,具有很好的灵活性.     

基于犹豫模糊语言环境的投资组合优化研究

跟传统模糊投资组合相比,基于犹豫模糊语言环境的投资组合不仅可以使用自然语言对金融资产及其不确定程度进行评价,还可以避免评价过程中信息的丢失。本文根据犹豫模糊语言投资组合综合评价系统,对不同金融产品计算得分。通过设置不同的语言尺度函数的参数值及犹豫模糊语言优化模型的临界值,针对激进型、稳健型和保守型三类投资者分别提出了收益最大化和风险最小化犹豫模糊语言投资组合模型,对建立的非线性模型进行求解,得到犹豫模糊语言投资组合的最优解。最后,用数值仿真验证了模型的合理性和有效性。     

可信性均值-绝对偏差投资组合优化

为了度量金融市场的不确定性,本文引入了模糊变量。假设资产收益率为模糊数,分别运用可信性均值和可信性绝对偏差度量投资组合的收益与风险。考虑到投资者偏好,分别提出了以收益最大化的均值-绝对偏差优化模型和以风险最小化的优化模型。基于可信性理论,将上述模型转化为线性规划问题,并运用旋转算法求解。通过实证研究,证明了该算法的有效性,并比较了两个模型在实际投资决策过程中的效率。结果表明,以收益最大化的均值-绝对偏差优化模型效率优于风险最小的优化模型。     

Portfolio rebalancing model with transaction costs based on fuzzy decision theory

The fuzzy set is one of the powerful tools used to describe an uncertain environment. As well as quantifying any potential return and risk, portfolio liquidity is taken into account and a linear programming model for portfolio rebalancing with transaction costs is proposed. The level of return that an investor might aspire to, the risk and the liquidity of portfolio are vague in an uncertain financial environment. Considering them as fuzzy numbers, we propose a portfolio rebalancing model with transaction costs based on fuzzy decision theory. An example is given to illustrate the behavior of the proposed model using real data from the Shanghai Stock Exchange.     

随机模糊的等比例-最小方差投资组合优化研究

Markowitz的均值-方差模型在投资组合优化中得到了广泛的运用和拓展,其中多数拓展模型仅局限于对随机投资组合或模糊投资组合的研究,而忽略了实际问题同时包含了随机信息和模糊信息两个方面。本文首先定义随机模糊变量的方差用以度量投资组合的风险,提出具有阀值约束的最小方差随机模糊投资组合模型,基于随机模糊理论,将该模型转化为具有线性等式和不等式约束的凸二次规划问题。为了提高上述模型的有效性,本文以投资者期望效用最大化为压缩目标对投资组合权重进行压缩,构建等比例-最小方差混合的随机模糊投资组合模型,并求解该模型的最优解。最后,运用滚动实际数据的方法,比较上述两个模型的夏普比率以验证其有效性。     

Multiobjective expected value model for portfolio selection in fuzzy environment

In this paper, we propose a credibilistic framework for portfolio selection problem using an expected value multiobjective model with fuzzy parameters. We consider short term return, long term return, risk and liquidity as key financial criteria. A solution procedure comprising fuzzy goal programming and fuzzy simulation based real-coded genetic algorithm is developed to solve the model. The proposed solution approach is considered advantageous particularly for the cases where the fuzzy parameters of the problem may assume any general functional form. An empirical study is included to illustrate the usefulness of the proposed model and solution approach in real-world applications of portfolio selection.     

A chance-constrained portfolio selection model with risk constraints

The paper by Huang [Fuzzy chance-constrained portfolio selection, Applied Mathematics and Computation 177 (2006) 500-507] proposes a fuzzy chance-constrained portfolio selection model and presents a numerical example to illustrate the proposed model. In this note, we will show that Huang’s model produces optimal portfolio investing in only one security when candidate security returns are independent to each other no matter how many independent securities are in the market. The reason for concentrative solution is that Huang’s model does not consider the investment risk. To avoid concentrative investment, a risk constraint is added to the fuzzy chance-constrained portfolio selection model. In addition, we point out that the result of the numerical example is inaccurate.     

Fuzzy portfolio model with different investor risk attitudes

We propose a fuzzy portfolio model designed for efficient portfolio selection with respect to uncertain or vague returns. Although many researchers have studied the fuzzy portfolio model, no researcher has yet attempted a behavioral analysis of the investor in the fuzzy portfolio model. To address this problem, we examined investor risk attitudes—risk-averse, risk-neutral, or risk-seeking behaviors—to discover an efficient method for fuzzy portfolio selection. In this study, we relied on the advantages of possibilistic mean–standard deviation models that we believed would fit the risk attitudes of investors. Thus, we developed a fuzzy portfolio model that focuses on different investor risk attitudes so that fuzzy portfolio selection for investors who possess different risk attitudes can be achieved more easily. Finally, we presented a numerical example of a portfolio selection problem to illustrate ways to address problems presented by a variety of investor risk attitudes.     

A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs

This paper deals with a multi-period portfolio selection problem with fuzzy returns. A possibilistic mean-semivariance-entropy model for multi-period portfolio selection is presented by taking into account four criteria viz., return, risk, transaction cost and diversification degree of portfolio. In the proposed model, the return level is quantified by the possibilistic mean value of return, the risk level is characterized by the lower possibilistic semivariance of return, and the diversification degree of portfolio is measured by the originally presented possibilistic entropy. Furthermore, a hybrid intelligent algorithm is designed to obtain the optimal portfolio strategy. Finally, the comparison analysis between the possibilistic entropy model and the proportion entropy model is provided by two numerical examples to illustrate the efficiency of the proposed approaches and the designed algorithm.     

基于极大模理想点法的投资组合决策模型分析

基于马克维茨投资组合模型的均值一方差理论,构建一种投资组合收益和风险在一定范围的双目标线性模糊优化模型,并尝试采用极大模理想点法来求解该模型．最后,给出一实际算例,对一具体投资组合模型进行研究,结果表明：本文所采用的极大模理想点法是可行的、有效的;本文所采用的算法比已有文献给出的模糊线性规划法具有更加广泛意义的优化结果．     

一种新的梯形模糊数间距离及在投资组合模型选择中的应用

给出一种新的模糊数间的距离公式.用新定义的距离公式来度量给定优先资产的条件下投资组合的分散度.用可能性均值度量投资组合的收益,可能性半方差度量投资组合的风险,在收益和风险满足一定的条件下构造分散度模型.通过实例分析,给出的方法不仅分散度更好,而且资产分配多元化程度更高,计算也更简单.