最小风险组合证券非负投资比例系数的确定

研究非负投资比例系数约束条件下,实现风险最小化的组合证券投资问题.应用罚函数法,对最小风险组合证券的非负投资比例系数进行研究.实例表明:这一方法是可行的、有效的.     

熵—证券投资组合风险的一种新的度量方法

本文在研究马科维茨 ( Markowitz)证券投资组合模型的基础上 ,分析了该模型用方差度量风险的缺陷 ,进而提出用熵作为风险的度量方法 ,改进马科维茨 ( Markowitz)证券投资组合模型 ,并建立新的证券投资组合优化模型     

稳定分布的多期投资组合模型及其应用

本文研究了多期投资组合模型的问题.利用非正态稳定分布和参数估计的方法,建立了市场上含一个无风险证券和多个风险证券时多期投资组合的模型,对于描述风险证券所具有的偏态和过度峰态的非正态特征及其股市中的应用起到了作用.     

区间证券多目标投资组合的β模型

基于区间证券组合的系统风险与非系统风险问题,建立一种新的含β约束的区间证券投资组合的多目标优化模型,使得证券组合投资更具柔性,最后,结合实例分析了该模型的现实应用价值.     

限制投资下界的风险证券有效组合模型及算法研究

本文研究了具有投资下界限制的风险证券有限组合决策问题，提出了限制投资下界的风险证券有效组合优化模型，在一定的条件下，给出了风险证券有限组合投资比例的算法及解析表示，最后进行了实际数值计算，结果说明了所给算法是有效和实用的。     

单位收益率风险最小的组合证券投资决策模型

章首先分析了组合证券投资的收益率和风险,根据组合证券投资的亏本概率上界最小的原则,建立了单位收益率风险最小的组合证券投资决策模型,并证明了该模型的有效性。     

投资组合风险的分散化研究

风险是金融投资领域的研究热点问题之下一,投资组合是降低投资风险的有效方法之一。人们在做出投资决策时总是追求在一定收益率下风险最小。本文论述了投资组合收益和风险的数学统计方法,阐明风险可分为系统风险和非系统风险,后者可以通过投资组合分散化。本文还探讨了证券相关性和组合风险之间的关系。最后作了实证分析。     

证券投资组合理论的一种新模型及其应用

马科维茨(Markowitz)以证券收益率的方差作为投资风险的测度建立了组合证券投资模型，本基于熵的概念，在研究马科维茨(Markowitz)证券投资组合模型的基础上，分析了该模型用方差度量风险的不足，进而提出一种新的证券投资组合优化模型，并以实例作了说明。     

具指数赋权指标的证券投资多目标线性规划模型

本文提出证券投资决策的指数赋权指标体系．在该指标体系中,建立风险证券组合投资决策和存在无风险证券或无风险贷款时证券组合投资决策的多目标线性规划模型．研究了有效风险证券组合集和有效证券组合集的结构和相互关系,市场证券组合以及证券均衡市场价格和投资风险分析．     

区间值模糊线性规划在证券组合投资优化中的应用

针对期望收益率与风险损失率为区间值模糊数的特征,就证券组合投资问题建立了一种区间值模糊线性规划模型,运用一种对区间值模糊数排序的新算法,将模型转化为经典的线性规划问题进行求解,最后通过一个算例说明其有效性和可靠性,为证券组合投资优化问题的解决提供了一种新的方法,对证券组合的理性投资具有重要的指导意义.     

限制卖空及带交易费用的证券组合的三参数模型

本文在 (Simaan(1993) )组合选择的三参数模型的框架下 ,考虑了交易费用 ,限制卖空 ,提出了新的风险证券投资组合模型 ,并给出了风险投资最优比例的算法 .     

A review of credibilistic portfolio selection

This paper reviews the credibilistic portfolio selection approaches which deal with fuzzy portfolio selection problem based on credibility measure. The reason for choosing credibility measure is given. Several mathematical definitions of risk of an investment in the portfolio are introduced. Some credibilistic portfolio selection models are presented, including mean-risk model, mean-variance model, mean-semivariance model, credibility maximization model, α-return maximization model, entropy optimization model and game models. A hybrid intelligent algorithm for solving the optimization models is documented. In addition, as extensions of credibilistic portfolio selection approaches, the paper also gives a brief review of some hybrid portfolio selection models.     

Portfolio selection with a new definition of risk

In the field of portfolio selection, variance, semivariance and probability of an adverse outcome are three best-known mathematical definitions of risk. Lots of models were built to minimize risk based on these definitions. This paper gives a new definition of risk for portfolio selection and proposes a new type of model based on this definition. In addition, a hybrid intelligent algorithm is employed to solve the optimization problem in general cases. One numerical example is also presented for the sake of illustration.     

含有资本结构因子、交易成本和风险偏好的模糊最优化投资模型

建立了含有资本结构因子、交易成本和风险偏好的模糊最优化投资模型,在允许卖空条件下,给出最优投资策略及有效边界;在不允许卖空条件下,给出了确定其有效边界的算法,并分析了风险偏好、无风险利率和交易成本对有效边界的影响,最后通过示例进行了分析.     

Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature

Since the pioneering work of Harry Markowitz, mean–variance portfolio selection model has been widely used in both theoretical and empirical studies, which maximizes the investment return under certain risk level or minimizes the investment risk under certain return level. In this paper, we review several variations or generalizations that substantially improve the performance of Markowitz’s mean–variance model, including dynamic portfolio optimization, portfolio optimization with practical factors, robust portfolio optimization and fuzzy portfolio optimization. The review provides a useful reference to handle portfolio selection problems for both researchers and practitioners. Some summaries about the current studies and future research directions are presented at the end of this paper.     

一种市场风险条件的贷款组合优化决策模型

针对不确定投资情况下风险与收益的选择方法，提出一种贷款组合的优化决策模型，以解决不同风险，收益下的贷款组合决策问题，并给出实例分析以表明该模型的科学性。     

Portfolio optimization with serially correlated, skewed and fat tailed index returns

This paper finds that mean-variance portfolio optimization of stocks, bonds, hedge funds, real estate investment trusts and commodities is sufficiently exact to optimize the investor’s utility. We approximate the expected utility using a Taylor series expansion including terms involving third and fourth order moments. The empirical findings for monthly data from August 1994–August 2009 suggest that the incorporation of skewness and kurtosis cause no noticeable change in the optimal portfolio allocation. However, the serial correlations of smoothed returns of hedge funds and real estate investment trusts indeed cause major changes in optimal portfolio allocation. Consequently, attention needs to be drawn to significant serial correlation and not to potential deviations from normality due to skewed and fat-tailed return distributions. The out-of-sample analysis using a moving window gives evidence that the optimal portfolio weight differ significantly considering serial correlation. The optimization using smoothed returns leads to the highest terminal wealth after 10 years. The highest utility is reached with smoothed as well as shrinked returns, while using unsmoothed as well as shrinked returns leads to an out-of-sample disaster. These findings have practical implications for investors who are willing to diversify their portfolios with hedge funds and real estate investment trusts.     

Uncertain portfolio optimization problem under a minimax risk measure

Portfolio optimization problem is concerned with choosing an optimal portfolio strategy that can strike a balance between maximizing investment return and minimizing investment risk. In many cases, the return rate of risky asset is neither a random variable nor a fuzzy variable. Then, it can be described as an uncertain variable. But, the existing works on uncertain portfolio optimization problem fail to find an analytic solution of optimal portfolio strategy. In this paper, we define a new uncertain risk measure for the modeling of investment risk. Then, an uncertain portfolio optimization model is formulated. By introducing a new variable, we transform it into an equivalent bi-criteria optimization model. Then, we derive a method for the construction of the set of analytic Pareto optimal solutions. Finally, a numerical simulation is carried out to show the applicability of the proposed model and the convenience of finding the analytic solution.     

鲁棒投资组合选择优化问题的研究进展

对近年来投资组合研究优化研究的热点问题——鲁棒投资组合优化研究的现状和发展趋势作了综述性研究．在投资组合选择优化的均值-方差模型的基础上,回顾了鲁棒投资组合选择优化问题的发展历史;详细地介绍了鲁棒投资组合选择优化的研究热点及国内外研究现状,就鲁棒投资组合选择优化问题的未来发展方向和主要研究内容,提出了新的观点,以期为相关领域的研究工作提供参考依据．