模糊环境下基于遗传差分协同进化的多阶段投资组合模型

现实经济活动中投资一般是不确定的和随机的,投资者对于风险资产的选择大多情况下是多阶段的。基于该现实因素,在模糊环境下考虑多个摩擦因素,利用交易限制引入资产的基数约束,建立可能性均值–下半方差–熵多阶段投资组合优化模型(V-S-M),该模型是一个多阶段混合整数规划问题。同时,给出了求解该模型的一个遗传差分协同进化算法(GAHDE),并对不同风险态度下的投资组合策略进行了分析,同时将所得数值结果与可能性均值–下半方差模型(V-M)和可能性均值–熵模型(S-M)进行模型对比,与标准的遗传算法和差分进化算法进行了算法对比,结果验证了所建模型和设计算法的优越性与有效性。     

有高阶矩约束的最优投资组合模型及近似线性规划解法

本文讨论有包括偏度和峰度在内的高阶矩约束的最优投资组合模型。证明了最优投资组合决策的存在性并导出解析解的隐式表达式,然后利用线性逼近的方法得到近似解,并给出了具体算例,最后分析了模型中的权重参数对最优目标的影响。     

带有交易成本的均值——方差——下半方差投资组合模型

投资组合选择研究为投资决策和风险管理提供了可量化的途径和科学决策的依据．本文引入了非凹非凸的典型交易成本函数,建立了含有交易成本函数的均值--方差--下半方差投资组合模型．考虑到不同的投资者对风险的厌恶程度不同,引入风险厌恶系数,把双目标的投资组合优化模型转化为单目标的投资组合优化模型,并运用教与学算法对模型进行了求解,得到不同收益下的最优投资组合,同时给出了投资组合的有效边界,最后对算法的优越性进行了分析,得到了比较好的仿真结果．     

投资权重限制下套利组合的均值-方差分析

由于在现实生活中,受监管当局的监管要求和公司投资者的偏好制约,套利操作往往存在一定的投资权重限制。因此,考虑到现实应用,对套利组合的分析也须研究存在投资权重限制时的选择问题。本文首先在证券投资权重限制下对套利组合进行均值-方差分析,证明此时均值-方差意义下最优套利组合的存在性,并通过将原问题分解为凸优化子问题的方法给出最优套利组合的求取方法。最后结合实际数据计算,我们可以得出结论,与没有投资权重限制的情形相比,投资权重限制将会劣化自由市场交易所能得到的最优套利组合,因此恰当制定投资权重限制是投资机构设立时必须慎重处理的问题。     

基于VMD散布熵与改进灰狼优化SVDD的轴承半监督故障诊断研究

为充分挖掘未标记样本所蕴含的有效信息,进而提升诊断精度,研究提出一种基于变分模态分解(VMD)散布熵与改进灰狼优化支持向量数据描述(SVDD)的轴承半监督故障诊断方法。采用中心频率观察法确定VMD分解模态参数K,进而将原始信号分解为一系列本征模态函数并计算各分量的散布熵值,构成测试样本和部分标记的训练样本;再由半监督模糊C均值(SSFCM)聚类对训练样本进行聚类分析,从而对所得聚类簇进行SVDD建模,同时采用k近邻准则进行决策优化,并由所提自适应变异灰狼算法优化SVDD模型参数;将基于最优参数训练的改进决策SVDD模型用于测试样本的故障模式识别。试验分析和对比结果表明,所提方法具有较好的诊断性能。     

基于随机市场系数模型的最优投资组合策略

本文将Merton的投资模型拓展到随机市场系数模型。在典型投资问题对应的动态规划中,值函数一般用Bellman方程的粘性解表示。本文通过指数变换把偏微分方程转变成一个半线性的抛物线方程,证明了其值函数连续解的存在性,并在此基础上给出了企业的最优投资组合策略。     

报童问题的“均值偏向”效应研究综述

2000年,Schweitzer等在有关报童模型的实验中发现,有限理性的报童所决策的订货量存在“均值偏向(pullto-center)”效应。之后,在大量的实验和理论研究中,“均值偏向”效应也被反复观测到。本文首先对2000～2021年间顶级期刊发表的探究“均值偏向”原因的文献,从锚定和不充分调整启发式、最小化事后库存误差、近因效应、过度自信、框架依赖、心理账户、参考点等方面进行总结分析。其次,根据个体对认知信息的加工特点,将决策过程划分为信息获取、信息编辑和信息评估3个阶段,并对引起“均值偏向”效应的偏差因素进行分类。研究表明,目前对引起“均值偏向”效应的偏差因素的探究,主要集中在信息编辑阶段。最后,本文探讨了该领域未来值得关注的研究方向。     

实物期权的项目投资组合决策优化研究

基于项目投资决策的可延迟性特征,将实物期权的决策灵活性思想引入到企业的投资组合决策中,建立了基于实物期权的0-1整数规划模型.模型以项目的期权价值而非净现值最大化作为投资组合项目选择的标准,通过项目组合投资时机的灵活安排,实现了项目组合的总投资价值最大化.     

多重碳政策下供应链最优减排投资策略

针对行为主体的认知偏差以及供应链碳减排投入的问题,在供应商过度自信-零售商理性-消费者低碳偏好的特征组合下,分别建立单一碳政策下的基本模型和联合碳政策下的拓展模型,研究供应链成员行为偏好和碳政策参数对供应链减排投资策略的影响。研究发现:一定条件下低碳供应链将不再"低碳",碳政策失效;过度自信的供应商会加大碳减排投资(高于理性的供应商),以短期交易为目标的零售商应该积极寻求一个过度自信的供应商。数值算例表明,无论从减排量还是减排率的角度,碳税与碳交易联合政策的减排效果最佳;对于清洁型行业,政府(碳交易市场)应加强碳约束,对于污染型行业,政府(碳交易市场)应降低碳约束。上述结论为供应链企业做出合理的减排投资决策提供一定的智力支持。     

考虑交易费用的均值——VaR多阶段投资组合优化模型

考虑到方差、下半方差和绝对偏差等度量投资组合风险的局限性以及单阶段投资决策不符合投资者的实际投资行为等因素,本文将风险价值（Value-at-Risk,简称VaR）作为风险度量标准应用到多阶段投资组合优化中．由于中国股票市场不允许卖空,因此本文在不允许卖空的情况下,在约束条件中同时考虑了交易费用和投资比例,建立了一个均值--VaR多阶段投资组合优化模型．考虑到粒子群算法具有收敛速度快,结构简单以及需要调控的参数比较少等优点,运用带有罚函数处理机制的粒子群算法对新建立的多阶段投资组合优化模型进行求解．求解得到了不同路径下各阶段资产的最优投资策略,从运算结果可以看出,在不同的投资路径下投资者的投资行为基本一致,在第一阶段对自己看好的股票买入,经过第一阶段股市的波动,在第二阶段对自己看好的股票继续买入,对不看好的股票不买入或者直接卖出,这种投资行为符合投资者的实际投资行为,说明本文所提出的模型具有合理性．     

Project Portfolio Ranking based on the Strategic Contribution Efficiency

Project portfolio management is proved to be remarkable for an enterprise to attain competences. When selecting project portfolios,enterprises are willing to know which one has the largest return on investment rate when realizing enterprise strategy. A methodology for project portfolio ranking by adopting the concept of Strategic Contribution Efficiency（ SCE） is proposed. SCE acts as the measure that demonstrates what degree a project portfolio would contribute to enterprise strategy at specific cost. Evaluation criteria are established according to the practical requirements of enterprises. Data Envelope Analysis（ DEA） is combined with fuzzy set to calculate SCE and the ranking,which takes project portfolio as a whole rather than evaluates individual projects separately and considers information imprecision at the same time. At last,a numerical example is illustrated the specific process of project portfolio ranking based on SCE,from the portfolio generation to analysis,and the efficiency of proposed model is verified.     

Credibilitic mean-variance model for multi-period portfolio selection problem with risk control

This paper proposes a credibilitic mean-variance model for multi-period portfolio selection problem in a fuzzy uncertain economic environment, which maximizes the terminal wealth and minimizes the risk of the terminal wealth. To avoid occurrence of bankruptcy in the whole investment horizon, a risk control constraint is imposed on the proposed model at the same time. In this model, the return rate of asset is quantified by credibilitic expected value and the risk is characterized by credibilitic variance. To solve the proposed model, a fuzzy programming technique is utilized to transform it into a single-objective programming model. Then, a novel hybrid genetic algorithm is designed for obtaining the optimal investment strategy. Finally, a numerical example is given to illustrate the application of the proposed model and a comparative analysis about solution algorithms are implemented.     

Dynamic portfolio optimization under multi-factor model in stochastic markets

We consider the modeling and solution of the multi-period portfolio selection problem in stochastic markets with bankruptcy risk control. This research differs from current results in the following ways: rather than in terms of return moments, the stochastic evolution of the market is directly described in terms of investment returns by a finite-state Markov chain; the multi-factor model is initially introduced in the modeling process to better control bankruptcy risk and to cope with large-scale portfolio selection problems; the stable distributions are adopted to describe factors’ fluctuations to properly reflect the return distribution characteristics of risky assets; the bankruptcy risk in each period is flexibly controlled by utilizing the properties of the multi-factor model and restricting the portfolio loss caused by each factor; a specific bi-level programming method is proposed to find the analytical investment strategy; the practical significance and good performance of the stage-wise investment decision, when not optimal, are verified. Empirical results are finally provided to illustrate the suitability and practical performance of the new model and the derived explicit investment strategy.     

Financing Model Decision of Inter-basin Water Transfer Projects

Inter-basin Water Transfer Projects require the appropriate financing model to attract large amounts of social investment. Therefore, financing model decision becomes the key of engineering construction. In three aspects, such as the subject, the object and the target of the financing model, Grey Target Model is established in this paper. First, the complex financing mode decision problems of Inter-basin Water Transfer Projects are decomposed by using hierarchical decomposition method. Then Analytical Hierarchy Process (AHP) method is used to calculate the comprehensive weight of evaluation index. Experts’ opinions financing model are transformed into the evaluation matrix based on the Dephi method. The Weighted Grey Target Model is used to calculate the approaching degree of financing model and assists financing mode decision. In addition, this paper takes the water diversion project from the Han to the Wei River of Shaanxi Province as a verification example for the model. For other water diversion projects, the evaluation results are also reliable and provide theoretical references for the financing model decision of Inter-basin Water Transfer Projects.     

Robust scenario optimization based on downside-risk measure for multi-period portfolio selection

We develop and test multistage portfolio selection models maximizing expected end-of-horizon wealth while minimizing one-sided deviation from a target wealth level. The trade-off between two objectives is controlled by means of a non-negative parameter as in Markowitz Mean-Variance portfolio theory. We use a piecewise-linear penalty function, leading to linear programming models and ensuring optimality of subsequent stage decisions. We adopt a simulated market model to randomly generate scenarios approximating the market stochasticity. We report results of rolling horizon simulation with two variants of the proposed models depending on the inclusion of transaction costs, and under different simulated stock market conditions. We compare our results with the usual stochastic programming models maximizing expected end-of-horizon portfolio value. The results indicate that the robust investment policies are indeed quite stable in the face of market risk while ensuring expected wealth levels quite similar to the competing expected value maximizing stochastic programming model at the expense of solving larger linear programs.     

不考虑交易费用的组合证券投资优化模型

在证券组合投资方面 ,根据 Markowits均值方差模型 ,提出了一种双目标规划优化模型 ,并且通过赋权的方式 ,给出了模型的解     

Mean-absolute deviation model

We survey the Mean-Absolute Deviation (MAD) portfolio optimization model, which was first introduced in 1990 to cope with very large-scale portfolio optimization problems. The MAD model is in fact used to solve huge portfolio optimization models including the internationally diversified investment model, the long-term asset liability management (ALM) model and the mortgage-backed security portfolio optimization model. It was recently shown that the MAD model possess several advantageous theoretical properties. In particular, all capital asset pricing model (CAPM)-type relations for the mean-variance model also hold for the MAD model. Furthermore, the MAD model is more compatible with the fundamental principle of rational decision-making.     

具有VaR约束和无风险投资的证券组合选择方法

本文提出了具有VaR约束和无风险投资的证券组合优化模型,在证券收益率服从正态分布的前提下,给出有效投资比例及有效边界的解析形式,它是传统的均值-方差模型及有效证券组合的推广。