奇异协方差阵及不同借贷利率下均值—方差模型的解析解

随着金融资产种类的增加,特别是考虑大规模投资组合问题时,很可能出现资产间的多重共线性或相关性,从而出现协方差阵奇异的情况。然而,目前关于投资组合的均值—方差分析大都是在协方差阵正定的条件下得到的,因此,不适用于奇异协方差阵的情形。针对这一问题,利用广义逆矩阵研究了协方差阵奇异时的均值—方差投资组合模型,在不同借贷利率条件下得到了前沿组合和组合前沿的解析解,突破了传统方法中要求协方差阵可逆的限制,推广了经典Markowitz模型。     

Markowitz’s mean-variance asset-liability management with regime switching: A continuous-time model

This paper considers an asset-liability management (ALM) problem under a continuous-time Markov regime-switching model. By adopting the techniques of [Zhou, X.Y., Yin, G., 2003. Markowitz’s mean-variance portfolio selection with regime switching: A continuous-time model. SIAM J. Control Optim. 42, 1466–1482], we investigate the feasibility, obtain the optimal strategy, delineate the efficient frontier, and establish the associated mutual fund theorem.     

Portfolio Selection: A Review

This paper reviews portfolio selection models and provides perspective on some open issues. It starts with a review of the classic Markowitz mean-variance framework. It then presents the intertemporal portfolio choice approach developed by Merton and the fundamental notion of dynamic hedging. Martingale methods and resulting portfolio formulas are also reviewed. Their usefulness for economic insights and numerical implementations is illustrated. Areas of future research are outlined.     

借贷利率限制下资产-负债管理问题的均值-方差模型

将负债过程和借款利率限制引入投资组合优化问题中,并建立该问题的均值-方差模型.通过引入拉格朗日函数并应用拉格朗日对偶定理得到一个等价的新的优化模型,然后应用动态规划原理得到了最优投资策略和有效前沿的解析表达式.算例解释了所得结论.     

一种改进的投资组合模型的算法和实证分析

目前,在Markowitz的均值-方差模型基础上对含有偏度和交易成本模型的研究较少,结合国内市场数据进行研究并做出三维投资组合有效前沿图像的成果更少。在建立两种在交易成本约束条件下以方差和偏度的线性组合为目标函数的最优投资组合模型之后,利用线性函数逼近,将模型转换成线性规划问题,而且这种逼近程度可以控制。用单纯形法求解以得到最优投资组合。利用国内八个上市公司的数据进行实证分析,做出了三维投资组合近似有效前沿图像,并讨论了目标函数最优值和参数的关系。可以发现,目标函数是期望r和参数m的增函数。     

Classical mean-variance model revisited: pseudo efficiency

Investigating the inverse problem of the classical Markowitz mean-variance formulation: Given a mean-variance pair, find initial investment levels and their corresponding portfolio policies such that the given mean-variance pair can be realized, we reveal that any mean-variance pair inside the reachable region can be achieved by multiple portfolio policies associated with different initial investment levels. Therefore, in the mean-variance world for a market of all risky assets, the common belief of monotonicity: ‘The larger you invest, the larger expected future wealth you can expect for a given risk (variance) level’ does not hold, which stimulates us to extend the classical two-objective mean-variance framework to an expanded three-objective framework: to maximize the mean and minimize the variance of the final wealth as well as to minimize the initial investment level. As a result, we eliminate from the policy candidate list the set of pseudo efficient policies that are efficient in the original mean-variance space, but inefficient in this newly introduced three-dimensional objective space.     

Heuristic algorithms for the cardinality constrained efficient frontier

This paper examines the application of genetic algorithm, tabu search and simulated annealing metaheuristic approaches to finding the cardinality constrained efficient frontier that arises in financial portfolio optimisation. We consider the mean-variance model of Markowitz as extended to include the discrete restrictions of buy-in thresholds and cardinality constraints. Computational results are reported for publicly available data sets drawn from seven major market indices involving up to 1318 assets. Our results are compared with previous results given in the literature illustrating the effectiveness of the proposed metaheuristics in terms of solution quality and computation time.     

基于模糊遗传算法的自融资有效投资组合研究

在马克维茨投资组合的均值一方差模型框架下,给出限制投资数量的自融资投资组合优化模型.把预期收益率不等式约束转化为模糊约束,采用一种通过惩罚因子,对适应度函数进行修正的模糊遗传算法来求解模型.在理论上,这种算法能够将最优基因较完整地遗传到下一代,有效地避免了早熟现象,可以得到更好的适应度函数值.在实际应用中,对一具体自融资有效投资组合实例进行计算,结果表明:本文所提出的模糊遗传算法是可行的、有效的,具有更好的优化结果.     

Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework

This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be ``embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem. Accepted 24 November 1999     

Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips

To create efficient funds appealing to a sector of bank clients, the objective of minimizing downside risk is relevant to managers of funds offered by the banks. In this paper, a case focusing on this objective is developed. More precisely, the scope and purpose of the paper is to apply the mean-semivariance efficient frontier model, which is a recent approach to portfolio selection of stocks when the investor is especially interested in the constrained minimization of downside risk measured by the portfolio semivariance. Concerning the opportunity set and observation period, the mean-semivariance efficient frontier model is applied to an actual case of portfolio choice from Dow Jones stocks with daily prices observed over the period 2005–2009. From these daily prices, time series of returns (capital gains weekly computed) are obtained as a piece of basic information. Diversification constraints are established so that each portfolio weight cannot exceed 5 per cent. The results show significant differences between the portfolios obtained by mean-semivariance efficient frontier model and those portfolios of equal expected returns obtained by classical Markowitz mean-variance efficient frontier model. Precise comparisons between them are made, leading to the conclusion that the results are consistent with the objective of reflecting downside risk.     

投资组合模型的改进研究:基于企业社会责任视角的实证分析

在尊重和借鉴前人对企业社会责任研究,尤其是在企业社会责任评价研究基础之上,本文从投资者的角度在投资组合过程中研究企业社会责任。在Markowitz(均值—方差)理论模型上添加企业社会责任的三个一级指标期望作为目标函数,由此将传统的投资组合模型扩展为五个目标函数的投资组合选择模型,而且我们根据经济学中经典的效用函数理论证明了此模型的正确性。本文引入主流的企业社会责任评价标准,并对一些典型公司进行打分量化。在此基础之上建立了以期望回报率、回报率的方差、核心利益相关者期望、蛰伏利益相关者期望和边缘利益相关者期望为目标函数的投资组合选择模型,在最小方差曲面上选取10个点构造投资组合,并以样本外的数据验证了模型的有效性。研究发现:根据此模型计算出来的部分投资组合回报率显著高于同期的市场指数。研究结果表明,这种关注企业社会责任的多目标投资组合选择模型,不仅让投资者可以直接控制企业社会责任,而且实际数据证明了此模型的优势之处,从而为关注企业社会责任的投资者提供一种投资的方法和思路。     

The efficient frontier for bounded assets

This paper develops a closed form solution of the mean-variance portfolio selection problem for uncorrelated and bounded assets when an additional technical assumption is satisfied. Although the assumption of uncorrelated assets is unduly restrictive, the explicit determination of the efficient asset holdings in the presence of bound constraints gives insight into the nature of the efficient frontier. The mean-variance portfolio selection problem considered here deals with the budget constraint and lower bounds or the budget constraint and upper bounds. For the mean-variance portfolio selection problem dealing with lower bounds the closed form solution is derived for two cases: a universe of only risky assets and a universe of risky assets plus an additional asset which is risk free. For the mean-variance portfolio selection problem dealing with upper bounds, the results presented are for a universe consisting only of risky assets. In each case, the order in which the assets are driven to their bounds depends on the ordering of their expected returns.     

工件具有任意尺寸的混合分批平行机排序问题的近似算法

本文考虑了工件具有任意尺寸且机器有容量限制的混合分批平行机排序问题。在该问题中, 一个待加工的工件集需在多台平行批处理机上进行加工。每个工件有它的加工时间和尺寸, 每台机器可以同时处理多个工件, 称为一个批, 只要这些工件尺寸之和不超过其容量; 一个批的加工时间等于该批中工件的最大加工时间和总加工时间的加权和; 目标函数是极小化最大完工时间。该问题包含一维装箱问题为其特殊情形, 为强NP-困难的。对此给出了一个$\left( {2 + 2\alpha+\alpha^{2}}\right)$-近似算法, 其中$\alpha$为给定的权重参数, 满足考虑了不同于Goldfarb和Iyengar （2003）的因子模型,通过横截面回归分析以及Fama-MacBeth估计构造了关于资产的平均收益向量和协方差矩阵的不确定性集合（置信区域）。基于这些不确定性集合以及Markowitz“均值-方差模型”的鲁棒投资组合问题,提出了多个鲁棒投资组合问题,并对应的推导出其等价的半正定规划形式,使得问题可以在多项式时间内求解。     

证券组合选择的有效子集

本文引进证券组合选择的有效子集概念。有效子集可取代原有的基本证券集来生成Markowitz有效组合前沿。本文给出一个证券集的子集是全集的有效子集的充要条件。在理论上，这是一条新的k-基金分离定理；在实际应用上，这有可能用来减少计算有效组合前沿的计算量。     

不允许卖空证券组合选择的有效子集

证券组合选择的有效子集是指它可取代原有的基本证券集来生成Markowits有效组合前沿.本文给出一个证券集的子集在不允许卖空的条件下是全集的有效子集的充要条件。     

奇异协方差阵下有效前沿及有效组合的解析解

利用广义逆矩阵研究了协方差阵奇异时的投资组合问题,突破了传统方法中要求协方差阵可逆的限制,得到了证券市场存在有效组合的充要条件,并给出了有效前沿和有效组合的解析解,成功地推广了经典Markowitz模型,同时还将有助于证券组合有效子集的深入研究.     

基于基准过程的动态均值-方差最优投资组合选择

利用动态规划方法研究了基于基准过程的动态均值-方差最优投资组合问题,证明了识别定理,得到了剩余过程的均方最优投资策略和有效前沿.     

基于最速曲线的投资组合调整方法

均值方差模型自1952年被提出以来在单期投资组合优化理论与实践中一直扮演着十分重要的角色。然而因为资金具有时间价值,所以投资者总是希望能够尽快实现他们的投资目标。鉴于此,本文利用数学中著名的最速曲线提出了一种新的投资组合调整方法并探讨其求解步骤。该方法在建模过程中考虑了投资活动中普遍存在的时间效应和处置效应两种现象。德国股票市场和中国股票市场中的实证结果不仅证实了投资组合调整的必要性,而且说明了新方法的实用性和有效性。