含有交易成本的均值-方差-偏度资产组合优化模型

提出了含有交易成本的均值 -方差 -偏度资产组合优化模型 ;结合一个非对称性收益分布的具体例子 ,对模型做了灵敏度分析 .     

带交易费用的离散多因素投资组合最优化(英文)

研究带有凹的交易费函数的离散多因素投资组合模型.与传统的投资组合模型不同的是,该模型中投资组合的决策变量是交易手数(整数),其最优化模型是一个非线性整数规划问题.为此本文提出了一个基于拉格朗日松弛和连续松弛的混合分枝定界算法,为测试算法的有效性,我们分别采用美国股票市场真实数据和随机产生的数据,数值结果表明该算法是有效的.     

带交易费用的离散多因素投资组合最优化

研究带有凹的交易费函数的离散多因素投资组合模型．与传统的投资组合模型不同的是,该模型中投资组合的决策变量是交易手数（整数）,其最优化模型是一个非线性整数规划问题．为此本文提出了一个基于拉格朗日松弛和连续松弛的混合分枝定界算法,为测试算法的有效性,我们分别采用美国股票市场真实数据和随机产生的数据,数值结果表明该算法是有效的．     

Optimization of a Long-Short Portfolio under Nonconvex Transaction Cost

The purpose of this paper is to propose a practical branch and bound algorithm for solving a class of long-short portfolio optimization problem with concave and d.c. transaction cost and complementarity conditions on the variables.We will show that this algorithm can solve a problem of practical size and that the long-short strategy leads to a portfolio with significantly better risk-return structure compared with standard purchase only portfolio both in terms of ex-ante and ex-post performance.     

模糊环境中带交易费用的投资组合策略问题

由于金融市场是波动的,风险资产的预期收益率由于很多不确定性是很难估计的,本文考虑预期收益率是可能性分布(模糊数),并且在此基础上用模糊数的可能性均值表示投资组合的收益,用模糊数的平均绝对偏差表示风险,考虑了交易费用后,得到投资组合模型,最后给出了数值计算的例子.     

有交易成本的投资组合策略

金融市场都存在交易成本,为此,本文建立了有交易成本的投资组合模型,讨论了模型解的条件,并提出模型的通用数值解法,最后给出了应用举例．     

Global Optimization Versus Integer Programming in Portfolio Optimization under Nonconvex Transaction Costs

This paper is concerned with a portfolio optimization problem under concave and piecewise constant transaction cost. We formulate the problem as nonconcave maximization problem under linear constraints using absolute deviation as a measure of risk and solve it by a branch and bound algorithm developed in the field of global optimization. Also, we compare it with a more standard 0–1 integer programming approach. We will show that a branch and bound method elaborating the special structure of the problem can solve the problem much faster than the state-of-the integer programming code.     

考虑完整交易费用的组合证券投资求解

针对中国证券市场现存的各种交易费用,建立一个更加符合实际的组合证券投资模型.该模型不仅继承了股票不可拆分、不能卖空等特点,而且完全反映了交易费用的核算情况;最后给出一个遗传算法结合动态罚函数求解的投资实例,计算结果证明了该模型及其求解方法的有效性和可操作性.     

具有指数赋权指标及交易费的资产组合模型

本文提出了具有指数赋权指标以及固定的和比例的交易费的资产组合模型，给出了辅助的数学规划，利用它可以得到近似解或用于分支-定界方法中界的估计。     

具有交易成本的证券组合投资决策研究

本文利用均值－方差模型，分析了有交易成本的证券投资组合的决策问题，给出了风险资产和无风险资产的最优投资比例与交易成本关系的一个有意义的结论。     

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.     

信用资产组合优化的"条件在险值-补偿"型随机规划模型

本文对于信用资产组合的优化问题给出了一个稳健的模型，所建模型涉及了条件在险值（CVaR）风险度量以及具有补偿限制的随机线性规划框架，其思想是在CVaR与信用资产组合的重构费用之间进行权衡，并降低解对于随机参数的实现的敏感性．为求解相应的非线性规划，本文将基本模型转化为一系列的线性规划的求解问题．     

有交易费的无套利资产组合优化性质

针对所给出的有交易费的资产过程模型，引入了资产折算函数以刻划套期保值和套利机会，并利用辅助鞅和凸分析的对偶方法，讨论了该模型下基于无套利分析的资产组合优化可达性的一些性质．     

Optimal Consumption Portfolio and No-Arbitrage with Nonproportional Transaction Costs

In this paper we consider a finite-state financial market with non-proportional transaction cost and bid-ask spreads. The transaction cost consists of two parts: a fixed cost and a proportional cost to the size of transaction. We show that the existence of an optimal consumption policy implies that the market has no strong arbitrage; the opposite, however, is not true, i.e., no strong arbitrage does not imply the existence of an optimal consumption policy. This is in sharp contrast with the case of proportional transaction cost and other cases reported in the literature, where no strong arbitrage is equivalent to the existence of an optimal consumption policy. We also study the relationship between weak arbitrage and strong arbitrage. Different from the market with proportional transaction cost, we find that these two forms of arbitrage are equivalent unless the fixed cost is zero. A necessary and sufficient condition for the existence of an optimal consumption policy is also obtained. Supported by CAS, NSFC, RGC of Hong Kong and NSF under Grant No. DMI-0196084 and DMI-0200306.     

含交易费用的证券组合投资的多目标规划模型

以Ｍａｒｋｏｗ ｉｔｚ证券组合投资理论为基础,采用相对偏好参数,建立了含交易费用的证券组合的多目标规划模型,并给出了它的解法及有效边界的确定方法     

基于均值-VaR的投资组合最优化

利用均值-VaR方法,提出了有交易费用存在时的最优投资组合模型。通过求解均值-方差模型来研究均值-VaR模型的有效前沿,并指出在收益率的分布为正态分布的假设下,均值-VaR模型的有效集是均值-方差有效前沿的子集。有关全局最小VaR的存在性的分析显示在选择VaR的置信水平时必须非常小心。最后给出了应用均值-VaR模型的实例分析。     

Portfolio Selection and Transactions Costs

This paper deals with the portfolio selection problem of risky assets with a diagonal covariance matrix, upper bounds on all assets and transactions costs. An algorithm for its solution is formulated which terminates in a number of iterations that is at most three times the number of assets. The efficient portfolios, under appropriate assumptions, are shown to have the following structure. As the risk tolerance parameter increases, an asset's holdings increases to its target, then stays there for a while, then increases to its upper bound, reaches it and stays there. Then the holdings of the asset with the next highest expected return proceeds in a similar way and so on.     

An Algorithm for Portfolio Optimization with Variable Transaction Costs,Part 1: Theory

A portfolio optimization problem consists of maximizing an expected utility function of n assets. At the end of a typical time period, the portfolio will be modified by buying and selling assets in response to changing conditions. Associated with this buying and selling are variable transaction costs that depend on the size of the transaction. A straightforward way of incorporating these costs can be interpreted as the reduction of portfolios’ expected returns by transaction costs if the utility function is the mean-variance or the power utility function. This results in a substantially higher-dimensional problem than the original n-dimensional one, namely (2K+1)n-dimensional optimization problem with (4K+1)n additional constraints, where 2K is the number of different transaction costs functions. The higher-dimensional problem is computationally expensive to solve. This two-part paper presents a method for solving the (2K+1)n-dimensional problem by solving a sequence of n-dimensional optimization problems, which account for the transaction costs implicitly rather than explicitly. The key idea of the new method in Part 1 is to formulate the optimality conditions for the higher-dimensional problem and enforce them by solving a sequence of lower-dimensional problems under the nondegeneracy assumption. In Part 2, we propose a degeneracy resolving rule, address the efficiency of the new method and present the computational results comparing our method with the interior-point optimizer of Mosek. This research was supported by the National Science and Engineering Research Council of Canada and the Austrian National Bank. The authors acknowledge the valuable assistance of Rob Grauer and Associate Editor Franco Giannessi for thoughtful comments and suggestions.     

基于不确定性期望效用模型的投资优化

针对资产的收益的分布不确切知道,并且所获得的矩信息也不是准确值的问题,提出了最大化最坏情形期望效用的鲁棒性方法.引入了凹凸类效用函数来度量模型不确定情形下投资者的效用,用一个不确定性结构来刻画资产收益的所有可能的分布和收益的矩信息,通过把具有不确定性结构的鲁棒性模型转化成参数二次规划问题,得到了最优投资策略、有效前沿和均衡价格的解析表示.方法为采用保守策略并且厌恶不确定性的投资者提供了一种有效的投资决策方案.     

Selecting Portfolios with Fixed Costs and Minimum Transaction Lots

The original Markowitz model of portfolio selection has received a widespread theoretical acceptance and it has been the basis for various portfolio selection techniques. Nevertheless, this normative model has found relatively little application in practice when some additional features, such as fixed costs and minimum transaction lots, are relevant in the portfolio selection problem. In this paper different mixed-integer linear programming models dealing with fixed costs and possibly minimum lots are introduced. Due to the high computational complexity of the models, heuristic procedures, based on the construction and optimal solution of mixed integer subproblems, are proposed. Computational results obtained using data from the Milan Stock Exchange show how the proposed heuristics yield very good solutions in a short computational time and make possible some interesting financial conclusions on the impact of fixed costs and minimum lots on portfolio composition.