证券投资组合优化问题的强健性的锥优化方法(英文)

本文研究了具有强健性的证券投资组合优化问题.模型以最差条件在值风险为风险度量方法,并且考虑了交易费用对收益的影响.当投资组合的收益率概率分布不能准确确定但是在有界的区间内,尤其是在箱型区间结构和椭球区域结构内时,我们可以把具有强健性的证券投资组合优化问题的模型分别转化成线性规划和二阶锥规划形式.最后,我们用一个真实市场数据的算例来验证此方法.     

Optimization of component reliability in the design phase of capital goods

We introduce a quantitative model to support the decision on the reliability level of a critical component during its design. We consider an OEM who is responsible for the availability of its systems in the field through service contracts. Upon a failure of a critical part in a system during the exploitation phase, the failed part is replaced by a ready-for-use part from a spare parts inventory. In an out-of-stock situation, a costly emergency procedure is applied. The reliability levels and spare parts inventory levels of the critical components are the two main factors that determine the downtime and corresponding costs of the systems. These two levels are decision variables in our model. We formulate the portions of Life Cycle Costs (LCC) which are affected by a component’s reliability and its spare parts inventory level. These costs consist of design costs, production costs, and maintenance and downtime costs in the exploitation phase. We conduct exact analysis and provide an efficient optimization algorithm. We provide managerial insights through a numerical experiment which is based on real-life data.     

Portfolio selection with transaction costs under expected shortfall constraints

An investor subject to proportional transaction costs allocates funds to multiple stocks and a bank account, to maximise the expected growth rate of the portfolio value under Expected Shortfall (ES) constraints. In a numerical example with ten time steps and one stock important innovations are caused by the introduction of the Expected Shortfall constraint: First, expected returns are reduced by less than one-tenth when the ES constraint is introduced. In comparison, economic capital as measured by ES, is reduced to amounts between one-half and three-quarters, when the ES constraint is introduced. Second, the dependence of expected return and ES on the initial portfolio, in particular when transaction costs are high, is largely removed by the introduction of the ES constraint.     

Mean-variance Hedging for Pricing European-type Contingent Claims with Transaction Costs

In this paper,a European-type contingent claim pricing problem with transaction costs is considered by a mean-variance hedging argument.The investor has to pay transaction costs which areproportional to the amount of stock transacted.The writer‘‘s hedging object is to minimize the hedgingrisk,defined as the variance of hedging error at expiration,with a proper expected excess return level.At first, we consider the mean-variance hedging problem:for initial hedging wealth f,maximizing the excess expected return under the minimum hedging risk level V0.On the other hand,we consider a mean-variance portfolio problem,which is to maximize the expected return with initial wealth 0 under the same risk level V0.The minimum initial hedging wealth f,which can offset the difference of the maximum expected return of these two problems,is the writer‘s price.     

具有比例摩擦金融市场的一般经济均衡与资产定价(英文)

本文建立具有比例摩擦金融市场的简单两时期模型．经济人具有均值－方差偏好,并且在交易金融资产的过程中支付交易费用．本文证明了两种金融资产的一般经济均衡与资产定价的基本估值公式．     

考虑交易成本的一种新型资本市场线模型研究

本文利用均值 -方差模型 ,通过引进优良资产 ,在考虑了交易成本的前提下 ,利用优良资产特性推导出一种新的资本市场线     

Joint rolling-horizon scheduling of materials processing and lot-sizing with sequence-dependent setups

A lot sizing and scheduling problem from a foundry is considered in which key materials are produced and then transformed into many products on a single machine. A mixed integer programming (MIP) model is developed, taking into account sequence-dependent setup costs and times, and then adapted for rolling horizon use. A relax-and-fix (RF) solution heuristic is proposed and computationally tested against a high-performance MIP solver. Three variants of local search are also developed to improve the RF method and tested. Finally the solutions are compared with those currently practiced at the foundry.     

An Algorithm for Portfolio Optimization with Variable Transaction Costs,Part 2: Computational Analysis

In Part 1 of this paper, we introduced a (2K+1)n-dimensional portfolio optimization problem with variable transaction costs taken into account. We presented a method for solving the (2K+1)n-dimensional problem by solving a sequence of n-dimensional optimization problems accounting for the transaction costs implicitly rather than explicitly. In Part 2, we propose a degeneracy resolving rule, present computational results comparing our method with the interior-point optimizer of Mosek, well known for its speed and efficient use of sparsity, and also address the efficiency of the new method. This research was supported by the National Science and Engineering Research Council of Canada and the Austrian National Bank. The authors wish to acknowledge the valuable assistance of Jivendra Kale, Zhengzheng Zhou and Associate Editor Franco Giannessi for thoughtful comments and suggestions.     

Nonlinear Programming Analysis to Estimate Implicit Inventory Backorder Costs

In this paper, we use nonlinear programming to provide an alternative treatment of the economic order quantity problem with planned backorders. Many businesses, such as capital-goods firms that deal with expensive products and some service industries that cannot store their services, operate with substantial backlogs. In practical problems, it is usually very difficult to estimate accurately the values of the two types of backorder costs, i.e., the time-dependent unit backorder cost and the unit backorder cost. We redefine the original problem without including these backorder costs and construct a nonlinear programming problem with two service measure constraints which may be easier to specify than the backorder costs. We find that, with this different formulation of our new problem, we obtain results which give implicit estimates of the backorder costs. The alternative formulation provides an easier-to-use model and managerially meaningful results. Next, we show that, for a wide range of parameter values, it usually suffices to consider only one type of backorder cost, or equivalently, only one type of service measure constraint. Finally, we develop expressions which bracket the optimal values of the decision variables in a narrow range and provide a simple method for computing the optimal solution. In the most complicated case, this method requires finding the unique root of a polynomial.