风险敏感性控制在CEV模型的应用研究

假设股票的价格遵循CEV过程,经济因子满足两个相互独立的布朗运动,运用风险敏感性随机最优控制理论得到新的结论,最后对于简化的模型,得到最优长期增长率的解析解.     

纳税最优的工资奖金分配方案研究

根据我国现行的税法,个人所得税纳税采用九级累进税率.年工资和年终奖在速算扣除数个数上存在不同,使得对于相同的税前年收入,如果采用不同的年工资和年终奖分配方案会产生不同的税后实际所得.通过简化变量和缩小有效解区域,以及一系列严格的数学推导,得到了任意年收入下,月工资和年终奖的最优分配方案,使得在现有税制下,纳税额最小,税后收入最大.这个最优方案避免了税金负效应现象,保证了纳税公平性,有利于国家税务监管,企业员工薪金分配和个人纳税筹划;具有广阔的应用前景.     

最优多期比例再保险策略的必要条件

研究最小化保险公司破产概率的最优多期比例再保险策略,给出了保险公司最小破产概率的一个递归表达式,证明了可用动态规划方法求解此类问题.在此基础上,我们推导出最优多期比例再保险策略的几个必要条件.     

Mortar element methods for parabolic problems

In this article a standard mortar finite element method and a mortar element method with Lagrange multiplier are used for spatial discretization of a class of parabolic initial‐boundary value problems. Optimal error estimates in L^∞(L²) and L^∞(H¹)‐norms for semidiscrete methods for both the cases are established. The key feature that we have adopted here is to introduce a modified elliptic projection. In the standard mortar element method, a completely discrete scheme using backward Euler scheme is discussed and optimal error estimates are derived. The results of numerical experiments support the theoretical results obtained in this article. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2008     

高校教育成本测算及其优化管理模型

在高校成本层次分类的基础上,建立了生均成本测算的一般模型,针对教育成本投入过程中因学生人数随机变化而存在的风险,引进教学质量函数,提出了办学效益和教学质量的双目标优化模型.利用凸分析和优化原理得到优化问题解的存在性,全部正解的β取值范围以及最优解满足的充要条件,对最优解的定量计算给出了基于Monte Carlo模拟的遗传算法设计,并进行了相应的经济意义分析.     

在DEA中有关输出与输入的比值的模型的探讨

对以决策单元的输出与输入的比值为目标函数的多目标规划模型,证明了有关它与(弱)DEA有效(C2R)关系的三个定理.     

Backward Stochastic Riccati Equations and Infinite Horizon L-Q Optimal Control with Infinite Dimensional State Space and Random Coefficients

We study the Riccati equation arising in a class of quadratic optimal control problems with infinite dimensional stochastic differential state equation and infinite horizon cost functional. We allow the coefficients, both in the state equation and in the cost, to be random. In such a context backward stochastic Riccati equations are backward stochastic differential equations in the whole positive real axis that involve quadratic non-linearities and take values in a non-Hilbertian space. We prove existence of a minimal non-negative solution and, under additional assumptions, its uniqueness. We show that such a solution allows to perform the synthesis of the optimal control and investigate its attractivity properties. Finally the case where the coefficients are stationary is addressed and an example concerning a controlled wave equation in random media is proposed.     

Optimal superconvergent one step quadratic spline collocation methods

We formulate new optimal quadratic spline collocation methods for the solution of various elliptic boundary value problems in the unit square. These methods are constructed so that the collocation equations can be solved using a matrix decomposition algorithm. The results of numerical experiments exhibit the expected optimal global accuracy as well as superconvergence phenomena. AMS subject classification (2000)  65N35, 65N22     

Optimal Conditional Estimation: Average Case Setting

We consider an estimation problem which appears in the identification of systems by means of restricted complexity models: find the optimal approximation to an element of a linear normed space (a system) based on noisy information, subject to the restriction that approximations (models) can be selected from a prescribed subspace M of the problem element space. In contrast to the worst-case optimization criterion, which may be pessimistic, in this paper the quality of an identification algorithm is measured by its local average performance. Two types of local average errors are considered: for a given information (measurement) y and for a given unknown element x, the latter in two versions. For a wide spectrum of norms in the measurement space, we define an optimal algorithm and give expressions for its average errors which show the dependence on information, information errors, unmodelled dynamics, and norm in the measurement space.