投资比例非负约束的风险证券组合有效集及动态分析

本文提出了风险证券有效组合的决策模型 ,给出了投资比例非负约束的风险证券有效组合的解析表示 ,研究了证券个数变动对证券组合有效集的影响 .分析了它的漂移方向和漂移范围 ,给出了最小风险有效证券组合和最大收益有效证券组合的漂移距离及风险与收益的增加或减少程度     

证券投资组合理论的一种新模型及其应用

马科维茨(Markowitz)以证券收益率的方差作为投资风险的测度建立了组合证券投资模型，本基于熵的概念，在研究马科维茨(Markowitz)证券投资组合模型的基础上，分析了该模型用方差度量风险的不足，进而提出一种新的证券投资组合优化模型，并以实例作了说明。     

最小方差组合证券集的性质

从分析最小方差组合证券集入手 ,研究了均值方差有效组合证券边界的性质 ,给出最小方差组合证券集是一个仿射集 ,并且对有效组合证券结构的统计特性进行了分析 ,对证券投资有一定的指导意义     

具指数赋权指标的证券投资多目标线性规划模型

本文提出证券投资决策的指数赋权指标体系．在该指标体系中,建立风险证券组合投资决策和存在无风险证券或无风险贷款时证券组合投资决策的多目标线性规划模型．研究了有效风险证券组合集和有效证券组合集的结构和相互关系,市场证券组合以及证券均衡市场价格和投资风险分析．     

限制投资下界的风险证券有效组合模型及算法研究

本文研究了具有投资下界限制的风险证券有限组合决策问题，提出了限制投资下界的风险证券有效组合优化模型，在一定的条件下，给出了风险证券有限组合投资比例的算法及解析表示，最后进行了实际数值计算，结果说明了所给算法是有效和实用的。     

熵—证券投资组合风险的一种新的度量方法

本文在研究马科维茨 ( Markowitz)证券投资组合模型的基础上 ,分析了该模型用方差度量风险的缺陷 ,进而提出用熵作为风险的度量方法 ,改进马科维茨 ( Markowitz)证券投资组合模型 ,并建立新的证券投资组合优化模型     

单位收益率风险最小的组合证券投资决策模型

章首先分析了组合证券投资的收益率和风险,根据组合证券投资的亏本概率上界最小的原则,建立了单位收益率风险最小的组合证券投资决策模型,并证明了该模型的有效性。     

目标规划法在证券组合投资中的应用

证券投资是目前我国经济中的一大热点。本以Markowitz证券组合投资理论为基础，运用目标规划的方法建立一种新的证券组合投资决策模型。在本模型中综合考虑了证券组合的收益，风险，交易费用等因素，对投资选择有效证券组合有一定的实用价值。     

含交易费用的投资组合问题的新模型及其求解途径

本文提出了证券投资组合的一个新模型.该模型综合考虑了证券的收益率、证券分红和证券价格的关系,并将证券分红和证券价格作为系统的随机参数处理,建立了证券投资组合的随机规划模型.利用机会约束规划方法,我们研究了将所建立的随机规划模型转化为普通光滑优化问题求解的方法,得到了该类问题求解的有效途径.     

证券投资组合的原理及其应用

本文利用概率统计原理对证券投资组合能减轻所遇风险带来的损失作了深刻的讨论,并介绍了多种证券投资组合方案的选择及如何在多种证券中选出几种进行投资组合     

泛系分析:数学·方法论·相对论·辩证思维

基于对广义系统、泛导、泛对称、泛箱原理、泛系相对性提出了新的分析模式与新的相对数学化的简化强化的定义,发展了泛系方法论与泛系相对论的框架与理法,具体内容涉及:相对普适的数学化的泛系,200类对偶,对偶转化,泛对称转化,泛系辩证,八畴方法,泛系数学方法,广义量化,逼近转化原则,泛等价定理,供求分析,思维实验,广义灰色系统,等等.     

Transverse compression of PPTA fibers

Results of single transverse compression testing of PPTA and PIPD fibers, using a novel test device, are presented and discussed. In the tests, short lengths of single fibers are compressed between two parallel, stiff platens. The fiber elastic deformation is analyzed as a Hertzian contact problem. The inelastic deformation is analyzed by elastic-plastic FE simulation and by laser-scanning confocal microscopy of the compressed fibers ex post facto. The results obtained are compared to those in the literature and to the theoretical predictions of PPTA fiber transverse elasticity based on PPTA crystal elasticity.Presented at the 11th International Conference on Mechanics of Composite Materials (Riga, June 11–15, 2000).3TEX, Inc. 109, MacKenan Drive, Cary, North Carolina 27511, USA. Published in Mekhanika Kompozitnykh Materialov, Vol. 36, No. 4, pp. 533–544, March–April, 2000.     

区组长为奇素数的自反MD设计

本文利用差方法对自反MD设计SCMD(4mp,p,1)的存在性给出了构造性证明,这里p为奇素数,m为正整数．     

Professor Sun Yongsheng

Sun Yongsheng, professor of mathematics, was born on January 22, 1929, in Wanghaisi Village, Cang County, Hebei Province, China. He died of lung cancer at 23 hour 15 minutes,March 22, 2006 in Beijing.     

Immersive Projection Technology for Visual Data Mining

The PlatoCAVE, the MiniCAVE, and the C2 are immersive stereoscopic projectionbased virtual reality environments oriented toward group interactions. As such they are particularly suited to collaborative efforts in data analysis and visual data mining. In this article, we provide an overview of virtual reality in general, including immersive projection technology, and the use of stereoscopic displays for data visualization. We discuss design considerations for the construction of these immersive environments including one-wall versus four-wall implementations, augmented reality, stereoscopic placement, head tracking, the use of LCD devices, polarized light stereo, voice control, and image synchronization.     

Components of the Fundamental Category II

In this article we carry on the study of the fundamental category (Goubault and Raussen, Dihomotopy as a tool in state space analysis. In: Rajsbaum, S. (ed.) LATIN 2002: Theoretical Informatics. Lecture Notes in Computer Science, vol. 2286, Cancun, Mexico, pp. 16–37, Springer, Berlin Heidelberg New York, 2002; Goubault, Homology, Homotopy Appl., 5(2): 95–136, 2003) of a partially ordered topological space (Nachbin, Topology and Order, Van Nostrand, Princeton, 1965; Johnstone, Stone Spaces, Cambridge University Press, Cambridge, MA, 1982), as arising in e.g. concurrency theory (Fajstrup et al., Theor. Comp. Sci. 357: 241–278, 2006), initiated in (Fajstrup et al., APCS, 12(1): 81–108, 2004). The “algebra” of dipaths modulo dihomotopy (the fundamental category) of such a po-space is essentially finite in a number of situations. We give new definitions of the component category that are more tractable than the one of Fajstrup et al. (APCS, 12(1): 81–108, 2004), as well as give definitions of future and past component categories, related to the past and future models of Grandis (Theory Appl. Categ., 15(4): 95–146, 2005). The component category is defined as a category of fractions, but it can be shown to be equivalent to a quotient category, much easier to portray. A van Kampen theorem is known to be available on fundamental categories (Grandis, Cahiers Topologie Géom. Différentielle Catég., 44: 281–316, 2003; Goubault, Homology, Homotopy Appl., 5(2): 95–136, 2003), we show in this paper a similar theorem for component categories (conjectured in Fajstrup et al. (APCS, 12(1): 81–108, 2004). This proves useful for inductively computing the component category in some circumstances, for instance, in the case of simple PV mutual exclusion models (Goubault and Haucourt, A practical application of geometric semantics to static analysis of concurrent programs. In: Abadi, M., de Alfaro, L. (eds.) CONCUR 2005 – Concurrency Theory: 16th International Conference, San Francisco, USA, August 23–26. Lecture Notes in Computer Science, vol. 3653, pp. 503–517, Springer, Berlin Heidelberg New York, 2005), corresponding to partially ordered subspaces of R ⁿ minus isothetic hyperrectangles. In this last case again, we conjecture (and give some hints) that component categories enjoy some nice adjunction relations directly with the fundamental category.      

Formulation of linear problems and solution by a universal machine

Using the predicate language for ordered fields a class of problems referred to aslinear problems is defined. This class contains, for example, all systems of linear equations and inequalities, all linear programming problems, all integer programming problems with bounded variables, all linear complementarity problems, the testing of whether sets that are defined by linear inequalities are semilattices, all satisfiability problems in sentenial logic, the rank-computation of matrices, the computation of row-reduced echelon forms of matrices, and all quadratic programming problems with bounded variables. A single, one, algorithm, to which we refer as theUniversal Linear Machine, is described. It solves any instance of any linear problem. The Universal Linear Machine runs in two phases. Given a linear problem, in the first phase a Compiler running on a Turing Machine generates alinear algorithm for the problem. Then, given an instance of the linear problem, in the second phase the linear algorithm solves the particular instance of the linear problem. The linear algorithm is finite, deterministic, loopless and executes only the five ordered field operations — additions, multiplications, subtractions, divisions and comparisons. Conversely, we show that for each linear algorithm there is a linear problem which the linear algorithm solves uniquely. Finally, it is shown that with a linear algorithm for a linear problem, one can solve certain parametric instances of the linear problem.Research was supported in part by the National Science Foundation Grant DMS 92-07409, by the Department of Energy Grant DE-FG03-87-ER-25028, by the United States—Israel Binational Science Foundation Grant 90-00434 and by ONR Grant N00014-92-J1142.Corresponding author.     

Financial Risk Modelling and Econometric Inference

In finance, the explicit modelling of uncertainty takes on a particularly important role. The values of financial derivatives increase in the return volatility of the underlying security. This notion requires a concept of volatility and hence uncertainty. In addition, the choice between modelling in discrete and continuous time is not arbitrary, since it corresponds to a distinction between incomplete and complete markets, respectively, and this distinction matters for asset pricing, financial risk modelling, and inference. Risk and volatility are closely connected, and implied volatility, volatility forecasting, volatility in term structure models, stochastic volatility, and portfolio analysis are considered and related to a more general interplay between cross-sectional and dynamic aspects in finance. Stocks, bonds, and options are considered and placed in the context of efficiency and separation in inference.